refactor: consolidate agent/editor plugins under integrations/ (#5491)
Co-authored-by: Claude <noreply@anthropic.com>
This commit is contained in:
Kartik
@@ -0,0 +1,22 @@
|
||||
{
|
||||
"name": "mem0",
|
||||
"version": "0.2.9",
|
||||
"description": "Persistent memory for Claude Code. Remembers decisions, patterns, and preferences across sessions.",
|
||||
"author": {
|
||||
"name": "Mem0",
|
||||
"email": "support@mem0.ai"
|
||||
},
|
||||
"homepage": "https://mem0.ai",
|
||||
"repository": "https://github.com/mem0ai/mem0",
|
||||
"license": "Apache-2.0",
|
||||
"keywords": ["memory", "personalization", "mcp", "semantic-search"],
|
||||
"userConfig": {
|
||||
"api_key": {
|
||||
"type": "string",
|
||||
"title": "Mem0 API Key",
|
||||
"description": "Your Mem0 Platform API key (starts with m0-). Get one at https://app.mem0.ai/dashboard/api-keys",
|
||||
"sensitive": true,
|
||||
"required": true
|
||||
}
|
||||
}
|
||||
}
|
||||
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|
||||
{
|
||||
"mcpServers": {
|
||||
"mem0": {
|
||||
"url": "https://mcp.mem0.ai/mcp",
|
||||
"bearer_token_env_var": "MEM0_API_KEY"
|
||||
}
|
||||
}
|
||||
}
|
||||
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|
||||
{
|
||||
"name": "mem0",
|
||||
"version": "0.2.9",
|
||||
"description": "Persistent memory for Codex. Remembers decisions, patterns, and preferences across sessions.",
|
||||
"author": {
|
||||
"name": "Mem0",
|
||||
"email": "support@mem0.ai",
|
||||
"url": "https://mem0.ai"
|
||||
},
|
||||
"homepage": "https://mem0.ai",
|
||||
"repository": "https://github.com/mem0ai/mem0",
|
||||
"license": "Apache-2.0",
|
||||
"keywords": ["memory", "personalization", "mcp", "semantic-search"],
|
||||
"skills": "./skills/",
|
||||
"mcpServers": "./.codex-mcp.json",
|
||||
"hooks": "./hooks/codex-hooks.json",
|
||||
"interface": {
|
||||
"displayName": "Mem0",
|
||||
"shortDescription": "Persistent memory layer for AI coding workflows",
|
||||
"longDescription": "Mem0 adds long-term memory to Codex. Store decisions, user preferences, project context, and session state across conversations. Memories are automatically retrieved via semantic search so Codex always has the right context.",
|
||||
"developerName": "Mem0",
|
||||
"category": "Productivity",
|
||||
"capabilities": ["Read", "Write"],
|
||||
"websiteURL": "https://mem0.ai",
|
||||
"privacyPolicyURL": "https://mem0.ai/privacy",
|
||||
"termsOfServiceURL": "https://mem0.ai/terms",
|
||||
"defaultPrompt": [
|
||||
"Search my memories for recent project decisions",
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||||
"Remember that I prefer TypeScript over JavaScript",
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||||
"What do you know about my coding preferences?"
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||||
],
|
||||
"brandColor": "#FBBF24",
|
||||
"logo": "./logo.svg"
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,10 @@
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||||
{
|
||||
"mcpServers": {
|
||||
"mem0": {
|
||||
"url": "https://mcp.mem0.ai/mcp/",
|
||||
"headers": {
|
||||
"Authorization": "Token ${env:MEM0_API_KEY}"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,17 @@
|
||||
{
|
||||
"name": "mem0",
|
||||
"version": "0.2.9",
|
||||
"description": "Mem0 memory layer for AI applications. Add persistent memory, personalization, and semantic search using the Mem0 Platform MCP server.",
|
||||
"author": {
|
||||
"name": "Mem0",
|
||||
"email": "support@mem0.ai"
|
||||
},
|
||||
"homepage": "https://mem0.ai",
|
||||
"repository": "https://github.com/mem0ai/mem0",
|
||||
"logo": "logo.svg",
|
||||
"license": "Apache-2.0",
|
||||
"keywords": ["mem0", "memory", "mcp", "personalization", "semantic-search"],
|
||||
"skills": "./skills/",
|
||||
"hooks": "./hooks/cursor-hooks.json",
|
||||
"mcpServers": ".cursor-mcp.json"
|
||||
}
|
||||
@@ -0,0 +1,11 @@
|
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{
|
||||
"mcpServers": {
|
||||
"mem0": {
|
||||
"type": "http",
|
||||
"url": "https://mcp.mem0.ai/mcp/",
|
||||
"headers": {
|
||||
"Authorization": "Token ${MEM0_API_KEY}"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,47 @@
|
||||
# Changelog
|
||||
|
||||
All notable changes to the `@mem0/opencode-plugin` will be documented in this file.
|
||||
|
||||
## 0.1.3 — File-context injection, session summaries & activity timeline
|
||||
|
||||
### Added
|
||||
|
||||
- **File-context injection (`tool.execute.before` / Read):** Before the agent reads a file, the plugin searches mem0 for memories referencing that file path and injects prior work as system context. Gates on file size (>= 1,500 bytes). Gives the agent "I've worked on this file before" awareness automatically.
|
||||
- **Stop hook session summary (`experimental.session.compacting`):** Enhanced session compaction to store a structured `session_summary` memory with `infer=True`, letting the mem0 backend AI extract key facts (request, decisions, learnings, next steps). Previously only stored a raw stats string.
|
||||
- **SessionStart activity timeline:** The initial memory loading now formats recent memories with type icons (⚖️ decision, 🔴 bug_fix, 🔵 task_learning, etc.) and relative age indicators (2h ago, 1d ago) instead of bare text. Provides a visual "Recent Activity" timeline on first message.
|
||||
|
||||
### Changed
|
||||
|
||||
- **`experimental.session.compacting` handler:** Now stores `metadata.type=session_summary` with `metadata.source=opencode-stop` instead of `metadata.type=session_state` with `metadata.source=pre-compaction`. Includes a structured prompt that instructs mem0's AI to extract request, decisions, learnings, and next steps.
|
||||
- **Initial context formatting:** Memories shown on first message now include type icons and age labels for quick scanning.
|
||||
|
||||
## 0.1.2 — Automatic coding categories & global search
|
||||
|
||||
### Added
|
||||
|
||||
- **Auto-configured coding categories:** The plugin now automatically sets up 17 coding categories (e.g. `architecture_decisions`, `api_design`, `security`, `debugging_notes`) on the Mem0 project at startup. Runs in the background on every session start via `autoSetupCategories()`, is fully idempotent, and never blocks initialization. Uses SHA-256 fingerprints of the category list and API key — stored in `~/.mem0/categories_setup.json` — to skip redundant API calls on subsequent sessions.
|
||||
- **Global search mode (`global_search` setting):** New `global_search` toggle in `~/.mem0/settings.json` (default: `false`). When enabled, all `search_memories` and `get_memories` calls use `{"OR": [{"user_id": "*"}]}` instead of the per-user per-project `AND` filter — returning all memories across all users and all `app_id` scopes. Writes (`add_memory`) still tag with the current `user_id` and `app_id`. Applies to all plugin search paths: initial load, per-message recall, resume detection, error-pattern lookup, and compaction context.
|
||||
- **`/mem0:switch-project --global` / `--no-global`:** Enables or disables global search via the switch-project skill. Persists to `~/.mem0/settings.json`. No manual config editing needed.
|
||||
- **`MEM0_GLOBAL_SEARCH` environment variable:** Exported to child shells via the `shell.env` hook (`"true"` or `"false"`).
|
||||
|
||||
### Changed
|
||||
|
||||
- **Search filters are now dynamic:** All search paths throughout the plugin construct filters based on the `global_search` setting instead of always using `AND [user_id, app_id]`.
|
||||
- **Resume-context searches broadened:** Resume and error-pattern searches no longer include `metadata.type` sub-filters (`session_state`, `decision`, `anti_pattern`, `bug_fix`), broadening recall.
|
||||
- **System context message updated:** Informs the model when global search is active (`"Global search is ON — searches return all memories across all users and projects. Writes still use user_id=..., app_id=..."`).
|
||||
- **`/mem0:onboard` Step 5 is no longer interactive:** Removed the manual category installation prompt. Categories now configure automatically in the background; the onboarding step only verifies status and stores a fallback `project_profile` memory if the background run hasn't finished yet.
|
||||
- **`/mem0:switch-project` skill expanded:** Description and execution updated to document the `--global` and `--no-global` flags alongside the existing project-name argument.
|
||||
|
||||
## 0.1.1
|
||||
|
||||
- CI/CD publish flow test (`#5288`).
|
||||
- Fixed tsconfig, added `publishConfig` and bun lockfile (`#5273`).
|
||||
- Renamed package to `@mem0/opencode-plugin` (`#5272`).
|
||||
- Added plugin array to bundled `opencode.json` (`#5271`).
|
||||
|
||||
## 0.1.0 — Initial release
|
||||
|
||||
- **OpenCode plugin** (`@mem0/opencode-plugin` on npm): Pure TypeScript plugin using the `mem0ai` TS SDK — no Python, no shell scripts. Hooks into all 6 OpenCode events (`chat.message`, `tool.execute.before`, `tool.execute.after`, `experimental.chat.system.transform`, `experimental.session.compacting`, `shell.env`). Features: session start memory loading, per-prompt semantic search, error pattern detection with memory lookup, resume/remember intent detection, auto-capture every 3rd message, periodic save nudges, full metadata defaults injection (confidence, source, type, session_id, files, branch), identity injection for search/get/delete filters, type-filtered error pre-fetch (anti_pattern + bug_fix), pre-compaction memory capture, MEMORY.md write blocking, and secret redaction.
|
||||
- **16 OpenCode-native skills** bundled in `opencode-skills/`: `context-loader`, `dream`, `export`, `forget`, `health`, `import`, `list-projects`, `mem0` (SDK reference), `memory-reviewer`, `onboard`, `peek`, `pin`, `remember`, `stats`, `switch-project`, `tour`. All skills are pure MCP-tool-based — no Python scripts, no shell scripts, no Claude Code dependencies.
|
||||
- **Auto-install skills and commands (`installSkills()`):** On plugin load, copies all 16 skills to `.opencode/skills/` and creates command wrapper files in `.opencode/commands/` so they appear in the OpenCode `/` palette.
|
||||
- **CLI installer (`cli.ts`):** `bunx @mem0/opencode-plugin install` auto-configures plugin and MCP server in `~/.config/opencode/opencode.json`.
|
||||
@@ -0,0 +1,201 @@
|
||||
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Copyright [2026] [Taranjeet Singh]
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@@ -0,0 +1,84 @@
|
||||
# @mem0/opencode-plugin
|
||||
|
||||
Persistent memory for [OpenCode](https://opencode.ai). Your agent remembers decisions, preferences, and learnings across sessions automatically.
|
||||
|
||||
## Install
|
||||
|
||||
```bash
|
||||
bunx @mem0/opencode-plugin@latest install
|
||||
```
|
||||
|
||||
Or using OpenCode's built-in CLI:
|
||||
|
||||
```bash
|
||||
opencode plugin @mem0/opencode-plugin
|
||||
```
|
||||
|
||||
**Or let your agent do it** — paste this into OpenCode:
|
||||
|
||||
```
|
||||
Install @mem0/opencode-plugin by following https://raw.githubusercontent.com/mem0ai/mem0/main/integrations/mem0-plugin/.opencode-plugin/README.md
|
||||
```
|
||||
|
||||
All commands auto-add the plugin and MCP server to your `~/.config/opencode/opencode.json`. No manual config needed.
|
||||
|
||||
Get your API key (free): [app.mem0.ai/dashboard/api-keys](https://app.mem0.ai/dashboard/api-keys)
|
||||
|
||||
```bash
|
||||
echo 'export MEM0_API_KEY="m0-your-key"' >> ~/.zshrc && source ~/.zshrc
|
||||
```
|
||||
|
||||
Restart OpenCode.
|
||||
|
||||
## What's included
|
||||
|
||||
| Component | Description |
|
||||
|-----------|-------------|
|
||||
| **MCP Server** | 9 memory tools — add, search, get, update, delete memories |
|
||||
| **Lifecycle Hooks** | Auto-search on session start and every prompt, metadata enforcement, error memory lookup, compaction context |
|
||||
| **16 Slash Commands** | `/mem0:remember`, `/mem0:tour`, `/mem0:stats`, `/mem0:health`, `/mem0:dream`, and more |
|
||||
|
||||
## Hooks
|
||||
|
||||
Pure TypeScript — no Python, no shell scripts. Uses the [mem0ai](https://www.npmjs.com/package/mem0ai) SDK directly.
|
||||
|
||||
| Hook | Event | What it does |
|
||||
|------|-------|-------------|
|
||||
| **Chat message** | `chat.message` | Loads prior memories on session start, searches relevant memories before each prompt, auto-captures learnings periodically |
|
||||
| **Pre-tool** | `tool.execute.before` | Blocks MEMORY.md writes, enforces `user_id`/`app_id` on mem0 tools |
|
||||
| **Post-tool** | `tool.execute.after` | Tracks stats, scans bash errors for related memories |
|
||||
| **System transform** | `experimental.chat.system.transform` | Injects memory context (session memories, search results, error lookups) into system prompt |
|
||||
| **Compaction** | `experimental.session.compacting` | Stores session state memory, then injects prior memories into compaction context so nothing is lost |
|
||||
| **Shell env** | `shell.env` | Exports `MEM0_USER_ID`, `MEM0_APP_ID`, `MEM0_SESSION_ID`, and `MEM0_BRANCH` to shell |
|
||||
|
||||
## MCP Tools
|
||||
|
||||
| Tool | Description |
|
||||
|------|-------------|
|
||||
| `add_memory` | Save text or conversation history |
|
||||
| `search_memories` | Semantic search across memories |
|
||||
| `get_memories` | List memories with filters and pagination |
|
||||
| `get_memory` | Retrieve a specific memory by ID |
|
||||
| `update_memory` | Overwrite a memory's text by ID |
|
||||
| `delete_memory` | Delete a single memory by ID |
|
||||
| `delete_all_memories` | Bulk delete all memories in scope |
|
||||
| `delete_entities` | Delete an entity and its memories |
|
||||
| `list_entities` | List users/agents/apps stored in Mem0 |
|
||||
|
||||
## Verify
|
||||
|
||||
Start OpenCode and ask: *"Search my memories for recent decisions"*
|
||||
|
||||
If the `mem0` tools respond, you're all set.
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
| Problem | Fix |
|
||||
|---------|-----|
|
||||
| No tools appearing | Restart OpenCode after installing |
|
||||
| 401 Unauthorized | `echo $MEM0_API_KEY` must print your `m0-` key |
|
||||
| Plugin not loading | Run `opencode plugin @mem0/opencode-plugin` again |
|
||||
|
||||
## License
|
||||
|
||||
Apache-2.0
|
||||
@@ -0,0 +1,765 @@
|
||||
{
|
||||
"lockfileVersion": 1,
|
||||
"configVersion": 1,
|
||||
"workspaces": {
|
||||
"": {
|
||||
"name": "@mem0/opencode-plugin",
|
||||
"dependencies": {
|
||||
"@opencode-ai/plugin": "^1.0.162",
|
||||
"mem0ai": "^3.0.5",
|
||||
},
|
||||
"devDependencies": {
|
||||
"bun-types": ">=1.3.14",
|
||||
"typescript": "^5.7.3",
|
||||
},
|
||||
"peerDependencies": {
|
||||
"bun": ">=1.0.0",
|
||||
},
|
||||
},
|
||||
},
|
||||
"packages": {
|
||||
"@anthropic-ai/sdk": ["@anthropic-ai/sdk@0.40.1", "", { "dependencies": { "@types/node": "^18.11.18", "@types/node-fetch": "^2.6.4", "abort-controller": "^3.0.0", "agentkeepalive": "^4.2.1", "form-data-encoder": "1.7.2", "formdata-node": "^4.3.2", "node-fetch": "^2.6.7" } }, "sha512-DJMWm8lTEM9Lk/MSFL+V+ugF7jKOn0M2Ujvb5fN8r2nY14aHbGPZ1k6sgjL+tpJ3VuOGJNG+4R83jEpOuYPv8w=="],
|
||||
|
||||
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|
||||
|
||||
"@azure/core-auth": ["@azure/core-auth@1.10.1", "", { "dependencies": { "@azure/abort-controller": "^2.1.2", "@azure/core-util": "^1.13.0", "tslib": "^2.6.2" } }, "sha512-ykRMW8PjVAn+RS6ww5cmK9U2CyH9p4Q88YJwvUslfuMmN98w/2rdGRLPqJYObapBCdzBVeDgYWdJnFPFb7qzpg=="],
|
||||
|
||||
"@azure/core-client": ["@azure/core-client@1.10.1", "", { "dependencies": { "@azure/abort-controller": "^2.1.2", "@azure/core-auth": "^1.10.0", "@azure/core-rest-pipeline": "^1.22.0", "@azure/core-tracing": "^1.3.0", "@azure/core-util": "^1.13.0", "@azure/logger": "^1.3.0", "tslib": "^2.6.2" } }, "sha512-Nh5PhEOeY6PrnxNPsEHRr9eimxLwgLlpmguQaHKBinFYA/RU9+kOYVOQqOrTsCL+KSxrLLl1gD8Dk5BFW/7l/w=="],
|
||||
|
||||
"@azure/core-http-compat": ["@azure/core-http-compat@2.4.0", "", { "dependencies": { "@azure/abort-controller": "^2.1.2" }, "peerDependencies": { "@azure/core-client": "^1.10.0", "@azure/core-rest-pipeline": "^1.22.0" } }, "sha512-f1P96IB399YiN2ARYHP7EpZi3Bf3wH4SN2lGzrw7JVwm7bbsVYtf2iKSBwTywD2P62NOPZGHFSZi+6jjb75JuA=="],
|
||||
|
||||
"@azure/core-paging": ["@azure/core-paging@1.6.2", "", { "dependencies": { "tslib": "^2.6.2" } }, "sha512-YKWi9YuCU04B55h25cnOYZHxXYtEvQEbKST5vqRga7hWY9ydd3FZHdeQF8pyh+acWZvppw13M/LMGx0LABUVMA=="],
|
||||
|
||||
"@azure/core-rest-pipeline": ["@azure/core-rest-pipeline@1.23.0", "", { "dependencies": { "@azure/abort-controller": "^2.1.2", "@azure/core-auth": "^1.10.0", "@azure/core-tracing": "^1.3.0", "@azure/core-util": "^1.13.0", "@azure/logger": "^1.3.0", "@typespec/ts-http-runtime": "^0.3.4", "tslib": "^2.6.2" } }, "sha512-Evs1INHo+jUjwHi1T6SG6Ua/LHOQBCLuKEEE6efIpt4ZOoNonaT1kP32GoOcdNDbfqsD2445CPri3MubBy5DEQ=="],
|
||||
|
||||
"@azure/core-tracing": ["@azure/core-tracing@1.3.1", "", { "dependencies": { "tslib": "^2.6.2" } }, "sha512-9MWKevR7Hz8kNzzPLfX4EAtGM2b8mr50HPDBvio96bURP/9C+HjdH3sBlLSNNrvRAr5/k/svoH457gB5IKpmwQ=="],
|
||||
|
||||
"@azure/core-util": ["@azure/core-util@1.13.1", "", { "dependencies": { "@azure/abort-controller": "^2.1.2", "@typespec/ts-http-runtime": "^0.3.0", "tslib": "^2.6.2" } }, "sha512-XPArKLzsvl0Hf0CaGyKHUyVgF7oDnhKoP85Xv6M4StF/1AhfORhZudHtOyf2s+FcbuQ9dPRAjB8J2KvRRMUK2A=="],
|
||||
|
||||
"@azure/identity": ["@azure/identity@4.13.1", "", { "dependencies": { "@azure/abort-controller": "^2.0.0", "@azure/core-auth": "^1.9.0", "@azure/core-client": "^1.9.2", "@azure/core-rest-pipeline": "^1.17.0", "@azure/core-tracing": "^1.0.0", "@azure/core-util": "^1.11.0", "@azure/logger": "^1.0.0", "@azure/msal-browser": "^5.5.0", "@azure/msal-node": "^5.1.0", "open": "^10.1.0", "tslib": "^2.2.0" } }, "sha512-5C/2WD5Vb1lHnZS16dNQRPMjN6oV/Upba+C9nBIs15PmOi6A3ZGs4Lr2u60zw4S04gi+u3cEXiqTVP7M4Pz3kw=="],
|
||||
|
||||
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|
||||
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||||
|
||||
"@azure/msal-common": ["@azure/msal-common@16.6.2", "", {}, "sha512-hQjjsekAjB00cM1EmatWJlzhEoK2Qhz7Rj5gvM6tYf8iL7RM3tkxlpU9fG0+ofkulzg9AEEA6dIEnSmDr5ZqUA=="],
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|
||||
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|
||||
|
||||
"@azure/search-documents": ["@azure/search-documents@12.2.0", "", { "dependencies": { "@azure/core-auth": "^1.9.0", "@azure/core-client": "^1.9.2", "@azure/core-http-compat": "^2.1.2", "@azure/core-paging": "^1.6.2", "@azure/core-rest-pipeline": "^1.18.0", "@azure/core-tracing": "^1.2.0", "@azure/core-util": "^1.11.0", "@azure/logger": "^1.1.4", "events": "^3.0.0", "tslib": "^2.8.1" } }, "sha512-4+Qw+qaGqnkdUCq/vEFzk/bkROogTvdbPb1fmI8poxNfDDN1q2WHxBmhI7CYwesrBj1yXC4i5E0aISBxZqZi0g=="],
|
||||
|
||||
"@babel/code-frame": ["@babel/code-frame@7.29.7", "", { "dependencies": { "@babel/helper-validator-identifier": "^7.29.7", "js-tokens": "^4.0.0", "picocolors": "^1.1.1" } }, "sha512-Aup7aUOfpbAUg2ROOJN6Iw5f9DMBlzu0mIkm/malLQFN/YQgO48wCj0Kxa3sEHJvPVFg7siR+qRInwXd2qhQKw=="],
|
||||
|
||||
"@babel/helper-validator-identifier": ["@babel/helper-validator-identifier@7.29.7", "", {}, "sha512-qehxGkRj55h/ff8EMaJ+cYhyaKlHIxqYDn682wQD7RNp9UujOQsHog2uS0r2vzr4pW+sXf90NeeayjcNaX3fFg=="],
|
||||
|
||||
"@cfworker/json-schema": ["@cfworker/json-schema@4.1.1", "", {}, "sha512-gAmrUZSGtKc3AiBL71iNWxDsyUC5uMaKKGdvzYsBoTW/xi42JQHl7eKV2OYzCUqvc+D2RCcf7EXY2iCyFIk6og=="],
|
||||
|
||||
"@cloudflare/workers-types": ["@cloudflare/workers-types@4.20260527.1", "", {}, "sha512-GK+C05N4fGptp1uG+pbjC/7Udonz8EhMEYvYFnVKdLLnEGS9nsmVOFi/RLQr7tq9l/0UEzcWjudzeY2ssuqyIA=="],
|
||||
|
||||
"@fastify/busboy": ["@fastify/busboy@2.1.1", "", {}, "sha512-vBZP4NlzfOlerQTnba4aqZoMhE/a9HY7HRqoOPaETQcSQuWEIyZMHGfVu6w9wGtGK5fED5qRs2DteVCjOH60sA=="],
|
||||
|
||||
"@google/genai": ["@google/genai@1.52.0", "", { "dependencies": { "google-auth-library": "^10.3.0", "p-retry": "^4.6.2", "protobufjs": "^7.5.4", "ws": "^8.18.0" }, "peerDependencies": { "@modelcontextprotocol/sdk": "^1.25.2" }, "optionalPeers": ["@modelcontextprotocol/sdk"] }, "sha512-gwSvbpiN/17O9TbsqSsE/OzZcpv5Fo4RQjdngGgogtuB9RsyJ8ZHhX5KjHj1bp5N9snN2eK8LDGXSaWW2hof8Q=="],
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|
||||
"@jest/expect-utils": ["@jest/expect-utils@29.7.0", "", { "dependencies": { "jest-get-type": "^29.6.3" } }, "sha512-GlsNBWiFQFCVi9QVSx7f5AgMeLxe9YCCs5PuP2O2LdjDAA8Jh9eX7lA1Jq/xdXw3Wb3hyvlFNfZIfcRetSzYcA=="],
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|
||||
"@jest/schemas": ["@jest/schemas@29.6.3", "", { "dependencies": { "@sinclair/typebox": "^0.27.8" } }, "sha512-mo5j5X+jIZmJQveBKeS/clAueipV7KgiX1vMgCxam1RNYiqE1w62n0/tJJnHtjW8ZHcQco5gY85jA3mi0L+nSA=="],
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||||
|
||||
"@jest/types": ["@jest/types@29.6.3", "", { "dependencies": { "@jest/schemas": "^29.6.3", "@types/istanbul-lib-coverage": "^2.0.0", "@types/istanbul-reports": "^3.0.0", "@types/node": "*", "@types/yargs": "^17.0.8", "chalk": "^4.0.0" } }, "sha512-u3UPsIilWKOM3F9CXtrG8LEJmNxwoCQC/XVj4IKYXvvpx7QIi/Kg1LI5uDmDpKlac62NUtX7eLjRh+jVZcLOzw=="],
|
||||
|
||||
"@langchain/core": ["@langchain/core@1.1.48", "", { "dependencies": { "@cfworker/json-schema": "^4.0.2", "@standard-schema/spec": "^1.1.0", "js-tiktoken": "^1.0.12", "langsmith": ">=0.5.0 <1.0.0", "mustache": "^4.2.0", "p-queue": "^6.6.2", "zod": "^3.25.76 || ^4" } }, "sha512-fQU6Guyb1pwc2fEplmA8FPbKfOMAofjnyJzExevro0FxEiuGHE18Ov/ZHmT9trWCDTZRI9eW1VIc6aChxV8pAQ=="],
|
||||
|
||||
"@mistralai/mistralai": ["@mistralai/mistralai@1.15.1", "", { "dependencies": { "ws": "^8.18.0", "zod": "^3.25.0 || ^4.0.0", "zod-to-json-schema": "^3.24.1" } }, "sha512-fb995eiz3r0KsBGtRjFV+/iLbX+UpfalxpF+YitT3R6ukrPD4PN+FGwwmYcRFhNAzVzDUtTVxQYnjQWEnwV5nw=="],
|
||||
|
||||
"@mongodb-js/saslprep": ["@mongodb-js/saslprep@1.4.11", "", { "dependencies": { "sparse-bitfield": "^3.0.3" } }, "sha512-o9rAHc0IpIjuPSxRutWpE1F62x7n+4mVS4rCNHkzhIUMQcc18bb6xEq5wd2NdN0WjepIyXIppRshYI2kQDOZVA=="],
|
||||
|
||||
"@msgpackr-extract/msgpackr-extract-darwin-arm64": ["@msgpackr-extract/msgpackr-extract-darwin-arm64@3.0.4", "", { "os": "darwin", "cpu": "arm64" }, "sha512-LCkGo6JDfaBhgST7UpPWgNgLINpcpabaHfyz5OBx75nUYxBsaEPxjnyNjWpeb/xBup/682QnBfRBy2/LvPutZQ=="],
|
||||
|
||||
"@msgpackr-extract/msgpackr-extract-darwin-x64": ["@msgpackr-extract/msgpackr-extract-darwin-x64@3.0.4", "", { "os": "darwin", "cpu": "x64" }, "sha512-zExlW9zUJKZH/tOtVMttwjKa4Xm/3KcNjnE3dPN92uCktwavMxpgCA3MoJK/DOnTWsQgo224OaST27/mPNAf+w=="],
|
||||
|
||||
"@msgpackr-extract/msgpackr-extract-linux-arm": ["@msgpackr-extract/msgpackr-extract-linux-arm@3.0.4", "", { "os": "linux", "cpu": "arm" }, "sha512-Tg3yX65f5GbtXLkrYEHE5oibZG9epyYWas7FogTTEJeDEF9JlXJzKgXaNhT3UXlTOeA+AfZpYZYZ0uPj7Cfquw=="],
|
||||
|
||||
"@msgpackr-extract/msgpackr-extract-linux-arm64": ["@msgpackr-extract/msgpackr-extract-linux-arm64@3.0.4", "", { "os": "linux", "cpu": "arm64" }, "sha512-dgX0P/9wGPJeHFBG+ZmhgE6bmtMt7NP5CRBGyyktpopdk/mW4POnrpQsSLtKI1dwpc+pPLuXHDh6vvskyQE/sw=="],
|
||||
|
||||
"@msgpackr-extract/msgpackr-extract-linux-x64": ["@msgpackr-extract/msgpackr-extract-linux-x64@3.0.4", "", { "os": "linux", "cpu": "x64" }, "sha512-8TNXMEjJc3QEy7R/x1INhgiU+XakDAFUzBhaz7+Rbrs8NH5UQeHQxxmzsSBJGyV6I1jW79undiQm8tOI+D+8FQ=="],
|
||||
|
||||
"@msgpackr-extract/msgpackr-extract-win32-x64": ["@msgpackr-extract/msgpackr-extract-win32-x64@3.0.4", "", { "os": "win32", "cpu": "x64" }, "sha512-CmCXPQrkbwExx3j946/PtHWHbYJiCRBRDl4BlkRQcJB/YOwQxJRTpoo7aTsortjgoJ1x7opzTSxn7C+ASSLVjQ=="],
|
||||
|
||||
"@opencode-ai/plugin": ["@opencode-ai/plugin@1.15.11", "", { "dependencies": { "@opencode-ai/sdk": "1.15.11", "effect": "4.0.0-beta.66", "zod": "4.1.8" }, "peerDependencies": { "@opentui/core": ">=0.2.15", "@opentui/keymap": ">=0.2.15", "@opentui/solid": ">=0.2.15" }, "optionalPeers": ["@opentui/core", "@opentui/keymap", "@opentui/solid"] }, "sha512-RDvYDCHO0+3OAGD590oDQqtryrENrUW04SjtoA4sgRV2efpZeBFjx3TnonBsXKq6nWqYg172nhltUEZsihGnXQ=="],
|
||||
|
||||
"@opencode-ai/sdk": ["@opencode-ai/sdk@1.15.11", "", { "dependencies": { "cross-spawn": "7.0.6" } }, "sha512-IyYyDVsO8SKbKbkSadHpDuYnYC+2vmEeLU+rW+rH2M54Sigq6l3gDHno16+U6SRut+lowbph7v/ry3WbV67V3w=="],
|
||||
|
||||
"@oven/bun-darwin-aarch64": ["@oven/bun-darwin-aarch64@1.3.14", "", { "os": "darwin", "cpu": "arm64" }, "sha512-Omj20SuiHBOUjUBIyqtkNjSUIjOtEOJwmbix/ZyFH4BaQ6OZTaaRWIR4TjHVz0yadHgli6lLTiAh1uarnvD49A=="],
|
||||
|
||||
"@oven/bun-darwin-x64": ["@oven/bun-darwin-x64@1.3.14", "", { "os": "darwin", "cpu": "x64" }, "sha512-FFj3QdU/OhlDyZOJ8CWfN5eWLpRlT4qjZg7lMQi7jA6GuoY5ajlO1zWLP/MuHYRSbXQUvV52RejNi8DVnAp13w=="],
|
||||
|
||||
"@oven/bun-darwin-x64-baseline": ["@oven/bun-darwin-x64-baseline@1.3.14", "", { "os": "darwin", "cpu": "x64" }, "sha512-OSfsTZstc898HHElhU4NccaBGOSSDn5VfahiVTnidZ9B/+wb7WTyfZJaBeJcfjwJ9H2W9uTh2TGtl3UfcXgV9g=="],
|
||||
|
||||
"@oven/bun-freebsd-aarch64": ["@oven/bun-freebsd-aarch64@1.3.14", "", { "os": "freebsd", "cpu": "arm64" }, "sha512-LIKrXaFxAHybVO5Pf+9XP2FHUj/5APvXTUKk9dqHm5iFz4oH+W24cmhjkJirNujh9hKeTyrpWSe3no9JZKowIw=="],
|
||||
|
||||
"@oven/bun-freebsd-x64": ["@oven/bun-freebsd-x64@1.3.14", "", { "os": "freebsd", "cpu": "x64" }, "sha512-uwD+fGUH1ADpIF3B1U2jWzzb20QwRLZfj5QZ28GUCGrAJ/nTmWrD6YYGsblCY1wuhldRez3lU40AyuvSCyLYmw=="],
|
||||
|
||||
"@oven/bun-linux-aarch64": ["@oven/bun-linux-aarch64@1.3.14", "", { "os": "linux", "cpu": "arm64" }, "sha512-X5SsPZHs+iYO8R/efIcRtc7gT2Q2DgPfliCxEkx4cXBumwkw0c/EsHMNwH3EgGpCDaZ7IYVPhpCG/xBOQHEwZw=="],
|
||||
|
||||
"@oven/bun-linux-aarch64-android": ["@oven/bun-linux-aarch64-android@1.3.14", "", { "os": "android", "cpu": "arm64" }, "sha512-y4kq5b85lsrmFb9Xvi4w9mA5IEFJkLMrSmYn06q24KjL9rUWDWO3VFZEtteZxUN5+ec3Zm5S8OnJw1umaCbVjA=="],
|
||||
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||||
|
||||
"mongodb-connection-string-url/whatwg-url/tr46": ["tr46@5.1.1", "", { "dependencies": { "punycode": "^2.3.1" } }, "sha512-hdF5ZgjTqgAntKkklYw0R03MG2x/bSzTtkxmIRw/sTNV8YXsCJ1tfLAX23lhxhHJlEf3CRCOCGGWw3vI3GaSPw=="],
|
||||
|
||||
"mongodb-connection-string-url/whatwg-url/webidl-conversions": ["webidl-conversions@7.0.0", "", {}, "sha512-VwddBukDzu71offAQR975unBIGqfKZpM+8ZX6ySk8nYhVoo5CYaZyzt3YBvYtRtO+aoGlqxPg/B87NGVZ/fu6g=="],
|
||||
|
||||
"natural/pg/pg-types": ["pg-types@2.2.0", "", { "dependencies": { "pg-int8": "1.0.1", "postgres-array": "~2.0.0", "postgres-bytea": "~1.0.0", "postgres-date": "~1.0.4", "postgres-interval": "^1.1.0" } }, "sha512-qTAAlrEsl8s4OiEQY69wDvcMIdQN6wdz5ojQiOy6YRMuynxenON0O5oCpJI6lshc6scgAY8qvJ2On/p+CXY0GA=="],
|
||||
|
||||
"natural/redis/@redis/bloom": ["@redis/bloom@5.12.1", "", { "peerDependencies": { "@redis/client": "^5.12.1" } }, "sha512-PUUfv+ms7jgPSBVoo/DN4AkPHj4D5TZSd6SbJX7egzBplkYUcKmHRE8RKia7UtZ8bSQbLguLvxVO+asKtQfZWA=="],
|
||||
|
||||
"natural/redis/@redis/client": ["@redis/client@5.12.1", "", { "dependencies": { "cluster-key-slot": "1.1.2" }, "peerDependencies": { "@node-rs/xxhash": "^1.1.0", "@opentelemetry/api": ">=1 <2" }, "optionalPeers": ["@node-rs/xxhash", "@opentelemetry/api"] }, "sha512-7aPGWeqA3uFm43o19umzdl16CEjK/JQGtSXVPevplTaOU3VJA/rseBC1QvYUz9lLDIMBimc4SW/zrW4S89BaCA=="],
|
||||
|
||||
"natural/redis/@redis/json": ["@redis/json@5.12.1", "", { "peerDependencies": { "@redis/client": "^5.12.1" } }, "sha512-eOze75esLve4vfqDel7aMX08CNaiLLQS2fV8mpRN9NxPe1rVR4vQyYiW/OgtGUysF6QOr9ANhfxABKNOJfXdKg=="],
|
||||
|
||||
"natural/redis/@redis/search": ["@redis/search@5.12.1", "", { "peerDependencies": { "@redis/client": "^5.12.1" } }, "sha512-ItlxbxC9cKI6IU1TLWoczwJCRb6TdmkEpWv05UrPawqaAnWGRu3rcIqsc5vN483T2fSociuyV1UkWIL5I4//2w=="],
|
||||
|
||||
"natural/redis/@redis/time-series": ["@redis/time-series@5.12.1", "", { "peerDependencies": { "@redis/client": "^5.12.1" } }, "sha512-c6JL6E3EcZJuNqKFz+KM+l9l5mpcQiKvTwgA3blt5glWJ8hjDk0yeHN3beE/MpqYIQ8UEX44ItQzgkE/gCBELQ=="],
|
||||
|
||||
"openai/@types/node/undici-types": ["undici-types@5.26.5", "", {}, "sha512-JlCMO+ehdEIKqlFxk6IfVoAUVmgz7cU7zD/h9XZ0qzeosSHmUJVOzSQvvYSYWXkFXC+IfLKSIffhv0sVZup6pA=="],
|
||||
|
||||
"pg/pg-types/postgres-array": ["postgres-array@2.0.0", "", {}, "sha512-VpZrUqU5A69eQyW2c5CA1jtLecCsN2U/bD6VilrFDWq5+5UIEVO7nazS3TEcHf1zuPYO/sqGvUvW62g86RXZuA=="],
|
||||
|
||||
"pg/pg-types/postgres-bytea": ["postgres-bytea@1.0.1", "", {}, "sha512-5+5HqXnsZPE65IJZSMkZtURARZelel2oXUEO8rH83VS/hxH5vv1uHquPg5wZs8yMAfdv971IU+kcPUczi7NVBQ=="],
|
||||
|
||||
"pg/pg-types/postgres-date": ["postgres-date@1.0.7", "", {}, "sha512-suDmjLVQg78nMK2UZ454hAG+OAW+HQPZ6n++TNDUX+L0+uUlLywnoxJKDou51Zm+zTCjrCl0Nq6J9C5hP9vK/Q=="],
|
||||
|
||||
"pg/pg-types/postgres-interval": ["postgres-interval@1.2.0", "", { "dependencies": { "xtend": "^4.0.0" } }, "sha512-9ZhXKM/rw350N1ovuWHbGxnGh/SNJ4cnxHiM0rxE4VN41wsg8P8zWn9hv/buK00RP4WvlOyr/RBDiptyxVbkZQ=="],
|
||||
|
||||
"natural/pg/pg-types/postgres-array": ["postgres-array@2.0.0", "", {}, "sha512-VpZrUqU5A69eQyW2c5CA1jtLecCsN2U/bD6VilrFDWq5+5UIEVO7nazS3TEcHf1zuPYO/sqGvUvW62g86RXZuA=="],
|
||||
|
||||
"natural/pg/pg-types/postgres-bytea": ["postgres-bytea@1.0.1", "", {}, "sha512-5+5HqXnsZPE65IJZSMkZtURARZelel2oXUEO8rH83VS/hxH5vv1uHquPg5wZs8yMAfdv971IU+kcPUczi7NVBQ=="],
|
||||
|
||||
"natural/pg/pg-types/postgres-date": ["postgres-date@1.0.7", "", {}, "sha512-suDmjLVQg78nMK2UZ454hAG+OAW+HQPZ6n++TNDUX+L0+uUlLywnoxJKDou51Zm+zTCjrCl0Nq6J9C5hP9vK/Q=="],
|
||||
|
||||
"natural/pg/pg-types/postgres-interval": ["postgres-interval@1.2.0", "", { "dependencies": { "xtend": "^4.0.0" } }, "sha512-9ZhXKM/rw350N1ovuWHbGxnGh/SNJ4cnxHiM0rxE4VN41wsg8P8zWn9hv/buK00RP4WvlOyr/RBDiptyxVbkZQ=="],
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,254 @@
|
||||
#!/usr/bin/env bun
|
||||
import {
|
||||
readFileSync,
|
||||
writeFileSync,
|
||||
existsSync,
|
||||
mkdirSync,
|
||||
copyFileSync,
|
||||
readdirSync,
|
||||
rmSync,
|
||||
statSync,
|
||||
} from "fs";
|
||||
import { join, dirname } from "path";
|
||||
import { homedir } from "os";
|
||||
|
||||
const PLUGIN_NAME = "@mem0/opencode-plugin";
|
||||
const MCP_CONFIG = {
|
||||
mem0: {
|
||||
type: "remote",
|
||||
url: "https://mcp.mem0.ai/mcp/",
|
||||
headers: {
|
||||
Authorization: "Token {env:MEM0_API_KEY}",
|
||||
},
|
||||
oauth: false,
|
||||
},
|
||||
};
|
||||
|
||||
const SKILLS_NAMESPACE = "mem0";
|
||||
|
||||
function getConfigDir(): string {
|
||||
const dir = join(homedir(), ".config", "opencode");
|
||||
if (!existsSync(dir)) mkdirSync(dir, { recursive: true });
|
||||
return dir;
|
||||
}
|
||||
|
||||
function getConfigPath(): string {
|
||||
const configDir = getConfigDir();
|
||||
const jsonc = join(configDir, "opencode.jsonc");
|
||||
if (existsSync(jsonc)) return jsonc;
|
||||
return join(configDir, "opencode.json");
|
||||
}
|
||||
|
||||
function stripJsonComments(text: string): string {
|
||||
let result = "";
|
||||
let i = 0;
|
||||
let inString = false;
|
||||
let escape = false;
|
||||
while (i < text.length) {
|
||||
const ch = text[i];
|
||||
if (escape) {
|
||||
result += ch;
|
||||
escape = false;
|
||||
i++;
|
||||
continue;
|
||||
}
|
||||
if (inString) {
|
||||
if (ch === "\\") escape = true;
|
||||
else if (ch === '"') inString = false;
|
||||
result += ch;
|
||||
i++;
|
||||
continue;
|
||||
}
|
||||
if (ch === '"') {
|
||||
inString = true;
|
||||
result += ch;
|
||||
i++;
|
||||
continue;
|
||||
}
|
||||
if (ch === "/" && text[i + 1] === "/") {
|
||||
while (i < text.length && text[i] !== "\n") i++;
|
||||
continue;
|
||||
}
|
||||
if (ch === "/" && text[i + 1] === "*") {
|
||||
i += 2;
|
||||
while (i < text.length && !(text[i] === "*" && text[i + 1] === "/")) i++;
|
||||
i += 2;
|
||||
continue;
|
||||
}
|
||||
result += ch;
|
||||
i++;
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
function resolvePluginDir(): string {
|
||||
try {
|
||||
return dirname(new URL(import.meta.url).pathname);
|
||||
} catch {}
|
||||
return __dirname ?? process.cwd();
|
||||
}
|
||||
|
||||
function findSkillsDir(): string {
|
||||
const base = resolvePluginDir();
|
||||
const candidates = [
|
||||
join(base, "opencode-skills"),
|
||||
join(dirname(base), "opencode-skills"),
|
||||
join(base, "..", "opencode-skills"),
|
||||
];
|
||||
for (const c of candidates) {
|
||||
try {
|
||||
if (existsSync(c) && statSync(c).isDirectory()) return c;
|
||||
} catch {}
|
||||
}
|
||||
return "";
|
||||
}
|
||||
|
||||
function installSkills(): number {
|
||||
const skillsSource = findSkillsDir();
|
||||
if (!skillsSource) {
|
||||
console.log(" ! Skills directory not found — skipping slash command install");
|
||||
return 0;
|
||||
}
|
||||
|
||||
const skillsTarget = join(getConfigDir(), "skills");
|
||||
if (!existsSync(skillsTarget)) mkdirSync(skillsTarget, { recursive: true });
|
||||
|
||||
let count = 0;
|
||||
const entries = readdirSync(skillsSource);
|
||||
|
||||
for (const name of entries) {
|
||||
const skillDir = join(skillsSource, name);
|
||||
try {
|
||||
if (!statSync(skillDir).isDirectory()) continue;
|
||||
} catch {
|
||||
continue;
|
||||
}
|
||||
|
||||
const skillFile = join(skillDir, "SKILL.md");
|
||||
if (!existsSync(skillFile)) continue;
|
||||
|
||||
const targetDir = join(skillsTarget, `${SKILLS_NAMESPACE}-${name}`);
|
||||
if (!existsSync(targetDir)) mkdirSync(targetDir, { recursive: true });
|
||||
|
||||
copyFileSync(skillFile, join(targetDir, "SKILL.md"));
|
||||
count++;
|
||||
}
|
||||
|
||||
return count;
|
||||
}
|
||||
|
||||
function uninstallSkills(): number {
|
||||
const skillsTarget = join(getConfigDir(), "skills");
|
||||
if (!existsSync(skillsTarget)) return 0;
|
||||
|
||||
let count = 0;
|
||||
const entries = readdirSync(skillsTarget);
|
||||
|
||||
for (const name of entries) {
|
||||
if (!name.startsWith(`${SKILLS_NAMESPACE}-`)) continue;
|
||||
const fullPath = join(skillsTarget, name);
|
||||
try {
|
||||
if (!statSync(fullPath).isDirectory()) continue;
|
||||
rmSync(fullPath, { recursive: true });
|
||||
count++;
|
||||
} catch {}
|
||||
}
|
||||
|
||||
return count;
|
||||
}
|
||||
|
||||
function install() {
|
||||
console.log("Installing Mem0 plugin for OpenCode...\n");
|
||||
|
||||
const configPath = getConfigPath();
|
||||
let config: any = {};
|
||||
|
||||
if (existsSync(configPath)) {
|
||||
try {
|
||||
const raw = readFileSync(configPath, "utf-8");
|
||||
config = JSON.parse(stripJsonComments(raw));
|
||||
} catch {
|
||||
console.log(` ! Could not parse ${configPath}, creating fresh config`);
|
||||
config = {};
|
||||
}
|
||||
}
|
||||
|
||||
if (!Array.isArray(config.plugin)) config.plugin = [];
|
||||
if (!config.plugin.includes(PLUGIN_NAME)) {
|
||||
config.plugin.push(PLUGIN_NAME);
|
||||
console.log(` + Added "${PLUGIN_NAME}" to plugin array`);
|
||||
} else {
|
||||
console.log(` ~ "${PLUGIN_NAME}" already in plugin array`);
|
||||
}
|
||||
|
||||
if (!config.mcp) config.mcp = {};
|
||||
if (!config.mcp.mem0) {
|
||||
config.mcp.mem0 = MCP_CONFIG.mem0;
|
||||
console.log(" + Added mem0 MCP server config");
|
||||
} else {
|
||||
console.log(" ~ mem0 MCP server already configured");
|
||||
}
|
||||
|
||||
writeFileSync(configPath, JSON.stringify(config, null, 2) + "\n");
|
||||
console.log(`\n Wrote ${configPath}`);
|
||||
|
||||
const skillCount = installSkills();
|
||||
if (skillCount > 0) {
|
||||
console.log(` + Installed ${skillCount} slash commands to ~/.config/opencode/skills/`);
|
||||
}
|
||||
|
||||
console.log("");
|
||||
|
||||
if (!process.env.MEM0_API_KEY) {
|
||||
console.log(" ! MEM0_API_KEY is not set in your environment.");
|
||||
console.log(
|
||||
' Run: echo \'export MEM0_API_KEY="m0-your-key"\' >> ~/.zshrc && source ~/.zshrc',
|
||||
);
|
||||
console.log(
|
||||
" Get a free key at: https://app.mem0.ai/dashboard/api-keys\n",
|
||||
);
|
||||
} else {
|
||||
console.log(" MEM0_API_KEY detected\n");
|
||||
}
|
||||
|
||||
console.log("Done! Restart OpenCode to activate Mem0.");
|
||||
console.log(" Then run /mem0-onboard in the TUI to complete setup.\n");
|
||||
}
|
||||
|
||||
function uninstall() {
|
||||
const configPath = getConfigPath();
|
||||
if (!existsSync(configPath)) {
|
||||
console.log("No OpenCode config found. Nothing to remove.");
|
||||
return;
|
||||
}
|
||||
|
||||
const raw = readFileSync(configPath, "utf-8");
|
||||
const config = JSON.parse(stripJsonComments(raw));
|
||||
|
||||
if (Array.isArray(config.plugin)) {
|
||||
config.plugin = config.plugin.filter((p: string) => p !== PLUGIN_NAME);
|
||||
if (config.plugin.length === 0) delete config.plugin;
|
||||
}
|
||||
|
||||
if (config.mcp?.mem0) {
|
||||
delete config.mcp.mem0;
|
||||
if (Object.keys(config.mcp).length === 0) delete config.mcp;
|
||||
}
|
||||
|
||||
writeFileSync(configPath, JSON.stringify(config, null, 2) + "\n");
|
||||
console.log(` Removed plugin + MCP from ${configPath}`);
|
||||
|
||||
const skillCount = uninstallSkills();
|
||||
if (skillCount > 0) {
|
||||
console.log(` Removed ${skillCount} slash commands from ~/.config/opencode/skills/`);
|
||||
}
|
||||
|
||||
console.log("Restart OpenCode to complete removal.");
|
||||
}
|
||||
|
||||
const cmd = process.argv[2];
|
||||
if (cmd === "uninstall" || cmd === "remove") {
|
||||
uninstall();
|
||||
} else {
|
||||
install();
|
||||
}
|
||||
@@ -0,0 +1,744 @@
|
||||
// Mem0 memory plugin for OpenCode: captures and recalls memories across sessions
|
||||
// (add / search / manage) via the Mem0 platform, wired through OpenCode plugin hooks.
|
||||
import type { Plugin } from "@opencode-ai/plugin";
|
||||
import { MemoryClient } from "mem0ai";
|
||||
import { userInfo } from "os";
|
||||
import { basename, resolve, dirname } from "path";
|
||||
import { randomBytes } from "crypto";
|
||||
import { existsSync, readdirSync, cpSync, mkdirSync, readFileSync, writeFileSync } from "fs";
|
||||
import { homedir } from "os";
|
||||
import { join } from "path";
|
||||
import { createHash } from "crypto";
|
||||
|
||||
async function getUserId(): Promise<string> {
|
||||
if (process.env.MEM0_USER_ID) return process.env.MEM0_USER_ID;
|
||||
try {
|
||||
return userInfo().username;
|
||||
} catch {}
|
||||
return process.env.USER || process.env.USERNAME || "unknown";
|
||||
}
|
||||
|
||||
async function getProjectId($: any): Promise<string> {
|
||||
if (process.env.MEM0_APP_ID) return process.env.MEM0_APP_ID;
|
||||
try {
|
||||
const r = await $`git remote get-url origin`.quiet();
|
||||
const remote = r.stdout.toString().trim();
|
||||
const m = remote.match(/[:/]([^/]+\/[^/]+?)(?:\.git)?$/);
|
||||
if (m) return m[1].replace("/", "-");
|
||||
} catch {}
|
||||
return basename(process.cwd());
|
||||
}
|
||||
|
||||
async function getBranch($: any): Promise<string> {
|
||||
try {
|
||||
const r = await $`git branch --show-current`.quiet();
|
||||
return r.stdout.toString().trim() || "main";
|
||||
} catch {}
|
||||
return "main";
|
||||
}
|
||||
|
||||
function extractMemories(res: any): Array<{ memory: string; id: string }> {
|
||||
const arr = res?.results ?? res;
|
||||
if (!Array.isArray(arr)) return [];
|
||||
return arr.map((m: any) => ({ memory: m.memory ?? "", id: m.id ?? "" }));
|
||||
}
|
||||
|
||||
function generateSessionId(): string {
|
||||
const ts = Math.floor(Date.now() / 1000);
|
||||
const rnd = randomBytes(3).toString("hex");
|
||||
return `ses_${ts}_${rnd}`;
|
||||
}
|
||||
|
||||
const SECRET_PATTERNS = [
|
||||
/sk-[A-Za-z0-9]{20,}/g,
|
||||
/m0-[A-Za-z0-9]{20,}/g,
|
||||
/AKIA[0-9A-Z]{16}/g,
|
||||
/xox[baprs]-[A-Za-z0-9-]{20,}/g,
|
||||
/ghp_[A-Za-z0-9]{36,}/g,
|
||||
/gho_[A-Za-z0-9]{36,}/g,
|
||||
];
|
||||
|
||||
function redact(text: string): string {
|
||||
let out = text;
|
||||
for (const re of SECRET_PATTERNS) {
|
||||
out = out.replace(re, "[REDACTED]");
|
||||
}
|
||||
return out;
|
||||
}
|
||||
|
||||
function formatAge(createdAt: string): string {
|
||||
try {
|
||||
const dt = new Date(createdAt);
|
||||
const now = Date.now();
|
||||
const seconds = Math.floor((now - dt.getTime()) / 1000);
|
||||
if (seconds < 3600) return `${Math.floor(seconds / 60)}m ago`;
|
||||
if (seconds < 86400) return `${Math.floor(seconds / 3600)}h ago`;
|
||||
const days = Math.floor(seconds / 86400);
|
||||
if (days === 1) return "1d ago";
|
||||
if (days < 30) return `${days}d ago`;
|
||||
return `${Math.floor(days / 30)}mo ago`;
|
||||
} catch {
|
||||
return "";
|
||||
}
|
||||
}
|
||||
|
||||
const TYPE_ICONS: Record<string, string> = {
|
||||
decision: "⚖️",
|
||||
anti_pattern: "🔴",
|
||||
bug_fix: "🔴",
|
||||
convention: "🔄",
|
||||
task_learning: "🔵",
|
||||
user_preference: "🟣",
|
||||
session_summary: "📋",
|
||||
session_state: "📋",
|
||||
project_profile: "📖",
|
||||
compact_summary: "📋",
|
||||
auto_capture: "✅",
|
||||
};
|
||||
|
||||
const FILE_READ_GATE_MIN_BYTES = 1500;
|
||||
|
||||
function loadGlobalSearch(): boolean {
|
||||
try {
|
||||
const settingsPath = join(homedir(), ".mem0", "settings.json");
|
||||
if (!existsSync(settingsPath)) return false;
|
||||
const settings = JSON.parse(readFileSync(settingsPath, "utf8"));
|
||||
return settings.global_search === true;
|
||||
} catch {}
|
||||
return false;
|
||||
}
|
||||
|
||||
const CODING_CATEGORIES = [
|
||||
"architecture_decisions", "api_design", "data_models", "algorithms",
|
||||
"dependencies", "environment_setup", "testing_strategy", "debugging_notes",
|
||||
"performance", "security", "deployment", "code_conventions",
|
||||
"error_handling", "refactoring_history", "integrations", "onboarding",
|
||||
"project_meta",
|
||||
];
|
||||
|
||||
function categoriesFingerprint(): string {
|
||||
const sorted = [...CODING_CATEGORIES].sort();
|
||||
return createHash("sha256").update(sorted.join("\n")).digest("hex").slice(0, 16);
|
||||
}
|
||||
|
||||
function apiKeyFingerprint(apiKey: string): string {
|
||||
return createHash("sha256").update(apiKey).digest("hex").slice(0, 16);
|
||||
}
|
||||
|
||||
async function autoSetupCategories(mem0: MemoryClient, apiKey: string): Promise<void> {
|
||||
const stateDir = join(homedir(), ".mem0");
|
||||
const stateFile = join(stateDir, "categories_setup.json");
|
||||
const keyFp = apiKeyFingerprint(apiKey);
|
||||
const catFp = categoriesFingerprint();
|
||||
|
||||
let state: Record<string, string> = {};
|
||||
try {
|
||||
if (existsSync(stateFile)) {
|
||||
state = JSON.parse(readFileSync(stateFile, "utf8"));
|
||||
}
|
||||
} catch {}
|
||||
|
||||
if (state[keyFp] === catFp) return;
|
||||
|
||||
try {
|
||||
const project = await mem0.getProject({ fields: ["customCategories"] });
|
||||
const existing: string[] = (project as any)?.custom_categories ?? (project as any)?.customCategories ?? [];
|
||||
const sortedExisting = [...existing].sort();
|
||||
const sortedTarget = [...CODING_CATEGORIES].sort();
|
||||
if (JSON.stringify(sortedExisting) === JSON.stringify(sortedTarget)) {
|
||||
state[keyFp] = catFp;
|
||||
mkdirSync(stateDir, { recursive: true });
|
||||
writeFileSync(stateFile, JSON.stringify(state, null, 2) + "\n");
|
||||
return;
|
||||
}
|
||||
|
||||
await mem0.updateProject({ customCategories: CODING_CATEGORIES as any });
|
||||
|
||||
state[keyFp] = catFp;
|
||||
mkdirSync(stateDir, { recursive: true });
|
||||
writeFileSync(stateFile, JSON.stringify(state, null, 2) + "\n");
|
||||
} catch {}
|
||||
}
|
||||
|
||||
const NUDGE_RE =
|
||||
/\b(remember\s+(this|that)|memorize|save\s+this|note\s+(this|that)|don'?t\s+forget|always\s+remember|never\s+forget|keep\s+(this|that)\s+in\s+(mind|memory)|store\s+(this|that))\b/i;
|
||||
|
||||
const RESUME_RE =
|
||||
/where\s+(did\s+)?(we|I)\s+(leave|left)\s+off|continue\s+(from\s+)?(where|last)|what\s+were\s+we\s+(working|doing)|pick\s+up\s+where|resume\s+(from\s+|where\s+)|what.s\s+the\s+(current|latest)\s+(state|status)|catch\s+me\s+up|where\s+are\s+we/i;
|
||||
|
||||
const ERROR_STRONG_RE =
|
||||
/Traceback \(most recent call last\)|panic: |FATAL:|error\[E\d+\]/;
|
||||
const ERROR_MULTI_RE = /(Error:|Exception:)/g;
|
||||
|
||||
const MEM0_MCP_RE = /mem0.*(?:add_memory|search_memories|get_memor|delete_memor|update_memory|delete_entities|list_entities)/i;
|
||||
const WRITE_TOOLS = new Set(["Write", "Edit", "MultiEdit", "write", "edit", "multiEdit"]);
|
||||
|
||||
function isMem0Tool(name: string): boolean {
|
||||
return MEM0_MCP_RE.test(name);
|
||||
}
|
||||
|
||||
function isMem0AddMemory(name: string): boolean {
|
||||
return /mem0.*add_memory/i.test(name);
|
||||
}
|
||||
|
||||
function isMem0SearchOrGet(name: string): boolean {
|
||||
return /mem0.*(search_memories|get_memories)/i.test(name);
|
||||
}
|
||||
|
||||
function isMem0DeleteAll(name: string): boolean {
|
||||
return /mem0.*delete_all_memories/i.test(name);
|
||||
}
|
||||
|
||||
function extractUserText(input: any, output: any): string {
|
||||
const parts: any[] = output?.parts;
|
||||
if (Array.isArray(parts)) {
|
||||
return parts
|
||||
.filter((p: any) => p.type === "text" && !p.synthetic)
|
||||
.map((p: any) => p.text ?? "")
|
||||
.join("\n");
|
||||
}
|
||||
const msg = output?.message ?? input?.message;
|
||||
if (typeof msg?.content === "string") return msg.content;
|
||||
if (typeof msg?.text === "string") return msg.text;
|
||||
return "";
|
||||
}
|
||||
|
||||
function installSkills(projectDir: string): void {
|
||||
const pluginDir = dirname(dirname(import.meta.filename));
|
||||
const srcSkills = resolve(pluginDir, "opencode-skills");
|
||||
if (!existsSync(srcSkills)) return;
|
||||
|
||||
const destSkills = resolve(projectDir, ".opencode", "skills");
|
||||
const destCommands = resolve(projectDir, ".opencode", "commands");
|
||||
try {
|
||||
const skills = readdirSync(srcSkills, { withFileTypes: true });
|
||||
for (const entry of skills) {
|
||||
if (!entry.isDirectory()) continue;
|
||||
const dest = resolve(destSkills, `mem0-${entry.name}`);
|
||||
if (existsSync(dest)) continue;
|
||||
cpSync(resolve(srcSkills, entry.name), dest, { recursive: true });
|
||||
}
|
||||
|
||||
for (const entry of skills) {
|
||||
if (!entry.isDirectory()) continue;
|
||||
const cmdFile = resolve(destCommands, `mem0-${entry.name}.md`);
|
||||
if (existsSync(cmdFile)) continue;
|
||||
const skillMd = resolve(srcSkills, entry.name, "SKILL.md");
|
||||
if (!existsSync(skillMd)) continue;
|
||||
let desc = "Mem0 " + entry.name + " skill";
|
||||
try {
|
||||
const content = readFileSync(skillMd, "utf8");
|
||||
const m = content.match(/^description:\s*(.+)$/m);
|
||||
if (m) desc = m[1].trim();
|
||||
} catch {}
|
||||
const cmdContent = `---\ndescription: ${desc}\n---\nLoad and follow the skill at .opencode/skills/mem0-${entry.name}/SKILL.md\n\nUse the mem0 MCP tools (search_memories, get_memories, add_memory, delete_memory, update_memory, list_entities, delete_entities, get_event_status) to execute the skill instructions.\n\nIdentity context (from environment):\n- user_id: Use MEM0_USER_ID env var, or fall back to $USER\n- app_id: Use MEM0_APP_ID env var\n- session_id: Use MEM0_SESSION_ID env var\n- branch: Use MEM0_BRANCH env var\n`;
|
||||
try {
|
||||
mkdirSync(destCommands, { recursive: true });
|
||||
writeFileSync(cmdFile, cmdContent, "utf8");
|
||||
} catch {}
|
||||
}
|
||||
} catch {}
|
||||
}
|
||||
|
||||
const Mem0Plugin: Plugin = async (ctx) => {
|
||||
const { $, client } = ctx;
|
||||
|
||||
try {
|
||||
const projectDir = (ctx as any).directory ?? process.cwd();
|
||||
installSkills(projectDir);
|
||||
} catch {}
|
||||
|
||||
const apiKey = process.env.MEM0_API_KEY;
|
||||
|
||||
if (!apiKey) {
|
||||
try {
|
||||
await client.app.log({
|
||||
body: {
|
||||
service: "mem0",
|
||||
level: "warn",
|
||||
message:
|
||||
"MEM0_API_KEY not set. Get one at https://app.mem0.ai/dashboard/api-keys",
|
||||
},
|
||||
});
|
||||
} catch {}
|
||||
return {};
|
||||
}
|
||||
|
||||
const mem0 = new MemoryClient({ apiKey });
|
||||
const userId = await getUserId();
|
||||
const appId = await getProjectId($);
|
||||
const branch = await getBranch($);
|
||||
const stats = { adds: 0, searches: 0, messages: 0 };
|
||||
const sessionId = generateSessionId();
|
||||
const globalSearch = loadGlobalSearch();
|
||||
|
||||
let initialized = false;
|
||||
let memoryCount = 0;
|
||||
let msgCount = 0;
|
||||
|
||||
const systemContext: string[] = [];
|
||||
|
||||
// Auto-configure coding categories in background (idempotent, never blocks)
|
||||
Promise.resolve().then(() => autoSetupCategories(mem0, apiKey)).catch(() => {});
|
||||
|
||||
return {
|
||||
"chat.message": async (input: any, output: any) => {
|
||||
const userText = extractUserText(input, output);
|
||||
if (!userText || userText.length < 10) return;
|
||||
|
||||
const safeText = redact(userText);
|
||||
msgCount++;
|
||||
stats.messages++;
|
||||
|
||||
if (!initialized) {
|
||||
initialized = true;
|
||||
|
||||
const searchFilters = globalSearch
|
||||
? { OR: [{ user_id: "*" }] }
|
||||
: { AND: [{ user_id: userId }, { app_id: appId }] };
|
||||
|
||||
try {
|
||||
const all = await mem0.getAll({
|
||||
filters: searchFilters,
|
||||
page: 1,
|
||||
pageSize: 1,
|
||||
});
|
||||
memoryCount =
|
||||
(all as any)?.count ??
|
||||
(all as any)?.results?.length ??
|
||||
0;
|
||||
|
||||
if (globalSearch) {
|
||||
systemContext.push(
|
||||
`Global search is ON — searches return all memories across all users and projects. Writes still use user_id="${userId}", app_id="${appId}".`,
|
||||
);
|
||||
} else {
|
||||
systemContext.push(
|
||||
`Always include user_id="${userId}" and app_id="${appId}" in every search_memories filter and add_memory call.`,
|
||||
);
|
||||
}
|
||||
|
||||
if (memoryCount === 0) {
|
||||
systemContext.push(
|
||||
"New project with 0 memories. Suggest running /mem0:onboard to import project files and install coding categories.",
|
||||
);
|
||||
}
|
||||
|
||||
if (memoryCount > 0) {
|
||||
systemContext.push(
|
||||
"Search mem0 for recent decisions and task learnings before responding. Run 2 parallel searches: one for decision type, one for task_learning type.",
|
||||
);
|
||||
try {
|
||||
const res = await mem0.search(
|
||||
"recent session state decisions and learnings",
|
||||
{
|
||||
filters: searchFilters,
|
||||
topK: 5,
|
||||
},
|
||||
);
|
||||
stats.searches++;
|
||||
const memories = extractMemories(res);
|
||||
if (memories.length > 0) {
|
||||
const memLines = memories
|
||||
.map((m) => {
|
||||
const meta = (m as any).metadata ?? {};
|
||||
const cat = meta.type ?? "unknown";
|
||||
const icon = TYPE_ICONS[cat] ?? "❓";
|
||||
const age = (m as any).created_at ? formatAge((m as any).created_at) : "";
|
||||
const ageStr = age ? ` (${age})` : "";
|
||||
return `- ${icon} [${cat}]${ageStr} ${m.memory.slice(0, 120)}`;
|
||||
})
|
||||
.join("\n");
|
||||
systemContext.push(`### Recent Activity\n\n${memLines}`);
|
||||
}
|
||||
} catch {}
|
||||
}
|
||||
|
||||
systemContext.push(
|
||||
"Mem0 searches apply when user references past work, decision questions, errors, or non-trivial tasks. Queries use noun-phrases, 2-4 parallel calls with different metadata.type filters, and include user_id + app_id.",
|
||||
);
|
||||
} catch (err: any) {
|
||||
try {
|
||||
await client.app.log({
|
||||
body: {
|
||||
service: "mem0",
|
||||
level: "error",
|
||||
message: `Session init error: ${err?.message}`,
|
||||
},
|
||||
});
|
||||
} catch {}
|
||||
}
|
||||
}
|
||||
|
||||
if (NUDGE_RE.test(safeText)) {
|
||||
systemContext.push(
|
||||
"[MEMORY TRIGGER] User asked to remember something. Call add_memory with the user's statement, confidence=1.0, infer=false.",
|
||||
);
|
||||
}
|
||||
|
||||
const hasResume = RESUME_RE.test(safeText);
|
||||
if (hasResume) {
|
||||
try {
|
||||
const resumeFilters = globalSearch
|
||||
? { OR: [{ user_id: "*" }] }
|
||||
: {
|
||||
AND: [
|
||||
{ user_id: userId },
|
||||
{ app_id: appId },
|
||||
],
|
||||
};
|
||||
const [stateRes, decisionsRes] = await Promise.all([
|
||||
mem0.search("session state current task", {
|
||||
filters: resumeFilters,
|
||||
topK: 3,
|
||||
}),
|
||||
mem0.search("recent decisions and learnings", {
|
||||
filters: resumeFilters,
|
||||
topK: 3,
|
||||
}),
|
||||
]);
|
||||
stats.searches += 2;
|
||||
const all = [
|
||||
...extractMemories(stateRes),
|
||||
...extractMemories(decisionsRes),
|
||||
];
|
||||
const seen = new Set<string>();
|
||||
const unique = all.filter((m) => {
|
||||
if (seen.has(m.id)) return false;
|
||||
seen.add(m.id);
|
||||
return true;
|
||||
});
|
||||
if (unique.length > 0) {
|
||||
const memLines = unique.map((m) => `- ${m.memory}`).join("\n");
|
||||
systemContext.push(
|
||||
`Session resume context:\n${memLines}\n\nThese memories provide context for resuming work.`,
|
||||
);
|
||||
}
|
||||
} catch {}
|
||||
}
|
||||
|
||||
if (!hasResume && memoryCount > 0) {
|
||||
try {
|
||||
const msgFilters = globalSearch
|
||||
? { OR: [{ user_id: "*" }] }
|
||||
: { AND: [{ user_id: userId }, { app_id: appId }] };
|
||||
const res = await mem0.search(safeText, {
|
||||
filters: msgFilters,
|
||||
topK: 5,
|
||||
});
|
||||
stats.searches++;
|
||||
const memories = extractMemories(res);
|
||||
if (memories.length > 0) {
|
||||
const memLines = memories.map((m) => `- ${m.memory}`).join("\n");
|
||||
systemContext.push(`Relevant memories:\n${memLines}`);
|
||||
}
|
||||
} catch {}
|
||||
}
|
||||
|
||||
if (msgCount % 3 === 0) {
|
||||
Promise.resolve().then(async () => {
|
||||
try {
|
||||
await mem0.add([{ role: "user", content: safeText }], {
|
||||
user_id: userId,
|
||||
app_id: appId,
|
||||
metadata: {
|
||||
type: "auto_capture",
|
||||
source: "opencode",
|
||||
confidence: 0.7,
|
||||
session_id: sessionId,
|
||||
branch,
|
||||
},
|
||||
infer: true,
|
||||
} as any);
|
||||
stats.adds++;
|
||||
} catch {}
|
||||
});
|
||||
}
|
||||
|
||||
if (msgCount % 5 === 0 && stats.adds < Math.floor(msgCount / 3)) {
|
||||
systemContext.push(
|
||||
"After responding, store any new decisions, learnings, or preferences from this exchange via add_memory. Keep it to 1 sentence per memory.",
|
||||
);
|
||||
}
|
||||
},
|
||||
|
||||
"experimental.chat.messages.transform": async (
|
||||
_input: any,
|
||||
output: { messages: { info: any; parts: any[] }[] },
|
||||
) => {
|
||||
if (systemContext.length === 0 || !output?.messages?.length) return;
|
||||
|
||||
const firstUser = output.messages.find(
|
||||
(m) => m.info.role === "user",
|
||||
);
|
||||
if (!firstUser || !firstUser.parts.length) return;
|
||||
|
||||
const marker = "## Mem0 Memory Context";
|
||||
if (firstUser.parts.some((p: any) => p.type === "text" && p.text?.includes(marker))) return;
|
||||
|
||||
const block = `${marker}\n\n${systemContext.join("\n\n")}`;
|
||||
const ref = firstUser.parts[0];
|
||||
firstUser.parts.unshift({ ...ref, type: "text", text: block });
|
||||
},
|
||||
|
||||
"tool.execute.before": async (input: any, output: any) => {
|
||||
const toolName: string = input?.tool ?? "";
|
||||
|
||||
// File-context injection: before reading a file, search mem0 for prior work on it
|
||||
if (toolName === "read" || toolName === "Read") {
|
||||
const filePath = String(output?.args?.file_path ?? output?.args?.filePath ?? "");
|
||||
if (filePath && filePath.length > 0) {
|
||||
try {
|
||||
const absPath = filePath.startsWith("/") ? filePath : resolve(process.cwd(), filePath);
|
||||
const { statSync } = await import("fs");
|
||||
const stat = statSync(absPath);
|
||||
if (stat.isFile() && stat.size >= FILE_READ_GATE_MIN_BYTES) {
|
||||
const searchFilters = globalSearch
|
||||
? { OR: [{ user_id: "*" }] }
|
||||
: { AND: [{ user_id: userId }, { app_id: appId }] };
|
||||
const relPath = filePath.startsWith("/")
|
||||
? filePath.replace(process.cwd() + "/", "")
|
||||
: filePath;
|
||||
const res = await mem0.search(relPath, {
|
||||
filters: searchFilters,
|
||||
topK: 5,
|
||||
});
|
||||
stats.searches++;
|
||||
const memories = extractMemories(res);
|
||||
if (memories.length > 0) {
|
||||
const lines = memories.map((m) => {
|
||||
const text = m.memory.slice(0, 150).replace(/\n/g, " ");
|
||||
return `- ${text} [mem0:${m.id.slice(0, 8)}]`;
|
||||
});
|
||||
systemContext.push(
|
||||
`Prior work on \`${relPath}\`:\n${lines.join("\n")}`,
|
||||
);
|
||||
}
|
||||
}
|
||||
} catch {}
|
||||
}
|
||||
}
|
||||
|
||||
if (WRITE_TOOLS.has(toolName)) {
|
||||
const fp = String(
|
||||
output?.args?.file_path ?? output?.args?.filePath ?? "",
|
||||
);
|
||||
if (/MEMORY\.md|\.claude\/memory/i.test(fp)) {
|
||||
throw new Error(
|
||||
"Use the add_memory MCP tool instead of writing to MEMORY.md",
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
if (isMem0Tool(toolName) && output?.args) {
|
||||
if (!output.args.user_id) output.args.user_id = userId;
|
||||
if (!output.args.app_id) output.args.app_id = appId;
|
||||
|
||||
if (isMem0AddMemory(toolName)) {
|
||||
if (!output.args.metadata) output.args.metadata = {};
|
||||
const meta = output.args.metadata;
|
||||
if (meta.confidence === undefined) meta.confidence = 0.7;
|
||||
if (!meta.source) meta.source = "opencode";
|
||||
if (!meta.type) meta.type = "task_learning";
|
||||
if (!meta.session_id) meta.session_id = sessionId;
|
||||
if (!meta.files) meta.files = ["*"];
|
||||
if (!meta.branch) meta.branch = branch;
|
||||
if (meta.confidence >= 1.0 && output.args.infer === undefined) {
|
||||
output.args.infer = false;
|
||||
}
|
||||
}
|
||||
|
||||
if (isMem0SearchOrGet(toolName)) {
|
||||
if (globalSearch) {
|
||||
output.args.filters = { OR: [{ user_id: "*" }] };
|
||||
} else {
|
||||
const existingFilters = output.args.filters;
|
||||
if (existingFilters === undefined || existingFilters === null) {
|
||||
output.args.filters = {
|
||||
AND: [{ user_id: userId }, { app_id: appId }],
|
||||
};
|
||||
} else if (typeof existingFilters === "object") {
|
||||
const andClauses: any[] = existingFilters.AND;
|
||||
if (Array.isArray(andClauses)) {
|
||||
const hasUid = andClauses.some(
|
||||
(c: any) => c && typeof c === "object" && "user_id" in c,
|
||||
);
|
||||
const hasAid = andClauses.some(
|
||||
(c: any) => c && typeof c === "object" && "app_id" in c,
|
||||
);
|
||||
if (!hasUid) andClauses.push({ user_id: userId });
|
||||
if (!hasAid) andClauses.push({ app_id: appId });
|
||||
} else if (andClauses === undefined) {
|
||||
const hasUid = "user_id" in existingFilters;
|
||||
const hasAid = "app_id" in existingFilters;
|
||||
if (!hasUid || !hasAid) {
|
||||
const existing = Object.entries(existingFilters).map(
|
||||
([k, v]) => ({ [k]: v }),
|
||||
);
|
||||
if (!hasUid) existing.push({ user_id: userId });
|
||||
if (!hasAid) existing.push({ app_id: appId });
|
||||
output.args.filters = { AND: existing };
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (isMem0DeleteAll(toolName)) {
|
||||
if (!output.args.user_id) output.args.user_id = userId;
|
||||
if (!output.args.app_id) output.args.app_id = appId;
|
||||
}
|
||||
|
||||
if (!isMem0AddMemory(toolName) && !output.args.metadata) {
|
||||
output.args.metadata = { source: "opencode", branch };
|
||||
}
|
||||
}
|
||||
},
|
||||
|
||||
"tool.execute.after": async (input: any, _output: any) => {
|
||||
const toolName: string = input?.tool ?? "";
|
||||
const toolOutput: string = input?.output ?? _output?.output ?? "";
|
||||
|
||||
if (MEM0_MCP_RE.test(toolName)) {
|
||||
if (toolName.includes("add_memory")) stats.adds++;
|
||||
if (toolName.includes("search")) stats.searches++;
|
||||
}
|
||||
|
||||
if (toolName === "bash" && toolOutput.length >= 50) {
|
||||
const command: string = input?.args?.command ?? "";
|
||||
if (/git\s+(commit|merge|rebase)/.test(command)) return;
|
||||
|
||||
const hasStrongError = ERROR_STRONG_RE.test(toolOutput);
|
||||
const multiErrors = (toolOutput.match(ERROR_MULTI_RE) ?? []).length;
|
||||
if (!hasStrongError && multiErrors < 2) return;
|
||||
|
||||
try {
|
||||
const errorLine =
|
||||
toolOutput
|
||||
.split("\n")
|
||||
.find((l: string) =>
|
||||
/Error:|Exception:|panic:|FAIL:|fatal:/i.test(l),
|
||||
)
|
||||
?.replace(/^\s+/, "")
|
||||
.slice(0, 120) ?? "";
|
||||
|
||||
const traceFiles = [
|
||||
...new Set(
|
||||
toolOutput.match(
|
||||
/[a-zA-Z0-9_./-]+\.(py|ts|tsx|js|jsx|rs|go|rb|java|sh)(:\d+)?/g,
|
||||
) ?? [],
|
||||
),
|
||||
].slice(0, 5);
|
||||
|
||||
const errorQuery = errorLine.slice(0, 80);
|
||||
if (errorQuery.length < 10) return;
|
||||
|
||||
const errorFilters = globalSearch
|
||||
? { OR: [{ user_id: "*" }] }
|
||||
: {
|
||||
AND: [
|
||||
{ user_id: userId },
|
||||
{ app_id: appId },
|
||||
],
|
||||
};
|
||||
const [antiPatternRes, bugFixRes] = await Promise.all([
|
||||
mem0.search(`error: ${errorQuery}`, {
|
||||
filters: errorFilters,
|
||||
topK: 3,
|
||||
}),
|
||||
mem0.search(`error: ${errorQuery}`, {
|
||||
filters: errorFilters,
|
||||
topK: 3,
|
||||
}),
|
||||
]);
|
||||
stats.searches += 2;
|
||||
|
||||
const allResults = [
|
||||
...extractMemories(antiPatternRes),
|
||||
...extractMemories(bugFixRes),
|
||||
];
|
||||
const seen = new Set<string>();
|
||||
const unique = allResults.filter((m) => {
|
||||
if (seen.has(m.id)) return false;
|
||||
seen.add(m.id);
|
||||
return true;
|
||||
});
|
||||
|
||||
let ctx = `Error detected: \`${command.slice(0, 100)}\` produced:\n> ${errorLine}`;
|
||||
if (traceFiles.length > 0) {
|
||||
ctx += `\nFiles in stack trace: ${traceFiles.join(", ")}`;
|
||||
}
|
||||
if (unique.length > 0) {
|
||||
const lines = unique.map((m) => `- ${m.memory}`).join("\n");
|
||||
ctx += `\nPrior error memories:\n${lines}`;
|
||||
}
|
||||
ctx +=
|
||||
"\nStore resolved errors as anti_pattern or bug_fix memories for future reference.";
|
||||
systemContext.push(ctx);
|
||||
} catch {}
|
||||
}
|
||||
},
|
||||
|
||||
"experimental.session.compacting": async (
|
||||
input: { sessionID?: string },
|
||||
output: { context: string[]; prompt?: string },
|
||||
) => {
|
||||
try {
|
||||
const compactSessionId = input?.sessionID ?? sessionId;
|
||||
|
||||
// Session summary capture: store a structured summary of the session
|
||||
const summaryPrompt = [
|
||||
`Session summary for project ${appId} (branch: ${branch}).`,
|
||||
`Session: ${compactSessionId}.`,
|
||||
`Stats: ${stats.adds} memories stored, ${stats.searches} searches, ${stats.messages} messages.`,
|
||||
`Extract and remember: what was requested, what was investigated, key decisions made, what was completed, and what needs to happen next.`,
|
||||
].join(" ");
|
||||
Promise.resolve().then(async () => {
|
||||
try {
|
||||
await mem0.add([{ role: "user", content: summaryPrompt }], {
|
||||
user_id: userId,
|
||||
app_id: appId,
|
||||
metadata: {
|
||||
type: "session_summary",
|
||||
source: "opencode-stop",
|
||||
session_id: compactSessionId,
|
||||
branch,
|
||||
},
|
||||
infer: true,
|
||||
} as any);
|
||||
} catch {}
|
||||
});
|
||||
|
||||
const compactFilters = globalSearch
|
||||
? { OR: [{ user_id: "*" }] }
|
||||
: { AND: [{ user_id: userId }, { app_id: appId }] };
|
||||
const res = await mem0.search("session state decisions learnings", {
|
||||
filters: compactFilters,
|
||||
topK: 10,
|
||||
});
|
||||
const memories = extractMemories(res);
|
||||
if (memories.length > 0 && output?.context) {
|
||||
const lines = memories.map((m) => `- ${m.memory}`).join("\n");
|
||||
output.context.push(
|
||||
`## Mem0 Memories (preserve across compaction)\n\n${lines}\n\nIMPORTANT: After compaction, store any key decisions or learnings using the add_memory MCP tool.`,
|
||||
);
|
||||
}
|
||||
} catch {}
|
||||
},
|
||||
|
||||
"shell.env": async (
|
||||
_input: { cwd: string; sessionID?: string },
|
||||
output: { env: Record<string, string> },
|
||||
) => {
|
||||
if (output?.env) {
|
||||
output.env.MEM0_USER_ID = userId;
|
||||
output.env.MEM0_APP_ID = appId;
|
||||
output.env.MEM0_SESSION_ID = sessionId;
|
||||
output.env.MEM0_BRANCH = branch;
|
||||
output.env.MEM0_GLOBAL_SEARCH = globalSearch ? "true" : "false";
|
||||
}
|
||||
},
|
||||
};
|
||||
};
|
||||
|
||||
export default Mem0Plugin;
|
||||
@@ -0,0 +1,52 @@
|
||||
---
|
||||
name: context-loader
|
||||
description: Searches and injects relevant memories into context before starting work on a task. Use when beginning a new task, switching context, or when project history, past decisions, or coding conventions need to be loaded.
|
||||
---
|
||||
|
||||
# Context Loader
|
||||
|
||||
Pre-fetches relevant memories to prime context before working on a task.
|
||||
|
||||
## When to use
|
||||
|
||||
- Session start (invoke manually or auto-triggered by skill description matching)
|
||||
- User starts work on a specific feature or file set
|
||||
- Complex multi-step task begins
|
||||
- User says "what do we know about X" or "context for X"
|
||||
|
||||
## Steps
|
||||
|
||||
1. **Extract topics** from current message/task. Identify: file paths, module names, feature areas, error patterns.
|
||||
|
||||
2. **Run 2-4 parallel `search_memories` calls** with different angles:
|
||||
|
||||
| Query angle | Filter | Purpose |
|
||||
|---|---|---|
|
||||
| Feature/module name | `{"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}, {"metadata": {"type": "decision"}}]}` | Architecture decisions |
|
||||
| File paths mentioned | `{"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}, {"metadata": {"type": "convention"}}]}` | Coding patterns |
|
||||
| Error keywords (if any) | `{"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}, {"metadata": {"type": "anti_pattern"}}]}` | Known pitfalls |
|
||||
| Broad project context | `{"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}]}` | Catch-all |
|
||||
|
||||
3. **Deduplicate** results by memory ID across all search responses.
|
||||
|
||||
4. **Output compact context block** (max 10 memories):
|
||||
|
||||
```
|
||||
context-loader: loaded <N> memories for "<task summary>"
|
||||
- [decision] <content> [mem0:<short_id>]
|
||||
- [convention] <content> [mem0:<short_id>]
|
||||
- [anti_pattern] <content> [mem0:<short_id>]
|
||||
```
|
||||
|
||||
5. If **zero results**: output nothing. Don't announce empty context.
|
||||
|
||||
## Constraints
|
||||
|
||||
- **Read-only** — never modify or delete memories
|
||||
- **Max 10 memories** returned (most relevant only)
|
||||
- **Silent on empty** — only surfaces findings if relevant context exists
|
||||
- Skip memories already visible in current session context
|
||||
|
||||
## Output formatting
|
||||
|
||||
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like **bold**, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.
|
||||
@@ -0,0 +1,237 @@
|
||||
---
|
||||
name: dream
|
||||
description: Consolidates stored memories by merging duplicates, resolving contradictions, and pruning stale entries. Use when memory count is high, search results feel noisy or repetitive, or periodic cleanup is needed to maintain memory quality.
|
||||
---
|
||||
|
||||
# Mem0 Dream — Memory Consolidation
|
||||
|
||||
This skill performs a memory consolidation pass: it fetches all project memories,
|
||||
identifies near-duplicates, flags contradictions, and prunes stale entries based on
|
||||
configured retention policies. All proposed changes are shown as a diff for user
|
||||
approval before anything is modified.
|
||||
|
||||
**IMPORTANT: Execute steps strictly in order (1 → 2 → 3 → 4 → 5 → 6). Each step depends on the previous one. Do NOT run steps in parallel or skip ahead.**
|
||||
|
||||
## Step 1: Load Retention Policies
|
||||
|
||||
Check for a project config file in the project root (current working directory):
|
||||
|
||||
1. Look for `.mem0.json` first. If it exists, parse it as JSON and read the
|
||||
`retention` field (a dict of `category → days | null`).
|
||||
2. If `.mem0.json` is not present, look for `.mem0.md`. If it exists, scan it
|
||||
for a `retention:` section or YAML front matter with retention settings and
|
||||
parse what you find.
|
||||
3. If neither file exists, skip config loading entirely.
|
||||
|
||||
If no config is found or the config contains no retention settings, fall back to
|
||||
these built-in defaults:
|
||||
|
||||
| `metadata.type` | Default retention |
|
||||
|---|---|
|
||||
| `session_state` | 90 days |
|
||||
| `compact_summary` | 90 days |
|
||||
| all others | no pruning |
|
||||
|
||||
Store the resolved policies for use in Step 3.
|
||||
|
||||
---
|
||||
|
||||
## Step 2: Fetch ALL Project Memories
|
||||
|
||||
Call `get_memories` to retrieve every memory for the active project:
|
||||
|
||||
```python
|
||||
get_memories(
|
||||
filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<active_project_id>"}]},
|
||||
page_size=200,
|
||||
)
|
||||
```
|
||||
|
||||
If the response indicates more pages exist, paginate until all memories are fetched.
|
||||
Collect the full list before proceeding. If zero memories are found, print:
|
||||
|
||||
```
|
||||
No memories found for project <project_id>. Nothing to consolidate.
|
||||
```
|
||||
|
||||
…and stop.
|
||||
|
||||
---
|
||||
|
||||
## Step 3: Analyze — Find Issues
|
||||
|
||||
Work entirely in-memory; do not modify anything yet.
|
||||
|
||||
Group memories by `metadata.type` (use `"unknown"` when the field is absent).
|
||||
For each group, identify the following:
|
||||
|
||||
### 3a. Near-duplicate pairs (merge candidates)
|
||||
|
||||
Two memories are near-duplicates when they express the same fact or decision but
|
||||
phrased differently (e.g., "Use PostgreSQL for auth" and "Auth DB is PostgreSQL").
|
||||
|
||||
Heuristics — two memories are near-duplicates if **all** of these hold:
|
||||
- Similarity threshold: estimated cosine similarity > 0.9 (use noun/keyword overlap as proxy — if >60% of significant nouns overlap, treat as >0.9 similarity).
|
||||
- Same `metadata.type`.
|
||||
- Neither memory is pinned (`metadata.pinned != true`).
|
||||
|
||||
For each qualifying pair, draft a merged version that is more complete and specific
|
||||
than either original.
|
||||
|
||||
### 3b. Contradictions
|
||||
|
||||
Two memories contradict when they assert opposing facts about the same topic
|
||||
(e.g., "Deploy to ECS" vs. "Deploy to Vercel").
|
||||
|
||||
Identify the likely winner: the more recent memory with higher confidence wins.
|
||||
Store both IDs and their content for user review.
|
||||
|
||||
### 3c. Prune candidates
|
||||
|
||||
A memory is a prune candidate when **any** of the following is true:
|
||||
|
||||
1. Its `metadata.type` has a retention policy and the memory is older than the
|
||||
configured number of days (compare `created_at` to today).
|
||||
2. Its confidence score is below 0.3 AND it contains no information unique to
|
||||
this project (no file paths, identifiers, or domain-specific nouns).
|
||||
|
||||
**Always skip memories where `metadata.pinned == true`**, regardless of age or
|
||||
confidence.
|
||||
|
||||
---
|
||||
|
||||
## Step 4: Print Diff Report
|
||||
|
||||
Print a structured diff to the terminal before making any changes. Use exactly
|
||||
this format:
|
||||
|
||||
```
|
||||
## dream — consolidation report
|
||||
|
||||
Merges (<N>):
|
||||
[mem0:<id1>] + [mem0:<id2>] → "<merged content, 100 chars>"
|
||||
|
||||
Conflicts (<N>):
|
||||
[mem0:<idA>] vs [mem0:<idB>] — "<topic>" [A/B/skip]
|
||||
|
||||
Prune (<N>):
|
||||
[mem0:<id>] — <type>, <age>d old
|
||||
|
||||
Proposed: <N> merges, <N> prunes, <N> conflicts. Apply? [Y/n]
|
||||
```
|
||||
|
||||
If there are zero items in any category, omit that section entirely.
|
||||
|
||||
If there are zero total proposals (no merges, no prunes, no conflicts), print:
|
||||
|
||||
```
|
||||
Dream complete. No duplicate, contradictory, or stale memories found.
|
||||
```
|
||||
|
||||
…and stop.
|
||||
|
||||
---
|
||||
|
||||
## Step 5: Wait for User Input and Apply
|
||||
|
||||
### 5a. Contradictions
|
||||
|
||||
For each `CONFLICT` pair in the report, wait for the user to type `A`, `B`, or
|
||||
`skip` (case-insensitive). If they enter nothing (empty), treat as `skip`.
|
||||
|
||||
Record the winner for each pair before proceeding to the final apply confirmation.
|
||||
|
||||
### 5b. Final confirmation
|
||||
|
||||
After all conflict resolutions are collected, prompt:
|
||||
|
||||
```
|
||||
Apply? [Y/n]
|
||||
```
|
||||
|
||||
If the user types `n` or `no` (case-insensitive), print `Cancelled. No changes made.`
|
||||
and stop.
|
||||
|
||||
If the user confirms (`Y`, `yes`, or empty / Enter), apply all changes in this order:
|
||||
|
||||
#### Merges
|
||||
|
||||
For each approved merge pair:
|
||||
1. `delete_memory(<id1>)`
|
||||
2. `delete_memory(<id2>)`
|
||||
3. `add_memory` with:
|
||||
- `text="<merged content>"`
|
||||
- `user_id=<active_user_id>`
|
||||
- `app_id=<active_project_id>` (top-level, not in metadata)
|
||||
- `metadata={"type": "<original type>", "branch": "<active_branch>", "confidence": <higher of the two original scores>, "source": "mem0-dream"}`
|
||||
- `infer=False`
|
||||
|
||||
#### Contradictions (resolved)
|
||||
|
||||
For each resolved conflict where the user chose A or B:
|
||||
- Delete the loser (the non-chosen memory): `delete_memory(memory_id=<loser_id>)`
|
||||
|
||||
Contradictions where the user chose `skip` are left untouched.
|
||||
|
||||
#### Prunes
|
||||
|
||||
For each prune candidate:
|
||||
- `delete_memory(<memory_id>)`
|
||||
|
||||
---
|
||||
|
||||
## Step 6: Print Summary
|
||||
|
||||
After all changes are applied, print:
|
||||
|
||||
```
|
||||
Dream complete — merged: <N>, pruned: <N>, conflicts resolved: <N>, skipped: <N>
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Auto mode
|
||||
|
||||
When invoked with `--auto` (e.g., `/mem0:dream --auto`), run non-interactively:
|
||||
|
||||
- **Merges**: applied automatically (no contradiction, both are compatible).
|
||||
- **Prunes**: applied automatically (age/confidence-based, no ambiguity).
|
||||
- **Contradictions**: skipped — they require human judgment.
|
||||
|
||||
### Concurrency guard
|
||||
|
||||
Before doing any work, check for a lock file at `/tmp/mem0_dream_auto.lock`:
|
||||
- If the lock file exists and is less than 10 minutes old, print `[mem0-dream --auto] Another run in progress — skipping.` and stop.
|
||||
- Otherwise, create the lock file (write the current timestamp). Delete it when done (in all exit paths).
|
||||
|
||||
### Execution
|
||||
|
||||
In auto mode:
|
||||
1. Load policies and fetch memories (Steps 1–3) as normal.
|
||||
2. Apply merges and prunes silently without printing the diff or prompting.
|
||||
3. Print a compact summary:
|
||||
```
|
||||
[mem0-dream --auto] project=<id> merged=<N> pruned=<N> conflicts_skipped=<N>
|
||||
```
|
||||
4. If contradictions were detected but skipped, check if a `mem0-dream-auto` reminder already exists before storing one:
|
||||
- Search for existing reminders: `search_memories(query="mem0-dream contradictions manual review", filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<active_project_id>"}, {"metadata": {"source": "mem0-dream-auto"}}]}, top_k=1)`
|
||||
- If a result exists with similarity > 0.9, skip storing the reminder (one already exists).
|
||||
- If no match, store the reminder:
|
||||
```python
|
||||
add_memory(
|
||||
text="mem0-dream detected <N> contradiction(s) requiring manual review. Run /mem0:dream to resolve them interactively.",
|
||||
user_id="<active_user_id>",
|
||||
app_id="<active_project_id>",
|
||||
metadata={"type": "task_learning", "source": "mem0-dream-auto", "branch": "<active_branch>"},
|
||||
infer=False,
|
||||
)
|
||||
```
|
||||
|
||||
## See also
|
||||
|
||||
- `/mem0:forget` — targeted deletion of specific memories (search + confirm + delete)
|
||||
- `/mem0:health --deep` — quick quality scan without applying changes
|
||||
|
||||
## Output formatting
|
||||
|
||||
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like **bold**, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.
|
||||
@@ -0,0 +1,80 @@
|
||||
---
|
||||
name: export
|
||||
description: Exports all project memories to a portable Markdown file for backup or migration. Use when backing up memories, migrating to another project, sharing memory state with teammates, or archiving before cleanup.
|
||||
---
|
||||
|
||||
# Mem0 Export
|
||||
|
||||
Export all memories for the current project to a portable Markdown file.
|
||||
|
||||
## Execution
|
||||
|
||||
### Step 1: Resolve identity
|
||||
|
||||
Determine the active identity:
|
||||
- `user_id` from `MEM0_USER_ID` env var, else `$USER`, else `"default"`
|
||||
- `project_id` (used as `app_id`) from `MEM0_PROJECT_ID` env var, or via the project resolver
|
||||
|
||||
### Step 2: Fetch all memories
|
||||
|
||||
Call `get_memories` with:
|
||||
- `filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<active_project_id>"}]}`
|
||||
- `page_size=200`
|
||||
|
||||
If the response is paginated (i.e. the result contains a `next` cursor or the count equals `page_size`), continue fetching pages until all memories are retrieved.
|
||||
|
||||
### Step 3: Format each memory as a YAML-frontmatter block
|
||||
|
||||
For each memory record, produce a block in this exact format:
|
||||
|
||||
```
|
||||
---
|
||||
id: <memory.id>
|
||||
created_at: <memory.created_at>
|
||||
type: <memory.metadata.type or "">
|
||||
confidence: <memory.metadata.confidence or "">
|
||||
branch: <memory.metadata.branch or "">
|
||||
files: <memory.metadata.files joined with ", " or "">
|
||||
categories: <memory.categories joined with ", " or "">
|
||||
---
|
||||
<memory.memory or memory content string>
|
||||
|
||||
```
|
||||
|
||||
Notes:
|
||||
- The `---` delimiters must be on their own lines with no extra whitespace.
|
||||
- `files` and `categories` are written as comma-separated values on a single line.
|
||||
- Leave a blank line after the content before the next `---` (for readability).
|
||||
- If a field is missing or null, write an empty string (not "null").
|
||||
|
||||
### Step 4: Write the export file
|
||||
|
||||
Determine the output filename:
|
||||
|
||||
```
|
||||
mem0-export-<project_id>-<YYYY-MM-DD>.md
|
||||
```
|
||||
|
||||
Where `<YYYY-MM-DD>` is today's date in UTC.
|
||||
|
||||
Write all formatted blocks to this file using the Write tool (or equivalent). The file is written to the current working directory.
|
||||
|
||||
### Step 5: Print summary
|
||||
|
||||
```
|
||||
Exported <N> memories to <filename>
|
||||
```
|
||||
|
||||
Where `<N>` is the total number of memory blocks written.
|
||||
|
||||
## Error Handling
|
||||
|
||||
- If `get_memories` returns an error or zero memories, print:
|
||||
```
|
||||
No memories found for project <project_id>. Nothing exported.
|
||||
```
|
||||
- If the write fails, report the error to the user.
|
||||
|
||||
## Output formatting
|
||||
|
||||
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like **bold**, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.
|
||||
@@ -0,0 +1,74 @@
|
||||
---
|
||||
name: forget
|
||||
description: Deletes memories by search query or memory ID with confirmation before removal. Use when removing outdated decisions, incorrect memories, sensitive data, or cleaning up after experiments. Also handles undo of recent additions.
|
||||
---
|
||||
|
||||
# Mem0 Forget
|
||||
|
||||
Delete specific memories from mem0.
|
||||
|
||||
## Execution
|
||||
|
||||
### Step 1: Parse input
|
||||
|
||||
The user provides either:
|
||||
- A search query: `/mem0:forget auth module decisions`
|
||||
- A memory ID: `/mem0:forget <memory_id>`
|
||||
|
||||
If no argument, ask: "What should I forget? Provide a search query or memory ID."
|
||||
|
||||
### Step 2: Find memories
|
||||
|
||||
**If memory ID provided** (looks like a UUID or hex string):
|
||||
- Call `get_memory` with the ID to verify it exists.
|
||||
- Show: `Found: "<memory content first 120 chars>" (created <date>)`
|
||||
|
||||
**If search query provided:**
|
||||
- Call `search_memories` with:
|
||||
- `query=<user's query>`
|
||||
- `filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<project_id>"}]}`
|
||||
- `top_k=10`
|
||||
- Show numbered list:
|
||||
```
|
||||
Found <N> memories matching "<query>":
|
||||
1. <content, 120 chars> (type: <type>, created: <date>) [ID: <short_id>]
|
||||
2. ...
|
||||
```
|
||||
|
||||
### Step 3: Confirm
|
||||
|
||||
Ask: "Delete which memories? Enter numbers (e.g., 1,3,5), 'all', or 'cancel'."
|
||||
|
||||
For a single memory ID, ask: "Delete this memory? [y/N]"
|
||||
|
||||
**Never delete without confirmation.** This is destructive.
|
||||
|
||||
### Step 4: Delete
|
||||
|
||||
For each confirmed memory, call `delete_memory` with the memory ID.
|
||||
|
||||
### Step 5: Report
|
||||
|
||||
```
|
||||
Deleted <N> memories.
|
||||
```
|
||||
|
||||
If any deletions failed, report which ones and why.
|
||||
|
||||
## Undo recent writes
|
||||
|
||||
If the user says "undo last N memories" or "undo last write":
|
||||
|
||||
1. Check the `MEM0_SESSION_ID` environment variable (set by the plugin's shell.env hook).
|
||||
2. If `MEM0_SESSION_ID` is set, call `search_memories` with:
|
||||
- `query="recently added"`
|
||||
- `filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<project_id>"}, {"metadata": {"session_id": "<MEM0_SESSION_ID>"}}]}`
|
||||
- `top_k=20`
|
||||
3. Sort results by creation time descending and show the last N entries (default 1). Ask for confirmation.
|
||||
4. Delete confirmed entries via `delete_memory`.
|
||||
|
||||
If `MEM0_SESSION_ID` is not set or the search returns no results, tell the user: "No recent memory IDs tracked this session. Try `/mem0:tour` to browse recent memories, or `/mem0:forget <search query>` to find specific ones."
|
||||
|
||||
## Output formatting
|
||||
|
||||
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like **bold**, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.
|
||||
@@ -0,0 +1,159 @@
|
||||
---
|
||||
name: health
|
||||
description: Diagnoses mem0 connectivity, API key validity, and memory read/write functionality. Use when memory operations fail, searches return empty, add_memory errors occur, MCP connection drops, or to verify the plugin is working correctly.
|
||||
---
|
||||
|
||||
# Mem0 Health Check
|
||||
|
||||
Run a diagnostic check on the mem0 plugin. Useful for troubleshooting.
|
||||
|
||||
## Execution
|
||||
|
||||
Run ALL checks, then display a single summary. Do not stop on the first failure.
|
||||
|
||||
### Check 1: API key
|
||||
|
||||
```bash
|
||||
_KEY="${MEM0_API_KEY:-}"
|
||||
[ -n "$_KEY" ] && echo "${_KEY:0:6}..." || echo "NOT_SET"
|
||||
```
|
||||
|
||||
- If `NOT_SET`: FAIL — "No API key configured"
|
||||
- If set: PASS — the command already prints only the first 6 chars
|
||||
|
||||
### Check 2: Identity resolution
|
||||
|
||||
Resolve identity from environment variables set by the plugin's `shell.env` hook:
|
||||
|
||||
```bash
|
||||
echo "user_id=${MEM0_USER_ID:-${USER:-}}"
|
||||
echo "project_id=${MEM0_APP_ID:-}"
|
||||
echo "branch=$(git branch --show-current 2>/dev/null || echo '')"
|
||||
```
|
||||
|
||||
- `user_id`: from `MEM0_USER_ID`, falling back to `$USER`
|
||||
- `project_id`: from `MEM0_APP_ID`
|
||||
- `branch`: from `git branch --show-current`
|
||||
|
||||
PASS if all three are non-empty. WARN if any falls back to defaults.
|
||||
|
||||
### Check 3: MCP server connectivity
|
||||
|
||||
Call `search_memories` with:
|
||||
- `query="health check"`
|
||||
- `filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<active_project_id>"}]}`
|
||||
- `top_k=1`
|
||||
|
||||
- If returns successfully (even empty): PASS
|
||||
- If errors: FAIL — show the error message
|
||||
|
||||
### Check 4: Memory write capability
|
||||
|
||||
Call `add_memory` with:
|
||||
- `text="Health check probe — safe to delete."`
|
||||
- `user_id=<active_user_id>`
|
||||
- `app_id=<active_project_id>`
|
||||
- `metadata={"type": "health_check", "probe": true}`
|
||||
- `infer=False`
|
||||
|
||||
The response returns `event_id` (v3 writes are async). Call `get_event_status(event_id=<event_id>)` to check processing.
|
||||
|
||||
- If status is `SUCCEEDED`: PASS — extract the memory ID from the event result, then call `delete_memory` with that ID to clean up.
|
||||
- If status is `PENDING` after 5 seconds: PASS (write accepted, processing delayed)
|
||||
- If errors: FAIL — show the error.
|
||||
|
||||
### Check 5: Session context
|
||||
|
||||
Check that the plugin's `shell.env` hook has injected session context into the environment:
|
||||
|
||||
```bash
|
||||
echo "session_id=${MEM0_SESSION_ID:-}"
|
||||
echo "app_id=${MEM0_APP_ID:-}"
|
||||
echo "branch=${MEM0_BRANCH:-}"
|
||||
```
|
||||
|
||||
- If all three are non-empty: PASS — "Session active"
|
||||
- If any are missing: WARN — "Plugin env vars not set; shell.env hook may not have fired"
|
||||
|
||||
### Display
|
||||
|
||||
```
|
||||
## mem0 health
|
||||
|
||||
PASS API Key m0-dVe...
|
||||
PASS Identity user=kartik, project=mem0, branch=main
|
||||
PASS MCP Connection 142ms
|
||||
PASS Write/Read write + delete OK
|
||||
PASS Session session_id=abc123, app_id=mem0, branch=main
|
||||
|
||||
All checks passed.
|
||||
```
|
||||
|
||||
If any check fails, add a `## Troubleshooting` section with specific fix steps for each failure.
|
||||
|
||||
## Extended mode: Memory Quality Analysis
|
||||
|
||||
When invoked with `--deep` (e.g., `/mem0:health --deep`), run the standard 5 checks above **plus** a memory quality scan.
|
||||
|
||||
### Quality Check 1: Duplicates
|
||||
|
||||
Call `get_memories` with `filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<active_project_id>"}]}`, `page_size=200`. Compare all pairs within the same `metadata.type` group for high textual overlap (shared nouns/keywords > 60%). Report:
|
||||
|
||||
```
|
||||
Potential duplicates: <N> pairs
|
||||
[mem0:<id1>] ≈ [mem0:<id2>] — both about "<shared topic>"
|
||||
```
|
||||
|
||||
### Quality Check 2: Stale memories
|
||||
|
||||
Flag memories where:
|
||||
- `metadata.type` is `session_state` or `compact_summary` AND older than 90 days
|
||||
- `metadata.confidence` < 0.3 AND older than 30 days
|
||||
|
||||
```
|
||||
Stale candidates: <N>
|
||||
[mem0:<id>] — session_state, 142d old
|
||||
```
|
||||
|
||||
### Quality Check 2b: Low-confidence memories
|
||||
|
||||
Flag memories where `metadata.confidence` < 0.5 (regardless of age). Report separately from stale:
|
||||
|
||||
```
|
||||
Low-confidence memories: <N>
|
||||
[mem0:<id>] — confidence=0.3, "<content preview>"
|
||||
```
|
||||
|
||||
### Quality Check 3: Contradictions
|
||||
|
||||
Within each `metadata.type` group, flag pairs that assert opposing facts about the same topic. Use semantic judgment — look for negation patterns, conflicting tool/framework choices, or reversed decisions.
|
||||
|
||||
```
|
||||
Possible contradictions: <N>
|
||||
[mem0:<idA>] vs [mem0:<idB>] — conflicting on "<topic>"
|
||||
```
|
||||
|
||||
### Quality Check 4: Orphan memories
|
||||
|
||||
Memories with no `metadata.type` set, or with `metadata.type` not in the 17 known coding categories. These were likely written without proper tagging.
|
||||
|
||||
```
|
||||
Untagged/orphan memories: <N>
|
||||
```
|
||||
|
||||
### Quality summary
|
||||
|
||||
```
|
||||
## Memory Quality
|
||||
|
||||
Duplicates: <N> · Stale: <N> · Contradictions: <N> · Orphans: <N>
|
||||
```
|
||||
|
||||
If all counts are 0: `Memory quality: clean.`
|
||||
If any non-zero: append `Run /mem0:dream to fix.`
|
||||
|
||||
To fix issues found by `--deep`, run `/mem0:dream` for automated consolidation (merges, prunes, conflict resolution).
|
||||
|
||||
## Output formatting
|
||||
|
||||
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like **bold**, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.
|
||||
@@ -0,0 +1,185 @@
|
||||
---
|
||||
name: import
|
||||
description: Imports memories from an exported Markdown file or MEMORY.md into the current project. Use when migrating from another project, restoring from backup, importing Claude Code native MEMORY.md content, or setting up a new project with existing knowledge.
|
||||
---
|
||||
|
||||
# Mem0 Import
|
||||
|
||||
Import memories from a mem0 export file into the current project.
|
||||
|
||||
## Execution
|
||||
|
||||
### Step 1: Determine the export file to import
|
||||
|
||||
If the user provided a filename as an argument to `/mem0:import <filename>`, use that file.
|
||||
|
||||
Otherwise, list `.md` files in the current directory whose names contain `mem0-export`:
|
||||
|
||||
```bash
|
||||
ls -1 *.md 2>/dev/null | grep mem0-export || echo "No export files found"
|
||||
```
|
||||
|
||||
If multiple files are found, ask the user which one to import. If none are found, print:
|
||||
```
|
||||
No mem0-export files found in the current directory.
|
||||
Run /mem0:export first, or provide the filename: /mem0:import <path-to-file>
|
||||
```
|
||||
|
||||
### Step 2: Parse the export file
|
||||
|
||||
Read the export file directly. It is a JSON file containing a top-level `memories` array. Each element has:
|
||||
- `id` — original memory ID (for reference only; a new ID will be assigned on import)
|
||||
- `type` — metadata type
|
||||
- `confidence` — metadata confidence value
|
||||
- `branch` — metadata branch
|
||||
- `files` — list of associated files
|
||||
- `categories` — list of categories
|
||||
- `content` — the memory text
|
||||
|
||||
Parse the JSON in-memory (do not run any external script). If the file cannot be read or parsed, or if the `memories` array is missing or empty, print:
|
||||
```
|
||||
Failed to parse <filename> or file contains no valid memory blocks.
|
||||
```
|
||||
and stop.
|
||||
|
||||
### Step 3: Resolve identity
|
||||
|
||||
Determine the active identity:
|
||||
- `user_id` from `MEM0_USER_ID` env var, else `$USER`, else `"default"`
|
||||
- `project_id` (used as `app_id`) from `MEM0_PROJECT_ID` env var, or via the project resolver
|
||||
|
||||
### Step 4: Import each memory
|
||||
|
||||
For each record in the parsed JSON array, call `add_memory` (MCP tool) with:
|
||||
|
||||
- `text="<record.content>"`
|
||||
- `user_id=<active_user_id>`
|
||||
- `app_id=<active_project_id>`
|
||||
- `metadata={`
|
||||
- `"type": "<record.type>"` (if non-empty)
|
||||
- `"confidence": "<record.confidence>"` (if non-empty)
|
||||
- `"branch": "<record.branch>"` (if non-empty)
|
||||
- `"files": <record.files>` (the list, if non-empty)
|
||||
- `"source": "import"`
|
||||
- `}`
|
||||
- `infer=False`
|
||||
|
||||
Notes:
|
||||
- Do NOT pass the original `id` — the platform assigns a new ID.
|
||||
- Skip records where `content` is empty.
|
||||
- Continue importing even if individual records fail; track the count of successes.
|
||||
|
||||
### Step 5: Print results
|
||||
|
||||
```
|
||||
Imported <N> memories into project <project_id>
|
||||
```
|
||||
|
||||
Where `<N>` is the number of successfully imported memories.
|
||||
|
||||
If any failed:
|
||||
```
|
||||
Imported <N>/<total> memories into project <project_id> (<failed> failed)
|
||||
```
|
||||
|
||||
## Importing from competing AI tools (`--tools`)
|
||||
|
||||
When invoked with `--tools` (e.g., `/mem0:import --tools`), detect and import
|
||||
from competing AI tool configuration files:
|
||||
|
||||
### Supported tools
|
||||
|
||||
| Tool | File/directory |
|
||||
|------|---------------|
|
||||
| Cursor | `.cursorrules` |
|
||||
| GitHub Copilot | `.github/copilot-instructions.md` |
|
||||
| Cline | `memory-bank/` (directory of `.md` files) |
|
||||
| Continue | `.continue/rules.md` |
|
||||
|
||||
### T1: Detect
|
||||
|
||||
```bash
|
||||
test -f .cursorrules && echo "cursor: .cursorrules"
|
||||
test -f .github/copilot-instructions.md && echo "copilot: .github/copilot-instructions.md"
|
||||
test -d memory-bank/ && echo "cline: memory-bank/"
|
||||
test -f .continue/rules.md && echo "continue: .continue/rules.md"
|
||||
```
|
||||
|
||||
### T2: Ask user
|
||||
|
||||
List found files, ask which to import (numbers, comma-separated, or "all").
|
||||
If none found:
|
||||
```
|
||||
No competing tool configuration files found.
|
||||
Checked: .cursorrules, .github/copilot-instructions.md, memory-bank/, .continue/rules.md
|
||||
```
|
||||
|
||||
### T3: Import
|
||||
|
||||
For each selected tool, read the file(s) directly and split the content into logical
|
||||
chunks to import as individual memories. No external scripts are used — all parsing
|
||||
and importing is done via MCP tools.
|
||||
|
||||
Chunking rules per tool:
|
||||
|
||||
- **cursorrules / copilot / continue**: Read the file as plain text. Split on blank
|
||||
lines or section headers (`#`, `##`). Each non-empty chunk becomes one memory.
|
||||
Skip chunks shorter than 50 characters.
|
||||
|
||||
- **cline (memory-bank/)**: List all `.md` files in the directory. Read each file.
|
||||
Split each file on blank lines or headers. Each non-empty chunk becomes one memory.
|
||||
Skip chunks shorter than 50 characters.
|
||||
|
||||
For each chunk, call `add_memory` (MCP tool) with:
|
||||
- `text="<chunk text>"`
|
||||
- `user_id=<active_user_id>`
|
||||
- `app_id=<active_project_id>`
|
||||
- `metadata={"type": "task_learning", "source": "<tool>-import", "confidence": 0.8}`
|
||||
- `infer=False`
|
||||
|
||||
Where `<tool>` is `cursorrules`, `copilot`, `cline`, or `continue`.
|
||||
|
||||
Notes: chunks longer than 10,000 characters are truncated before import. Safe to
|
||||
re-run — deduplication handles repeated entries.
|
||||
|
||||
### T4: Report
|
||||
|
||||
```
|
||||
Imported <N> memories into <project_id> (cursor: <N>, copilot: <N>)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Importing Claude Code's native MEMORY.md
|
||||
|
||||
When invoked with a path to Claude Code's native `MEMORY.md` file (typically
|
||||
`~/.claude/projects/<proj-key>/memory/MEMORY.md`), or when `on_session_start.sh`
|
||||
detects native auto-memory and the user chooses to import:
|
||||
|
||||
1. Read the file directly. It contains newline-separated memory entries (one fact per
|
||||
line, sometimes with `- ` bullet prefix).
|
||||
2. Split by non-empty lines. Each line becomes one memory.
|
||||
3. Skip lines shorter than 20 characters or lines that are just headers (`#`).
|
||||
4. For each line, call `add_memory` (MCP tool) with:
|
||||
- `text="<line>"`
|
||||
- `user_id=<active_user_id>`
|
||||
- `app_id=<active_project_id>`
|
||||
- `metadata={"type": "task_learning", "source": "memory-md-import", "confidence": 0.8}`
|
||||
- `infer=False`
|
||||
5. Report: `Imported <N> memories from MEMORY.md into project <project_id>`
|
||||
6. Suggest disabling native auto-memory:
|
||||
```
|
||||
To avoid duplicate memory systems, add to ~/.claude/settings.json:
|
||||
"autoMemoryEnabled": false
|
||||
```
|
||||
|
||||
This handles the cold-start gap when a user has been using Claude Code's native
|
||||
memory and switches to mem0.
|
||||
|
||||
## Error Handling
|
||||
|
||||
- If `add_memory` calls fail consistently (e.g. auth error), report the issue and stop early.
|
||||
|
||||
## Output formatting
|
||||
|
||||
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like **bold**, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.
|
||||
@@ -0,0 +1,64 @@
|
||||
---
|
||||
name: list-projects
|
||||
description: Lists all projects with stored memories for the current user, showing memory counts and last activity dates. Use when checking which projects have memories, comparing memory distribution across repos, or finding a specific project scope.
|
||||
---
|
||||
|
||||
# Mem0 List Projects
|
||||
|
||||
Show all known project scopes for the current user.
|
||||
|
||||
## Execution
|
||||
|
||||
### Step 1: Fetch memories to discover app_ids
|
||||
|
||||
There is no dedicated "list projects" API endpoint. Discover projects by fetching
|
||||
the user's memories across all scopes.
|
||||
|
||||
**Important:** A filter with only `user_id` triggers implicit null scoping — it
|
||||
excludes memories that have a non-null `app_id`. Run two queries and merge:
|
||||
|
||||
1. **Null-scoped:** `get_memories` with `filters={"AND": [{"user_id": "<active_user_id>"}]}`, `page_size=200`
|
||||
— catches memories without `app_id`
|
||||
2. **App-scoped:** `get_memories` with `filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": {"exists": true}}]}`, `page_size=200`
|
||||
— catches memories with any `app_id`
|
||||
|
||||
Run both calls in parallel. Merge results, deduplicate by memory `id`.
|
||||
|
||||
If either response indicates more pages, paginate (up to 1000 total).
|
||||
|
||||
### Step 2: Extract distinct projects
|
||||
|
||||
For each memory, determine project by:
|
||||
1. Top-level `app_id` field (preferred)
|
||||
2. `metadata.project_id` (legacy memories)
|
||||
3. `metadata.project` (oldest format)
|
||||
4. `"(unscoped)"` if none found
|
||||
|
||||
Group by resolved project name. For each project, count:
|
||||
- Total memories
|
||||
- Most recent `created_at` date
|
||||
- Top 3 `metadata.type` values by frequency
|
||||
|
||||
### Step 3: Display
|
||||
|
||||
```
|
||||
## mem0 projects
|
||||
|
||||
<app_id_1> <count> memories (last: <date>) ← current
|
||||
<app_id_2> <count> memories (last: <date>)
|
||||
|
||||
<N> projects, <M> total memories
|
||||
```
|
||||
|
||||
Mark current project with `← current`. Sort by memory count descending.
|
||||
|
||||
### Step 4: Empty state
|
||||
|
||||
If zero memories found:
|
||||
```
|
||||
No projects found. Run /mem0:onboard to get started.
|
||||
```
|
||||
|
||||
## Output formatting
|
||||
|
||||
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like **bold**, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.
|
||||
@@ -0,0 +1,189 @@
|
||||
Apache License
|
||||
Version 2.0, January 2004
|
||||
http://www.apache.org/licenses/
|
||||
|
||||
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
|
||||
|
||||
1. Definitions.
|
||||
|
||||
"License" shall mean the terms and conditions for use, reproduction,
|
||||
and distribution as defined by Sections 1 through 9 of this document.
|
||||
|
||||
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|
||||
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|
||||
|
||||
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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or as an addendum to the NOTICE text from the Work, provided
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||||
You may add Your own copyright statement to Your modifications and
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may provide additional or different license terms and conditions
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for any such Derivative Works as a whole, provided Your use,
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reproduction, and distribution of the Work otherwise complies with
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5. Submission of Contributions. Unless You explicitly state otherwise,
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any Contribution intentionally submitted for inclusion in the Work
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by You to the Licensor shall be under the terms and conditions of
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Notwithstanding the above, nothing herein shall supersede or modify
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7. Disclaimer of Warranty. Unless required by applicable law or
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unless required by applicable law (such as deliberate and grossly
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has been advised of the possibility of such damages.
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9. Accepting Warranty or Additional Liability. While redistributing
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defend, and hold each Contributor harmless for any liability
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incurred by, or claims asserted against, such Contributor by reason
|
||||
of your accepting any such warranty or additional liability.
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||||
|
||||
END OF TERMS AND CONDITIONS
|
||||
|
||||
Copyright 2024 Mem0.ai
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
@@ -0,0 +1,73 @@
|
||||
# Mem0 Skill for Claude
|
||||
|
||||
Add persistent memory to any AI application in minutes using [Mem0 Platform](https://app.mem0.ai?utm_source=oss&utm_medium=mem0-plugin-skill-readme).
|
||||
|
||||
## What This Skill Does
|
||||
|
||||
When installed, Claude can:
|
||||
|
||||
- **Set up Mem0** in your Python or TypeScript project
|
||||
- **Integrate memory** into your existing AI app (LangChain, CrewAI, Vercel AI, OpenAI Agents, LangGraph, LlamaIndex, etc.)
|
||||
- **Generate working code** using real API references and tested patterns
|
||||
- **Search live docs** on demand for the latest Mem0 documentation
|
||||
|
||||
## Installation
|
||||
|
||||
This skill is included automatically when you install the Mem0 plugin:
|
||||
|
||||
```
|
||||
/plugin marketplace add mem0ai/mem0
|
||||
/plugin install mem0@mem0-plugins
|
||||
```
|
||||
|
||||
See the [plugin README](../../README.md) for full setup instructions.
|
||||
|
||||
### Prerequisites
|
||||
|
||||
- A Mem0 Platform API key ([Get one here](https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=mem0-plugin-skill-readme))
|
||||
- Python 3.10+ or Node.js 18+
|
||||
- Set the environment variable:
|
||||
|
||||
```bash
|
||||
export MEM0_API_KEY="m0-your-api-key"
|
||||
```
|
||||
|
||||
## Quick Start
|
||||
|
||||
After installing, just ask Claude:
|
||||
|
||||
- "Set up mem0 in my project"
|
||||
- "Add memory to my chatbot"
|
||||
- "Help me search user memories with filters"
|
||||
- "Integrate mem0 with my LangChain app"
|
||||
- "Add graph memory to track entity relationships"
|
||||
|
||||
## What's Inside
|
||||
|
||||
```text
|
||||
skills/mem0/
|
||||
├── SKILL.md # Skill definition and instructions
|
||||
├── README.md # This file
|
||||
├── LICENSE # Apache-2.0
|
||||
├── scripts/
|
||||
│ └── mem0_doc_search.py # Search live Mem0 docs on demand
|
||||
└── references/ # Documentation (loaded on demand)
|
||||
├── quickstart.md # Full quickstart (Python, TS, cURL)
|
||||
├── sdk-guide.md # All SDK methods (Python + TypeScript)
|
||||
├── api-reference.md # REST endpoints, filters, memory object
|
||||
├── architecture.md # Processing pipeline, lifecycle, scoping, performance
|
||||
├── features.md # Retrieval, graph, categories, MCP, webhooks, multimodal
|
||||
├── integration-patterns.md # LangChain, CrewAI, Vercel AI, LangGraph, LlamaIndex, etc.
|
||||
└── use-cases.md # 7 real-world patterns with Python + TypeScript code
|
||||
```
|
||||
|
||||
## Links
|
||||
|
||||
- [Mem0 Platform Dashboard](https://app.mem0.ai?utm_source=oss&utm_medium=mem0-plugin-skill-readme)
|
||||
- [Mem0 Documentation](https://docs.mem0.ai)
|
||||
- [Mem0 GitHub](https://github.com/mem0ai/mem0)
|
||||
- [API Reference](https://docs.mem0.ai/api-reference)
|
||||
|
||||
## License
|
||||
|
||||
Apache-2.0
|
||||
@@ -0,0 +1,191 @@
|
||||
---
|
||||
name: mem0
|
||||
description: Mem0 SDK reference covering Python and TypeScript APIs, memory client methods, configuration, and framework integrations. Use when writing code that calls mem0 APIs, configuring memory providers, or integrating mem0 into an application.
|
||||
license: Apache-2.0
|
||||
metadata:
|
||||
author: mem0ai
|
||||
version: "0.1.1"
|
||||
category: ai-memory
|
||||
tags: "memory, personalization, ai, python, typescript, vector-search"
|
||||
compatibility: Requires Python 3.10+ or Node.js 18+, pip install mem0ai or npm install mem0ai, MEM0_API_KEY env var (Platform), and internet access to api.mem0.ai. Uses Mem0 v3 API.
|
||||
---
|
||||
|
||||
# Mem0 Platform Integration
|
||||
|
||||
> **Skill Graph:** This skill is part of the Mem0 skill graph:
|
||||
> - **mem0** (this skill) -- Platform Client SDK + OSS (Python + TypeScript)
|
||||
> - **[mem0-vercel-ai-sdk](https://github.com/mem0ai/mem0/tree/main/skills/mem0-vercel-ai-sdk)** -- Vercel AI SDK provider
|
||||
|
||||
Mem0 is a managed memory layer for AI applications. It stores, retrieves, and manages user memories via API — no infrastructure to deploy. For self-hosted usage, see the OSS section in the client references below.
|
||||
|
||||
## Step 1: Install and authenticate
|
||||
|
||||
**Python:**
|
||||
```bash
|
||||
pip install mem0ai
|
||||
export MEM0_API_KEY="m0-your-api-key"
|
||||
```
|
||||
|
||||
**TypeScript/JavaScript:**
|
||||
```bash
|
||||
npm install mem0ai
|
||||
export MEM0_API_KEY="m0-your-api-key"
|
||||
```
|
||||
|
||||
Get an API key at: https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=mem0-plugin-skill
|
||||
|
||||
> **Don't have a `MEM0_API_KEY`?** Sign up at https://app.mem0.ai and create one from the dashboard. Keys start with `m0-`.
|
||||
|
||||
## Step 2: Initialize the client
|
||||
|
||||
**Python:**
|
||||
```python
|
||||
from mem0 import MemoryClient
|
||||
client = MemoryClient(api_key="m0-xxx")
|
||||
```
|
||||
|
||||
**TypeScript:**
|
||||
```typescript
|
||||
import MemoryClient from 'mem0ai';
|
||||
const client = new MemoryClient({ apiKey: 'm0-xxx' });
|
||||
```
|
||||
|
||||
For async Python, use `AsyncMemoryClient`.
|
||||
|
||||
## Step 3: Core operations
|
||||
|
||||
Every Mem0 integration follows the same pattern: **retrieve → generate → store**.
|
||||
|
||||
### Add memories
|
||||
```python
|
||||
messages = [
|
||||
{"role": "user", "content": "I'm a vegetarian and allergic to nuts."},
|
||||
{"role": "assistant", "content": "Got it! I'll remember that."}
|
||||
]
|
||||
client.add(messages, user_id="alice")
|
||||
```
|
||||
|
||||
### Search memories
|
||||
```python
|
||||
results = client.search("dietary preferences", filters={"user_id": "alice"})
|
||||
for mem in results.get("results", []):
|
||||
print(mem["memory"])
|
||||
```
|
||||
|
||||
### Get all memories
|
||||
```python
|
||||
all_memories = client.get_all(filters={"user_id": "alice"})
|
||||
```
|
||||
|
||||
### Update a memory
|
||||
```python
|
||||
client.update("memory-uuid", text="Updated: vegetarian, nut allergy, prefers organic")
|
||||
```
|
||||
|
||||
### Delete a memory
|
||||
```python
|
||||
client.delete("memory-uuid")
|
||||
client.delete_all(user_id="alice") # delete all for a user
|
||||
```
|
||||
|
||||
## Common integration pattern
|
||||
|
||||
```python
|
||||
from mem0 import MemoryClient
|
||||
from openai import OpenAI
|
||||
|
||||
mem0 = MemoryClient()
|
||||
openai = OpenAI()
|
||||
|
||||
def chat(user_input: str, user_id: str) -> str:
|
||||
# 1. Retrieve relevant memories
|
||||
memories = mem0.search(user_input, filters={"user_id": user_id})
|
||||
context = "\n".join([m["memory"] for m in memories.get("results", [])])
|
||||
|
||||
# 2. Generate response with memory context
|
||||
response = openai.chat.completions.create(
|
||||
model="gpt-5-mini",
|
||||
messages=[
|
||||
{"role": "system", "content": f"User context:\n{context}"},
|
||||
{"role": "user", "content": user_input},
|
||||
]
|
||||
)
|
||||
reply = response.choices[0].message.content
|
||||
|
||||
# 3. Store interaction for future context
|
||||
mem0.add(
|
||||
[{"role": "user", "content": user_input}, {"role": "assistant", "content": reply}],
|
||||
user_id=user_id
|
||||
)
|
||||
return reply
|
||||
```
|
||||
|
||||
## Common edge cases
|
||||
|
||||
- **Search returns empty:** v3 processes `add()` asynchronously — returns an event ID immediately. Wait 2-3s before searching. Also verify `user_id` matches exactly (case-sensitive) and use `filters={"user_id": "..."}` syntax.
|
||||
- **AND filter with user_id + agent_id returns empty:** Entities are stored separately. `{"AND": [{"user_id": "alice"}, {"agent_id": "bot"}]}` returns nothing. Use `OR` instead, or query each separately.
|
||||
- **Duplicate memories:** Don't mix `infer=True` (default) and `infer=False` for the same data. `infer=True` extracts facts via LLM with dedup. `infer=False` stores raw — same text can be stored twice.
|
||||
- **Implicit null scoping:** `filters={"user_id": "alice"}` only returns memories where `agent_id`, `app_id`, `run_id` are ALL null. Wrap in `{"OR": [...]}` to include memories with non-null scoping fields.
|
||||
- **Platform vs OSS imports:** Platform: `from mem0 import MemoryClient`. OSS: `from mem0 import Memory`. Don't mix them — `MemoryClient` talks to `api.mem0.ai`, `Memory` runs locally.
|
||||
- **v3 defaults:** `top_k=20`, `threshold=0.1`, `rerank=False`. Adjust as needed.
|
||||
|
||||
## v3 API (Current)
|
||||
|
||||
Mem0 v3 uses single-pass extraction, entity linking, and multi-signal retrieval.
|
||||
|
||||
**Key v3 changes from v2:**
|
||||
- **Endpoints:** `POST /v3/memories/add/`, `POST /v3/memories/search/`, `POST /v3/memories/` (paginated list)
|
||||
- **Extraction:** Single ADD-only pass — no more UPDATE/DELETE operations during extraction. Memories accumulate rather than consolidate.
|
||||
- **Entity linking:** Replaces graph memory. Auto-extracted during `add()`, no config needed. Remove `enable_graph` and `graph_store` from any old config.
|
||||
- **Defaults:** `top_k=20`, `threshold=0.1`, `rerank=False`
|
||||
- **Removed params:** `org_id`, `project_id`, `enable_graph` — all removed from SDK
|
||||
- **TypeScript:** Exclusively camelCase (`userId`, `agentId`, `appId`, `topK`)
|
||||
- **Add response:** Async — returns event ID immediately, poll via `GET /v1/event/{event_id}/`
|
||||
|
||||
See the [migration guide](https://docs.mem0.ai/migration/platform-v2-to-v3) for details.
|
||||
|
||||
## Live documentation search
|
||||
|
||||
For the latest docs beyond what's in the references, use the doc search tool:
|
||||
|
||||
```bash
|
||||
bun ${CLAUDE_SKILL_DIR}/scripts/mem0_doc_search.ts --query "topic"
|
||||
bun ${CLAUDE_SKILL_DIR}/scripts/mem0_doc_search.ts --page "/platform/features/graph-memory"
|
||||
bun ${CLAUDE_SKILL_DIR}/scripts/mem0_doc_search.ts --index
|
||||
```
|
||||
|
||||
No API key needed — searches docs.mem0.ai directly.
|
||||
|
||||
## Client SDK References
|
||||
|
||||
Language-specific deep references (Platform + OSS):
|
||||
|
||||
| Language | File |
|
||||
|----------|------|
|
||||
| Python (MemoryClient + AsyncMemoryClient + Memory OSS) | [client/python.md](client/python.md) |
|
||||
| TypeScript/Node.js (MemoryClient + Memory OSS) | [client/node.md](client/node.md) |
|
||||
| Python vs TypeScript differences | [client/differences.md](client/differences.md) |
|
||||
|
||||
## Platform References
|
||||
|
||||
Load these on demand for deeper detail:
|
||||
|
||||
| Topic | File |
|
||||
|-------|------|
|
||||
| Quickstart (Python, TS, cURL) | [references/quickstart.md](references/quickstart.md) |
|
||||
| SDK guide (all methods, both languages) | [references/sdk-guide.md](references/sdk-guide.md) |
|
||||
| API reference (endpoints, filters, object schema) | [references/api-reference.md](references/api-reference.md) |
|
||||
| Architecture (pipeline, lifecycle, scoping, performance) | [references/architecture.md](references/architecture.md) |
|
||||
| Platform features (retrieval, graph, categories, MCP, etc.) | [references/features.md](references/features.md) |
|
||||
| Framework integrations (LangChain, CrewAI, OpenAI Agents, etc.) | [references/integration-patterns.md](references/integration-patterns.md) |
|
||||
| Use cases & examples (real-world patterns with code) | [references/use-cases.md](references/use-cases.md) |
|
||||
|
||||
## Related Mem0 Skills
|
||||
|
||||
| Skill | When to use | Link |
|
||||
|-------|-------------|------|
|
||||
| mem0-vercel-ai-sdk | Vercel AI SDK provider with automatic memory | [GitHub](https://github.com/mem0ai/mem0/tree/main/skills/mem0-vercel-ai-sdk) |
|
||||
|
||||
## Output formatting
|
||||
|
||||
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like **bold**, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.
|
||||
@@ -0,0 +1,129 @@
|
||||
# Python vs TypeScript SDK Differences
|
||||
|
||||
Quick-reference cheatsheet for developers working across both Mem0 SDKs.
|
||||
|
||||
## Constructor
|
||||
|
||||
| Aspect | Python | TypeScript |
|
||||
|--------|--------|------------|
|
||||
| Import (Platform) | `from mem0 import MemoryClient` | `import MemoryClient from 'mem0ai'` |
|
||||
| Import (OSS) | `from mem0 import Memory` | `import { Memory } from 'mem0ai/oss'` |
|
||||
| Constructor | `MemoryClient(api_key="m0-xxx")` | `new MemoryClient({ apiKey: 'm0-xxx' })` |
|
||||
| Required param | `api_key` (positional or kwarg) | `apiKey` (in options object) |
|
||||
|
||||
Both read from `MEM0_API_KEY` env var if no key provided.
|
||||
|
||||
## Method Naming
|
||||
|
||||
| Operation | Python | TypeScript |
|
||||
|-----------|--------|------------|
|
||||
| Add | `add()` | `add()` |
|
||||
| Search | `search()` | `search()` |
|
||||
| Get | `get()` | `get()` |
|
||||
| Get all | `get_all()` | `getAll()` |
|
||||
| Update | `update()` | `update()` |
|
||||
| Delete | `delete()` | `delete()` |
|
||||
| Delete all | `delete_all()` | `deleteAll()` |
|
||||
| History | `history()` | `history()` |
|
||||
| Batch update | `batch_update()` | `batchUpdate()` |
|
||||
| Batch delete | `batch_delete()` | `batchDelete()` |
|
||||
| List users | `users()` | `users()` |
|
||||
| Delete users | `delete_users()` | `deleteUsers()` |
|
||||
| Get project | `project.get()` | `getProject()` |
|
||||
| Update project | `project.update()` | `updateProject()` |
|
||||
| Create webhook | `create_webhook()` | `createWebhook()` |
|
||||
| Get webhooks | `get_webhooks()` | `getWebhooks()` |
|
||||
| Update webhook | `update_webhook()` | `updateWebhook()` |
|
||||
| Delete webhook | `delete_webhook()` | `deleteWebhook()` |
|
||||
| Create export | `create_memory_export()` | `createMemoryExport()` |
|
||||
| Get export | `get_memory_export()` | `getMemoryExport()` |
|
||||
| Feedback | `feedback()` | `feedback()` |
|
||||
|
||||
**Rule:** Python uses `snake_case`, TypeScript uses `camelCase` for method names.
|
||||
|
||||
## Parameter Passing
|
||||
|
||||
```python
|
||||
# Python: kwargs
|
||||
client.add(messages, user_id="alice", metadata={"source": "chat"})
|
||||
client.search("query", filters={"user_id": "alice"}, top_k=5, rerank=True)
|
||||
```
|
||||
|
||||
```typescript
|
||||
// TypeScript: options object with camelCase for top-level params, snake_case for filter keys
|
||||
await client.add(messages, { userId: 'alice', metadata: { source: 'chat' } });
|
||||
await client.search('query', { filters: { user_id: 'alice' }, topK: 5, rerank: true });
|
||||
```
|
||||
|
||||
**v3:** Python uses `snake_case` everywhere. TypeScript uses `camelCase` for top-level params (`userId`, `topK`) but `snake_case` for filter keys (`user_id`, `agent_id`).
|
||||
|
||||
## Architectural Differences
|
||||
|
||||
| Aspect | Python | TypeScript |
|
||||
|--------|--------|------------|
|
||||
| HTTP library | httpx | axios |
|
||||
| Default timeout | 300s | 60s |
|
||||
| Sync support | Yes (`MemoryClient`) | No (all async) |
|
||||
| Async support | Yes (`AsyncMemoryClient`) | All methods are async |
|
||||
| Project management | `client.project.*` (separate class) | `client.getProject()` / `client.updateProject()` |
|
||||
| Context manager | `async with AsyncMemoryClient()` | Not supported |
|
||||
|
||||
## Platform Features: Python-only
|
||||
|
||||
These methods exist in Python but not TypeScript:
|
||||
|
||||
| Method | Description |
|
||||
|--------|-------------|
|
||||
| `get_summary(filters)` | Get summary of memories |
|
||||
| `reset()` | Delete ALL data (users + memories) |
|
||||
| `project.create(name)` | Create a new project |
|
||||
| `project.delete()` | Delete current project |
|
||||
| `project.get_members()` | List project members |
|
||||
| `project.add_member(email, role)` | Add member to project |
|
||||
| `project.update_member(email, role)` | Change member role |
|
||||
| `project.remove_member(email)` | Remove member |
|
||||
|
||||
## Platform Features: TypeScript-only
|
||||
|
||||
| Method | Description |
|
||||
|--------|-------------|
|
||||
| `deleteUser(data)` | Convenience method for single entity deletion |
|
||||
| `ping()` | Health check endpoint |
|
||||
|
||||
## OSS Config Naming
|
||||
|
||||
| Python config key | TypeScript config key |
|
||||
|-------------------|----------------------|
|
||||
| `vector_store` | `vectorStore` |
|
||||
| `history_db_path` | `historyDbPath` |
|
||||
| `custom_instructions` | `customInstructions` |
|
||||
|
||||
## OSS Scope Parameter Naming
|
||||
|
||||
| Python | TypeScript |
|
||||
|--------|------------|
|
||||
| `user_id="alice"` | `userId: 'alice'` |
|
||||
| `agent_id="bot"` | `agentId: 'bot'` |
|
||||
| `run_id="session"` | `runId: 'session'` |
|
||||
|
||||
## Entity ID Passing (v3)
|
||||
|
||||
| Method | Python | TypeScript |
|
||||
|--------|--------|------------|
|
||||
| add() | Top-level: `user_id="alice"` | Top-level: `{ userId: 'alice' }` |
|
||||
| search() | In filters: `filters={"user_id": "alice"}` | In filters: `{ filters: { user_id: 'alice' } }` |
|
||||
| get_all() | In filters: `filters={"user_id": "alice"}` | In filters: `{ filters: { user_id: 'alice' } }` |
|
||||
|
||||
## Common Gotcha
|
||||
|
||||
When searching/filtering, both Python and TypeScript use `snake_case` for filter keys. TypeScript only uses `camelCase` for top-level method parameters:
|
||||
|
||||
```python
|
||||
# Python - snake_case in filters
|
||||
results = client.search("query", filters={"user_id": "alice"})
|
||||
```
|
||||
|
||||
```typescript
|
||||
// TypeScript - snake_case in filters, camelCase for top-level params
|
||||
const results = await client.search('query', { filters: { user_id: 'alice' }, topK: 20 });
|
||||
```
|
||||
@@ -0,0 +1,418 @@
|
||||
# Mem0 Node.js / TypeScript SDK Reference
|
||||
|
||||
Complete reference for the `mem0ai` npm package. Covers both the Platform client (managed API) and the Open Source self-hosted variant.
|
||||
|
||||
---
|
||||
|
||||
## Platform Client
|
||||
|
||||
### Installation
|
||||
|
||||
```bash
|
||||
npm install mem0ai
|
||||
export MEM0_API_KEY="m0-your-api-key"
|
||||
```
|
||||
|
||||
### MemoryClient
|
||||
|
||||
```typescript
|
||||
import MemoryClient from 'mem0ai';
|
||||
|
||||
const client = new MemoryClient({ apiKey: 'm0-xxx' });
|
||||
```
|
||||
|
||||
**Constructor:** `new MemoryClient({ apiKey })`. If `apiKey` is not provided, reads from `MEM0_API_KEY` environment variable.
|
||||
|
||||
- HTTP library: `axios`
|
||||
- Timeout: 60 seconds
|
||||
- Base URL: `https://api.mem0.ai`
|
||||
- All methods are async (return `Promise`)
|
||||
|
||||
---
|
||||
|
||||
### Memory Methods
|
||||
|
||||
#### add(messages, options?)
|
||||
|
||||
Store new memories from messages.
|
||||
|
||||
```typescript
|
||||
const messages = [
|
||||
{ role: 'user', content: "I'm a vegetarian and allergic to nuts." },
|
||||
{ role: 'assistant', content: "Got it! I'll remember that." },
|
||||
];
|
||||
await client.add(messages, { userId: 'alice' });
|
||||
```
|
||||
|
||||
| Parameter | Type | Description |
|
||||
|-----------|------|-------------|
|
||||
| `messages` | `Message[]` | Array of `{role, content}` objects |
|
||||
| `options.userId` | string | User identifier |
|
||||
| `options.agentId` | string | Agent identifier |
|
||||
| `options.appId` | string | Application identifier |
|
||||
| `options.runId` | string | Session identifier |
|
||||
| `options.metadata` | object | Custom key-value pairs |
|
||||
| `options.infer` | boolean | If false, store raw text (default: true) |
|
||||
|
||||
**Returns:** `Promise<any>` -- list of events
|
||||
|
||||
#### search(query, options?)
|
||||
|
||||
Search memories by semantic similarity.
|
||||
|
||||
```typescript
|
||||
const results = await client.search('dietary preferences', { filters: { user_id: 'alice' }, topK: 20 });
|
||||
for (const mem of results.results) {
|
||||
console.log(mem.memory, mem.score);
|
||||
}
|
||||
```
|
||||
|
||||
| Parameter | Type | Description |
|
||||
|-----------|------|-------------|
|
||||
| `query` | string | Natural language search query |
|
||||
| `options.filters` | object | Filter object with entity IDs (`user_id`, `agent_id`, etc.) and/or `AND`/`OR`/`NOT` conditions |
|
||||
| `options.topK` | number | Number of results (default: 20) |
|
||||
| `options.rerank` | boolean | Enable semantic reranking (default: false) |
|
||||
| `options.threshold` | number | Minimum similarity (default: 0.1) |
|
||||
|
||||
**Returns:** `Promise<SearchResult>` -- `{results: [{id, memory, score, ...}]}`
|
||||
|
||||
#### get(memoryId)
|
||||
|
||||
```typescript
|
||||
const memory = await client.get('ea925981-...');
|
||||
```
|
||||
|
||||
#### getAll(options?)
|
||||
|
||||
Retrieve all memories. Requires at least one entity identifier in filters.
|
||||
|
||||
```typescript
|
||||
const memories = await client.getAll({ filters: { user_id: 'alice' } });
|
||||
// With filters
|
||||
const filtered = await client.getAll({
|
||||
filters: { AND: [{ user_id: 'alice' }, { categories: { contains: 'health' } }] },
|
||||
});
|
||||
```
|
||||
|
||||
| Parameter | Type | Description |
|
||||
|-----------|------|-------------|
|
||||
| `options.filters` | object | Filter object with entity IDs (`user_id`, `agent_id`, etc.) and/or `AND`/`OR`/`NOT` conditions |
|
||||
| `options.page` | number | Page number |
|
||||
| `options.pageSize` | number | Results per page |
|
||||
|
||||
#### update(memoryId, data)
|
||||
|
||||
```typescript
|
||||
await client.update('ea925981-...', { text: 'Updated: vegan since 2024' });
|
||||
await client.update('ea925981-...', { text: 'Updated', metadata: { verified: true } });
|
||||
```
|
||||
|
||||
| Parameter | Type | Description |
|
||||
|-----------|------|-------------|
|
||||
| `memoryId` | string | Memory ID |
|
||||
| `data.text` | string | New content |
|
||||
| `data.metadata` | object | New metadata |
|
||||
| `data.timestamp` | string | New timestamp |
|
||||
|
||||
#### delete(memoryId)
|
||||
|
||||
```typescript
|
||||
await client.delete('ea925981-...');
|
||||
```
|
||||
|
||||
#### deleteAll(options?)
|
||||
|
||||
```typescript
|
||||
await client.deleteAll({ userId: 'alice' });
|
||||
```
|
||||
|
||||
#### history(memoryId)
|
||||
|
||||
```typescript
|
||||
const history = await client.history('ea925981-...');
|
||||
// Returns: [{previousValue, newValue, action, timestamps}]
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### Batch Methods
|
||||
|
||||
#### batchUpdate(memories)
|
||||
|
||||
```typescript
|
||||
await client.batchUpdate([
|
||||
{ memoryId: 'uuid-1', text: 'Updated text' },
|
||||
{ memoryId: 'uuid-2', text: 'Another update' },
|
||||
]);
|
||||
```
|
||||
|
||||
#### batchDelete(memories)
|
||||
|
||||
```typescript
|
||||
await client.batchDelete(['uuid-1', 'uuid-2', 'uuid-3']);
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### User/Entity Management
|
||||
|
||||
#### users()
|
||||
|
||||
```typescript
|
||||
const users = await client.users();
|
||||
// Returns: {results: [{type: "user", name: "alice"}, ...]}
|
||||
```
|
||||
|
||||
#### deleteUser(data) / deleteUsers(data)
|
||||
|
||||
```typescript
|
||||
await client.deleteUser({ userId: 'alice' }); // Single entity
|
||||
await client.deleteUsers({ agentId: 'bot-1' }); // Flexible
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### Project Management
|
||||
|
||||
```typescript
|
||||
// Get project config
|
||||
const config = await client.getProject({ fields: ['customCategories'] });
|
||||
|
||||
// Update project settings
|
||||
await client.updateProject({
|
||||
customInstructions: 'Extract dietary preferences and health info',
|
||||
customCategories: [{ health: 'Medical and dietary info' }],
|
||||
});
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### Webhooks
|
||||
|
||||
```typescript
|
||||
// List
|
||||
const webhooks = await client.getWebhooks({ projectId: 'proj_123' });
|
||||
|
||||
// Create
|
||||
const webhook = await client.createWebhook({
|
||||
url: 'https://your-app.com/webhook',
|
||||
name: 'Memory Logger',
|
||||
projectId: 'proj_123',
|
||||
eventTypes: ['memory_add', 'memory_update'],
|
||||
});
|
||||
|
||||
// Update
|
||||
await client.updateWebhook({
|
||||
webhookId: 'wh_123',
|
||||
name: 'Updated Logger',
|
||||
url: 'https://new-url.com',
|
||||
});
|
||||
|
||||
// Delete
|
||||
await client.deleteWebhook({ webhookId: 'wh_123' });
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### Feedback
|
||||
|
||||
```typescript
|
||||
await client.feedback({
|
||||
memoryId: 'mem-123',
|
||||
feedback: 'POSITIVE',
|
||||
feedbackReason: 'Accurately captured preference',
|
||||
});
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### Export
|
||||
|
||||
```typescript
|
||||
const exportReq = await client.createMemoryExport({
|
||||
schema: JSON.stringify({ type: 'object', properties: { name: { type: 'string' } } }),
|
||||
filters: { user_id: 'alice' },
|
||||
});
|
||||
|
||||
const result = await client.getMemoryExport({ memoryExportId: exportReq.id });
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### TypeScript Types
|
||||
|
||||
Key interfaces from `mem0.types.ts`:
|
||||
|
||||
```typescript
|
||||
interface Message { role: string; content: string; }
|
||||
interface Memory { id: string; memory: string; userId: string; categories: string[]; score?: number; /* ... */ }
|
||||
interface MemoryOptions { userId?: string; agentId?: string; appId?: string; runId?: string; metadata?: object; /* ... */ }
|
||||
interface SearchOptions { filters?: object; topK?: number; rerank?: boolean; threshold?: number; /* ... */ }
|
||||
interface MemoryHistory { id: string; memoryId: string; previousValue: string; newValue: string; action: string; /* ... */ }
|
||||
interface FeedbackPayload { memoryId: string; feedback: string; feedbackReason?: string; }
|
||||
interface WebhookCreatePayload { url: string; name: string; projectId: string; eventTypes: string[]; }
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Open Source / Self-Hosted
|
||||
|
||||
### Installation
|
||||
|
||||
```bash
|
||||
npm install mem0ai
|
||||
```
|
||||
|
||||
### Memory Class
|
||||
|
||||
```typescript
|
||||
import { Memory } from 'mem0ai/oss';
|
||||
|
||||
const m = new Memory(); // Uses default config
|
||||
```
|
||||
|
||||
**Import:** `from 'mem0ai/oss'` (NOT the default export -- that is `MemoryClient` for Platform)
|
||||
|
||||
### Configuration
|
||||
|
||||
```typescript
|
||||
const config = {
|
||||
llm: {
|
||||
provider: 'openai', // openai, groq, anthropic, google, ollama, lmstudio, mistral, azure
|
||||
config: {
|
||||
model: 'gpt-5-mini',
|
||||
apiKey: 'sk-xxx',
|
||||
},
|
||||
},
|
||||
embedder: {
|
||||
provider: 'openai', // openai, ollama, lmstudio, google, azure, langchain, anthropic
|
||||
config: {
|
||||
model: 'text-embedding-3-small',
|
||||
apiKey: 'sk-xxx',
|
||||
},
|
||||
},
|
||||
vectorStore: {
|
||||
provider: 'qdrant', // memory, qdrant, redis, supabase, langchain, azure_ai_search, pgvector
|
||||
config: {
|
||||
collectionName: 'my_memories',
|
||||
host: 'localhost',
|
||||
port: 6333,
|
||||
},
|
||||
},
|
||||
historyDbPath: 'history.db',
|
||||
customInstructions: '...',
|
||||
disableHistory: false,
|
||||
};
|
||||
|
||||
const m = new Memory(config);
|
||||
// Or from dict with validation:
|
||||
const m2 = Memory.fromConfig(config);
|
||||
```
|
||||
|
||||
### Methods
|
||||
|
||||
All methods are async (return `Promise`):
|
||||
|
||||
#### add(messages, config)
|
||||
|
||||
```typescript
|
||||
await m.add('I prefer dark mode', { userId: 'alice' });
|
||||
await m.add([
|
||||
{ role: 'user', content: 'I like hiking' },
|
||||
{ role: 'assistant', content: 'Great outdoor activity!' },
|
||||
], { userId: 'alice' });
|
||||
```
|
||||
|
||||
| Parameter | Type | Description |
|
||||
|-----------|------|-------------|
|
||||
| `messages` | `string \| Message[]` | Content to store |
|
||||
| `config.userId` | string | User identifier (at least one scope required) |
|
||||
| `config.agentId` | string | Agent identifier |
|
||||
| `config.runId` | string | Session identifier |
|
||||
| `config.metadata` | object | Custom key-value pairs |
|
||||
| `config.filters` | object | Additional filters |
|
||||
| `config.infer` | boolean | LLM inference (default: true) |
|
||||
|
||||
**Returns:** `Promise<{results: [...], relations?: [...]}>`
|
||||
|
||||
#### search(query, config)
|
||||
|
||||
```typescript
|
||||
const results = await m.search('dietary preferences', { filters: { user_id: 'alice' }, topK: 5 });
|
||||
```
|
||||
|
||||
| Parameter | Type | Description |
|
||||
|-----------|------|-------------|
|
||||
| `query` | string | Search query |
|
||||
| `config.filters` | object | Filter object with entity IDs (`user_id`, `agent_id`, `run_id`, etc.) |
|
||||
| `config.topK` | number | Max results (default: 20) |
|
||||
|
||||
#### get(memoryId) / getAll(config) / update(memoryId, data) / delete(memoryId) / deleteAll(config) / history(memoryId)
|
||||
|
||||
Same interface patterns. Note: OSS `update` takes a string for data, not an object.
|
||||
|
||||
```typescript
|
||||
await m.update('mem-id', 'new content');
|
||||
```
|
||||
|
||||
#### reset()
|
||||
|
||||
Clear the entire vector store and history.
|
||||
|
||||
```typescript
|
||||
await m.reset();
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Key Differences: Platform vs OSS
|
||||
|
||||
| Aspect | Platform (`MemoryClient`) | OSS (`Memory`) |
|
||||
|--------|--------------------------|----------------|
|
||||
| **Import** | `import MemoryClient from 'mem0ai'` | `import { Memory } from 'mem0ai/oss'` |
|
||||
| **Auth** | API key required (`MEM0_API_KEY`) | No API key -- config-based |
|
||||
| **Execution** | API calls to `api.mem0.ai` | Local execution |
|
||||
| **Infrastructure** | Fully managed | Self-managed vector DB, embedder, LLM |
|
||||
| **Param style** | Top-level: `camelCase` (`userId`, `topK`), filter keys: `snake_case` (`user_id`) | Top-level: `camelCase` (`userId`, `topK`), filter keys: `snake_case` (`user_id`) |
|
||||
| **Batch ops** | `batchUpdate`, `batchDelete` | Not available |
|
||||
| **Webhooks** | Full CRUD | Not available |
|
||||
| **Export** | `createMemoryExport` | Not available |
|
||||
| **Feedback** | `feedback()` | Not available |
|
||||
| **Project mgmt** | `getProject`, `updateProject` | Not available |
|
||||
| **User listing** | `users()`, `deleteUser()` | Not available |
|
||||
| **History** | Platform-managed | SQLite (configurable) |
|
||||
|
||||
---
|
||||
|
||||
## v2 Compatibility
|
||||
|
||||
If you're using SDK v2.x:
|
||||
|
||||
**Naming Changes:**
|
||||
- Top-level params now use camelCase: `topK`, `rerank` (not `top_k`)
|
||||
- Filter keys use snake_case: `user_id`, `agent_id`
|
||||
- OSS: `limit` renamed to `topK`
|
||||
|
||||
**API Changes:**
|
||||
```typescript
|
||||
// v2 - top-level entity IDs, snake_case
|
||||
await client.search("query", { user_id: "alice", top_k: 20 });
|
||||
|
||||
// v3 - filters object with snake_case keys, camelCase top-level params
|
||||
await client.search("query", { filters: { user_id: "alice" }, topK: 20 });
|
||||
```
|
||||
|
||||
**Default Changes:**
|
||||
| Param | v2 | v3 |
|
||||
|-------|----|----|
|
||||
| `topK` | 100 | 20 |
|
||||
| `threshold` | none | 0.1 |
|
||||
| `rerank` | true | false |
|
||||
|
||||
**Removed:**
|
||||
- `OutputFormat` and `API_VERSION` enums
|
||||
- `organizationId`, `projectId` from constructor
|
||||
- `enableGraph`, `asyncMode`, `outputFormat`, `immutable`, `expirationDate`, `filterMemories`, `batchSize`, `forceAddOnly`, `includes`, `excludes`, `keywordSearch`
|
||||
|
||||
See the [v2 to v3 migration guide](https://docs.mem0.ai/migration/oss-v2-to-v3) for details.
|
||||
@@ -0,0 +1,487 @@
|
||||
# Mem0 Python SDK Reference
|
||||
|
||||
Complete reference for the `mem0ai` Python package. Covers both the Platform client (managed API) and the Open Source self-hosted variant.
|
||||
|
||||
---
|
||||
|
||||
## Platform Client
|
||||
|
||||
### Installation
|
||||
|
||||
```bash
|
||||
pip install mem0ai
|
||||
export MEM0_API_KEY="m0-your-api-key"
|
||||
```
|
||||
|
||||
### MemoryClient (Synchronous)
|
||||
|
||||
```python
|
||||
from mem0 import MemoryClient
|
||||
|
||||
client = MemoryClient(api_key="m0-xxx")
|
||||
```
|
||||
|
||||
**Constructor:** `MemoryClient(api_key=None)`. If `api_key` is not provided, reads from `MEM0_API_KEY` environment variable. Raises `ValueError` if no key found.
|
||||
|
||||
- HTTP library: `httpx`
|
||||
- Timeout: 300 seconds
|
||||
- Base URL: `https://api.mem0.ai`
|
||||
|
||||
### AsyncMemoryClient (Asynchronous)
|
||||
|
||||
```python
|
||||
from mem0 import AsyncMemoryClient
|
||||
|
||||
client = AsyncMemoryClient(api_key="m0-xxx")
|
||||
|
||||
# Or use as context manager
|
||||
async with AsyncMemoryClient(api_key="m0-xxx") as client:
|
||||
results = await client.search("query", filters={"user_id": "alice"})
|
||||
```
|
||||
|
||||
Same methods as `MemoryClient`, all `async`/`await`. Supports async context manager.
|
||||
|
||||
---
|
||||
|
||||
### Memory Methods
|
||||
|
||||
#### add(messages, **kwargs)
|
||||
|
||||
Store new memories from messages.
|
||||
|
||||
```python
|
||||
messages = [
|
||||
{"role": "user", "content": "I'm a vegetarian and allergic to nuts."},
|
||||
{"role": "assistant", "content": "Got it! I'll remember that."}
|
||||
]
|
||||
client.add(messages, user_id="alice")
|
||||
```
|
||||
|
||||
| Parameter | Type | Default | Description |
|
||||
|-----------|------|---------|-------------|
|
||||
| `messages` | str \| dict \| list[dict] | required | Message content. Strings auto-convert to user messages |
|
||||
| `user_id` | str | None | User identifier |
|
||||
| `agent_id` | str | None | Agent identifier |
|
||||
| `app_id` | str | None | Application identifier |
|
||||
| `run_id` | str | None | Session/run identifier |
|
||||
| `metadata` | dict | None | Custom key-value pairs |
|
||||
| `infer` | bool | True | If False, store raw text without LLM inference |
|
||||
| `custom_categories` | list | None | Override project categories |
|
||||
| `custom_instructions` | str | None | Override extraction instructions |
|
||||
| `timestamp` | int \| float \| str | None | Custom timestamp (Unix epoch or ISO 8601) |
|
||||
|
||||
**Returns:** `dict` -- list of events: `[{"id": "...", "event": "ADD", "data": {"memory": "..."}}]`
|
||||
|
||||
#### search(query, **kwargs)
|
||||
|
||||
Search memories by semantic similarity.
|
||||
|
||||
```python
|
||||
results = client.search("dietary preferences", filters={"user_id": "alice"})
|
||||
for mem in results.get("results", []):
|
||||
print(mem["memory"], mem["score"])
|
||||
```
|
||||
|
||||
| Parameter | Type | Default | Description |
|
||||
|-----------|------|---------|-------------|
|
||||
| `query` | str | required | Natural language search query |
|
||||
| `filters` | dict | None | Filter object with entity IDs and/or `AND`/`OR`/`NOT` conditions (e.g., `{"user_id": "alice"}`) |
|
||||
| `top_k` | int | 10 | Number of results |
|
||||
| `rerank` | bool | False | Enable deep semantic reranking (+150-200ms) |
|
||||
| `threshold` | float | 0.1 | Minimum similarity score |
|
||||
| `fields` | list | None | Specific fields to return |
|
||||
| `categories` | list | None | Filter by category |
|
||||
|
||||
**Returns:** `dict` -- `{"results": [{id, memory, user_id, categories, score, created_at, ...}]}`
|
||||
|
||||
#### get(memory_id)
|
||||
|
||||
Retrieve a single memory by ID.
|
||||
|
||||
```python
|
||||
memory = client.get(memory_id="ea925981-...")
|
||||
```
|
||||
|
||||
**Returns:** `dict` -- full memory object
|
||||
|
||||
#### get_all(**kwargs)
|
||||
|
||||
Retrieve all memories with optional filtering. Requires at least one entity identifier.
|
||||
|
||||
```python
|
||||
memories = client.get_all(filters={"user_id": "alice"})
|
||||
# With compound filters
|
||||
memories = client.get_all(filters={"AND": [{"user_id": "alice"}, {"categories": {"contains": "health"}}]})
|
||||
```
|
||||
|
||||
| Parameter | Type | Default | Description |
|
||||
|-----------|------|---------|-------------|
|
||||
| `filters` | dict | None | Filter object with entity IDs and/or `AND`/`OR`/`NOT` conditions |
|
||||
| `top_k` | int | None | Limit results |
|
||||
| `page` | int | None | Page number |
|
||||
| `page_size` | int | None | Results per page |
|
||||
|
||||
**Returns:** `dict` -- `{"results": [...]}`
|
||||
|
||||
#### update(memory_id, text=None, metadata=None, timestamp=None)
|
||||
|
||||
Update a memory's content, metadata, or timestamp. At least one parameter required.
|
||||
|
||||
```python
|
||||
client.update("ea925981-...", text="Updated: vegan since 2024")
|
||||
client.update("ea925981-...", metadata={"verified": True})
|
||||
```
|
||||
|
||||
**Returns:** `dict` -- updated memory
|
||||
|
||||
#### delete(memory_id)
|
||||
|
||||
Permanently delete a single memory.
|
||||
|
||||
```python
|
||||
client.delete("ea925981-...")
|
||||
```
|
||||
|
||||
#### delete_all(**kwargs)
|
||||
|
||||
Delete all memories matching filters. Irreversible.
|
||||
|
||||
```python
|
||||
client.delete_all(user_id="alice")
|
||||
```
|
||||
|
||||
#### history(memory_id)
|
||||
|
||||
Get the change history of a memory.
|
||||
|
||||
```python
|
||||
history = client.history("ea925981-...")
|
||||
# Returns: [{previous_value, new_value, action, timestamps}]
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### Batch Methods
|
||||
|
||||
#### batch_update(memories)
|
||||
|
||||
Update up to 1000 memories in a single request.
|
||||
|
||||
```python
|
||||
client.batch_update([
|
||||
{"memory_id": "uuid-1", "text": "Updated text"},
|
||||
{"memory_id": "uuid-2", "text": "Another update", "metadata": {"verified": True}},
|
||||
])
|
||||
```
|
||||
|
||||
#### batch_delete(memories)
|
||||
|
||||
Delete up to 1000 memories in a single request.
|
||||
|
||||
```python
|
||||
client.batch_delete([
|
||||
{"memory_id": "uuid-1"},
|
||||
{"memory_id": "uuid-2"},
|
||||
])
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### User/Entity Management
|
||||
|
||||
#### users()
|
||||
|
||||
List all users, agents, and sessions that have memories.
|
||||
|
||||
```python
|
||||
users = client.users()
|
||||
# Returns: {"results": [{"type": "user", "name": "alice"}, ...]}
|
||||
```
|
||||
|
||||
#### delete_users(user_id=None, agent_id=None, app_id=None, run_id=None)
|
||||
|
||||
Delete a specific entity and all its memories.
|
||||
|
||||
```python
|
||||
client.delete_users(user_id="alice")
|
||||
```
|
||||
|
||||
#### reset()
|
||||
|
||||
Delete ALL users, agents, sessions, and memories. Complete data reset.
|
||||
|
||||
```python
|
||||
client.reset()
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### Export & Summary
|
||||
|
||||
#### create_memory_export(schema, **kwargs)
|
||||
|
||||
Create a structured export of memories.
|
||||
|
||||
```python
|
||||
import json
|
||||
|
||||
schema = json.dumps({
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"name": {"type": "string"},
|
||||
"preferences": {"type": "array", "items": {"type": "string"}},
|
||||
}
|
||||
})
|
||||
export = client.create_memory_export(schema=schema, user_id="alice")
|
||||
```
|
||||
|
||||
#### get_memory_export(**kwargs)
|
||||
|
||||
Retrieve a previously created export.
|
||||
|
||||
```python
|
||||
result = client.get_memory_export(memory_export_id=export["id"])
|
||||
```
|
||||
|
||||
#### get_summary(filters=None)
|
||||
|
||||
Get a summary of memories.
|
||||
|
||||
```python
|
||||
summary = client.get_summary(filters={"user_id": "alice"})
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### Feedback
|
||||
|
||||
#### feedback(memory_id, feedback=None, feedback_reason=None)
|
||||
|
||||
Provide quality feedback on a memory.
|
||||
|
||||
```python
|
||||
client.feedback(
|
||||
memory_id="mem-123",
|
||||
feedback="POSITIVE", # POSITIVE | NEGATIVE | VERY_NEGATIVE | None (clear)
|
||||
feedback_reason="Accurately captured preference"
|
||||
)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### Webhooks
|
||||
|
||||
```python
|
||||
# List
|
||||
webhooks = client.get_webhooks(project_id="proj_123")
|
||||
|
||||
# Create
|
||||
webhook = client.create_webhook(
|
||||
url="https://your-app.com/webhook",
|
||||
name="Memory Logger",
|
||||
project_id="proj_123",
|
||||
event_types=["memory_add", "memory_update"]
|
||||
)
|
||||
|
||||
# Update
|
||||
client.update_webhook(webhook_id=123, name="Updated", url="https://new-url.com")
|
||||
|
||||
# Delete
|
||||
client.delete_webhook(webhook_id=123)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### Project Management
|
||||
|
||||
Access via `client.project.*`:
|
||||
|
||||
```python
|
||||
# Get project config
|
||||
config = client.project.get(fields=["custom_categories", "custom_instructions"])
|
||||
|
||||
# Update project settings
|
||||
client.project.update(
|
||||
custom_instructions="Extract dietary preferences and health info",
|
||||
custom_categories=[{"health": "Medical and dietary info"}],
|
||||
multilingual=True,
|
||||
)
|
||||
|
||||
# Create/delete project
|
||||
client.project.create(name="My Project", description="...")
|
||||
client.project.delete()
|
||||
|
||||
# Member management
|
||||
members = client.project.get_members()
|
||||
client.project.add_member(email="user@example.com", role="READER") # READER or OWNER
|
||||
client.project.update_member(email="user@example.com", role="OWNER")
|
||||
client.project.remove_member(email="user@example.com")
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Open Source / Self-Hosted
|
||||
|
||||
### Installation
|
||||
|
||||
```bash
|
||||
pip install mem0ai
|
||||
```
|
||||
|
||||
### Memory Class
|
||||
|
||||
```python
|
||||
from mem0 import Memory
|
||||
|
||||
m = Memory() # Uses default config (OpenAI embedder + in-memory vector store)
|
||||
```
|
||||
|
||||
**Import:** `from mem0 import Memory` (NOT `MemoryClient` -- that is the Platform client)
|
||||
|
||||
### Configuration
|
||||
|
||||
```python
|
||||
config = {
|
||||
"llm": {
|
||||
"provider": "openai", # openai, groq, azure, ollama, lmstudio, google, anthropic, mistral
|
||||
"config": {
|
||||
"model": "gpt-5-mini",
|
||||
"api_key": "sk-xxx",
|
||||
}
|
||||
},
|
||||
"embedder": {
|
||||
"provider": "openai", # openai, ollama, azure, lmstudio, google, huggingface
|
||||
"config": {
|
||||
"model": "text-embedding-3-small",
|
||||
"api_key": "sk-xxx",
|
||||
}
|
||||
},
|
||||
"vector_store": {
|
||||
"provider": "qdrant", # faiss, qdrant, pgvector, redis, supabase, azure_ai_search, memory
|
||||
"config": {
|
||||
"collection_name": "my_memories",
|
||||
"host": "localhost",
|
||||
"port": 6333,
|
||||
}
|
||||
},
|
||||
"history_db_path": "history.db", # SQLite path for change history
|
||||
"custom_instructions": "...", # Custom LLM prompt for extraction
|
||||
}
|
||||
|
||||
m = Memory.from_config(config)
|
||||
```
|
||||
|
||||
### Context Manager
|
||||
|
||||
```python
|
||||
with Memory(config) as m:
|
||||
m.add("I prefer dark mode", user_id="alice")
|
||||
results = m.search("preferences", filters={"user_id": "alice"})
|
||||
# SQLite connections released automatically
|
||||
```
|
||||
|
||||
### Methods
|
||||
|
||||
All methods mirror the Platform client but run locally:
|
||||
|
||||
#### add(messages, *, user_id, agent_id, run_id, metadata, infer=True)
|
||||
|
||||
```python
|
||||
m.add("I'm a vegetarian", user_id="alice")
|
||||
m.add([
|
||||
{"role": "user", "content": "I like hiking"},
|
||||
{"role": "assistant", "content": "Great outdoor activity!"}
|
||||
], user_id="alice")
|
||||
```
|
||||
|
||||
At least one of `user_id`, `agent_id`, `run_id` required.
|
||||
|
||||
**Returns:** `{"results": [...], "relations": [...]}`
|
||||
|
||||
#### search(query, *, filters=None, top_k=20, threshold=0.1, rerank=False)
|
||||
|
||||
```python
|
||||
results = m.search("dietary preferences", filters={"user_id": "alice"}, top_k=5)
|
||||
```
|
||||
|
||||
Entity IDs (`user_id`, `agent_id`, `run_id`) must be passed inside the `filters` dict.
|
||||
|
||||
Supports filter operators: `eq`, `ne`, `in`, `nin`, `gt`, `gte`, `lt`, `lte`, `contains`, `not_contains`.
|
||||
|
||||
#### get(memory_id) / get_all(**kwargs) / update(memory_id, data, metadata=None) / delete(memory_id) / delete_all(**kwargs) / history(memory_id)
|
||||
|
||||
Same interface as Platform client.
|
||||
|
||||
#### reset()
|
||||
|
||||
Clear the entire vector store collection and history database. Recreates the vector store.
|
||||
|
||||
```python
|
||||
m.reset()
|
||||
```
|
||||
|
||||
#### close()
|
||||
|
||||
Release SQLite connections. Called automatically when using context manager.
|
||||
|
||||
### AsyncMemory
|
||||
|
||||
```python
|
||||
from mem0 import AsyncMemory
|
||||
|
||||
m = AsyncMemory(config)
|
||||
await m.add("text", user_id="alice")
|
||||
results = await m.search("query", filters={"user_id": "alice"})
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Key Differences: Platform vs OSS
|
||||
|
||||
| Aspect | Platform (`MemoryClient`) | OSS (`Memory`) |
|
||||
|--------|--------------------------|----------------|
|
||||
| **Import** | `from mem0 import MemoryClient` | `from mem0 import Memory` |
|
||||
| **Auth** | API key required (`MEM0_API_KEY`) | No API key -- config-based |
|
||||
| **Execution** | API calls to `api.mem0.ai` | Local execution |
|
||||
| **Infrastructure** | Fully managed | Self-managed vector DB, embedder, LLM |
|
||||
| **Entity filtering** | `filters={"user_id": "..."}` | `filters={"user_id": "..."}` |
|
||||
| **Batch ops** | `batch_update`, `batch_delete` | Not available |
|
||||
| **Webhooks** | Full CRUD | Not available |
|
||||
| **Export** | `create_memory_export`, `get_memory_export` | Not available |
|
||||
| **Feedback** | `feedback()` | Not available |
|
||||
| **Project mgmt** | `client.project.*` | Not available |
|
||||
| **User listing** | `users()`, `delete_users()` | Not available |
|
||||
| **Custom prompts** | Via project settings | Direct config (`custom_instructions`) |
|
||||
| **History** | Platform-managed | SQLite (configurable) |
|
||||
| **Async** | `AsyncMemoryClient` | `AsyncMemory` |
|
||||
|
||||
---
|
||||
|
||||
## v2 Compatibility
|
||||
|
||||
If you're using SDK v2.x or the v2 API:
|
||||
|
||||
**API Changes:**
|
||||
- **Entity IDs in search/get_all:** Pass `user_id`, `agent_id` as top-level kwargs instead of inside `filters`
|
||||
```python
|
||||
# v2
|
||||
results = client.search("query", user_id="alice")
|
||||
# v3
|
||||
results = client.search("query", filters={"user_id": "alice"})
|
||||
```
|
||||
- **add() returns:** v2 returns ADD, UPDATE, DELETE events; v3 returns ADD only
|
||||
|
||||
**Default Changes:**
|
||||
| Param | v2 | v3 |
|
||||
|-------|----|----|
|
||||
| `top_k` | 100 | 20 |
|
||||
| `threshold` | None | 0.1 |
|
||||
| `rerank` | True | False |
|
||||
|
||||
**Removed Parameters:**
|
||||
- Constructor: `org_id`, `project_id`
|
||||
- add(): `async_mode`, `output_format`, `enable_graph`, `immutable`, `expiration_date`, `filter_memories`, `batch_size`, `force_add_only`, `includes`, `excludes`, `keyword_search`
|
||||
- search()/get_all(): `enable_graph`
|
||||
- Config: `enable_graph`, `graph_store`, `custom_fact_extraction_prompt` (renamed to `custom_instructions`)
|
||||
|
||||
See the [v2 to v3 migration guide](https://docs.mem0.ai/migration/oss-v2-to-v3) for full details.
|
||||
+150
@@ -0,0 +1,150 @@
|
||||
# Mem0 Platform API Reference
|
||||
|
||||
REST API endpoints for the Mem0 Platform. Base URL: `https://api.mem0.ai`
|
||||
|
||||
All endpoints require: `Authorization: Token <MEM0_API_KEY>`
|
||||
|
||||
## Endpoints
|
||||
|
||||
| Operation | Method | URL |
|
||||
|-----------|--------|-----|
|
||||
| Add Memories | `POST` | `/v3/memories/add/` |
|
||||
| Search Memories | `POST` | `/v3/memories/search/` |
|
||||
| Get All Memories | `POST` | `/v3/memories/` |
|
||||
| Get Single Memory | `GET` | `/v1/memories/{memory_id}/` |
|
||||
| Update Memory | `PUT` | `/v1/memories/{memory_id}/` |
|
||||
| Delete Memory | `DELETE` | `/v1/memories/{memory_id}/` |
|
||||
| Delete All Memories | `DELETE` | `/v1/memories/?user_id=X&app_id=Y` |
|
||||
| Get Event Status | `GET` | `/v1/event/{event_id}/` |
|
||||
|
||||
## Memory Object Structure
|
||||
|
||||
| Field | Type | Description |
|
||||
|-------|------|-------------|
|
||||
| `id` | string (UUID) | Unique memory identifier |
|
||||
| `memory` | string | Text content of the memory |
|
||||
| `user_id` | string | Associated user |
|
||||
| `agent_id` | string (nullable) | Agent identifier |
|
||||
| `app_id` | string (nullable) | Application identifier |
|
||||
| `run_id` | string (nullable) | Run/session identifier |
|
||||
| `metadata` | object | Custom key-value pairs |
|
||||
| `categories` | array of strings | Auto-assigned category tags |
|
||||
| `hash` | string | Content hash |
|
||||
| `created_at` | datetime | Creation timestamp |
|
||||
| `updated_at` | datetime | Last modification timestamp |
|
||||
|
||||
Search results additionally include `score` (relevance metric).
|
||||
|
||||
## Scoping Identifiers
|
||||
|
||||
Memories can be scoped to different levels:
|
||||
|
||||
| Scope | Parameter | Use Case |
|
||||
|-------|-----------|----------|
|
||||
| User | `user_id` | Per-user memory isolation |
|
||||
| Agent | `agent_id` | Per-agent memory partitioning |
|
||||
| Application | `app_id` | Cross-agent app-level memory |
|
||||
| Run/Session | `run_id` | Session-scoped temporary memory |
|
||||
|
||||
**Critical:** Combining `user_id` and `agent_id` in a single AND filter yields empty results. Entities are stored separately. Use `OR` logic or separate queries.
|
||||
|
||||
## Processing Model
|
||||
|
||||
- Memories are processed **asynchronously** (v3 default)
|
||||
- Add responses return queued `ADD` events only (v3 is ADD-only, no UPDATE/DELETE)
|
||||
- Poll status via `GET /v1/event/{event_id}/`
|
||||
|
||||
## Filter System
|
||||
|
||||
Filters use nested JSON with a logical operator at the root:
|
||||
|
||||
```json
|
||||
{
|
||||
"AND": [
|
||||
{"user_id": "alice"},
|
||||
{"categories": {"contains": "finance"}},
|
||||
{"created_at": {"gte": "2024-01-01"}}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
Root must be `AND`, `OR`, or `NOT`. Simple shorthand `{"user_id": "alice"}` also works.
|
||||
|
||||
### Supported Operators
|
||||
|
||||
| Operator | Description |
|
||||
|----------|-------------|
|
||||
| `eq` | Equal to (default) |
|
||||
| `ne` | Not equal to |
|
||||
| `in` | Matches any value in array |
|
||||
| `gt`, `gte` | Greater than / greater than or equal |
|
||||
| `lt`, `lte` | Less than / less than or equal |
|
||||
| `contains` | Case-sensitive containment |
|
||||
| `icontains` | Case-insensitive containment |
|
||||
| `*` | Wildcard -- matches any non-null value |
|
||||
|
||||
### Filterable Fields
|
||||
|
||||
| Field | Valid Operators |
|
||||
|-------|-----------------|
|
||||
| `user_id`, `agent_id`, `app_id`, `run_id` | `eq`, `ne`, `in`, `*` |
|
||||
| `created_at`, `updated_at`, `timestamp` | `gt`, `gte`, `lt`, `lte`, `eq`, `ne` |
|
||||
| `categories` | `eq`, `ne`, `in`, `contains` |
|
||||
| `metadata` | `eq`, `ne`, `contains` (top-level keys only) |
|
||||
| `keywords` | `contains`, `icontains` |
|
||||
| `memory_ids` | `in` |
|
||||
|
||||
### Filter Constraints
|
||||
|
||||
1. **Entity scope partitioning:** `user_id` AND `agent_id` in one `AND` block yields empty results.
|
||||
2. **Metadata limitations:** Only top-level keys. Only `eq`, `contains`, `ne`. No `in` or `gt`.
|
||||
3. **Operator syntax:** Use `gte`, `lt`, `ne`. SQL-style (`>=`, `!=`) rejected.
|
||||
4. **Entity filter required for get-all:** At least one of `user_id`, `agent_id`, `app_id`, or `run_id`.
|
||||
5. **Wildcard excludes null:** `*` matches only non-null values.
|
||||
6. **Date format:** ISO 8601 (`YYYY-MM-DDTHH:MM:SSZ`). Timezone-naive defaults to UTC.
|
||||
|
||||
## Response Formats
|
||||
|
||||
### Add Response (v3)
|
||||
|
||||
```json
|
||||
{
|
||||
"message": "Memory processing has been queued for background execution",
|
||||
"status": "PENDING",
|
||||
"event_id": "evt-uuid"
|
||||
}
|
||||
```
|
||||
|
||||
v3 is ADD-only. No UPDATE or DELETE events.
|
||||
|
||||
### Search Response
|
||||
|
||||
```json
|
||||
{
|
||||
"results": [
|
||||
{
|
||||
"id": "ea925981-...",
|
||||
"memory": "Is a vegetarian and allergic to nuts.",
|
||||
"user_id": "user123",
|
||||
"categories": ["food", "health"],
|
||||
"score": 0.89,
|
||||
"created_at": "2024-07-26T10:29:36.630547-07:00"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
In v3, `score` is a combined multi-signal relevance score.
|
||||
|
||||
### Get All Response (v3)
|
||||
|
||||
```json
|
||||
{
|
||||
"count": 123,
|
||||
"next": "https://api.mem0.ai/v3/memories/?page=2&page_size=50",
|
||||
"previous": null,
|
||||
"results": [...]
|
||||
}
|
||||
```
|
||||
|
||||
v3 returns paginated envelope. Use `page` and `page_size` query params.
|
||||
+330
@@ -0,0 +1,330 @@
|
||||
# Mem0 Platform Architecture
|
||||
|
||||
How Mem0 processes, stores, and retrieves memories under the hood.
|
||||
|
||||
## Table of Contents
|
||||
|
||||
- [Core Concept](#core-concept)
|
||||
- [Memory Processing Pipeline](#memory-processing-pipeline)
|
||||
- [Retrieval Pipeline](#retrieval-pipeline)
|
||||
- [Memory Lifecycle](#memory-lifecycle)
|
||||
- [Memory Object Structure](#memory-object-structure)
|
||||
- [Scoping & Multi-Tenancy](#scoping--multi-tenancy)
|
||||
- [Memory Layers](#memory-layers)
|
||||
- [Performance Characteristics](#performance-characteristics)
|
||||
|
||||
---
|
||||
|
||||
## Core Concept
|
||||
|
||||
Mem0 is a managed memory layer that sits between your AI application and users. Every integration follows the same 3-step loop:
|
||||
|
||||
```
|
||||
User Input → Retrieve relevant memories → Enrich LLM prompt → Generate response → Store new memories
|
||||
```
|
||||
|
||||
Mem0 handles the complexity of extraction, deduplication, conflict resolution, and semantic retrieval so your application only needs to call `search()` and `add()`.
|
||||
|
||||
**Storage architecture:**
|
||||
- **Vector store**: Embeddings for semantic similarity search
|
||||
- **Entity store**: Automatic entity linking for relationship-aware retrieval
|
||||
|
||||
---
|
||||
|
||||
## Memory Processing Pipeline
|
||||
|
||||
### What happens when you call `client.add()`
|
||||
|
||||
```
|
||||
Messages In
|
||||
│
|
||||
▼
|
||||
┌─────────────────────┐
|
||||
│ 1. EXTRACTION │ Single LLM call extracts all distinct new facts
|
||||
│ (infer=True) │ If infer=False, stores raw text as-is
|
||||
└─────────┬───────────┘
|
||||
│
|
||||
▼
|
||||
┌─────────────────────┐
|
||||
│ 2. DEDUPLICATION │ Hash-based dedup (MD5 prevents exact duplicates)
|
||||
│ │ No UPDATE/DELETE - v3 is ADD-only
|
||||
└─────────┬───────────┘
|
||||
│
|
||||
▼
|
||||
┌─────────────────────┐
|
||||
│ 3. STORAGE │ Batch embed → vector store
|
||||
│ │ Entity extraction → entity store
|
||||
└─────────┬───────────┘
|
||||
│
|
||||
▼
|
||||
Memory Object
|
||||
```
|
||||
|
||||
### Processing (v3)
|
||||
|
||||
v3 processes memories asynchronously by default:
|
||||
- API returns immediately: `{"status": "PENDING", "event_id": "evt-..."}`
|
||||
- Poll status via `GET /v1/event/{event_id}/`
|
||||
- Use webhooks for completion notifications
|
||||
|
||||
### Extraction modes
|
||||
|
||||
**Inferred (`infer=True`, default):**
|
||||
- LLM extracts structured facts from conversation
|
||||
- Conflict resolution deduplicates and resolves contradictions
|
||||
- Best for: natural conversation → memory
|
||||
|
||||
**Raw (`infer=False`):**
|
||||
- Stores text exactly as provided, no LLM processing
|
||||
- Skips conflict resolution — same fact can be stored twice
|
||||
- Only `user` role messages are stored; `assistant` messages ignored
|
||||
- Best for: bulk imports, pre-structured data, migrations
|
||||
|
||||
**Warning:** Don't mix `infer=True` and `infer=False` for the same data — the same fact will be stored twice.
|
||||
|
||||
---
|
||||
|
||||
## Retrieval Pipeline (v3)
|
||||
|
||||
### What happens when you call `client.search()`
|
||||
|
||||
```
|
||||
Query In
|
||||
│
|
||||
▼
|
||||
┌─────────────────────┐
|
||||
│ 1. PREPROCESSING │ Lemmatize keywords, extract entities
|
||||
└─────────┬───────────┘
|
||||
│
|
||||
▼
|
||||
┌─────────────────────┐
|
||||
│ 2. PARALLEL SCORING │ Semantic search (vector similarity)
|
||||
│ │ BM25 keyword search (term matching)
|
||||
│ │ Entity matching (entity graph boost)
|
||||
└─────────┬───────────┘
|
||||
│
|
||||
▼
|
||||
┌─────────────────────┐
|
||||
│ 3. SCORE FUSION │ Combine signals into single score
|
||||
│ │ Optional: rerank=True for deep reordering
|
||||
└─────────┬───────────┘
|
||||
│
|
||||
▼
|
||||
Results (combined score per memory)
|
||||
```
|
||||
|
||||
### v3 Search Defaults
|
||||
|
||||
| Parameter | Default | Notes |
|
||||
|-----------|---------|-------|
|
||||
| `top_k` | 20 | Was 100 in v2 |
|
||||
| `threshold` | 0.1 | Was None in v2 |
|
||||
| `rerank` | False | Was True in v2 |
|
||||
|
||||
### Implicit null scoping
|
||||
|
||||
When you search with `filters={"user_id": "alice"}` only, Mem0 returns memories where `agent_id`, `app_id`, and `run_id` are all null. This prevents cross-scope leakage by default.
|
||||
|
||||
To include memories with non-null fields, use explicit filters:
|
||||
```python
|
||||
# Gets memories for alice regardless of agent/app/run
|
||||
filters={"OR": [{"user_id": "alice"}]}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Memory Lifecycle (v3)
|
||||
|
||||
v3 uses ADD-only extraction. Memories accumulate over time rather than being consolidated.
|
||||
|
||||
### Creation
|
||||
- `client.add(messages, user_id="...")`
|
||||
- Single-pass extraction → deduplication → storage
|
||||
- Returns `{"event_id": "...", "status": "PENDING"}`
|
||||
|
||||
### Updates
|
||||
- `client.update(memory_id, text="...")` replaces text
|
||||
- Batch: `client.batch_update([...])`
|
||||
|
||||
### Deletion
|
||||
- Single: `client.delete(memory_id)`
|
||||
- Batch: `client.batch_delete([...])`
|
||||
- Bulk: `client.delete_all(filters={"user_id": "alice"})`
|
||||
|
||||
---
|
||||
|
||||
## Memory Object Structure
|
||||
|
||||
```json
|
||||
{
|
||||
"id": "uuid-string",
|
||||
"memory": "Extracted memory text",
|
||||
"user_id": "user-identifier",
|
||||
"agent_id": null,
|
||||
"app_id": null,
|
||||
"run_id": null,
|
||||
"metadata": { "source": "chat", "priority": "high" },
|
||||
"categories": ["health", "preferences"],
|
||||
"created_at": "2025-03-12T12:34:56Z",
|
||||
"updated_at": "2025-03-12T12:34:56Z",
|
||||
"structured_attributes": {
|
||||
"day": 12, "month": 3, "year": 2025,
|
||||
"hour": 12, "minute": 34,
|
||||
"day_of_week": "wednesday",
|
||||
"is_weekend": false,
|
||||
"quarter": 1, "week_of_year": 11
|
||||
},
|
||||
"score": 0.85
|
||||
}
|
||||
```
|
||||
|
||||
| Field | Type | Description |
|
||||
|-------|------|-------------|
|
||||
| `id` | UUID | Unique identifier, used for update/delete |
|
||||
| `memory` | string | Extracted or stored text content |
|
||||
| `user_id` | string | Primary entity scope |
|
||||
| `agent_id` | string | Agent scope |
|
||||
| `app_id` | string | Application scope |
|
||||
| `run_id` | string | Session/run scope |
|
||||
| `metadata` | object | Custom key-value pairs for filtering |
|
||||
| `categories` | array | Auto-assigned or custom category tags |
|
||||
| `created_at` | datetime | Creation timestamp |
|
||||
| `updated_at` | datetime | Last modification timestamp |
|
||||
| `structured_attributes` | object | Temporal breakdown for time-based queries |
|
||||
| `score` | float | Semantic similarity (search results only, 0-1) |
|
||||
|
||||
---
|
||||
|
||||
## Scoping & Multi-Tenancy
|
||||
|
||||
Mem0 separates memories across four dimensions to prevent data mixing:
|
||||
|
||||
| Dimension | Field | Purpose | Example |
|
||||
|-----------|-------|---------|---------|
|
||||
| User | `user_id` | Persistent persona or account | `"customer_6412"` |
|
||||
| Agent | `agent_id` | Distinct agent or tool | `"meal_planner"` |
|
||||
| App | `app_id` | Product surface or deployment | `"ios_retail_app"` |
|
||||
| Session | `run_id` | Short-lived flow or thread | `"ticket-9241"` |
|
||||
|
||||
### Storage model
|
||||
|
||||
Each entity combination creates separate records. A memory with `user_id="alice"` is stored separately from one with `user_id="alice"` + `agent_id="bot"`.
|
||||
|
||||
### Critical: cross-entity queries
|
||||
|
||||
```python
|
||||
# This returns NOTHING — user and agent memories are stored separately
|
||||
filters={"AND": [{"user_id": "alice"}, {"agent_id": "bot"}]}
|
||||
|
||||
# Use OR to query multiple scopes
|
||||
filters={"OR": [{"user_id": "alice"}, {"agent_id": "bot"}]}
|
||||
|
||||
# Use wildcard to include any non-null value
|
||||
filters={"AND": [{"user_id": "*"}]} # All users (excludes null)
|
||||
```
|
||||
|
||||
### Recommended scoping patterns
|
||||
|
||||
```python
|
||||
# User-level: persistent preferences
|
||||
client.add(messages, user_id="alice")
|
||||
|
||||
# Session-level: temporary context
|
||||
client.add(messages, user_id="alice", run_id="session_123")
|
||||
# Clean up when done: client.delete_all(run_id="session_123")
|
||||
|
||||
# Agent-level: agent-specific knowledge
|
||||
client.add(messages, agent_id="support_bot", app_id="helpdesk")
|
||||
|
||||
# Multi-tenant: full isolation
|
||||
client.add(messages, user_id="alice", agent_id="bot", app_id="acme_corp", run_id="ticket_42")
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Memory Layers
|
||||
|
||||
Mem0 supports three layers of memory, from shortest to longest lived:
|
||||
|
||||
### Conversation memory
|
||||
- In-flight messages within a single turn
|
||||
- Tool calls, chain-of-thought reasoning
|
||||
- **Lifetime:** Single response — lost after turn finishes
|
||||
- **Managed by:** Your application, not Mem0
|
||||
|
||||
### Session memory
|
||||
- Short-lived facts for current task or channel
|
||||
- Multi-step flows (onboarding, debugging, support tickets)
|
||||
- **Lifetime:** Minutes to hours
|
||||
- **Managed by:** Mem0 via `run_id` parameter
|
||||
- Clean up with `client.delete_all(run_id="session_id")`
|
||||
|
||||
### User memory
|
||||
- Long-lived knowledge tied to a person or account
|
||||
- Personal preferences, account state, compliance details
|
||||
- **Lifetime:** Weeks to forever
|
||||
- **Managed by:** Mem0 via `user_id` parameter
|
||||
- Persists across all sessions and interactions
|
||||
|
||||
### How layering works in practice
|
||||
|
||||
```python
|
||||
def chat(user_input: str, user_id: str, session_id: str) -> str:
|
||||
# 1. Retrieve user memories (long-term preferences)
|
||||
user_mems = mem0.search(user_input, filters={"user_id": user_id})
|
||||
|
||||
# 2. Retrieve session memories (current task context)
|
||||
session_mems = mem0.search(user_input, filters={
|
||||
"AND": [{"user_id": user_id}, {"run_id": session_id}]
|
||||
})
|
||||
|
||||
# 3. Combine both layers for LLM context
|
||||
context = format_memories(user_mems) + format_memories(session_mems)
|
||||
|
||||
# 4. Generate response
|
||||
response = llm.generate(context=context, input=user_input)
|
||||
|
||||
# 5. Store in session scope (temporary) + user scope (persistent)
|
||||
messages = [{"role": "user", "content": user_input}, {"role": "assistant", "content": response}]
|
||||
mem0.add(messages, user_id=user_id, run_id=session_id)
|
||||
|
||||
return response
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Performance Characteristics
|
||||
|
||||
### Latency
|
||||
|
||||
| Operation | Typical Latency |
|
||||
|-----------|----------------|
|
||||
| Hybrid search (v3 default) | ~100-150ms |
|
||||
| + reranking | +150-200ms |
|
||||
| Add (async) | < 50ms response |
|
||||
|
||||
### Processing
|
||||
|
||||
- **Async (default):** Returns immediately, processes in background
|
||||
- **Batch operations:** Up to 1000 memories per batch_update/batch_delete
|
||||
- **Webhooks:** Real-time notifications when async processing completes
|
||||
|
||||
### Scoping strategy for performance
|
||||
|
||||
- Use `user_id` for all user-facing queries (most common, fastest)
|
||||
- Add `run_id` for session isolation (narrows search space)
|
||||
- Avoid wildcard `"*"` filters on large datasets (scans all non-null records)
|
||||
- Use `top_k` to limit result count when you only need a few memories
|
||||
|
||||
---
|
||||
|
||||
## Comparison with Alternatives
|
||||
|
||||
| Approach | Pros | Cons |
|
||||
|----------|------|------|
|
||||
| **Raw vector DB** | Fast, full control | No extraction, no dedup, no conflict resolution |
|
||||
| **In-memory chat history** | Zero latency | Lost on restart, no cross-session, grows unbounded |
|
||||
| **RAG over documents** | Good for static knowledge | No personalization, no memory updates |
|
||||
| **Mem0 Platform** | Managed extraction + dedup + graph + scoping | External dependency, async processing delay |
|
||||
|
||||
Mem0 combines the best of vector search (semantic retrieval) with automatic extraction (LLM-powered), conflict resolution (deduplication), and structured scoping (multi-tenancy) — in a single managed API.
|
||||
+425
@@ -0,0 +1,425 @@
|
||||
# Platform Features -- Mem0 Platform
|
||||
|
||||
Additional platform capabilities beyond core CRUD operations.
|
||||
|
||||
## Table of Contents
|
||||
|
||||
- [Advanced Retrieval](#advanced-retrieval)
|
||||
- [Entity Linking](#entity-linking)
|
||||
- [Custom Categories](#custom-categories)
|
||||
- [Custom Instructions](#custom-instructions)
|
||||
- [Criteria Retrieval](#criteria-retrieval)
|
||||
- [Feedback Mechanism](#feedback-mechanism)
|
||||
- [Memory Export](#memory-export)
|
||||
- [Group Chat](#group-chat)
|
||||
- [MCP Integration](#mcp-integration)
|
||||
- [Webhooks](#webhooks)
|
||||
- [Multimodal Support](#multimodal-support)
|
||||
|
||||
## Advanced Retrieval
|
||||
|
||||
### Hybrid Search (v3 Default)
|
||||
|
||||
v3 uses multi-signal hybrid search combining:
|
||||
- **Semantic search** (vector similarity)
|
||||
- **BM25 keyword search** (normalized term matching)
|
||||
- **Entity matching** (entity graph boost)
|
||||
|
||||
This is automatic — no configuration needed.
|
||||
|
||||
### Reranking (`rerank=True`)
|
||||
|
||||
Deep semantic reordering of results — most relevant first.
|
||||
|
||||
- Latency: +150-200ms
|
||||
- Default: `False` (was `True` in v2)
|
||||
- Best for: user-facing results, top-N precision
|
||||
|
||||
**Python:**
|
||||
```python
|
||||
results = client.search(query, filters={"user_id": "user123"}, rerank=True)
|
||||
```
|
||||
|
||||
**TypeScript:**
|
||||
```typescript
|
||||
const results = await client.search(query, {
|
||||
filters: { user_id: 'user123' },
|
||||
rerank: true,
|
||||
});
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Entity Linking
|
||||
|
||||
v3 replaces graph memory with built-in entity linking. Entities (proper nouns, quoted text, compound noun phrases) are automatically extracted and linked across memories.
|
||||
|
||||
### How It Works
|
||||
|
||||
1. **Extraction**: During `add()`, entities are automatically extracted from memory text
|
||||
2. **Storage**: Entities are stored in a parallel collection (`{collection}_entities`)
|
||||
3. **Retrieval**: During `search()`, query entities are matched and used to boost relevant memories
|
||||
|
||||
Entity linking is automatic — no configuration required. The boost is folded into the combined `score` on each result.
|
||||
|
||||
### v2 Migration Note
|
||||
|
||||
If you were using `enable_graph=True` in v2:
|
||||
- Remove `enable_graph` from all API calls
|
||||
- Remove `graph_store` from OSS configuration
|
||||
- Entity relationships are now consumed through retrieval ranking, not exposed as a separate `relations` array
|
||||
|
||||
See the [v2 to v3 migration guide](https://docs.mem0.ai/migration/platform-v2-to-v3) for details.
|
||||
|
||||
---
|
||||
|
||||
## Custom Categories
|
||||
|
||||
Replace Mem0's default 15 labels with domain-specific categories. The system automatically tags memories to the closest matching category.
|
||||
|
||||
### Default Categories (15)
|
||||
|
||||
`personal_details`, `family`, `professional_details`, `sports`, `travel`, `food`, `music`, `health`, `technology`, `hobbies`, `fashion`, `entertainment`, `milestones`, `user_preferences`, `misc`
|
||||
|
||||
### Configuration
|
||||
|
||||
**Set project-level categories:**
|
||||
```python
|
||||
new_categories = [
|
||||
{"lifestyle_management": "Tracks daily routines, habits, wellness activities"},
|
||||
{"seeking_structure": "Documents goals around creating routines and systems"},
|
||||
{"personal_information": "Basic information about the user"}
|
||||
]
|
||||
client.project.update(custom_categories=new_categories)
|
||||
```
|
||||
|
||||
```javascript
|
||||
await client.updateProject({ customCategories: newCategories });
|
||||
```
|
||||
|
||||
**Retrieve active categories:**
|
||||
```python
|
||||
categories = client.project.get(fields=["custom_categories"])
|
||||
```
|
||||
|
||||
### Key Constraint
|
||||
|
||||
Per-request overrides (`custom_categories=...` on `client.add`) are **not supported** on the managed API. Only project-level configuration works. Workaround: store ad-hoc labels in `metadata` field.
|
||||
|
||||
---
|
||||
|
||||
## Custom Instructions
|
||||
|
||||
Natural language filters that control what information Mem0 extracts when creating memories.
|
||||
|
||||
### Set Instructions
|
||||
|
||||
```python
|
||||
client.project.update(custom_instructions="Your guidelines here...")
|
||||
```
|
||||
|
||||
```javascript
|
||||
await client.updateProject({ customInstructions: "Your guidelines here..." });
|
||||
```
|
||||
|
||||
### Template Structure
|
||||
|
||||
1. **Task Description** -- brief extraction overview
|
||||
2. **Information Categories** -- numbered sections with specific details to capture
|
||||
3. **Processing Guidelines** -- quality and handling rules
|
||||
4. **Exclusion List** -- sensitive/irrelevant data to filter out
|
||||
|
||||
### Domain Examples
|
||||
|
||||
**E-commerce:** Capture product issues, preferences, service experience; exclude payment data.
|
||||
|
||||
**Education:** Extract learning progress, student preferences, performance patterns; exclude specific grades.
|
||||
|
||||
**Finance:** Track financial goals, life events, investment interests; exclude account numbers and SSNs.
|
||||
|
||||
### Best Practices
|
||||
|
||||
- Start simply, test with sample messages, iterate based on results
|
||||
- Avoid overly lengthy instructions
|
||||
- Be specific about what to include AND exclude
|
||||
|
||||
---
|
||||
|
||||
## Criteria Retrieval
|
||||
|
||||
Custom attribute-based memory ranking using LLM-evaluated criteria with weights. Goes beyond semantic similarity to prioritize memories based on domain-specific signals.
|
||||
|
||||
### Configuration
|
||||
|
||||
```python
|
||||
# Define criteria at project level
|
||||
retrieval_criteria = [
|
||||
{"name": "joy", "description": "Positive emotions like happiness and excitement", "weight": 3},
|
||||
{"name": "curiosity", "description": "Inquisitiveness and desire to learn", "weight": 2},
|
||||
{"name": "urgency", "description": "Time-sensitive or high-priority items", "weight": 4},
|
||||
]
|
||||
client.project.update(retrieval_criteria=retrieval_criteria)
|
||||
```
|
||||
|
||||
```typescript
|
||||
await client.updateProject({
|
||||
retrievalCriteria: [
|
||||
{ name: 'joy', description: 'Positive emotions', weight: 3 },
|
||||
{ name: 'urgency', description: 'Time-sensitive items', weight: 4 },
|
||||
],
|
||||
});
|
||||
```
|
||||
|
||||
### Usage
|
||||
|
||||
Once configured, `client.search()` automatically applies criteria ranking:
|
||||
|
||||
```python
|
||||
# Criteria-weighted results returned automatically
|
||||
results = client.search("Why am I feeling happy?", filters={"user_id": "alice"})
|
||||
```
|
||||
|
||||
**Best for:** Wellness assistants, tutoring platforms, productivity tools — any app needing intent-aware retrieval.
|
||||
|
||||
---
|
||||
|
||||
## Feedback Mechanism
|
||||
|
||||
Provide feedback on extracted memories to improve system quality over time.
|
||||
|
||||
### Feedback Types
|
||||
|
||||
| Type | Meaning |
|
||||
|------|---------|
|
||||
| `POSITIVE` | Memory is useful and accurate |
|
||||
| `NEGATIVE` | Memory is not useful |
|
||||
| `VERY_NEGATIVE` | Memory is harmful or completely wrong |
|
||||
| `None` | Clear existing feedback |
|
||||
|
||||
### Usage
|
||||
|
||||
**Python:**
|
||||
```python
|
||||
client.feedback(
|
||||
memory_id="mem-123",
|
||||
feedback="POSITIVE",
|
||||
feedback_reason="Accurately captured dietary preference"
|
||||
)
|
||||
|
||||
# Bulk feedback
|
||||
for item in feedback_data:
|
||||
client.feedback(**item)
|
||||
```
|
||||
|
||||
**TypeScript:**
|
||||
```typescript
|
||||
await client.feedback('mem-123', {
|
||||
feedback: 'POSITIVE',
|
||||
feedbackReason: 'Accurately captured dietary preference',
|
||||
});
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Memory Export
|
||||
|
||||
Create structured exports of memories using customizable schemas with filters.
|
||||
|
||||
### Usage
|
||||
|
||||
```python
|
||||
import json
|
||||
|
||||
# Define export schema
|
||||
schema = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"name": {"type": "string"},
|
||||
"preferences": {"type": "array", "items": {"type": "string"}},
|
||||
"health_info": {"type": "string"},
|
||||
}
|
||||
}
|
||||
|
||||
# Create export
|
||||
response = client.create_memory_export(
|
||||
schema=json.dumps(schema),
|
||||
filters={"user_id": "alice"},
|
||||
export_instructions="Create comprehensive profile based on all memories"
|
||||
)
|
||||
|
||||
# Retrieve export (may take a moment to process)
|
||||
result = client.get_memory_export(memory_export_id=response["id"])
|
||||
```
|
||||
|
||||
**Best for:** Data analytics, user profile generation, compliance audits, CRM sync.
|
||||
|
||||
---
|
||||
|
||||
## Group Chat
|
||||
|
||||
Process multi-participant conversations and automatically attribute memories to individual speakers.
|
||||
|
||||
### Usage
|
||||
|
||||
```python
|
||||
messages = [
|
||||
{"role": "user", "name": "Alice", "content": "I think we should use React for the frontend"},
|
||||
{"role": "user", "name": "Bob", "content": "I prefer Vue.js, it's simpler for our use case"},
|
||||
{"role": "assistant", "content": "Both are great choices. Let me note your preferences."},
|
||||
]
|
||||
|
||||
# Mem0 automatically attributes memories to each speaker
|
||||
response = client.add(messages, run_id="team_meeting_1")
|
||||
|
||||
# Retrieve Alice's memories from that session
|
||||
alice_mems = client.get_all(
|
||||
filters={"AND": [{"user_id": "alice"}, {"run_id": "team_meeting_1"}]}
|
||||
)
|
||||
```
|
||||
|
||||
Use the `name` field in messages to identify speakers. Mem0 maps names to entity scopes automatically.
|
||||
|
||||
---
|
||||
|
||||
## MCP Integration
|
||||
|
||||
Model Context Protocol integration enables AI clients (Claude, Claude Code, Cursor, Windsurf, VS Code, OpenCode) to manage Mem0 memory autonomously.
|
||||
|
||||
### Setup
|
||||
|
||||
Add Mem0 MCP to your clients with a single command:
|
||||
|
||||
```bash
|
||||
npx mcp-add \
|
||||
--name mem0-mcp \
|
||||
--type http \
|
||||
--url "https://mcp.mem0.ai/mcp" \
|
||||
--clients "claude,claude code,cursor,windsurf,vscode,opencode"
|
||||
```
|
||||
|
||||
### Available MCP Tools
|
||||
|
||||
The MCP server exposes 9 memory tools that AI agents can use autonomously:
|
||||
- Add, search, get, update, delete memories
|
||||
- Get history, list users, delete users
|
||||
- Search Mem0 documentation
|
||||
|
||||
### How It Works
|
||||
|
||||
1. Add Mem0 MCP to your AI client using the setup command above
|
||||
2. The agent autonomously decides when to store/retrieve memories
|
||||
3. No manual API calls needed — the agent manages memory as part of its reasoning
|
||||
|
||||
**Best for:** Universal AI client integration — one protocol works everywhere.
|
||||
|
||||
---
|
||||
|
||||
## Webhooks
|
||||
|
||||
Real-time event notifications for memory operations.
|
||||
|
||||
### Supported Events
|
||||
|
||||
| Event | Trigger |
|
||||
|-------|---------|
|
||||
| `memory_add` | Memory created |
|
||||
| `memory_update` | Memory modified |
|
||||
| `memory_delete` | Memory removed |
|
||||
| `memory_categorize` | Memory tagged |
|
||||
|
||||
### Create Webhook
|
||||
|
||||
Note: `project_id` here refers to the Mem0 dashboard project scope for webhooks — not the deprecated client init parameter.
|
||||
|
||||
```python
|
||||
webhook = client.create_webhook(
|
||||
url="https://your-app.com/webhook",
|
||||
name="Memory Logger",
|
||||
project_id="proj_123",
|
||||
event_types=["memory_add", "memory_categorize"]
|
||||
)
|
||||
```
|
||||
|
||||
### Manage Webhooks
|
||||
|
||||
```python
|
||||
# Retrieve
|
||||
webhooks = client.get_webhooks(project_id="proj_123")
|
||||
|
||||
# Update
|
||||
client.update_webhook(
|
||||
name="Updated Logger",
|
||||
url="https://your-app.com/new-webhook",
|
||||
event_types=["memory_update", "memory_add"],
|
||||
webhook_id="wh_123"
|
||||
)
|
||||
|
||||
# Delete
|
||||
client.delete_webhook(webhook_id="wh_123")
|
||||
```
|
||||
|
||||
### Payload Structure
|
||||
|
||||
Memory events contain: ID, data object with memory content, event type (`ADD`/`UPDATE`/`DELETE`).
|
||||
Categorization events contain: memory ID, event type (`CATEGORIZE`), assigned category labels.
|
||||
|
||||
---
|
||||
|
||||
## Multimodal Support
|
||||
|
||||
Mem0 can process images and documents alongside text.
|
||||
|
||||
### Supported Media Types
|
||||
|
||||
- Images: JPG, PNG
|
||||
- Documents: MDX, TXT, PDF
|
||||
|
||||
### Image via URL
|
||||
|
||||
```python
|
||||
image_message = {
|
||||
"role": "user",
|
||||
"content": {
|
||||
"type": "image_url",
|
||||
"image_url": {"url": "https://example.com/image.jpg"}
|
||||
}
|
||||
}
|
||||
client.add([image_message], user_id="alice")
|
||||
```
|
||||
|
||||
### Image via Base64
|
||||
|
||||
```python
|
||||
import base64
|
||||
with open("photo.jpg", "rb") as f:
|
||||
base64_image = base64.b64encode(f.read()).decode("utf-8")
|
||||
|
||||
image_message = {
|
||||
"role": "user",
|
||||
"content": {
|
||||
"type": "image_url",
|
||||
"image_url": {"url": f"data:image/jpeg;base64,{base64_image}"}
|
||||
}
|
||||
}
|
||||
client.add([image_message], user_id="alice")
|
||||
```
|
||||
|
||||
### Document (MDX/TXT)
|
||||
|
||||
```python
|
||||
doc_message = {
|
||||
"role": "user",
|
||||
"content": {"type": "mdx_url", "mdx_url": {"url": document_url}}
|
||||
}
|
||||
client.add([doc_message], user_id="alice")
|
||||
```
|
||||
|
||||
### PDF Document
|
||||
|
||||
```python
|
||||
pdf_message = {
|
||||
"role": "user",
|
||||
"content": {"type": "pdf_url", "pdf_url": {"url": pdf_url}}
|
||||
}
|
||||
client.add([pdf_message], user_id="alice")
|
||||
```
|
||||
+395
@@ -0,0 +1,395 @@
|
||||
# Mem0 Integration Patterns
|
||||
|
||||
Working code examples for integrating Mem0 Platform with popular AI frameworks.
|
||||
All examples use `MemoryClient` (Platform API key).
|
||||
|
||||
Code examples are sourced from official Mem0 integration docs at docs.mem0.ai, simplified for quick reference.
|
||||
|
||||
---
|
||||
|
||||
## Common Pattern
|
||||
|
||||
Every integration follows the same 3-step loop:
|
||||
|
||||
1. **Retrieve** -- search relevant memories before generating a response
|
||||
2. **Generate** -- include memories as context in the LLM prompt
|
||||
3. **Store** -- save the interaction back to Mem0 for future use
|
||||
|
||||
---
|
||||
|
||||
## LangChain
|
||||
|
||||
Source: [docs.mem0.ai/integrations/langchain](https://docs.mem0.ai/integrations/langchain)
|
||||
|
||||
```python
|
||||
from langchain_openai import ChatOpenAI
|
||||
from langchain_core.messages import SystemMessage, HumanMessage
|
||||
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
|
||||
from mem0 import MemoryClient
|
||||
|
||||
llm = ChatOpenAI(model="gpt-5-mini")
|
||||
mem0 = MemoryClient()
|
||||
|
||||
prompt = ChatPromptTemplate.from_messages([
|
||||
SystemMessage(content="You are a helpful travel agent AI. Use the provided context to personalize your responses."),
|
||||
MessagesPlaceholder(variable_name="context"),
|
||||
HumanMessage(content="{input}")
|
||||
])
|
||||
|
||||
def retrieve_context(query: str, user_id: str):
|
||||
"""Retrieve relevant memories from Mem0"""
|
||||
memories = mem0.search(query, filters={"user_id": user_id})
|
||||
memory_list = memories['results']
|
||||
serialized = ' '.join([m["memory"] for m in memory_list])
|
||||
return [
|
||||
{"role": "system", "content": f"Relevant information: {serialized}"},
|
||||
{"role": "user", "content": query}
|
||||
]
|
||||
|
||||
def chat_turn(user_input: str, user_id: str) -> str:
|
||||
# 1. Retrieve
|
||||
context = retrieve_context(user_input, user_id)
|
||||
# 2. Generate
|
||||
chain = prompt | llm
|
||||
response = chain.invoke({"context": context, "input": user_input})
|
||||
# 3. Store
|
||||
mem0.add(
|
||||
[{"role": "user", "content": user_input}, {"role": "assistant", "content": response.content}],
|
||||
user_id=user_id
|
||||
)
|
||||
return response.content
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## CrewAI
|
||||
|
||||
Source: [docs.mem0.ai/integrations/crewai](https://docs.mem0.ai/integrations/crewai)
|
||||
|
||||
CrewAI has native Mem0 integration via `memory_config`:
|
||||
|
||||
```python
|
||||
from crewai import Agent, Task, Crew, Process
|
||||
from mem0 import MemoryClient
|
||||
|
||||
client = MemoryClient()
|
||||
|
||||
# Store user preferences first
|
||||
messages = [
|
||||
{"role": "user", "content": "I am more of a beach person than a mountain person."},
|
||||
{"role": "assistant", "content": "Noted! I'll recommend beach destinations."},
|
||||
{"role": "user", "content": "I like Airbnb more than hotels."},
|
||||
]
|
||||
client.add(messages, user_id="crew_user_1")
|
||||
|
||||
# Create agent
|
||||
travel_agent = Agent(
|
||||
role="Personalized Travel Planner",
|
||||
goal="Plan personalized travel itineraries",
|
||||
backstory="You are a seasoned travel planner.",
|
||||
memory=True,
|
||||
)
|
||||
|
||||
# Create task
|
||||
task = Task(
|
||||
description="Find places to live, eat, and visit in San Francisco.",
|
||||
expected_output="A detailed list of places to live, eat, and visit.",
|
||||
agent=travel_agent,
|
||||
)
|
||||
|
||||
# Setup crew with Mem0 memory
|
||||
crew = Crew(
|
||||
agents=[travel_agent],
|
||||
tasks=[task],
|
||||
process=Process.sequential,
|
||||
memory=True,
|
||||
memory_config={
|
||||
"provider": "mem0",
|
||||
"config": {"user_id": "crew_user_1"},
|
||||
}
|
||||
)
|
||||
|
||||
result = crew.kickoff()
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Vercel AI SDK
|
||||
|
||||
> **Dedicated skill available.** For comprehensive Vercel AI SDK documentation, see the [mem0-vercel-ai-sdk skill](https://github.com/mem0ai/mem0/tree/main/skills/mem0-vercel-ai-sdk).
|
||||
|
||||
Install: `npm install @mem0/vercel-ai-provider`
|
||||
|
||||
Quick example (wrapped model with automatic memory):
|
||||
|
||||
```typescript
|
||||
import { generateText } from "ai";
|
||||
import { createMem0 } from "@mem0/vercel-ai-provider";
|
||||
|
||||
const mem0 = createMem0();
|
||||
const { text } = await generateText({
|
||||
model: mem0("gpt-5-mini", { user_id: "borat" }),
|
||||
prompt: "Suggest me a good car to buy!",
|
||||
});
|
||||
```
|
||||
|
||||
Supported providers: `openai`, `anthropic`, `google`, `groq`, `cohere`
|
||||
|
||||
---
|
||||
|
||||
## OpenAI Agents SDK
|
||||
|
||||
Source: [docs.mem0.ai/integrations/openai-agents-sdk](https://docs.mem0.ai/integrations/openai-agents-sdk)
|
||||
|
||||
```python
|
||||
from agents import Agent, Runner, function_tool
|
||||
from mem0 import MemoryClient
|
||||
|
||||
mem0 = MemoryClient()
|
||||
|
||||
@function_tool
|
||||
def search_memory(query: str, user_id: str) -> str:
|
||||
"""Search through past conversations and memories"""
|
||||
memories = mem0.search(query, filters={"user_id": user_id}, top_k=3)
|
||||
if memories and memories.get('results'):
|
||||
return "\n".join([f"- {mem['memory']}" for mem in memories['results']])
|
||||
return "No relevant memories found."
|
||||
|
||||
@function_tool
|
||||
def save_memory(content: str, user_id: str) -> str:
|
||||
"""Save important information to memory"""
|
||||
mem0.add([{"role": "user", "content": content}], user_id=user_id)
|
||||
return "Information saved to memory."
|
||||
|
||||
agent = Agent(
|
||||
name="Personal Assistant",
|
||||
instructions="""You are a helpful personal assistant with memory capabilities.
|
||||
Use search_memory to recall past conversations.
|
||||
Use save_memory to store important information.""",
|
||||
tools=[search_memory, save_memory],
|
||||
model="gpt-5-mini"
|
||||
)
|
||||
|
||||
result = Runner.run_sync(agent, "I love Italian food and I'm planning a trip to Rome next month")
|
||||
print(result.final_output)
|
||||
```
|
||||
|
||||
### Multi-Agent with Handoffs
|
||||
|
||||
```python
|
||||
from agents import Agent, Runner, function_tool
|
||||
|
||||
travel_agent = Agent(
|
||||
name="Travel Planner",
|
||||
instructions="You are a travel planning specialist. Use search_memory and save_memory tools.",
|
||||
tools=[search_memory, save_memory],
|
||||
model="gpt-5-mini"
|
||||
)
|
||||
|
||||
health_agent = Agent(
|
||||
name="Health Advisor",
|
||||
instructions="You are a health and wellness advisor. Use search_memory and save_memory tools.",
|
||||
tools=[search_memory, save_memory],
|
||||
model="gpt-5-mini"
|
||||
)
|
||||
|
||||
triage_agent = Agent(
|
||||
name="Personal Assistant",
|
||||
instructions="""Route travel questions to Travel Planner, health questions to Health Advisor.""",
|
||||
handoffs=[travel_agent, health_agent],
|
||||
model="gpt-5-mini"
|
||||
)
|
||||
|
||||
result = Runner.run_sync(triage_agent, "Plan a healthy meal for my Italy trip")
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Pipecat (Voice / Real-Time)
|
||||
|
||||
Source: [docs.mem0.ai/integrations/pipecat](https://docs.mem0.ai/integrations/pipecat)
|
||||
|
||||
```python
|
||||
from pipecat.services.mem0 import Mem0MemoryService
|
||||
|
||||
memory = Mem0MemoryService(
|
||||
api_key=os.getenv("MEM0_API_KEY"),
|
||||
user_id="alice",
|
||||
agent_id="voice_bot",
|
||||
params={
|
||||
"search_limit": 10,
|
||||
"search_threshold": 0.1,
|
||||
"system_prompt": "Here are your past memories:",
|
||||
"add_as_system_message": True,
|
||||
}
|
||||
)
|
||||
|
||||
# Use in pipeline
|
||||
pipeline = Pipeline([
|
||||
transport.input(),
|
||||
stt,
|
||||
user_context,
|
||||
memory, # Memory enhances context automatically
|
||||
llm,
|
||||
transport.output(),
|
||||
assistant_context
|
||||
])
|
||||
```
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## LangGraph
|
||||
|
||||
Source: [docs.mem0.ai/integrations/langgraph](https://docs.mem0.ai/integrations/langgraph)
|
||||
|
||||
State-based agent workflows with memory persistence. Best for complex conversation flows with branching logic.
|
||||
|
||||
```python
|
||||
from typing import Annotated, TypedDict, List
|
||||
from langgraph.graph import StateGraph, START
|
||||
from langgraph.graph.message import add_messages
|
||||
from langchain_openai import ChatOpenAI
|
||||
from mem0 import MemoryClient
|
||||
from langchain_core.messages import SystemMessage, HumanMessage, AIMessage
|
||||
|
||||
llm = ChatOpenAI(model="gpt-5-mini")
|
||||
mem0 = MemoryClient()
|
||||
|
||||
class State(TypedDict):
|
||||
messages: Annotated[List[HumanMessage | AIMessage], add_messages]
|
||||
mem0_user_id: str
|
||||
|
||||
def chatbot(state: State):
|
||||
messages = state["messages"]
|
||||
user_id = state["mem0_user_id"]
|
||||
|
||||
# Retrieve relevant memories
|
||||
memories = mem0.search(messages[-1].content, filters={"user_id": user_id})
|
||||
context = "Relevant context:\n"
|
||||
for memory in memories["results"]:
|
||||
context += f"- {memory['memory']}\n"
|
||||
|
||||
system_message = SystemMessage(content=f"""You are a helpful support assistant.
|
||||
{context}""")
|
||||
|
||||
response = llm.invoke([system_message] + messages)
|
||||
|
||||
# Store the interaction
|
||||
mem0.add(
|
||||
[{"role": "user", "content": messages[-1].content},
|
||||
{"role": "assistant", "content": response.content}],
|
||||
user_id=user_id
|
||||
)
|
||||
return {"messages": [response]}
|
||||
|
||||
graph = StateGraph(State)
|
||||
graph.add_node("chatbot", chatbot)
|
||||
graph.add_edge(START, "chatbot")
|
||||
app = graph.compile()
|
||||
|
||||
# Usage
|
||||
result = app.invoke({
|
||||
"messages": [HumanMessage(content="I need help with my order")],
|
||||
"mem0_user_id": "customer_123"
|
||||
})
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## LlamaIndex
|
||||
|
||||
Source: [docs.mem0.ai/integrations/llama-index](https://docs.mem0.ai/integrations/llama-index)
|
||||
|
||||
Install: `pip install llama-index-core llama-index-memory-mem0`
|
||||
|
||||
LlamaIndex has native Mem0 support via `Mem0Memory`. Works with ReAct and FunctionCalling agents.
|
||||
|
||||
```python
|
||||
from llama_index.memory.mem0 import Mem0Memory
|
||||
|
||||
context = {"user_id": "alice", "agent_id": "llama_agent_1"}
|
||||
memory = Mem0Memory.from_client(
|
||||
context=context,
|
||||
search_msg_limit=4, # messages from chat history used for retrieval (default: 5)
|
||||
)
|
||||
|
||||
# Use with LlamaIndex agent
|
||||
from llama_index.core.agent import FunctionCallingAgent
|
||||
from llama_index.llms.openai import OpenAI
|
||||
|
||||
llm = OpenAI(model="gpt-5-mini")
|
||||
agent = FunctionCallingAgent.from_tools(
|
||||
tools=[],
|
||||
llm=llm,
|
||||
memory=memory,
|
||||
verbose=True,
|
||||
)
|
||||
|
||||
response = agent.chat("I prefer vegetarian restaurants")
|
||||
# Memory automatically stores and retrieves context
|
||||
response = agent.chat("What kind of food do I like?")
|
||||
# Agent retrieves the vegetarian preference from Mem0
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## AutoGen
|
||||
|
||||
Source: [docs.mem0.ai/integrations/autogen](https://docs.mem0.ai/integrations/autogen)
|
||||
|
||||
Install: `pip install autogen mem0ai`
|
||||
|
||||
Multi-agent conversational systems with memory persistence.
|
||||
|
||||
```python
|
||||
from autogen import ConversableAgent
|
||||
from mem0 import MemoryClient
|
||||
|
||||
memory_client = MemoryClient()
|
||||
USER_ID = "alice"
|
||||
|
||||
agent = ConversableAgent(
|
||||
"chatbot",
|
||||
llm_config={"config_list": [{"model": "gpt-5-mini", "api_key": os.environ["OPENAI_API_KEY"]}]},
|
||||
code_execution_config=False,
|
||||
human_input_mode="NEVER",
|
||||
)
|
||||
|
||||
def get_context_aware_response(question: str) -> str:
|
||||
# Retrieve memories for context
|
||||
relevant_memories = memory_client.search(question, filters={"user_id": USER_ID})
|
||||
context = "\n".join([m["memory"] for m in relevant_memories.get("results", [])])
|
||||
|
||||
prompt = f"""Answer considering previous interactions:
|
||||
Previous context: {context}
|
||||
Question: {question}"""
|
||||
|
||||
reply = agent.generate_reply(messages=[{"content": prompt, "role": "user"}])
|
||||
|
||||
# Store the new interaction
|
||||
memory_client.add(
|
||||
[{"role": "user", "content": question}, {"role": "assistant", "content": reply}],
|
||||
user_id=USER_ID
|
||||
)
|
||||
return reply
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## All Supported Frameworks
|
||||
|
||||
Beyond the examples above, Mem0 integrates with:
|
||||
|
||||
| Framework | Type | Install |
|
||||
|-----------|------|---------|
|
||||
| [Mastra](https://docs.mem0.ai/integrations/mastra) | TS agent framework | `npm install @mastra/mem0` |
|
||||
| [ElevenLabs](https://docs.mem0.ai/integrations/elevenlabs) | Voice AI | `pip install elevenlabs mem0ai` |
|
||||
| [LiveKit](https://docs.mem0.ai/integrations/livekit) | Real-time voice/video | `pip install livekit-agents mem0ai` |
|
||||
| [Camel AI](https://docs.mem0.ai/integrations/camel-ai) | Multi-agent framework | `pip install camel-ai[all] mem0ai` |
|
||||
| [AWS Bedrock](https://docs.mem0.ai/integrations/aws-bedrock) | Cloud LLM provider | `pip install boto3 mem0ai` |
|
||||
| [Dify](https://docs.mem0.ai/integrations/dify) | Low-code AI platform | Plugin-based |
|
||||
| [Google AI ADK](https://docs.mem0.ai/integrations/google-ai-adk) | Google agent framework | `pip install google-adk mem0ai` |
|
||||
|
||||
For the general Python pattern (no framework), see the "Common integration pattern" in [SKILL.md](../SKILL.md).
|
||||
+119
@@ -0,0 +1,119 @@
|
||||
# Mem0 Platform Quickstart
|
||||
|
||||
Get running with Mem0 in 2 minutes. No infrastructure to deploy -- just an API key.
|
||||
|
||||
## Prerequisites
|
||||
|
||||
- Python 3.10+ or Node.js 18+
|
||||
- A Mem0 Platform API key ([Get one here](https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=mem0-plugin-skill-quickstart))
|
||||
|
||||
## Python Setup
|
||||
|
||||
```bash
|
||||
pip install mem0ai
|
||||
export MEM0_API_KEY="m0-your-api-key"
|
||||
```
|
||||
|
||||
```python
|
||||
from mem0 import MemoryClient
|
||||
|
||||
client = MemoryClient(api_key="your-api-key")
|
||||
|
||||
# Add a memory
|
||||
messages = [
|
||||
{"role": "user", "content": "I'm a vegetarian and allergic to nuts."},
|
||||
{"role": "assistant", "content": "Got it! I'll remember your dietary preferences."}
|
||||
]
|
||||
client.add(messages, user_id="user123")
|
||||
|
||||
# Search memories
|
||||
results = client.search("What are my dietary restrictions?", filters={"user_id": "user123"})
|
||||
print(results)
|
||||
```
|
||||
|
||||
### Async Client
|
||||
|
||||
```python
|
||||
from mem0 import AsyncMemoryClient
|
||||
|
||||
client = AsyncMemoryClient(api_key="your-api-key")
|
||||
|
||||
await client.add(messages, user_id="user123")
|
||||
results = await client.search("query", filters={"user_id": "user123"})
|
||||
```
|
||||
|
||||
## TypeScript / JavaScript Setup
|
||||
|
||||
```bash
|
||||
npm install mem0ai
|
||||
export MEM0_API_KEY="m0-your-api-key"
|
||||
```
|
||||
|
||||
```javascript
|
||||
import MemoryClient from 'mem0ai';
|
||||
|
||||
const client = new MemoryClient({ apiKey: 'your-api-key' });
|
||||
|
||||
// Add a memory
|
||||
const messages = [
|
||||
{"role": "user", "content": "I'm a vegetarian and allergic to nuts."},
|
||||
{"role": "assistant", "content": "Got it! I'll remember your dietary preferences."}
|
||||
];
|
||||
await client.add(messages, { userId: "user123" });
|
||||
|
||||
// Search memories
|
||||
const results = await client.search("What are my dietary restrictions?", {
|
||||
filters: { user_id: "user123" }
|
||||
});
|
||||
console.log(results);
|
||||
```
|
||||
|
||||
## cURL
|
||||
|
||||
```bash
|
||||
export MEM0_API_KEY="m0-your-api-key"
|
||||
|
||||
# Add memory
|
||||
curl -X POST https://api.mem0.ai/v3/memories/add/ \
|
||||
-H "Authorization: Token $MEM0_API_KEY" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"messages": [
|
||||
{"role": "user", "content": "I am a vegetarian and allergic to nuts."},
|
||||
{"role": "assistant", "content": "Got it! I will remember your dietary preferences."}
|
||||
],
|
||||
"user_id": "user123"
|
||||
}'
|
||||
|
||||
# Search memories
|
||||
curl -X POST https://api.mem0.ai/v3/memories/search/ \
|
||||
-H "Authorization: Token $MEM0_API_KEY" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"query": "What are my dietary restrictions?",
|
||||
"filters": {"user_id": "user123"}
|
||||
}'
|
||||
```
|
||||
|
||||
## Sample Response
|
||||
|
||||
```json
|
||||
{
|
||||
"results": [
|
||||
{
|
||||
"id": "14e1b28a-2014-40ad-ac42-69c9ef42193d",
|
||||
"memory": "Allergic to nuts",
|
||||
"user_id": "user123",
|
||||
"categories": ["health"],
|
||||
"created_at": "2025-10-22T04:40:22.864647-07:00",
|
||||
"score": 0.30
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
## Next Steps
|
||||
|
||||
- [SDK Guide](sdk-guide.md) -- all methods for Python and TypeScript
|
||||
- [API Reference](api-reference.md) -- REST endpoints and memory object structure
|
||||
- [Integration Patterns](integration-patterns.md) -- LangChain, CrewAI, Vercel AI, etc.
|
||||
+353
@@ -0,0 +1,353 @@
|
||||
# Mem0 SDK Guide
|
||||
|
||||
Complete SDK reference for Python and TypeScript. All methods use `MemoryClient` (Platform API).
|
||||
|
||||
> **For language-specific deep references (including OSS):** See [client/python.md](../client/python.md) and [client/node.md](../client/node.md). For Python vs TypeScript differences: [client/differences.md](../client/differences.md).
|
||||
|
||||
## Initialization
|
||||
|
||||
**Python:**
|
||||
```python
|
||||
from mem0 import MemoryClient
|
||||
client = MemoryClient(api_key="m0-your-api-key")
|
||||
```
|
||||
|
||||
**Python (Async):**
|
||||
```python
|
||||
from mem0 import AsyncMemoryClient
|
||||
client = AsyncMemoryClient(api_key="m0-your-api-key")
|
||||
```
|
||||
|
||||
**TypeScript:**
|
||||
```typescript
|
||||
import MemoryClient from 'mem0ai';
|
||||
const client = new MemoryClient({ apiKey: 'm0-your-api-key' });
|
||||
```
|
||||
|
||||
Constructor accepts `apiKey` (required) and `host` (optional, default: `https://api.mem0.ai`).
|
||||
|
||||
---
|
||||
|
||||
## add() -- Store Memories
|
||||
|
||||
**Python:**
|
||||
```python
|
||||
messages = [
|
||||
{"role": "user", "content": "I'm a vegetarian and allergic to nuts."},
|
||||
{"role": "assistant", "content": "Got it! I'll remember that."}
|
||||
]
|
||||
client.add(messages, user_id="alice")
|
||||
|
||||
# With metadata
|
||||
client.add(messages, user_id="alice", metadata={"source": "onboarding"})
|
||||
```
|
||||
|
||||
**TypeScript:**
|
||||
```typescript
|
||||
await client.add(messages, { userId: "alice" });
|
||||
await client.add(messages, { userId: "alice", metadata: { source: "onboarding" } });
|
||||
```
|
||||
|
||||
### Parameters
|
||||
|
||||
| Name | Type | Description |
|
||||
|------|------|-------------|
|
||||
| `messages` | array | `[{"role": "user", "content": "..."}]` |
|
||||
| `user_id` | string | User identifier (recommended) |
|
||||
| `agent_id` | string | Agent identifier |
|
||||
| `run_id` | string | Session identifier |
|
||||
| `metadata` | object | Custom key-value pairs |
|
||||
| `infer` | boolean | If `false`, store raw text without inference (default: `true`) |
|
||||
|
||||
### Advanced Add Options
|
||||
|
||||
```python
|
||||
# Agent + session scoping
|
||||
client.add(messages, user_id="alice", agent_id="nutrition-agent", run_id="session-456")
|
||||
|
||||
# Raw text -- skip LLM inference
|
||||
client.add(
|
||||
[{"role": "user", "content": "User prefers dark mode."}],
|
||||
user_id="alice",
|
||||
infer=False,
|
||||
)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## search() -- Find Memories
|
||||
|
||||
**Python:**
|
||||
```python
|
||||
results = client.search("dietary preferences?", filters={"user_id": "alice"})
|
||||
|
||||
# With filters and reranking
|
||||
results = client.search(
|
||||
query="work experience",
|
||||
filters={"AND": [{"user_id": "alice"}, {"categories": {"contains": "professional_details"}}]},
|
||||
top_k=5,
|
||||
rerank=True,
|
||||
threshold=0.5
|
||||
)
|
||||
```
|
||||
|
||||
**TypeScript:**
|
||||
```typescript
|
||||
const results = await client.search("dietary preferences", { filters: { user_id: "alice" } });
|
||||
const results = await client.search("work experience", {
|
||||
filters: { AND: [{ user_id: "alice" }, { categories: { contains: "professional_details" } }] },
|
||||
topK: 5,
|
||||
rerank: true,
|
||||
});
|
||||
```
|
||||
|
||||
### Parameters
|
||||
|
||||
| Name | Type | Description |
|
||||
|------|------|-------------|
|
||||
| `query` | string | Natural language search query |
|
||||
| `filters` | object | Filter object (AND/OR operators). Use `{"user_id": "..."}` to filter by user |
|
||||
| `top_k` | number | Number of results (default: 10 for Platform) |
|
||||
| `rerank` | boolean | Enable reranking for better relevance (default: `false`) |
|
||||
| `threshold` | number | Minimum similarity score (default: 0.1) |
|
||||
|
||||
### Common Filter Patterns
|
||||
|
||||
**Python:**
|
||||
```python
|
||||
# Single user filter
|
||||
filters={"user_id": "alice"}
|
||||
|
||||
# OR across agents
|
||||
filters={"OR": [{"user_id": "alice"}, {"agent_id": {"in": ["travel-agent", "sports-agent"]}}]}
|
||||
|
||||
# Category filtering (partial match)
|
||||
filters={"AND": [{"user_id": "alice"}, {"categories": {"contains": "finance"}}]}
|
||||
|
||||
# Category filtering (exact match)
|
||||
filters={"AND": [{"user_id": "alice"}, {"categories": {"in": ["personal_information"]}}]}
|
||||
|
||||
# Wildcard (match any non-null run)
|
||||
filters={"AND": [{"user_id": "alice"}, {"run_id": "*"}]}
|
||||
|
||||
# Date range
|
||||
filters={"AND": [
|
||||
{"user_id": "alice"},
|
||||
{"created_at": {"gte": "2024-01-01T00:00:00Z"}},
|
||||
{"created_at": {"lt": "2024-02-01T00:00:00Z"}}
|
||||
]}
|
||||
|
||||
# Exclude categories with NOT
|
||||
filters={"AND": [{"user_id": "user_123"}, {"NOT": {"categories": {"in": ["spam", "test"]}}}]}
|
||||
|
||||
# Multi-dimensional query
|
||||
filters={"AND": [
|
||||
{"user_id": "user_123"},
|
||||
{"keywords": {"icontains": "invoice"}},
|
||||
{"categories": {"in": ["finance"]}},
|
||||
{"created_at": {"gte": "2024-01-01T00:00:00Z"}}
|
||||
]}
|
||||
```
|
||||
|
||||
**TypeScript:**
|
||||
```typescript
|
||||
// Single user filter
|
||||
filters: { user_id: "alice" }
|
||||
|
||||
// OR across agents
|
||||
filters: { OR: [{ user_id: "alice" }, { agent_id: { in: ["travel-agent", "sports-agent"] } }] }
|
||||
|
||||
// Category filtering (partial match)
|
||||
filters: { AND: [{ user_id: "alice" }, { categories: { contains: "finance" } }] }
|
||||
|
||||
// Category filtering (exact match)
|
||||
filters: { AND: [{ user_id: "alice" }, { categories: { in: ["personal_information"] } }] }
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## get() / getAll() -- Retrieve Memories
|
||||
|
||||
**Python:**
|
||||
```python
|
||||
# Single memory by ID
|
||||
memory = client.get(memory_id="ea925981-...")
|
||||
|
||||
# All memories for a user
|
||||
memories = client.get_all(filters={"user_id": "alice"})
|
||||
|
||||
# With date range
|
||||
memories = client.get_all(
|
||||
filters={"AND": [
|
||||
{"user_id": "alex"},
|
||||
{"created_at": {"gte": "2024-07-01", "lte": "2024-07-31"}}
|
||||
]}
|
||||
)
|
||||
```
|
||||
|
||||
**TypeScript:**
|
||||
```typescript
|
||||
const memory = await client.get("ea925981-...");
|
||||
const memories = await client.getAll({ filters: { user_id: "alice" } });
|
||||
```
|
||||
|
||||
**Note:** `get_all` requires at least one of `user_id`, `agent_id`, `app_id`, or `run_id` in filters.
|
||||
|
||||
---
|
||||
|
||||
## update() -- Modify Memories
|
||||
|
||||
**Python:**
|
||||
```python
|
||||
client.update(memory_id="ea925981-...", text="Updated: vegan since 2024")
|
||||
client.update(memory_id="ea925981-...", text="Updated", metadata={"verified": True})
|
||||
```
|
||||
|
||||
**TypeScript:**
|
||||
```typescript
|
||||
await client.update("ea925981-...", { text: "Updated: vegan since 2024" });
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## delete() / deleteAll() -- Remove Memories
|
||||
|
||||
**Python:**
|
||||
```python
|
||||
client.delete(memory_id="ea925981-...")
|
||||
client.delete_all(user_id="alice") # Irreversible bulk delete
|
||||
```
|
||||
|
||||
**TypeScript:**
|
||||
```typescript
|
||||
await client.delete("ea925981-...");
|
||||
await client.deleteAll({ userId: "alice" });
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## history() -- Track Changes
|
||||
|
||||
**Python:**
|
||||
```python
|
||||
history = client.history(memory_id="ea925981-...")
|
||||
# Returns: [{previous_value, new_value, action, timestamps}]
|
||||
```
|
||||
|
||||
**TypeScript:**
|
||||
```typescript
|
||||
const history = await client.history("ea925981-...");
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Batch Operations (TypeScript)
|
||||
|
||||
```typescript
|
||||
// Batch update
|
||||
await client.batchUpdate([
|
||||
{ memoryId: "uuid-1", text: "Updated text" },
|
||||
{ memoryId: "uuid-2", text: "Another updated text" },
|
||||
]);
|
||||
|
||||
// Batch delete
|
||||
await client.batchDelete(["uuid-1", "uuid-2", "uuid-3"]);
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Additional Methods
|
||||
|
||||
```python
|
||||
# List all users/agents/sessions with memories
|
||||
users = client.users()
|
||||
|
||||
# Delete a user/agent entity
|
||||
client.delete_users(user_id="alice")
|
||||
|
||||
# Submit feedback on a memory
|
||||
client.feedback(memory_id="...", feedback="POSITIVE", feedback_reason="Accurate extraction")
|
||||
|
||||
# Export memories
|
||||
export = client.create_memory_export(filters={"AND": [{"user_id": "alice"}]})
|
||||
data = client.get_memory_export(memory_export_id=export["id"])
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Common Pitfalls
|
||||
|
||||
1. **Entity cross-filtering fails silently** -- `AND` with `user_id` + `agent_id` returns empty. Use `OR`.
|
||||
2. **SQL operators rejected** -- use `gte`, `lt`, etc. Not `>=`, `<`.
|
||||
3. **Metadata filtering is limited** -- only top-level keys with `eq`, `contains`, `ne`.
|
||||
4. **Wildcard `*` excludes null** -- only matches non-null values.
|
||||
5. **Default threshold is 0.1** -- increase for stricter matching.
|
||||
6. **Async processing** -- memories process asynchronously. Wait 2-3s after `add()` before searching.
|
||||
|
||||
## Naming Conventions
|
||||
|
||||
Python uses `snake_case` everywhere (`user_id`, `memory_id`, `get_all`). TypeScript uses `camelCase` for methods (`getAll`, `deleteAll`, `batchUpdate`) and top-level parameters (`userId`, `topK`, `pageSize`), but filter keys use `snake_case` (`user_id`, `agent_id`).
|
||||
|
||||
---
|
||||
|
||||
## v2 to v3 Migration
|
||||
|
||||
### Breaking Changes in v3
|
||||
|
||||
**1. Entity IDs in search() and getAll()**
|
||||
|
||||
v3 requires entity IDs (`user_id`, `agent_id`, `run_id`) inside `filters` instead of as top-level parameters:
|
||||
|
||||
```python
|
||||
# v2 (deprecated)
|
||||
client.search("query", user_id="alice")
|
||||
client.get_all(user_id="alice")
|
||||
|
||||
# v3
|
||||
client.search("query", filters={"user_id": "alice"})
|
||||
client.get_all(filters={"user_id": "alice"})
|
||||
```
|
||||
|
||||
```typescript
|
||||
// v2 (deprecated)
|
||||
await client.search("query", { user_id: "alice" });
|
||||
await client.getAll({ user_id: "alice" });
|
||||
|
||||
// v3
|
||||
await client.search("query", { filters: { user_id: "alice" } });
|
||||
await client.getAll({ filters: { user_id: "alice" } });
|
||||
```
|
||||
|
||||
**2. TypeScript Parameter Naming**
|
||||
|
||||
v3 TypeScript uses camelCase for all parameters:
|
||||
|
||||
| v2 | v3 |
|
||||
|----|-----|
|
||||
| `user_id` | `userId` |
|
||||
| `agent_id` | `agentId` |
|
||||
| `run_id` | `runId` |
|
||||
| `top_k` | `topK` |
|
||||
| `page_size` | `pageSize` |
|
||||
|
||||
**3. Default Values Changed**
|
||||
|
||||
| Parameter | v2 Default | v3 Default |
|
||||
|-----------|------------|------------|
|
||||
| `threshold` | 0.3 | 0.1 |
|
||||
| `rerank` | (not specified) | `false` |
|
||||
|
||||
**4. Removed Parameters**
|
||||
|
||||
The following parameters are no longer supported:
|
||||
|
||||
| Parameter | Status |
|
||||
|-----------|--------|
|
||||
| `enable_graph` | Removed from add/search/getAll |
|
||||
| `keyword_search` | Removed from search |
|
||||
| `filter_memories` | Removed |
|
||||
| `immutable` | Removed from add |
|
||||
| `expiration_date` | Removed from add |
|
||||
| `includes` | Removed from add |
|
||||
| `excludes` | Removed from add |
|
||||
| `async_mode` | Removed from add |
|
||||
+720
@@ -0,0 +1,720 @@
|
||||
# Mem0 Use Cases & Examples
|
||||
|
||||
Real-world implementation patterns for Mem0 Platform. Each use case includes complete, runnable code in both Python and TypeScript.
|
||||
|
||||
## Table of Contents
|
||||
|
||||
- [Personalized AI Companion](#1-personalized-ai-companion)
|
||||
- [Customer Support with Categories](#2-customer-support-with-categories)
|
||||
- [Healthcare Coach](#3-healthcare-coach)
|
||||
- [Content Creation Workflow](#4-content-creation-workflow)
|
||||
- [Multi-Agent / Multi-Tenant](#5-multi-agent--multi-tenant)
|
||||
- [Personalized Search](#6-personalized-search)
|
||||
- [Email Intelligence](#7-email-intelligence)
|
||||
- [Common Patterns Across Use Cases](#common-patterns-across-use-cases)
|
||||
|
||||
---
|
||||
|
||||
## 1. Personalized AI Companion
|
||||
|
||||
A fitness coach that remembers goals, preferences, and progress across sessions. Mem0 persists context across app restarts — no session state needed.
|
||||
|
||||
### Implementation (Python)
|
||||
|
||||
```python
|
||||
from mem0 import MemoryClient
|
||||
from openai import OpenAI
|
||||
|
||||
mem0 = MemoryClient()
|
||||
openai_client = OpenAI()
|
||||
|
||||
def chat(user_input: str, user_id: str) -> str:
|
||||
# 1. Retrieve relevant memories
|
||||
memories = mem0.search(user_input, user_id=user_id)
|
||||
context = "\n".join([f"- {m['memory']}" for m in memories.get("results", [])])
|
||||
|
||||
# 2. Generate response with memory context
|
||||
system_prompt = f"""You are Ray, a personal fitness coach.
|
||||
Use these known facts about the user to personalize your response:
|
||||
{context if context else 'No prior context yet.'}"""
|
||||
|
||||
response = openai_client.chat.completions.create(
|
||||
model="gpt-5-mini",
|
||||
messages=[
|
||||
{"role": "system", "content": system_prompt},
|
||||
{"role": "user", "content": user_input},
|
||||
]
|
||||
)
|
||||
reply = response.choices[0].message.content
|
||||
|
||||
# 3. Store interaction for future context
|
||||
mem0.add(
|
||||
[{"role": "user", "content": user_input}, {"role": "assistant", "content": reply}],
|
||||
user_id=user_id
|
||||
)
|
||||
return reply
|
||||
|
||||
# Usage
|
||||
chat("I want to run a marathon in under 4 hours", user_id="max")
|
||||
# Next day, app restarted:
|
||||
chat("What should I focus on today?", user_id="max")
|
||||
# Ray remembers the sub-4 marathon goal
|
||||
```
|
||||
|
||||
### Implementation (TypeScript)
|
||||
|
||||
```typescript
|
||||
import MemoryClient from 'mem0ai';
|
||||
import OpenAI from 'openai';
|
||||
|
||||
const mem0 = new MemoryClient({ apiKey: process.env.MEM0_API_KEY! });
|
||||
const openai = new OpenAI();
|
||||
|
||||
async function chat(userInput: string, userId: string): Promise<string> {
|
||||
// 1. Retrieve relevant memories
|
||||
const memories = await mem0.search(userInput, { filters: { user_id: userId } });
|
||||
const context = memories.results
|
||||
?.map((m: any) => `- ${m.memory}`)
|
||||
.join('\n') || 'No prior context yet.';
|
||||
|
||||
// 2. Generate response with memory context
|
||||
const response = await openai.chat.completions.create({
|
||||
model: 'gpt-5-mini',
|
||||
messages: [
|
||||
{ role: 'system', content: `You are Ray, a personal fitness coach.\nUser context:\n${context}` },
|
||||
{ role: 'user', content: userInput },
|
||||
],
|
||||
});
|
||||
const reply = response.choices[0].message.content!;
|
||||
|
||||
// 3. Store interaction
|
||||
await mem0.add(
|
||||
[{ role: 'user', content: userInput }, { role: 'assistant', content: reply }],
|
||||
{ userId: userId }
|
||||
);
|
||||
return reply;
|
||||
}
|
||||
```
|
||||
|
||||
### Key Benefits
|
||||
|
||||
- Context persists across app restarts — no session management needed
|
||||
- Memories are automatically deduplicated and updated
|
||||
- Works with any LLM provider (OpenAI, Anthropic, etc.)
|
||||
|
||||
**Best for:** Fitness coaches, tutors, therapists — any assistant that needs to remember goals across sessions.
|
||||
|
||||
---
|
||||
|
||||
## 2. Customer Support with Categories
|
||||
|
||||
Auto-categorize support data so teams retrieve the right facts fast. Uses custom categories for structured retrieval.
|
||||
|
||||
### Implementation (Python)
|
||||
|
||||
```python
|
||||
from mem0 import MemoryClient
|
||||
|
||||
client = MemoryClient()
|
||||
|
||||
# 1. Define categories at the project level (one-time setup)
|
||||
custom_categories = [
|
||||
{"support_tickets": "Customer issues and resolutions"},
|
||||
{"account_info": "Account details and preferences"},
|
||||
{"billing": "Payment history and billing questions"},
|
||||
{"product_feedback": "Feature requests and feedback"},
|
||||
]
|
||||
client.project.update(custom_categories=custom_categories)
|
||||
|
||||
# 2. Store interactions — auto-classified into categories
|
||||
def log_support_interaction(user_id: str, message: str, priority: str = "normal"):
|
||||
client.add(
|
||||
[{"role": "user", "content": message}],
|
||||
user_id=user_id,
|
||||
metadata={"priority": priority, "source": "support_chat"}
|
||||
)
|
||||
|
||||
# 3. Retrieve by category
|
||||
def get_billing_issues(user_id: str):
|
||||
return client.get_all(
|
||||
filters={
|
||||
"AND": [
|
||||
{"user_id": user_id},
|
||||
{"categories": {"in": ["billing"]}}
|
||||
]
|
||||
}
|
||||
)
|
||||
|
||||
def search_support_history(user_id: str, query: str):
|
||||
return client.search(
|
||||
query,
|
||||
filters={
|
||||
"AND": [
|
||||
{"user_id": user_id},
|
||||
{"categories": {"contains": "support_tickets"}}
|
||||
]
|
||||
},
|
||||
top_k=5
|
||||
)
|
||||
|
||||
# Usage
|
||||
log_support_interaction("maria", "I was charged twice for last month's subscription", priority="high")
|
||||
log_support_interaction("maria", "The dashboard is loading slowly on mobile")
|
||||
billing = get_billing_issues("maria") # Returns only billing-related memories
|
||||
```
|
||||
|
||||
### Implementation (TypeScript)
|
||||
|
||||
```typescript
|
||||
import MemoryClient from 'mem0ai';
|
||||
|
||||
const client = new MemoryClient({ apiKey: process.env.MEM0_API_KEY! });
|
||||
|
||||
// Setup categories (one-time)
|
||||
await client.updateProject({
|
||||
custom_categories: [
|
||||
{ support_tickets: 'Customer issues and resolutions' },
|
||||
{ billing: 'Payment history and billing questions' },
|
||||
{ product_feedback: 'Feature requests and feedback' },
|
||||
],
|
||||
});
|
||||
|
||||
async function logInteraction(userId: string, message: string, priority = 'normal') {
|
||||
await client.add(
|
||||
[{ role: 'user', content: message }],
|
||||
{ userId: userId, metadata: { priority, source: 'support_chat' } }
|
||||
);
|
||||
}
|
||||
|
||||
async function getBillingIssues(userId: string) {
|
||||
return client.getAll({
|
||||
filters: { AND: [{ user_id: userId }, { categories: { in: ['billing'] } }] },
|
||||
});
|
||||
}
|
||||
```
|
||||
|
||||
### Key Benefits
|
||||
|
||||
- Automatic categorization — no manual tagging
|
||||
- Filter by category for structured retrieval
|
||||
- Metadata (`priority`, `source`) enables multi-dimensional queries
|
||||
|
||||
**Best for:** Help desks, SaaS support, e-commerce — structured retrieval by category eliminates manual scanning.
|
||||
|
||||
---
|
||||
|
||||
## 3. Healthcare Coach
|
||||
|
||||
Guide patients with an assistant that remembers medical history. Uses high `threshold` for confident retrieval in safety-critical contexts.
|
||||
|
||||
### Implementation (Python)
|
||||
|
||||
```python
|
||||
from mem0 import MemoryClient
|
||||
from openai import OpenAI
|
||||
|
||||
mem0 = MemoryClient()
|
||||
openai_client = OpenAI()
|
||||
|
||||
def save_patient_info(user_id: str, information: str):
|
||||
mem0.add(
|
||||
[{"role": "user", "content": information}],
|
||||
user_id=user_id,
|
||||
run_id="healthcare_session",
|
||||
metadata={"type": "patient_information"}
|
||||
)
|
||||
|
||||
def consult(user_id: str, question: str) -> str:
|
||||
# High threshold for medical accuracy
|
||||
memories = mem0.search(question, user_id=user_id, top_k=5, threshold=0.7)
|
||||
context = "\n".join([f"- {m['memory']}" for m in memories.get("results", [])])
|
||||
|
||||
response = openai_client.chat.completions.create(
|
||||
model="gpt-5-mini",
|
||||
messages=[
|
||||
{"role": "system", "content": f"You are a health coach. Patient context:\n{context}"},
|
||||
{"role": "user", "content": question},
|
||||
]
|
||||
)
|
||||
reply = response.choices[0].message.content
|
||||
|
||||
# Store the interaction
|
||||
mem0.add(
|
||||
[{"role": "user", "content": question}, {"role": "assistant", "content": reply}],
|
||||
user_id=user_id,
|
||||
run_id="healthcare_session",
|
||||
)
|
||||
return reply
|
||||
|
||||
# Usage
|
||||
save_patient_info("alex", "I'm allergic to penicillin and take metformin for type 2 diabetes")
|
||||
consult("alex", "Can I take amoxicillin for my sore throat?")
|
||||
# Remembers penicillin allergy — amoxicillin is a penicillin-type antibiotic
|
||||
```
|
||||
|
||||
### Implementation (TypeScript)
|
||||
|
||||
```typescript
|
||||
import MemoryClient from 'mem0ai';
|
||||
import OpenAI from 'openai';
|
||||
|
||||
const mem0 = new MemoryClient({ apiKey: process.env.MEM0_API_KEY! });
|
||||
const openai = new OpenAI();
|
||||
|
||||
async function savePatientInfo(userId: string, info: string) {
|
||||
await mem0.add(
|
||||
[{ role: 'user', content: info }],
|
||||
{ userId: userId, runId: 'healthcare_session', metadata: { type: 'patient_information' } }
|
||||
);
|
||||
}
|
||||
|
||||
async function consult(userId: string, question: string): Promise<string> {
|
||||
const memories = await mem0.search(question, {
|
||||
filters: { user_id: userId },
|
||||
topK: 5,
|
||||
threshold: 0.7,
|
||||
});
|
||||
const context = memories.results?.map((m: any) => `- ${m.memory}`).join('\n') || '';
|
||||
|
||||
const response = await openai.chat.completions.create({
|
||||
model: 'gpt-5-mini',
|
||||
messages: [
|
||||
{ role: 'system', content: `You are a health coach. Patient context:\n${context}` },
|
||||
{ role: 'user', content: question },
|
||||
],
|
||||
});
|
||||
const reply = response.choices[0].message.content!;
|
||||
|
||||
await mem0.add(
|
||||
[{ role: 'user', content: question }, { role: 'assistant', content: reply }],
|
||||
{ userId: userId, runId: 'healthcare_session' }
|
||||
);
|
||||
return reply;
|
||||
}
|
||||
```
|
||||
|
||||
### Key Benefits
|
||||
|
||||
- High threshold (0.7) ensures only confident matches for safety-critical retrieval
|
||||
- Session scoping via `run_id` groups related health interactions
|
||||
- Metadata tagging separates patient info from conversation history
|
||||
|
||||
**Best for:** Telehealth, wellness apps, patient management — persistent health context across visits.
|
||||
|
||||
---
|
||||
|
||||
## 4. Content Creation Workflow
|
||||
|
||||
Store voice guidelines once and apply them across every draft. Uses `run_id` and `metadata` to scope writing preferences per session.
|
||||
|
||||
### Implementation (Python)
|
||||
|
||||
```python
|
||||
from mem0 import MemoryClient
|
||||
from openai import OpenAI
|
||||
|
||||
mem0 = MemoryClient()
|
||||
openai_client = OpenAI()
|
||||
|
||||
def store_writing_preferences(user_id: str, preferences: str):
|
||||
mem0.add(
|
||||
[{"role": "user", "content": preferences}],
|
||||
user_id=user_id,
|
||||
run_id="editing_session",
|
||||
metadata={"type": "preferences", "category": "writing_style"}
|
||||
)
|
||||
|
||||
def draft_content(user_id: str, topic: str) -> str:
|
||||
# Retrieve writing preferences
|
||||
prefs = mem0.search(
|
||||
"writing style preferences",
|
||||
filters={"AND": [{"user_id": user_id}, {"run_id": "editing_session"}]}
|
||||
)
|
||||
style_context = "\n".join([f"- {m['memory']}" for m in prefs.get("results", [])])
|
||||
|
||||
response = openai_client.chat.completions.create(
|
||||
model="gpt-5-mini",
|
||||
messages=[
|
||||
{"role": "system", "content": f"Write content matching these style preferences:\n{style_context}"},
|
||||
{"role": "user", "content": f"Write a blog post about: {topic}"},
|
||||
]
|
||||
)
|
||||
return response.choices[0].message.content
|
||||
|
||||
# Usage
|
||||
store_writing_preferences("writer_01", "I prefer short sentences. Active voice. No jargon. Use analogies.")
|
||||
draft_content("writer_01", "Why AI memory matters for chatbots")
|
||||
# Drafts content matching the stored voice guidelines
|
||||
```
|
||||
|
||||
### Implementation (TypeScript)
|
||||
|
||||
```typescript
|
||||
import MemoryClient from 'mem0ai';
|
||||
import OpenAI from 'openai';
|
||||
|
||||
const mem0 = new MemoryClient({ apiKey: process.env.MEM0_API_KEY! });
|
||||
const openai = new OpenAI();
|
||||
|
||||
async function storePreferences(userId: string, preferences: string) {
|
||||
await mem0.add(
|
||||
[{ role: 'user', content: preferences }],
|
||||
{ userId: userId, runId: 'editing_session', metadata: { type: 'preferences' } }
|
||||
);
|
||||
}
|
||||
|
||||
async function draftContent(userId: string, topic: string): Promise<string> {
|
||||
const prefs = await mem0.search('writing style preferences', {
|
||||
filters: { AND: [{ user_id: userId }, { run_id: 'editing_session' }] },
|
||||
});
|
||||
const styleContext = prefs.results?.map((m: any) => `- ${m.memory}`).join('\n') || '';
|
||||
|
||||
const response = await openai.chat.completions.create({
|
||||
model: 'gpt-5-mini',
|
||||
messages: [
|
||||
{ role: 'system', content: `Write content matching these preferences:\n${styleContext}` },
|
||||
{ role: 'user', content: `Write a blog post about: ${topic}` },
|
||||
],
|
||||
});
|
||||
return response.choices[0].message.content!;
|
||||
}
|
||||
```
|
||||
|
||||
### Key Benefits
|
||||
|
||||
- Voice consistency across all content without repeating guidelines
|
||||
- Scoped sessions let you maintain different style profiles
|
||||
- Preferences update automatically as you refine them
|
||||
|
||||
**Best for:** Marketing teams, technical writers, agencies — consistent voice across all content.
|
||||
|
||||
---
|
||||
|
||||
## 5. Multi-Agent / Multi-Tenant
|
||||
|
||||
Keep memories separate using `user_id`, `agent_id`, `app_id`, and `run_id` scoping. Critical for multi-agent workflows and multi-tenant apps.
|
||||
|
||||
### Implementation (Python)
|
||||
|
||||
```python
|
||||
from mem0 import MemoryClient
|
||||
|
||||
client = MemoryClient()
|
||||
|
||||
# Store memories scoped to user + agent + session
|
||||
def store_scoped_memory(messages: list, user_id: str, agent_id: str, run_id: str, app_id: str):
|
||||
client.add(
|
||||
messages,
|
||||
user_id=user_id,
|
||||
agent_id=agent_id,
|
||||
run_id=run_id,
|
||||
app_id=app_id
|
||||
)
|
||||
|
||||
# Query within a specific scope
|
||||
def search_user_session(query: str, user_id: str, app_id: str, run_id: str):
|
||||
"""Search memories for a specific user within a specific session."""
|
||||
return client.search(
|
||||
query,
|
||||
filters={
|
||||
"AND": [
|
||||
{"user_id": user_id},
|
||||
{"app_id": app_id},
|
||||
{"run_id": run_id}
|
||||
]
|
||||
}
|
||||
)
|
||||
|
||||
def search_agent_knowledge(query: str, agent_id: str, app_id: str):
|
||||
"""Search all memories an agent has across all users."""
|
||||
return client.search(
|
||||
query,
|
||||
filters={
|
||||
"AND": [
|
||||
{"agent_id": agent_id},
|
||||
{"app_id": app_id}
|
||||
]
|
||||
}
|
||||
)
|
||||
|
||||
# Usage: Travel concierge app with multiple agents
|
||||
store_scoped_memory(
|
||||
[{"role": "user", "content": "I'm vegetarian and prefer window seats"}],
|
||||
user_id="traveler_cam",
|
||||
agent_id="travel_planner",
|
||||
run_id="tokyo-2025",
|
||||
app_id="concierge_app"
|
||||
)
|
||||
|
||||
# User-scoped query: "What does Cam prefer?"
|
||||
user_mems = search_user_session("dietary restrictions?", "traveler_cam", "concierge_app", "tokyo-2025")
|
||||
|
||||
# Agent-scoped query: "What do all travelers prefer?" (across users)
|
||||
agent_mems = search_agent_knowledge("common dietary restrictions?", "travel_planner", "concierge_app")
|
||||
```
|
||||
|
||||
### Implementation (TypeScript)
|
||||
|
||||
```typescript
|
||||
import MemoryClient from 'mem0ai';
|
||||
|
||||
const client = new MemoryClient({ apiKey: process.env.MEM0_API_KEY! });
|
||||
|
||||
async function storeScopedMemory(
|
||||
messages: Array<{ role: string; content: string }>,
|
||||
userId: string, agentId: string, runId: string, appId: string
|
||||
) {
|
||||
await client.add(messages, {
|
||||
userId: userId,
|
||||
agentId: agentId,
|
||||
runId: runId,
|
||||
appId: appId,
|
||||
});
|
||||
}
|
||||
|
||||
async function searchUserSession(query: string, userId: string, appId: string, runId: string) {
|
||||
return client.search(query, {
|
||||
filters: { AND: [{ user_id: userId }, { app_id: appId }, { run_id: runId }] },
|
||||
});
|
||||
}
|
||||
|
||||
async function searchAgentKnowledge(query: string, agentId: string, appId: string) {
|
||||
return client.search(query, {
|
||||
filters: { AND: [{ agent_id: agentId }, { app_id: appId }] },
|
||||
});
|
||||
}
|
||||
```
|
||||
|
||||
### Key Benefits
|
||||
|
||||
- Full isolation between users, agents, sessions, and apps
|
||||
- Query at any scope level — user, agent, session, or app-wide
|
||||
- No memory leakage between tenants
|
||||
|
||||
**Best for:** Multi-agent workflows, multi-tenant SaaS — proper isolation at every level.
|
||||
|
||||
---
|
||||
|
||||
## 6. Personalized Search
|
||||
|
||||
Blend real-time search results with personal context. Uses `custom_instructions` to infer preferences from queries.
|
||||
|
||||
### Implementation (Python)
|
||||
|
||||
```python
|
||||
from mem0 import MemoryClient
|
||||
from openai import OpenAI
|
||||
|
||||
mem0 = MemoryClient()
|
||||
openai_client = OpenAI()
|
||||
|
||||
# One-time setup: configure Mem0 to infer from queries
|
||||
mem0.project.update(
|
||||
custom_instructions="""Infer user preferences and facts from their search queries.
|
||||
Extract dietary preferences, location, interests, and purchase history."""
|
||||
)
|
||||
|
||||
def personalized_search(user_id: str, query: str, search_results: list) -> str:
|
||||
# Get user context from memory
|
||||
memories = mem0.search(query, user_id=user_id, top_k=5)
|
||||
user_context = "\n".join([f"- {m['memory']}" for m in memories.get("results", [])])
|
||||
|
||||
response = openai_client.chat.completions.create(
|
||||
model="gpt-5-mini",
|
||||
messages=[
|
||||
{"role": "system", "content": f"Personalize search results using user context:\n{user_context}"},
|
||||
{"role": "user", "content": f"Query: {query}\n\nSearch results:\n{search_results}"},
|
||||
]
|
||||
)
|
||||
reply = response.choices[0].message.content
|
||||
|
||||
# Store the query to learn preferences over time
|
||||
mem0.add(
|
||||
[{"role": "user", "content": query}],
|
||||
user_id=user_id
|
||||
)
|
||||
return reply
|
||||
|
||||
# Usage
|
||||
personalized_search("user_42", "best restaurants nearby", ["Restaurant A", "Restaurant B"])
|
||||
# Over time, Mem0 learns: "user prefers vegetarian, lives in Austin"
|
||||
# Future searches are automatically personalized
|
||||
```
|
||||
|
||||
### Implementation (TypeScript)
|
||||
|
||||
```typescript
|
||||
import MemoryClient from 'mem0ai';
|
||||
import OpenAI from 'openai';
|
||||
|
||||
const mem0 = new MemoryClient({ apiKey: process.env.MEM0_API_KEY! });
|
||||
const openai = new OpenAI();
|
||||
|
||||
async function personalizedSearch(userId: string, query: string, searchResults: string[]): Promise<string> {
|
||||
const memories = await mem0.search(query, { filters: { user_id: userId }, topK: 5 });
|
||||
const context = memories.results?.map((m: any) => `- ${m.memory}`).join('\n') || '';
|
||||
|
||||
const response = await openai.chat.completions.create({
|
||||
model: 'gpt-5-mini',
|
||||
messages: [
|
||||
{ role: 'system', content: `Personalize results using user context:\n${context}` },
|
||||
{ role: 'user', content: `Query: ${query}\nResults: ${searchResults.join(', ')}` },
|
||||
],
|
||||
});
|
||||
const reply = response.choices[0].message.content!;
|
||||
|
||||
await mem0.add([{ role: 'user', content: query }], { userId: userId });
|
||||
return reply;
|
||||
}
|
||||
```
|
||||
|
||||
### Key Benefits
|
||||
|
||||
- Learns preferences from queries automatically via `custom_instructions`
|
||||
- Personalizes any search provider (Tavily, Google, Bing)
|
||||
- Zero manual preference setup — improves over time
|
||||
|
||||
**Best for:** Personalized search engines, recommendation systems — search results tailored to individual users.
|
||||
|
||||
---
|
||||
|
||||
## 7. Email Intelligence
|
||||
|
||||
Capture, categorize, and recall inbox threads using persistent memories with rich metadata.
|
||||
|
||||
### Implementation (Python)
|
||||
|
||||
```python
|
||||
from mem0 import MemoryClient
|
||||
|
||||
client = MemoryClient()
|
||||
|
||||
def store_email(user_id: str, sender: str, subject: str, body: str, date: str):
|
||||
client.add(
|
||||
[{"role": "user", "content": f"Email from {sender}: {subject}\n\n{body}"}],
|
||||
user_id=user_id,
|
||||
metadata={"email_type": "incoming", "sender": sender, "subject": subject, "date": date}
|
||||
)
|
||||
|
||||
def search_emails(user_id: str, query: str):
|
||||
return client.search(
|
||||
query,
|
||||
filters={"AND": [{"user_id": user_id}, {"categories": {"contains": "email"}}]},
|
||||
top_k=10
|
||||
)
|
||||
|
||||
def get_emails_from_sender(user_id: str, sender: str):
|
||||
return client.get_all(
|
||||
filters={
|
||||
"AND": [
|
||||
{"user_id": user_id},
|
||||
{"metadata": {"contains": sender}}
|
||||
]
|
||||
}
|
||||
)
|
||||
|
||||
# Usage
|
||||
store_email("alice", "bob@acme.com", "Q3 Budget Review", "Attached is the Q3 budget...", "2025-01-15")
|
||||
store_email("alice", "carol@acme.com", "Sprint Planning", "Here are the priorities...", "2025-01-16")
|
||||
|
||||
results = search_emails("alice", "budget discussions")
|
||||
sender_emails = get_emails_from_sender("alice", "bob@acme.com")
|
||||
```
|
||||
|
||||
### Implementation (TypeScript)
|
||||
|
||||
```typescript
|
||||
import MemoryClient from 'mem0ai';
|
||||
|
||||
const client = new MemoryClient({ apiKey: process.env.MEM0_API_KEY! });
|
||||
|
||||
async function storeEmail(userId: string, sender: string, subject: string, body: string, date: string) {
|
||||
await client.add(
|
||||
[{ role: 'user', content: `Email from ${sender}: ${subject}\n\n${body}` }],
|
||||
{ userId: userId, metadata: { email_type: 'incoming', sender, subject, date } }
|
||||
);
|
||||
}
|
||||
|
||||
async function searchEmails(userId: string, query: string) {
|
||||
return client.search(query, {
|
||||
filters: { AND: [{ user_id: userId }, { categories: { contains: 'email' } }] },
|
||||
topK: 10,
|
||||
});
|
||||
}
|
||||
```
|
||||
|
||||
### Key Benefits
|
||||
|
||||
- Rich metadata enables multi-dimensional queries (sender, date, subject)
|
||||
- Category filtering separates emails from other memory types
|
||||
- Semantic search across all email content
|
||||
|
||||
**Best for:** Inbox management, email automation — searchable email memories with metadata filtering.
|
||||
|
||||
---
|
||||
|
||||
## Common Patterns Across Use Cases
|
||||
|
||||
### Pattern 1: Retrieve → Generate → Store
|
||||
|
||||
Every use case follows the same 3-step loop:
|
||||
|
||||
```python
|
||||
# 1. Retrieve relevant context
|
||||
memories = mem0.search(user_input, user_id=user_id)
|
||||
context = "\n".join([m["memory"] for m in memories.get("results", [])])
|
||||
|
||||
# 2. Generate with context
|
||||
response = llm.generate(system_prompt=f"Context:\n{context}", user_input=user_input)
|
||||
|
||||
# 3. Store the interaction
|
||||
mem0.add(
|
||||
[{"role": "user", "content": user_input}, {"role": "assistant", "content": response}],
|
||||
user_id=user_id
|
||||
)
|
||||
```
|
||||
|
||||
### Pattern 2: Scope with Entity Identifiers
|
||||
|
||||
Use `user_id`, `agent_id`, `app_id`, and `run_id` to isolate memories:
|
||||
|
||||
```python
|
||||
# User-level: personal preferences
|
||||
client.add(messages, user_id="alice")
|
||||
|
||||
# Session-level: conversation within one session
|
||||
client.add(messages, user_id="alice", run_id="session_123")
|
||||
|
||||
# Agent-level: agent-specific knowledge
|
||||
client.add(messages, agent_id="support_bot", app_id="helpdesk")
|
||||
```
|
||||
|
||||
### Pattern 3: Rich Metadata for Filtering
|
||||
|
||||
Attach structured metadata for multi-dimensional queries:
|
||||
|
||||
```python
|
||||
# Store with metadata
|
||||
client.add(messages, user_id="alice", metadata={"priority": "high", "source": "phone_call"})
|
||||
|
||||
# Filter by category + metadata
|
||||
client.search("billing issues", filters={
|
||||
"AND": [{"user_id": "alice"}, {"categories": {"contains": "billing"}}]
|
||||
})
|
||||
```
|
||||
|
||||
### Pattern 4: Custom Instructions for Domain-Specific Extraction
|
||||
|
||||
Control what Mem0 extracts from conversations:
|
||||
|
||||
```python
|
||||
client.project.update(
|
||||
custom_instructions="Extract medical conditions, medications, and allergies. Exclude billing info."
|
||||
)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## More Examples
|
||||
|
||||
For 30+ cookbooks with complete working code: [docs.mem0.ai/cookbooks](https://docs.mem0.ai/cookbooks)
|
||||
+181
@@ -0,0 +1,181 @@
|
||||
#!/usr/bin/env bun
|
||||
export {};
|
||||
const DOCS_BASE = "https://docs.mem0.ai";
|
||||
const SEARCH_ENDPOINT = `${DOCS_BASE}/api/search`;
|
||||
const LLMS_INDEX = `${DOCS_BASE}/llms.txt`;
|
||||
|
||||
const SECTION_MAP: Record<string, string[]> = {
|
||||
platform: [
|
||||
"/platform/overview",
|
||||
"/platform/quickstart",
|
||||
"/platform/features",
|
||||
"/platform/features/graph-memory",
|
||||
"/platform/features/selective-memory",
|
||||
"/platform/features/custom-categories",
|
||||
"/platform/features/v2-memory-filters",
|
||||
"/platform/features/async-client",
|
||||
"/platform/features/webhooks",
|
||||
"/platform/features/multimodal-support",
|
||||
],
|
||||
api: [
|
||||
"/api-reference/memory/add-memories",
|
||||
"/api-reference/memory/v2-search-memories",
|
||||
"/api-reference/memory/v2-get-memories",
|
||||
"/api-reference/memory/get-memory",
|
||||
"/api-reference/memory/update-memory",
|
||||
"/api-reference/memory/delete-memory",
|
||||
],
|
||||
"open-source": [
|
||||
"/open-source/overview",
|
||||
"/open-source/python-quickstart",
|
||||
"/open-source/node-quickstart",
|
||||
"/open-source/features",
|
||||
"/open-source/features/graph-memory",
|
||||
"/open-source/features/rest-api",
|
||||
"/open-source/configure-components",
|
||||
],
|
||||
openmemory: [
|
||||
"/openmemory/overview",
|
||||
"/openmemory/quickstart",
|
||||
],
|
||||
sdks: ["/sdks/python", "/sdks/js"],
|
||||
integrations: ["/integrations"],
|
||||
};
|
||||
|
||||
async function fetchUrl(url: string): Promise<string> {
|
||||
try {
|
||||
const res = await fetch(url, {
|
||||
headers: { "User-Agent": "Mem0DocSearchAgent/1.0" },
|
||||
signal: AbortSignal.timeout(15000),
|
||||
});
|
||||
if (!res.ok) return `HTTP Error ${res.status}: ${res.statusText}`;
|
||||
return await res.text();
|
||||
} catch (e: any) {
|
||||
return `Error: ${e.message}`;
|
||||
}
|
||||
}
|
||||
|
||||
async function searchDocs(query: string, section?: string) {
|
||||
const params = new URLSearchParams({ query });
|
||||
try {
|
||||
const result = await fetchUrl(`${SEARCH_ENDPOINT}?${params}`);
|
||||
const data = JSON.parse(result);
|
||||
if (data?.results) {
|
||||
let results = data.results;
|
||||
if (section && SECTION_MAP[section]) {
|
||||
const paths = SECTION_MAP[section];
|
||||
results = results.filter((r: any) =>
|
||||
paths.some((p) => r.url?.startsWith(p)),
|
||||
);
|
||||
}
|
||||
return { source: "mintlify_search", results };
|
||||
}
|
||||
} catch {}
|
||||
|
||||
const indexContent = await fetchUrl(LLMS_INDEX);
|
||||
const queryLower = query.toLowerCase();
|
||||
let matching = indexContent
|
||||
.split("\n")
|
||||
.map((l) => l.trim())
|
||||
.filter((l) => l && !l.startsWith("#") && l.toLowerCase().includes(queryLower));
|
||||
|
||||
if (section && SECTION_MAP[section]) {
|
||||
const paths = SECTION_MAP[section];
|
||||
matching = matching.filter((u) => paths.some((p) => u.includes(p)));
|
||||
}
|
||||
|
||||
return {
|
||||
source: "llms_txt_index",
|
||||
query,
|
||||
matching_urls: matching.slice(0, 20),
|
||||
suggestion: "Fetch specific URLs for detailed content",
|
||||
};
|
||||
}
|
||||
|
||||
async function fetchPage(pagePath: string) {
|
||||
const url = pagePath.startsWith("/") ? `${DOCS_BASE}${pagePath}` : pagePath;
|
||||
const content = await fetchUrl(url);
|
||||
return { url, content: content.slice(0, 10000), truncated: content.length > 10000 };
|
||||
}
|
||||
|
||||
async function getIndex() {
|
||||
const content = await fetchUrl(LLMS_INDEX);
|
||||
const urls = content
|
||||
.split("\n")
|
||||
.map((l) => l.trim())
|
||||
.filter((l) => l && !l.startsWith("#"));
|
||||
return { total_pages: urls.length, urls, sections: Object.keys(SECTION_MAP) };
|
||||
}
|
||||
|
||||
function listSection(section: string) {
|
||||
if (!SECTION_MAP[section]) {
|
||||
return { error: `Unknown section: ${section}`, available: Object.keys(SECTION_MAP) };
|
||||
}
|
||||
return { section, pages: SECTION_MAP[section].map((p) => `${DOCS_BASE}${p}`) };
|
||||
}
|
||||
|
||||
function printResult(result: any) {
|
||||
if (result.results) {
|
||||
console.log(`Source: ${result.source ?? "unknown"}`);
|
||||
for (const r of result.results) {
|
||||
console.log(` - ${r.title ?? "N/A"}: ${r.url ?? "N/A"}`);
|
||||
if (r.description) console.log(` ${r.description.slice(0, 200)}`);
|
||||
}
|
||||
} else if (result.matching_urls) {
|
||||
console.log(`Source: ${result.source}`);
|
||||
console.log(`Query: ${result.query}`);
|
||||
for (const url of result.matching_urls) console.log(` - ${url}`);
|
||||
if (result.suggestion) console.log(`\n${result.suggestion}`);
|
||||
} else if (result.urls) {
|
||||
console.log(`Total documentation pages: ${result.total_pages}`);
|
||||
console.log(`Sections: ${result.sections.join(", ")}`);
|
||||
for (const url of result.urls.slice(0, 30)) console.log(` - ${url}`);
|
||||
if (result.total_pages > 30) console.log(` ... and ${result.total_pages - 30} more`);
|
||||
} else if (result.pages) {
|
||||
console.log(`Section: ${result.section}`);
|
||||
for (const page of result.pages) console.log(` - ${page}`);
|
||||
} else if (result.content) {
|
||||
console.log(`URL: ${result.url}`);
|
||||
if (result.truncated) console.log("[Content truncated to 10000 chars]");
|
||||
console.log(result.content);
|
||||
} else if (result.error) {
|
||||
console.log(`Error: ${result.error}`);
|
||||
if (result.available) console.log(`Available sections: ${result.available.join(", ")}`);
|
||||
} else {
|
||||
console.log(JSON.stringify(result, null, 2));
|
||||
}
|
||||
}
|
||||
|
||||
const args = process.argv.slice(2);
|
||||
const flags: Record<string, string | boolean> = {};
|
||||
for (let i = 0; i < args.length; i++) {
|
||||
if (args[i] === "--query" && args[i + 1]) flags.query = args[++i];
|
||||
else if (args[i] === "--page" && args[i + 1]) flags.page = args[++i];
|
||||
else if (args[i] === "--section" && args[i + 1]) flags.section = args[++i];
|
||||
else if (args[i] === "--index") flags.index = true;
|
||||
else if (args[i] === "--json") flags.json = true;
|
||||
}
|
||||
|
||||
let result: any;
|
||||
if (flags.index) {
|
||||
result = await getIndex();
|
||||
} else if (flags.section && !flags.query) {
|
||||
result = listSection(flags.section as string);
|
||||
} else if (flags.page) {
|
||||
result = await fetchPage(flags.page as string);
|
||||
} else if (flags.query) {
|
||||
result = await searchDocs(flags.query as string, flags.section as string | undefined);
|
||||
} else {
|
||||
console.log("Usage:");
|
||||
console.log(" bun scripts/mem0_doc_search.ts --query \"topic\"");
|
||||
console.log(" bun scripts/mem0_doc_search.ts --page \"/platform/features/graph-memory\"");
|
||||
console.log(" bun scripts/mem0_doc_search.ts --index");
|
||||
console.log(" bun scripts/mem0_doc_search.ts --section platform");
|
||||
process.exit(1);
|
||||
}
|
||||
|
||||
if (flags.json) {
|
||||
console.log(JSON.stringify(result, null, 2));
|
||||
} else {
|
||||
printResult(result);
|
||||
}
|
||||
@@ -0,0 +1,63 @@
|
||||
---
|
||||
name: memory-reviewer
|
||||
description: Reviews stored memory quality by detecting duplicates, contradictions, and stale entries with actionable recommendations. Use when search results seem conflicting, before running dream consolidation, or for periodic memory hygiene audits.
|
||||
---
|
||||
|
||||
# Memory Reviewer
|
||||
|
||||
Audits memory quality for the active project. Finds duplicates, contradictions, and low-confidence entries.
|
||||
|
||||
## When to use
|
||||
|
||||
- User asks "check my memories", "memory quality", "any duplicates?"
|
||||
- User runs `/mem0:memory-reviewer` directly
|
||||
- After a session with 5+ memory writes (suggest proactively)
|
||||
- After `/mem0:health --deep` identifies issues
|
||||
|
||||
## Steps
|
||||
|
||||
1. **Fetch all memories** for active project via `get_memories` with `filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<active_project_id>"}]}`, `page_size=200`. Paginate if needed — cap at 200 memories.
|
||||
|
||||
2. **Group by `metadata.type`**. Common types: `decision`, `convention`, `anti_pattern`, `task_learning`, `project_profile`, `user_preference`, `session_state`.
|
||||
|
||||
3. **Scan each group for issues:**
|
||||
|
||||
| Issue | Detection method |
|
||||
|---|---|
|
||||
| **Near-duplicates** | >60% noun overlap within same type. Compare memory text after stripping stop words. |
|
||||
| **Contradictions** | Opposing facts about same topic (e.g., "use PostgreSQL" vs "use MySQL" for same component) |
|
||||
| **Low-confidence** | `metadata.confidence < 0.3` |
|
||||
| **Missing type** | No `metadata.type` set |
|
||||
| **Stale** | `created_at` older than 180 days with no updates |
|
||||
|
||||
4. **Output compact summary:**
|
||||
|
||||
```
|
||||
memory-reviewer: project=<id> total=<N>
|
||||
duplicates: <N> found
|
||||
contradictions: <N> found
|
||||
low_confidence: <N> found
|
||||
untagged: <N> found
|
||||
stale: <N> found
|
||||
```
|
||||
|
||||
5. **If issues found**, list them with memory IDs:
|
||||
|
||||
```
|
||||
Issues:
|
||||
[duplicate] "<memory_a>" ≈ "<memory_b>" [mem0:<id_a>, mem0:<id_b>]
|
||||
[contradiction] "<memory_x>" vs "<memory_y>" [mem0:<id_x>, mem0:<id_y>]
|
||||
[low_conf] "<memory_z>" (confidence: 0.1) [mem0:<id_z>]
|
||||
```
|
||||
|
||||
6. **Suggest action**: "Run `/mem0:dream` to consolidate duplicates and resolve contradictions."
|
||||
|
||||
## Constraints
|
||||
|
||||
- **Read-only** — never modify or delete memories (that's `/mem0:dream`'s job)
|
||||
- **Max 200 memories** per scan
|
||||
- Report findings, let user decide on action
|
||||
|
||||
## Output formatting
|
||||
|
||||
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like **bold**, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.
|
||||
@@ -0,0 +1,181 @@
|
||||
---
|
||||
name: onboard
|
||||
description: Sets up mem0 for a new project including API key configuration, MCP authentication, project file import, and coding categories. Use on first run in a new project, when API key needs updating, or to re-run initial setup after configuration changes.
|
||||
---
|
||||
|
||||
# Mem0 Onboarding Wizard
|
||||
|
||||
Run this wizard to set up the mem0 plugin for the current project. Complete in ~60 seconds.
|
||||
|
||||
**IMPORTANT: Execute steps strictly in order (0 → 1 → 2 → 3 → 4 → 5 → 6). Each step depends on the previous one. Do NOT run steps in parallel or skip ahead. Complete one step fully before starting the next.**
|
||||
|
||||
## Step 0: Skip dependency install
|
||||
|
||||
The plugin lists `mem0ai` as a declared dependency — no install step is needed. Proceed directly to Step 1.
|
||||
|
||||
## Step 1: Set up API key
|
||||
|
||||
Check if the API key is available:
|
||||
|
||||
```bash
|
||||
[ -n "${MEM0_API_KEY:-}" ] && echo "SET" || echo "NOT_SET"
|
||||
```
|
||||
|
||||
IMPORTANT: Never run `echo $MEM0_API_KEY` — that prints the secret in plaintext to the conversation log.
|
||||
|
||||
### If API key IS set (output is "SET")
|
||||
|
||||
Print: `- API key found.` and proceed to Step 2.
|
||||
|
||||
### If API key is NOT set (output is "NOT_SET")
|
||||
|
||||
Guide the user through API key setup. Show this message:
|
||||
|
||||
```
|
||||
Step 1: Setting up API key.
|
||||
|
||||
- API key not found. Let's set it up.
|
||||
|
||||
1. Get your API key from https://app.mem0.ai/dashboard/api-keys
|
||||
|
||||
2. Choose ONE method:
|
||||
|
||||
Option A — Shell profile:
|
||||
echo 'export MEM0_API_KEY="m0-your-key-here"' >> ~/.zshrc
|
||||
source ~/.zshrc
|
||||
|
||||
Option B — OpenCode environment config:
|
||||
Add MEM0_API_KEY to your OpenCode environment settings
|
||||
so it is available in all sessions.
|
||||
|
||||
3. Verify:
|
||||
[ -n "${MEM0_API_KEY:-}" ] && echo "SET" || echo "NOT_SET"
|
||||
```
|
||||
|
||||
After the user confirms, re-run the verify command. If NOT_SET, repeat. If SET, proceed to Step 2.
|
||||
|
||||
## Step 2: MCP server connection
|
||||
|
||||
First, check if MCP tools are already available using ToolSearch with query `"mem0 search_memories"`. The exact tool name varies by install method (may be `mcp__mem0__search_memories` or `mcp__plugin_mem0_mem0__search_memories`).
|
||||
|
||||
**If MCP tools ARE found:** Print `- MCP already connected.` and proceed to Step 3.
|
||||
|
||||
**If MCP tools are NOT found:**
|
||||
|
||||
The MCP server authenticates using the `MEM0_API_KEY` set in Step 1. No OAuth or browser login is needed.
|
||||
|
||||
1. Verify the API key is set (re-run the Step 1 check)
|
||||
2. Check the plugin is installed and the MCP server for mem0 is listed in OpenCode's MCP configuration
|
||||
3. If the server shows an error, ask the user to restart OpenCode and run `/mem0:onboard` again
|
||||
4. If all checks pass but tools are still missing: "Restart OpenCode and run `/mem0:onboard` again."
|
||||
|
||||
**STOP here** — do not proceed without MCP tools.
|
||||
|
||||
## Step 3: Verify connectivity and show identity
|
||||
|
||||
Call `search_memories` with `query="project setup"`, `filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<active_project_id>"}]}`, `top_k=1` to verify connectivity.
|
||||
|
||||
Print:
|
||||
```
|
||||
- Connected
|
||||
user: <user_id>
|
||||
project: <project_id>
|
||||
branch: <branch>
|
||||
```
|
||||
|
||||
If the search fails, troubleshoot the API key and MCP connection.
|
||||
|
||||
## Step 4: Import project files
|
||||
|
||||
Check for common project context files in the working directory root. Read any that exist and store their key facts as memories using `add_memory`.
|
||||
|
||||
### 4a: Detect project files
|
||||
|
||||
```bash
|
||||
for f in CLAUDE.md AGENTS.md .cursorrules .windsurfrules mem0.md .mem0.md; do
|
||||
[ -f "$f" ] && echo "FOUND: $f ($(wc -c < "$f") bytes)"
|
||||
done || true
|
||||
```
|
||||
|
||||
If no files found, print `- No project files found. Skipping import.` and proceed to Step 5.
|
||||
|
||||
### 4b: Read and import via MCP
|
||||
|
||||
For each file found in 4a:
|
||||
|
||||
1. Read the file contents with the Read tool.
|
||||
2. Extract the key facts, conventions, and decisions documented in the file. Do not import the entire file verbatim — summarize meaningful chunks.
|
||||
3. Call `add_memory` for each meaningful chunk with:
|
||||
- `data`: the extracted fact or convention
|
||||
- `user_id`: the active user id
|
||||
- `app_id`: the active project id
|
||||
- `metadata`: `{"source": "<filename>", "type": "project_context"}`
|
||||
|
||||
If a file is very large (over 4000 bytes), split it into logical sections (one `add_memory` call per section).
|
||||
|
||||
### 4c: Report to user
|
||||
|
||||
After processing all files, print a user-friendly summary:
|
||||
|
||||
```
|
||||
- Importing project files into mem0... done.
|
||||
<N> file(s) read, <M> memories stored.
|
||||
These are available as context for future sessions.
|
||||
```
|
||||
|
||||
If `add_memory` calls fail, print:
|
||||
```
|
||||
- Project file import failed. Check API key and MCP connection, then retry with: /mem0:onboard
|
||||
```
|
||||
|
||||
## Step 5: Verify coding categories
|
||||
|
||||
Coding categories are now configured automatically in the background when the plugin starts. This step only verifies they are set up.
|
||||
|
||||
Check if the categories are already configured by searching for a project_profile memory:
|
||||
|
||||
Call `search_memories` with `query="coding categories project profile"`, `filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<active_project_id>"}]}`, `top_k=1`.
|
||||
|
||||
If a project_profile memory is found, print:
|
||||
```
|
||||
- Coding categories already configured (17 categories, auto-installed).
|
||||
```
|
||||
|
||||
If no project_profile memory is found, store one as a fallback. Call `add_memory` once with:
|
||||
|
||||
- `data`: a plain-text description of the project profile and the list of active coding categories:
|
||||
```
|
||||
Project profile for <project_id>.
|
||||
Active coding categories: architecture_decisions, api_design, data_models,
|
||||
algorithms, dependencies, environment_setup, testing_strategy, debugging_notes,
|
||||
performance, security, deployment, code_conventions, error_handling,
|
||||
refactoring_history, integrations, onboarding, project_meta.
|
||||
```
|
||||
- `user_id`: the active user id
|
||||
- `app_id`: the active project id
|
||||
- `metadata`: `{"type": "project_profile", "source": "onboard"}`
|
||||
|
||||
After the `add_memory` call succeeds, print:
|
||||
```
|
||||
- Coding categories installed (17 categories).
|
||||
```
|
||||
|
||||
## Step 6: Summary
|
||||
|
||||
Print a summary:
|
||||
```
|
||||
- Onboarding complete.
|
||||
user_id: <user_id>
|
||||
project_id: <project_id> (app_id)
|
||||
files: <N> found, <M> memories stored
|
||||
categories: <N installed | already installed | skipped by user>
|
||||
|
||||
Memory is now active for this project. Start working — mem0 will
|
||||
automatically search relevant context and capture learnings.
|
||||
|
||||
Run /mem0:tour to see what mem0 already knows about this project.
|
||||
```
|
||||
|
||||
## Output formatting
|
||||
|
||||
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like **bold**, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.
|
||||
@@ -0,0 +1,56 @@
|
||||
---
|
||||
name: peek
|
||||
description: Searches memories and displays compact one-liner results, or looks up a specific memory by ID. Use for quick memory lookups, checking if a decision was recorded, resolving [mem0:id] citations, or browsing memories without full category detail.
|
||||
---
|
||||
|
||||
# Mem0 Peek
|
||||
|
||||
Quick search with compact output. Lighter than `/mem0:tour`.
|
||||
|
||||
## Execution
|
||||
|
||||
### Step 1: Parse query
|
||||
|
||||
The user provides a search query: `/mem0:peek auth middleware`
|
||||
|
||||
If no query provided, ask: "What should I search for?"
|
||||
|
||||
**Memory ID detection:** If the query matches any of these patterns, treat it as a
|
||||
direct memory ID lookup instead of a search:
|
||||
- Bare hex: `^[a-f0-9]{8}$` (short ID) or `^[a-f0-9]{8}-[a-f0-9-]+$` (full UUID)
|
||||
- Citation ref: `[mem0:<hex>]` — extract the hex portion
|
||||
|
||||
When an ID is detected:
|
||||
1. Call `get_memory(<id>)` directly (if short ID, try as prefix of full UUID)
|
||||
2. If found, skip to Step 3 and display the single result
|
||||
3. If not found, fall through to search using the ID as query text
|
||||
|
||||
### Step 2: Search
|
||||
|
||||
Run 2 parallel `search_memories` calls:
|
||||
|
||||
1. Broad: `query=<user's query>`, `filters={"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}]}`, `top_k=10`, `rerank=true`
|
||||
2. Targeted: `query=<user's query>`, `filters={"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}, {"metadata": {"type": "decision"}}]}`, `top_k=5`, `rerank=true`
|
||||
|
||||
### Step 3: Display
|
||||
|
||||
Deduplicate by ID, then show compact results:
|
||||
|
||||
```
|
||||
## mem0 peek: "<query>" (<N> results)
|
||||
|
||||
1. [decision] Auth module uses JWT with RS256 keys (2025-05-15) [mem0:a3f8b2c1]
|
||||
2. [anti_pattern] Don't use symmetric HS256 — leaked in env (2025-05-10) [mem0:7e2d9f4a]
|
||||
3. [convention] All middleware in src/middleware/ (2025-05-08) [mem0:c4d5e6f7]
|
||||
```
|
||||
|
||||
Format: `<number>. [<type>] <content, 80 chars> (<date>) [mem0:<short_id>]`
|
||||
|
||||
If no results:
|
||||
```
|
||||
No memories matching "<query>" for project <project_id>.
|
||||
```
|
||||
|
||||
## Output formatting
|
||||
|
||||
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like **bold**, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.
|
||||
@@ -0,0 +1,71 @@
|
||||
---
|
||||
name: pin
|
||||
description: Pins or unpins a memory to protect it from pruning during dream consolidation. Use when a memory is critical and must never be removed, such as architecture decisions, security constraints, or immutable team conventions.
|
||||
---
|
||||
|
||||
# Mem0 Pin
|
||||
|
||||
Pin a memory to mark it as high-priority and protect from pruning.
|
||||
|
||||
## Execution
|
||||
|
||||
### Step 1: Find the memory
|
||||
|
||||
The user provides either a search query or memory ID.
|
||||
|
||||
**If memory ID:**
|
||||
- Call `get_memory` with the ID.
|
||||
|
||||
**If search query:**
|
||||
- Call `search_memories` with the query, `filters={"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}]}`, `top_k=5`.
|
||||
- Show numbered list with content previews.
|
||||
- Ask: "Which memory to pin? Enter a number."
|
||||
|
||||
### Step 2: Read current content
|
||||
|
||||
Call `get_memory` with the selected memory ID. Store:
|
||||
- `original_text` — the memory's text content
|
||||
- `original_metadata` — the existing `metadata` dict
|
||||
|
||||
### Step 3: Pin it
|
||||
|
||||
The MCP `update_memory` tool only accepts `memory_id`, `text`, and `source` — it
|
||||
does not accept a `metadata` parameter. To pin, append a pin marker to the text:
|
||||
|
||||
```python
|
||||
pinned_text = "[PINNED] " + original_text if not original_text.startswith("[PINNED]") else original_text
|
||||
update_memory(memory_id=<selected_id>, text=pinned_text)
|
||||
```
|
||||
|
||||
**For new memories** (user wants to pin text that isn't stored yet):
|
||||
1. Call `add_memory` with:
|
||||
- `text="[PINNED] <the user's text>"`
|
||||
- `user_id=<active_user_id>`
|
||||
- `app_id=<active_project_id>`
|
||||
- `metadata={"pinned": true, "type": "decision", "confidence": 1.0}`
|
||||
- `infer=False`
|
||||
2. The response contains `event_id`. Call `get_event_status(event_id=<event_id>)` once to retrieve the memory ID, then confirm.
|
||||
|
||||
### Step 4: Confirm
|
||||
|
||||
```
|
||||
Pinned: "<memory content, first 80 chars>"
|
||||
Memory ID: <id>
|
||||
```
|
||||
|
||||
Append `...` only if content exceeds 80 characters.
|
||||
|
||||
### Unpin
|
||||
|
||||
If the user says "unpin":
|
||||
1. Call `get_memory` to read current content.
|
||||
2. Remove the pin marker from the text:
|
||||
```python
|
||||
unpinned_text = original_text.removeprefix("[PINNED] ")
|
||||
update_memory(memory_id=<id>, text=unpinned_text)
|
||||
```
|
||||
3. Print: `Unpinned: "<content>..."`
|
||||
|
||||
## Output formatting
|
||||
|
||||
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like **bold**, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.
|
||||
@@ -0,0 +1,61 @@
|
||||
---
|
||||
name: remember
|
||||
description: Stores a memory verbatim from user input with appropriate type classification and metadata. Use when the user says remember this, save this, store this, note that, or explicitly asks to record a decision, preference, convention, or learning.
|
||||
---
|
||||
|
||||
# Mem0 Remember
|
||||
|
||||
Store a fact or learning directly into mem0.
|
||||
|
||||
## Execution
|
||||
|
||||
### Step 1: Extract the content
|
||||
|
||||
The user provides the content as an argument: `/mem0:remember <text>`
|
||||
|
||||
If no text was provided, ask: "What should I remember?"
|
||||
|
||||
### Step 2: Classify the memory
|
||||
|
||||
Based on the content, pick the best `metadata.type`:
|
||||
|
||||
| Content signal | Type |
|
||||
|---|---|
|
||||
| "we decided...", "always use...", "never..." | `decision` |
|
||||
| "X doesn't work because...", "don't try..." | `anti_pattern` |
|
||||
| "I prefer...", "use X instead of Y" | `user_preference` |
|
||||
| "the convention is...", "we always..." | `convention` |
|
||||
| "learned that...", "figured out..." | `task_learning` |
|
||||
| setup, env, tooling, config | `environmental` |
|
||||
| anything else | `task_learning` |
|
||||
|
||||
### Step 3: Store
|
||||
|
||||
Call `add_memory` with:
|
||||
- `text="<the user's text>"`
|
||||
- `user_id=<active_user_id>`
|
||||
- `app_id=<active_project_id>`
|
||||
- `metadata={"type": "<classified_type>", "branch": "<active_branch>", "confidence": 1.0, "source": "remember_command"}`
|
||||
- `infer=False`
|
||||
|
||||
`infer=False` because the user stated the fact explicitly — no extraction needed.
|
||||
`confidence=1.0` because the user explicitly asked to store this.
|
||||
|
||||
### Step 4: Confirm
|
||||
|
||||
The `add_memory` response returns `event_id` (not `memory_id`) because writes are async.
|
||||
Call `get_event_status(event_id=<event_id>)` once.
|
||||
|
||||
- If status is `SUCCEEDED`: print the memory ID from the result.
|
||||
- If status is `PENDING` or `processing`: print with the event ID as fallback.
|
||||
|
||||
```
|
||||
Remembered as <type>: "<content, first 80 chars>"
|
||||
Memory ID: <id from event status>
|
||||
```
|
||||
|
||||
Append `...` only if content was truncated (longer than 80 chars).
|
||||
|
||||
## Output formatting
|
||||
|
||||
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like **bold**, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.
|
||||
@@ -0,0 +1,135 @@
|
||||
---
|
||||
name: stats
|
||||
description: Displays memory usage statistics for the current session and project including counts by category, age distribution, and API latency. Use when checking how many memories exist, reviewing session activity, or auditing memory distribution across categories.
|
||||
---
|
||||
|
||||
# Mem0 Stats
|
||||
|
||||
Show session and lifetime memory statistics.
|
||||
|
||||
## Execution
|
||||
|
||||
### Step 1: Gather session context
|
||||
|
||||
Read the session identity from env vars set by the plugin's shell.env hook:
|
||||
|
||||
- `MEM0_USER_ID` (falls back to `$USER` if unset)
|
||||
- `MEM0_APP_ID` — the active project identifier
|
||||
- `MEM0_SESSION_ID` — current session identifier
|
||||
- `MEM0_BRANCH` — current git branch
|
||||
|
||||
If `MEM0_USER_ID` is unset, use `$USER`. If `MEM0_APP_ID` is unset, note "No project configured" and stop.
|
||||
|
||||
### Step 2: Fetch total memory count
|
||||
|
||||
Call `get_memories` MCP tool to get the total count for this project:
|
||||
|
||||
`filters={"AND": [{"user_id": "<MEM0_USER_ID>"}, {"app_id": "<MEM0_APP_ID>"}]}`, `page_size=1`
|
||||
|
||||
Read the `count` field from the response — this is the total number of memories for the project regardless of page size.
|
||||
|
||||
### Step 3: Fetch memories for category breakdown
|
||||
|
||||
Call `get_memories` MCP tool to retrieve memories for grouping:
|
||||
|
||||
`filters={"AND": [{"user_id": "<MEM0_USER_ID>"}, {"app_id": "<MEM0_APP_ID>"}]}`, `page_size=200`
|
||||
|
||||
Group each memory by:
|
||||
1. `categories[0]` (platform-assigned) — primary grouping
|
||||
2. `metadata.type` (agent-assigned) — secondary if `categories` is empty or absent
|
||||
3. `created_at` date — for age analysis
|
||||
|
||||
**Category normalization:** Merge `auto_capture` and `uncategorized` into a single `uncategorized` row. Do NOT show `auto_capture` as its own row.
|
||||
|
||||
Also run a `search_memories` MCP tool call with `query="project"`, `filters={"AND": [{"user_id": "<MEM0_USER_ID>"}, {"app_id": "<MEM0_APP_ID>"}]}`, `top_k=1` to measure round-trip latency. Note the time before and after the MCP call — do NOT attempt raw HTTP calls to the API.
|
||||
|
||||
### Step 4: Display
|
||||
|
||||
Print a minimal plain-text dashboard. No markdown formatting — OpenCode TUI renders text verbatim.
|
||||
|
||||
Example output shape:
|
||||
|
||||
```
|
||||
mem0 stats
|
||||
|
||||
Session (<first 12 chars of MEM0_SESSION_ID>) branch: main
|
||||
|
||||
Project: my-project — 55 memories — API: 84ms
|
||||
|
||||
Category Count
|
||||
-------------------- -----
|
||||
decision 24
|
||||
convention 15
|
||||
anti_pattern 6
|
||||
task_learning 5
|
||||
user_preference 3
|
||||
session_state 2
|
||||
|
||||
Age — oldest: 2026-02-15 newest: 2026-05-23
|
||||
< 7 days: 5 | 7-30d: 12 | 30-90d: 10 | > 90d: 8
|
||||
|
||||
Identity — user: kartik project: my-project branch: main
|
||||
```
|
||||
|
||||
**Display rules:**
|
||||
- Use plain text with spaces to align columns — no markdown tables, no | pipes, no ** bold, no ## headers
|
||||
- Category section: sort by count descending, omit categories with 0 memories
|
||||
- Age: single line with pipe-separated buckets, computed from `created_at`
|
||||
- Session line: show MEM0_SESSION_ID (first 12 chars) and MEM0_BRANCH if available; skip the line entirely if both are unset
|
||||
- If only 1-2 total memories, skip the category table — just show the count
|
||||
- Keep everything compact — no decorative borders or filler
|
||||
|
||||
## Weekly digest mode
|
||||
|
||||
When invoked with `--weekly` (e.g., `/mem0:stats --weekly`), append a weekly
|
||||
activity digest after the standard stats dashboard.
|
||||
|
||||
### W1: Fetch recent memories
|
||||
|
||||
Call `search_memories` in parallel with time-scoped queries:
|
||||
1. `query="decisions made this week"`, `filters={"AND": [{"user_id": "<MEM0_USER_ID>"}, {"app_id": "<MEM0_APP_ID>"}, {"created_at": {"gte": "<7 days ago YYYY-MM-DD>"}}]}`, `top_k=20`
|
||||
2. `query="bugs errors fixes"`, same time filter, `top_k=20`
|
||||
3. `query="patterns conventions learnings"`, same time filter, `top_k=20`
|
||||
|
||||
### W2: Analyze
|
||||
|
||||
Merge by ID. Group into "New this week" by `categories[0]` or `metadata.type`.
|
||||
Calculate: memories added last 7 days, most active categories, most active day.
|
||||
|
||||
### W3: Display
|
||||
|
||||
Append after the standard stats in plain text (no markdown):
|
||||
|
||||
```
|
||||
This week (May 16 - May 23)
|
||||
|
||||
+12 memories — most active: Wednesday (5)
|
||||
|
||||
Category New
|
||||
-------------- ---
|
||||
decision 5
|
||||
task_learning 4
|
||||
bug_fix 3
|
||||
|
||||
Highlights
|
||||
- <2-3 sentence summary of most important decisions/learnings this week>
|
||||
```
|
||||
|
||||
### W4: Write digest file
|
||||
|
||||
Write to `~/.mem0/weekly-digest.txt` (overwrite). Append one line to
|
||||
`~/.mem0/digest-history.log`:
|
||||
```
|
||||
<YYYY-MM-DD> | <MEM0_APP_ID> | +<new_count> memories | top: <top_category>
|
||||
```
|
||||
|
||||
### W5: Empty state
|
||||
|
||||
If no new memories in 7 days, output:
|
||||
```
|
||||
No new memories in the past week. Total: <N> memories in <MEM0_APP_ID>.
|
||||
```
|
||||
|
||||
## Output formatting
|
||||
|
||||
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like **bold**, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.
|
||||
@@ -0,0 +1,107 @@
|
||||
---
|
||||
name: switch-project
|
||||
description: Overrides the auto-detected project scope to read and write memories under a different project ID, or enables global search to access all memories across all users and projects. Use when working across multiple projects, accessing memories from another repo, enabling team-wide memory access, or when auto-detection resolves to the wrong project.
|
||||
---
|
||||
|
||||
# Mem0 Switch Project
|
||||
|
||||
Override the automatic project_id detection for the current directory, or enable global search mode.
|
||||
|
||||
## Usage
|
||||
|
||||
- `/mem0:switch-project <project-name>` — switch to a specific project scope
|
||||
- `/mem0:switch-project --global` — enable global search (all memories, all users, all projects)
|
||||
- `/mem0:switch-project --no-global` — disable global search and return to per-project scoping
|
||||
|
||||
## Execution
|
||||
|
||||
### If `--global` flag is provided:
|
||||
|
||||
1. Set `global_search: true` in `~/.mem0/settings.json` using the Bash tool:
|
||||
|
||||
```bash
|
||||
python3 -c "
|
||||
import json, os
|
||||
settings_file = os.path.expanduser('~/.mem0/settings.json')
|
||||
settings = {}
|
||||
if os.path.isfile(settings_file):
|
||||
with open(settings_file) as f:
|
||||
settings = json.load(f)
|
||||
settings['global_search'] = True
|
||||
with open(settings_file, 'w') as f:
|
||||
json.dump(settings, f, indent=2)
|
||||
print('Global search enabled')
|
||||
"
|
||||
```
|
||||
|
||||
2. Print:
|
||||
```
|
||||
Global search enabled.
|
||||
Searches now return all memories across all users and projects.
|
||||
Writes still use the current user_id and app_id.
|
||||
Restart the session for the change to take effect.
|
||||
```
|
||||
|
||||
### If `--no-global` flag is provided:
|
||||
|
||||
1. Set `global_search: false` in `~/.mem0/settings.json` using the Bash tool:
|
||||
|
||||
```bash
|
||||
python3 -c "
|
||||
import json, os
|
||||
settings_file = os.path.expanduser('~/.mem0/settings.json')
|
||||
settings = {}
|
||||
if os.path.isfile(settings_file):
|
||||
with open(settings_file) as f:
|
||||
settings = json.load(f)
|
||||
settings['global_search'] = False
|
||||
with open(settings_file, 'w') as f:
|
||||
json.dump(settings, f, indent=2)
|
||||
print('Global search disabled')
|
||||
"
|
||||
```
|
||||
|
||||
2. Print:
|
||||
```
|
||||
Global search disabled.
|
||||
Searches now return only memories scoped to the current project.
|
||||
Restart the session for the change to take effect.
|
||||
```
|
||||
|
||||
### If a project name is provided (no flags):
|
||||
|
||||
1. If no project name was given, ask: "What project_id should this directory use?"
|
||||
|
||||
2. Write the mapping to `~/.mem0/project_map.json` using the Bash tool:
|
||||
|
||||
```bash
|
||||
python3 -c "
|
||||
import json, os
|
||||
map_file = os.path.expanduser('~/.mem0/project_map.json')
|
||||
mapping = {}
|
||||
if os.path.isfile(map_file):
|
||||
with open(map_file) as f:
|
||||
mapping = json.load(f)
|
||||
mapping[os.getcwd()] = '<PROJECT_NAME>'
|
||||
os.makedirs(os.path.dirname(map_file), exist_ok=True)
|
||||
with open(map_file, 'w') as f:
|
||||
json.dump(mapping, f, indent=2)
|
||||
print(f'Mapped {os.getcwd()} -> <PROJECT_NAME>')
|
||||
"
|
||||
```
|
||||
|
||||
(Replace `<PROJECT_NAME>` with the user's chosen project name.)
|
||||
|
||||
3. Verify by searching for existing memories:
|
||||
- Call `search_memories` with `query="project"`, `filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<PROJECT_NAME>"}]}`, `top_k=1`
|
||||
|
||||
4. Print:
|
||||
```
|
||||
Switched to project <PROJECT_NAME>.
|
||||
<N> memories found for this project.
|
||||
Note: This override persists across sessions for this directory.
|
||||
```
|
||||
|
||||
## Output formatting
|
||||
|
||||
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like **bold**, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.
|
||||
@@ -0,0 +1,156 @@
|
||||
---
|
||||
name: tour
|
||||
description: Browses all stored memories grouped by category with full content display. Use when reviewing all project memories, exploring stored knowledge, onboarding to a project, or getting an overview of captured decisions, conventions, and learnings.
|
||||
---
|
||||
|
||||
# Mem0 Project Tour
|
||||
|
||||
Show the user what mem0 has stored for the current project.
|
||||
|
||||
## Cross-project mode
|
||||
|
||||
When invoked with `--all-projects` (e.g., `/mem0:tour --all-projects` or
|
||||
`/mem0:tour --all-projects auth middleware`), search across ALL projects:
|
||||
|
||||
1. Call `get_memories` with `filters={"AND": [{"user_id": "<active_user_id>"}]}`, `page_size=200` — **no `app_id` filter**.
|
||||
2. If a search query was also provided, run `search_memories` with `query=<query>`,
|
||||
`filters={"AND": [{"user_id": "<active_user_id>"}]}`, `top_k=20` — again no `app_id`.
|
||||
3. Group results by `app_id` first, then by category within each project.
|
||||
4. Display:
|
||||
```
|
||||
## <app_id_1> (<N> memories) ← current
|
||||
**Architecture Decisions** — <memory content>
|
||||
...
|
||||
|
||||
## <app_id_2> (<N> memories)
|
||||
...
|
||||
|
||||
<N> memories across <M> projects
|
||||
```
|
||||
5. Mark the current project with `← (current)` in the heading.
|
||||
|
||||
If `--all-projects` is NOT present, use the standard single-project flow below.
|
||||
|
||||
## Peek mode (compact search)
|
||||
|
||||
When `/mem0:tour` receives a search query argument (e.g., `/mem0:tour auth middleware`)
|
||||
WITHOUT `--all-projects`, run in **peek mode** — compact one-liner results:
|
||||
|
||||
1. Run 2 parallel `search_memories` calls:
|
||||
- Broad: `query=<query>`, `filters={"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}]}`, `top_k=10`, `rerank=true`
|
||||
- Targeted: `query=<query>`, `filters={"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}, {"metadata": {"type": "decision"}}]}`, `top_k=5`, `rerank=true`
|
||||
2. Deduplicate by ID, display compact results:
|
||||
```
|
||||
## mem0 search: "<query>" (<N> results)
|
||||
|
||||
1. [decision] Auth module uses JWT with RS256 keys (2025-05-15) [mem0:a3f8b2c1]
|
||||
2. [anti_pattern] Don't use symmetric HS256 — leaked in env (2025-05-10) [mem0:7e2d9f4a]
|
||||
3. [convention] All middleware in src/middleware/ (2025-05-08) [mem0:c4d5e6f7]
|
||||
```
|
||||
Format: `<number>. [<type>] <content, 80 chars> (<date>) [mem0:<short_id>]`
|
||||
3. If no results: `No memories matching "<query>" for project <project_id>.`
|
||||
|
||||
If no query argument and no `--all-projects` flag, use the full tour flow below.
|
||||
|
||||
## Execution
|
||||
|
||||
### Step 1: Fetch ALL memories for this project
|
||||
|
||||
Call `get_memories` to fetch all memories for this project:
|
||||
|
||||
`filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<active_project_id>"}]}`, `page_size=100`
|
||||
|
||||
### Step 2: Run supplementary semantic searches
|
||||
|
||||
In parallel, run these `search_memories` calls to get relevance-ranked results for key topics:
|
||||
|
||||
- `query="architecture decisions design choices"`, `filters={"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}]}`, `top_k=10`, `rerank=true`
|
||||
- `query="bugs errors failures anti-patterns"`, `filters={"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}]}`, `top_k=10`, `rerank=true`
|
||||
- `query="project setup tooling conventions preferences"`, `filters={"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}]}`, `top_k=10`, `rerank=true`
|
||||
|
||||
**Do NOT filter by `metadata.type` in these calls.** The platform auto-assigns `categories` — filtering on `metadata.type` misses memories that were auto-categorized but don't have an explicit `metadata.type`.
|
||||
|
||||
### Step 3: Merge and group
|
||||
|
||||
Merge all results by memory ID (deduplicate). For each memory, determine its group using this priority:
|
||||
|
||||
1. **Platform `categories` field** (array on each memory, auto-assigned by Mem0). Use the first category value.
|
||||
2. **`metadata.type` field** (if present, set explicitly by hooks/agent). Use as fallback if no `categories`.
|
||||
3. **"other"** bucket for memories with neither.
|
||||
|
||||
Map category names to display names:
|
||||
|
||||
| Platform category / metadata.type | Display name |
|
||||
|---|---|
|
||||
| `architecture decisions`, `architecture_decisions`, `decision` | Architecture Decisions |
|
||||
| `anti patterns`, `anti_patterns`, `anti_pattern` | Anti-Patterns |
|
||||
| `task learnings`, `task_learnings`, `task_learning` | Task Learnings |
|
||||
| `coding conventions`, `coding_conventions`, `convention` | Coding Conventions |
|
||||
| `user preferences`, `user_preferences`, `user_preference` | User Preferences |
|
||||
| `project profile`, `project_profile` | Project Profile |
|
||||
| `tooling setup`, `tooling_setup`, `environmental` | Tooling & Setup |
|
||||
| `technology`, `professional_details` | Tooling & Setup |
|
||||
| `session_state` | Session State |
|
||||
| `compact_summary` | Compact Summaries |
|
||||
| anything else | Other |
|
||||
|
||||
### Step 4: Display results
|
||||
|
||||
Sort groups by descending memory count. Display in compact tabular format:
|
||||
|
||||
First show the category summary table:
|
||||
|
||||
```
|
||||
mem0 tour
|
||||
|
||||
Session (ses_abc123) branch: main
|
||||
Project: my-project - 349 memories
|
||||
|
||||
Category Count
|
||||
-----------------------------------------
|
||||
tooling_setup 119
|
||||
bug_fixes 78
|
||||
architecture_decisions 32
|
||||
task_learnings 14
|
||||
...
|
||||
```
|
||||
|
||||
Then for each category (sorted by count descending), show memories as numbered one-liners. Truncate each memory to 100 chars max:
|
||||
|
||||
```
|
||||
tooling_setup (119)
|
||||
1. User requires that no git commit or push be performed without explicit permission...
|
||||
2. OpenCode plugins are loaded from ~/.config/opencode/plugins/ for global installation...
|
||||
3. Assistant determined that the symlink method for loading the Mem0 plugin was failing...
|
||||
... and 116 more
|
||||
|
||||
bug_fixes (78)
|
||||
1. Fixed getAll filter format from flat object to AND-wrapped array for mem0ai TS SDK v3...
|
||||
2. Root cause of user_id mismatch: plugin derived kartik.labhshetwar from git email...
|
||||
... and 76 more
|
||||
```
|
||||
|
||||
Show top 5 memories per category by recency. If a group has more than 5, note `... and <N> more`.
|
||||
|
||||
Skip empty groups entirely.
|
||||
|
||||
### Step 5: Print totals
|
||||
|
||||
```
|
||||
<N> memories across <M> categories
|
||||
project: <project_id> branch: <active_branch>
|
||||
|
||||
Identity - user: <user_id> project: <project_id> branch: <branch>
|
||||
```
|
||||
|
||||
### Step 6: Empty state
|
||||
|
||||
If zero memories found for this project, print:
|
||||
```
|
||||
No memories stored yet for project <project_id>.
|
||||
Run /mem0-onboard to import project files, or start working - mem0 captures learnings automatically.
|
||||
```
|
||||
|
||||
## Output formatting
|
||||
|
||||
IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim - markdown like **bold**, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.
|
||||
@@ -0,0 +1,14 @@
|
||||
{
|
||||
"$schema": "https://opencode.ai/config.json",
|
||||
"plugin": ["@mem0/opencode-plugin"],
|
||||
"mcp": {
|
||||
"mem0": {
|
||||
"type": "remote",
|
||||
"url": "https://mcp.mem0.ai/mcp/",
|
||||
"headers": {
|
||||
"Authorization": "Token {env:MEM0_API_KEY}"
|
||||
},
|
||||
"oauth": false
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,71 @@
|
||||
{
|
||||
"name": "@mem0/opencode-plugin",
|
||||
"version": "0.1.3",
|
||||
"type": "module",
|
||||
"description": "Mem0 persistent memory plugin for OpenCode — add, search, and manage memories across sessions",
|
||||
"main": "dist/index.js",
|
||||
"types": "dist/index.d.ts",
|
||||
"exports": {
|
||||
".": {
|
||||
"types": "./dist/index.d.ts",
|
||||
"import": "./dist/index.js"
|
||||
}
|
||||
},
|
||||
"bin": {
|
||||
"mem0-opencode": "./cli.ts"
|
||||
},
|
||||
"publishConfig": {
|
||||
"access": "public"
|
||||
},
|
||||
"license": "Apache-2.0",
|
||||
"keywords": [
|
||||
"opencode",
|
||||
"opencode-plugin",
|
||||
"mem0",
|
||||
"memory",
|
||||
"mcp",
|
||||
"ai-memory",
|
||||
"persistent-memory"
|
||||
],
|
||||
"repository": {
|
||||
"type": "git",
|
||||
"url": "https://github.com/mem0ai/mem0",
|
||||
"directory": "integrations/mem0-plugin/.opencode-plugin"
|
||||
},
|
||||
"files": [
|
||||
"dist",
|
||||
"cli.ts",
|
||||
"opencode.json",
|
||||
"LICENSE",
|
||||
"opencode-skills"
|
||||
],
|
||||
"scripts": {
|
||||
"build": "bun build opencode-mem0.ts --outdir dist --target bun --format esm --entry-naming index.[ext] && tsc --emitDeclarationOnly --outDir dist --declaration",
|
||||
"dev": "bun build opencode-mem0.ts --outdir dist --target bun --format esm --entry-naming index.[ext] --watch",
|
||||
"type-check": "tsc --noEmit",
|
||||
"prepack": "bun run build",
|
||||
"postpack": ""
|
||||
},
|
||||
"opencode": {
|
||||
"type": "plugin",
|
||||
"hooks": [
|
||||
"chat.message",
|
||||
"tool.execute.before",
|
||||
"tool.execute.after",
|
||||
"experimental.chat.messages.transform",
|
||||
"experimental.session.compacting",
|
||||
"shell.env"
|
||||
]
|
||||
},
|
||||
"dependencies": {
|
||||
"@opencode-ai/plugin": "^1.0.162",
|
||||
"mem0ai": "^3.0.5"
|
||||
},
|
||||
"devDependencies": {
|
||||
"bun-types": ">=1.3.14",
|
||||
"typescript": "^5.7.3"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"bun": ">=1.0.0"
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,20 @@
|
||||
{
|
||||
"compilerOptions": {
|
||||
"target": "ESNext",
|
||||
"module": "ESNext",
|
||||
"moduleResolution": "bundler",
|
||||
"declaration": true,
|
||||
"declarationDir": "dist",
|
||||
"outDir": "dist",
|
||||
"rootDir": ".",
|
||||
"strict": true,
|
||||
"esModuleInterop": true,
|
||||
"skipLibCheck": true,
|
||||
"lib": ["ESNext"],
|
||||
"types": ["bun-types"],
|
||||
"noEmit": false,
|
||||
"emitDeclarationOnly": true
|
||||
},
|
||||
"include": ["**/*"],
|
||||
"exclude": ["node_modules", "dist"]
|
||||
}
|
||||
@@ -0,0 +1,370 @@
|
||||
# Changelog
|
||||
|
||||
All notable changes to the Mem0 plugin will be documented in this file.
|
||||
|
||||
## 0.2.9 — File-context injection, session summaries & activity timeline
|
||||
|
||||
### Added
|
||||
|
||||
- **File-context injection (`PreToolUse/Read` hook):** Before Claude reads a file, the new `on_file_read.sh` hook searches mem0 for memories that reference that file path and injects a compact timeline of prior work as `additionalContext`. Gives Claude "I've seen this file before and here's what I remember" context automatically. Gates on file size (>= 1,500 bytes), 5-second hard timeout, silent skip on any failure. Applies to Claude Code, Codex, and Cursor (`on_file_read_cursor.sh`).
|
||||
- **Stop hook session summary (`on_stop.sh`):** On session end, parses the transcript JSONL, extracts the last assistant message and files touched, builds a structured prompt, and stores it via the mem0 API with `infer=True` — letting the platform's backend AI extract structured facts (request, decisions, learnings, next steps). Memories are stored as `metadata.type=session_summary` with 90-day expiry. Guards: skips subagent sessions (`agent_id` present), dedup via marker file, always exits 0. Applies to Claude Code, Codex, and Cursor (`on_stop_cursor.sh`).
|
||||
- **SessionStart activity timeline (`session_timeline.py`):** On startup (when project has existing memories), fetches the 10 most recent memories and renders a compact timeline with type icons, age indicators, and short text below the existing banner. Shows recent decisions, bug fixes, and session summaries at a glance. 5-second timeout — if the API is slow, the timeline silently skips while the banner still displays.
|
||||
- **`scripts/file_context.py`:** Core Python module for file-context injection. Searches mem0 cloud API with both relative and absolute file paths, deduplicates results, formats as compact timeline with type icons and memory age.
|
||||
- **`scripts/capture_session_summary.py`:** Core Python module for Stop hook. Reads transcript JSONL (tail 3,000 lines), extracts last assistant message, extracts file paths from tool_input fields, strips system tags and `<private>` blocks, stores via mem0 API.
|
||||
- **`scripts/session_timeline.py`:** Core Python module for SessionStart timeline. Fetches recent memories from mem0 API, formats with type icons, relative age, and short text.
|
||||
|
||||
### Changed
|
||||
|
||||
- **`on_session_start.sh`:** On startup (when memories > 0), calls `session_timeline.py` to inject a compact recent activity timeline below the existing banner and rubric instructions.
|
||||
- **`hooks/hooks.json`:** Added `PreToolUse` matcher for `Read` (5s timeout) and `Stop` hook (30s timeout).
|
||||
- **`hooks/codex-hooks.json`:** Added `PreToolUse` matcher for `Read` (5s timeout) and `Stop` hook (30s timeout).
|
||||
- **`hooks/cursor-hooks.json`:** Added `preToolUse` matcher for `Read` (5s timeout) and `stop` hook (30s timeout).
|
||||
|
||||
## 0.2.8 — Automatic coding categories & global search
|
||||
|
||||
### Added
|
||||
|
||||
- **Global search mode (`global_search` setting):** New `global_search` toggle in `~/.mem0/settings.json` (default: `false`). When enabled, `search_memories` and `get_memories` calls use `{"OR": [{"user_id": "*"}]}` instead of the per-user per-project `AND` filter — returning all memories across all users and all `app_id` scopes in the platform project. Writes (`add_memory`) still tag with the current `user_id` and `app_id`. Solves the team-shared-memory use case where multiple team members need access to all memories regardless of which repo or user created them. Works on Claude Code, Cursor, and Codex.
|
||||
- **`/mem0:switch-project --global` / `--no-global`:** Enables or disables global search via the switch-project skill. Persists to `~/.mem0/settings.json`. No manual config editing needed.
|
||||
- **Session banner scope indicator:** Banner shows `scope=global` when global search is active instead of `project=<app_id>`.
|
||||
- **Global-aware memory count:** Session start memory count query uses the global filter when `global_search` is enabled.
|
||||
- **Background coding-category setup (`scripts/auto_setup_categories.py`):** The coding-focused category taxonomy (17 categories tuned for development work) is now installed automatically in the background on session start — the same way `auto_import.py` imports `CLAUDE.md`/`AGENTS.md`. Users are no longer asked to configure it during onboarding. Mirrors the auto-import design: resolves the API key, holds a lock file (`~/.mem0/categories_setup.lock`), reuses the proven `setup_coding_categories.py` taxonomy + `project.update` path via the plugin venv, logs to stderr only, and always exits 0 so it can never block a session.
|
||||
- **Per-account state gating (`~/.mem0/categories_setup.json`):** Keyed by a hash of the API key → a hash of the taxonomy. Categories are scoped to the mem0 project tied to the API key (not the local repo), so setup runs once per account and skips all network calls thereafter — re-applying only if the taxonomy itself changes.
|
||||
- **`tests/test_auto_setup_categories.py`:** Covers fingerprint determinism/sensitivity, state-file load/save/gating, and idempotent apply via an injected fake client (no SDK, no network).
|
||||
|
||||
### Changed
|
||||
|
||||
- **`on_session_start.sh`:** Spawns `auto_setup_categories.py` in the background on `startup` (alongside `auto_import.py`), preferring the venv python so the SDK is available. Covers Claude Code, Cursor, and Codex, which all route SessionStart through this script.
|
||||
- **`/mem0:onboard` Step 5 is no longer interactive:** Removed the `Install coding categories? [Y/n]` prompt. Categories now configure automatically in the background; the onboarding step only verifies status and applies them if the background run hasn't finished yet — mirroring how Step 4 (project-file import) already works.
|
||||
- **Session-start "new project" hint** now notes that coding categories install automatically in the background.
|
||||
|
||||
## 0.1.0 — Antigravity
|
||||
|
||||
### Added
|
||||
|
||||
- **Antigravity plugin** (`.antigravity/`): Restructured to follow the same shared-infrastructure pattern as Claude Code, Cursor, and Codex. Self-contained plugin directory with `plugin.json`, `mcp_config.json`, `hooks/hooks.json` (own file), `scripts/` (symlink → `../scripts/`), and `skills/` (symlink → `../skills/`). Installable via `agy plugin install .antigravity` or `npx degit mem0ai/mem0/mem0-plugin/.antigravity ~/.gemini/config/plugins/mem0`. Uses `contextFileName: "AGENTS.md"` per Antigravity convention.
|
||||
- **Codex hooks parity:** Added missing `PreToolUse` Write/Edit/MultiEdit block and `PreCompact` hook to Codex hooks config, bringing it to full parity with Claude Code.
|
||||
|
||||
### Changed
|
||||
|
||||
- **Antigravity plugin directory:** Renamed `.antigravity-plugin/` → `.antigravity/` to match the naming convention of `.claude-plugin/`, `.cursor-plugin/`, `.codex-plugin/`. Plugin is now self-contained so `agy plugin install` and `npx degit` both work.
|
||||
- **Antigravity hooks:** Hooks now live directly in `.antigravity/hooks/hooks.json` as a standalone file — no indirection.
|
||||
- **Antigravity install command:** Updated from `npx degit mem0ai/mem0/mem0-plugin` to `npx degit mem0ai/mem0/mem0-plugin/.antigravity`. Added `agy plugin install` as alternative for local clones.
|
||||
|
||||
### Removed
|
||||
|
||||
- **Stale root-level files:** Deleted `mem0-plugin/hooks.json`, `mem0-plugin/mcp_config.json`, `mem0-plugin/plugin.json` — leftover artifacts from before plugin restructuring into per-editor subdirectories. Nothing referenced them; install commands point to `.antigravity/`.
|
||||
|
||||
## 0.2.7
|
||||
|
||||
### Fixed
|
||||
|
||||
- **First-install auth failure (closes #4876):** Removed `authorizationUrl` from `.mcp.json`. When both a static `Authorization` header and `authorizationUrl` were present, Claude Code preferred the OAuth flow, which failed on reconnect — leaving new users stuck with only `authenticate`/`complete_authentication` stub tools. Authentication now uses the `MEM0_API_KEY` header exclusively; no browser OAuth flow is triggered.
|
||||
- **Onboarding skill removed OAuth step:** `/mem0:onboard` Step 2 no longer guides users through a browser-based OAuth login. The MCP server authenticates via the API key set in Step 1.
|
||||
- **Removed `claude plugin configure mem0` references:** This CLI command does not exist. The `userConfig` mechanism works through the plugin enable UI prompt — Claude Code prompts for the API key when the plugin is first enabled and stores it securely in the system keychain. Updated session start banner, onboarding skill, identity script comments, and manual testing guide.
|
||||
|
||||
## 0.2.6
|
||||
|
||||
### Fixed
|
||||
|
||||
- **Memory count zero / stats and tour showing 0 memories:** The `run_id: "*"` wildcard filter — added in the initial v0.2.6 fix — returns 0 on both the v3 list endpoint (`/v3/memories/`) and search endpoint (`/v3/memories/search/`) when memories were written without a `run_id` (which is all memories since v0.2.6 stopped setting `run_id` on `add_memory`). Removed `run_id: "*"` from: `on_session_start.sh` count queries, `enforce_metadata_defaults.sh` hook injection (was injecting into every `search_memories` and `get_memories` call), `_search.py` search payload, `/mem0:stats` and `/mem0:tour` skill instructions. All read paths now use simple `user_id` + `app_id` filters without `run_id`, matching how v0.2.3 worked.
|
||||
- **`add_memory` no longer sets `run_id`:** Session tracking moved from top-level `run_id` (which creates a separate API partition) to `metadata.session_id`. New memories land in the default partition and are visible to all queries.
|
||||
- **`enforce_metadata_defaults.sh` no longer injects `run_id`:** The hook was appending `{"run_id": "*"}` to every `search_memories` and `get_memories` filter, which broke both endpoints. Removed entirely — identity injection (`user_id`/`app_id`) still works.
|
||||
- **`_search.py` simplified:** Removed `run_id: "*"` from search payload. Uses plain `user_id` + `app_id` filters.
|
||||
- **`auto_import.py` delete endpoint 404:** Stale chunk deletion used `DELETE /v3/memories/{id}/` which returns 404 (v3 is ADD-only). Changed to `DELETE /v1/memories/{id}/`.
|
||||
- **Banner count accurate:** `on_session_start.sh` count query uses `user_id` + `app_id` filters without `run_id`. Shows total count only (removed noisy auto-import breakdown).
|
||||
- **`quickstart.md` wrong add endpoint:** cURL example used `POST /v1/memories/` (v1 add is removed). Fixed to `POST /v3/memories/add/`.
|
||||
- **Session stats always 0:** PostToolUse hooks never fire for plugin MCP tools (confirmed via debug logs — only SessionStart, UserPromptSubmit, PreToolUse, and Stop fire). Moved session stats tracking (`session_stats.py add/search`) into `enforce_metadata_defaults.sh` (PreToolUse), which does fire on every MCP tool call.
|
||||
- **Periodic nudge never firing:** Message count file used session UUID in filename (`/tmp/mem0_msg_count_${SESSION_ID}`) which was cleared on session start. Changed to `$USER`-keyed filename, matching the session stats file convention.
|
||||
- **`/mem0:stats` session query returning 0:** Stats skill attempted API queries with `run_id` and `metadata.session_id` filters that return empty results. Session stats now come exclusively from the local stats file (which is accurate now that PreToolUse tracks adds).
|
||||
- **Auto-capture stops working mid-session:** After the initial rubric injection (first message), subsequent messages got zero context from the UserPromptSubmit hook. The banner instruction to "proactively store learnings" fades as conversation grows and Claude forgets. Two-pronged fix: (1) **Direct API auto-capture hook** (`auto_capture.py`): every 3rd message, `on_user_prompt.sh` spawns a background Python script that reads the last 3 exchanges from the transcript JSONL and sends them directly to `POST /v3/memories/add/` with `infer=True`. No reliance on Claude calling `add_memory`. (2) **Proportional prompt nudge** as fallback: starting from 3rd message, if Claude has stored fewer than 1 memory per 3 messages, a brief "store learnings via add_memory" directive is injected.
|
||||
- **Desktop app: API key not found:** Claude Code Desktop does not inherit shell environment variables — only `PATH` is read from shell profiles. Users who set `export MEM0_API_KEY=m0-...` in `~/.zshrc` or `~/.bashrc` got "Setup Required" on Desktop while CLI worked fine. Added grep-based shell profile extraction as a 4th fallback in both `_identity.sh` (bash) and `_identity.py` (Python). Scans `~/.zshrc`, `~/.bashrc`, `~/.zprofile`, `~/.bash_profile`, `~/.profile` for `MEM0_API_KEY=` assignments. Skips variable references (`$OTHER_VAR`), commented-out lines, and strips quotes/inline comments.
|
||||
- **Desktop app: zero memories added over multi-day usage:** Agent never proactively called `add_memory` — only `search_memories` and `get_all`. Root cause: session banner instruction was passive ("before finishing a session, store learnings") and easily ignored. No mechanism existed to re-prompt the agent mid-session. Fixed with a periodic nudge in `on_user_prompt.sh`: every 5th substantial message, the hook checks `session_stats` for add count; if fewer than 2 memories stored, injects a directive into Claude's context via `additionalContext` telling it to store learnings immediately. Counter resets on session start.
|
||||
- **Setup Required banner missing Desktop instructions:** Updated no-API-key banner with Desktop-specific setup paths: `claude plugin configure mem0`, Desktop app environment editor (Settings > Environment), and CLI `export` as fallback.
|
||||
|
||||
### Removed
|
||||
|
||||
- **Stop hook (all 3 editors):** Removed from `hooks.json`, `cursor-hooks.json`, `codex-hooks.json`. Deleted `on_stop.sh`, `on_stop_cursor.sh`, `on_stop_codex.sh`, `stop_hook_check.py`. The Stop hook could not reliably feed context back to Claude (command-type hooks' `reason` field is user-facing only, not injected into Claude's context). Auto-capture handled by PreCompact hook instead.
|
||||
- **SessionEnd hook:** Removed from `hooks.json`. Deleted `on_session_end.sh`. Redundant with PreCompact auto-capture.
|
||||
- **5 redundant hook scripts:** `on_git_commit_capture.sh` (fired on every Bash command containing "git"), `on_post_commit.sh` (fired on every Bash command), `on_task_completed.sh`, `on_post_compact.sh`, `on_subagent_stop.sh`. These were already removed from Claude's `hooks.json` in v0.2.5 but script files remained on disk. Also removed `on_post_commit.sh` references from `cursor-hooks.json` and `codex-hooks.json`.
|
||||
- **Dead settings:** Removed `output_style`, `skip_tools`, `capture_tools` from `load_settings.py` defaults. The `output-styles/` directory and `on_tool_failure.sh` script were already deleted.
|
||||
- **`test_on_file_read.py`:** Removed test file for deleted `on_file_read.sh` hook.
|
||||
|
||||
### Changed
|
||||
|
||||
- **`/mem0:stats` lifetime query:** Single `get_memories` call with `user_id` + `app_id` filters (no `run_id`).
|
||||
- **`/mem0:tour` full fetch:** Single `get_memories` call with `user_id` + `app_id` filters (no `run_id`).
|
||||
- **API key resolution order (4 fallbacks):** `MEM0_API_KEY` env var > `CLAUDE_PLUGIN_OPTION_API_KEY` (plugin configure) > `CLAUDE_PLUGIN_OPTION_MEM0_API_KEY` (legacy userConfig) > shell profile extraction. Applies to both `_identity.sh` and `_identity.py`.
|
||||
- **Session start banner:** Proactive memory instruction changed from passive "before finishing a session" to active "proactively store learnings incrementally as work progresses. Do NOT wait until the session ends."
|
||||
- **Message counter on session start:** `on_session_start.sh` now resets `/tmp/mem0_msg_count_*` files to ensure nudge counter starts fresh each session.
|
||||
|
||||
## 0.2.5
|
||||
|
||||
### Fixed
|
||||
|
||||
- **PostToolUse field name: `tool_output` → `tool_response`:** All three PostToolUse scripts (`on_bash_output.sh`, `on_post_commit.sh`, `on_post_tool_use.sh`) were reading `.tool_output` from stdin JSON — a field that never existed in the Claude Code hooks spec. The correct field is `.tool_response` (confirmed via official docs at code.claude.com/docs/en/hooks). This was silently `null` on every invocation, meaning bash error detection and post-commit checks never actually fired.
|
||||
- **Stop hook invalid `hookSpecificOutput`:** `on_stop.sh` returned `hookSpecificOutput` with `hookEventName: "Stop"` — but `Stop` is not a valid `hookEventName` discriminant. Claude Code rejected the JSON with "Hook JSON output validation failed". Replaced with spec-compliant `{ decision: "block", reason: "..." }`.
|
||||
- **SessionStart banner invisible:** Switched from JSON `hookSpecificOutput.additionalContext` (discrete/hidden system reminder) back to raw text `cat <<BANNER` (shown directly in transcript). Per official docs, raw stdout from SessionStart hooks is visible context; `additionalContext` is not.
|
||||
- **`Write|Edit` matcher missing `MultiEdit`:** `block_memory_write.sh` could be bypassed via `MultiEdit` tool. Matcher now `Write|Edit|MultiEdit`.
|
||||
- **PreToolUse MCP matcher coverage gap:** `enforce_metadata_defaults.sh` not triggered for `get_memory` or `update_memory`. Added 4 tool name variants.
|
||||
- **`capture_compact_summary.py` never called:** `on_session_start.sh` compact branch never spawned it. Post-compaction summaries were not stored. Added background spawn.
|
||||
- **Unguarded variables under `set -u` in `on_session_start.sh`:** Bare `${MEM0_RESOLVED_USER_ID}` etc. without `:-` fallbacks. Script died silently if `_identity.sh` failed to source. All references now use `${VAR:-default}`.
|
||||
- **`enforce_metadata_defaults.sh` silent failure on jq error:** Final `jq -n --argjson` had no error guard under `set -euo pipefail`. Added `|| true`.
|
||||
- **Single-quote injection in `on_git_commit_capture.sh`:** Shell variables interpolated via `'$VAR'` inside `python3 -c`. Filenames with `'` broke Python syntax. Replaced with `os.environ.get()`.
|
||||
- **Identity injection on `add_memory` (`enforce_metadata_defaults.sh`):** Hook now sources `_identity.sh` and injects `user_id` and `app_id` as top-level params when the agent omits them. Prevents orphaned memories with null scoping that were invisible to filtered queries. Root cause of onboarding writes landing with `user_id=null, app_id=null`.
|
||||
- **Identity injection on `search_memories` and `get_memories`:** Hook now intercepts these tools and injects `user_id`/`app_id` into `filters.AND[]` when missing. Handles three filter states: no filters (creates from scratch), flat filters (converts to AND format), existing AND array (appends missing clauses). Prevents MCP server from auto-injecting wrong identity.
|
||||
- **Identity injection on `delete_all_memories`:** Hook injects top-level `user_id`/`app_id` to prevent accidental cross-scope deletion.
|
||||
- **`/mem0:export` incorrect `get_memories` call:** Was passing `user_id`/`app_id` as top-level params; MCP tool only accepts them inside `filters`. Changed to `filters={"AND": [{"user_id": "..."}, {"app_id": "..."}]}`.
|
||||
- **`/mem0:stats` same `get_memories` issue:** Fixed both lifetime and session stat queries to use `filters` instead of top-level identity params.
|
||||
- **`/mem0:pin` passes `metadata` to `update_memory`:** MCP `update_memory` tool only accepts `memory_id`, `text`, `source` — no `metadata` param. Pin/unpin now uses `[PINNED]` text prefix marker instead. Also added explicit `user_id`/`app_id` to `add_memory` for new pinned memories.
|
||||
- **`/mem0:health --deep` ambiguous `get_memories` call:** Clarified identity goes in `filters`, not as top-level params.
|
||||
- **`/mem0:memory-reviewer` same ambiguity:** Explicit `filters={"AND": [...]}` for `get_memories`.
|
||||
- **`/mem0:dream` stale artifact:** Removed `(item 15)` from Step 4 heading.
|
||||
- **`/mem0:dream` contradiction resolution no-op:** `update_memory` on loser with its own text did nothing. Changed to `delete_memory(memory_id=<loser_id>)` to actually remove the losing memory.
|
||||
- **`/mem0:health` Check 3 `search_memories` top-level `user_id`:** Removed top-level `user_id` param; identity only in `filters.AND[]`. Changed `limit` to `top_k`.
|
||||
- **`/mem0:health` Check 4 `add_memory` missing `infer=False`:** Health probe wasted LLM tokens on extraction. Added `infer=False`. Also fixed: was expecting `memory_id` in response but v3 returns `event_id`. Now uses `get_event_status` to get memory ID for cleanup.
|
||||
- **`/mem0:tour` `get_memories` top-level identity:** Both standard and cross-project modes passed `user_id`/`app_id` as top-level params. Moved to `filters.AND[]`.
|
||||
- **`/mem0:onboard` `search_memories` top-level `user_id`:** Removed extra top-level `user_id` param from connectivity check.
|
||||
- **`/mem0:context-loader` incomplete filter table:** Filter examples showed only `metadata.type` without `user_id`/`app_id`. Now shows full `AND` filter structure.
|
||||
- **7 skills used `limit` instead of `top_k` for `search_memories`:** MCP tool param is `top_k`, not `limit`. Fixed in: health, onboard, tour (3 places), switch-project, stats (weekly mode + latency probe).
|
||||
- **`/mem0:stats` latency probe missing `filters`:** `search_memories` call had no identity filters. Added `user_id`/`app_id` in `filters.AND[]`.
|
||||
|
||||
### Added
|
||||
|
||||
- **`stop_hook_check.py`:** Pure-stdlib transcript analyzer for the Stop hook. Reads last 500 lines of transcript JSONL, parses tool calls, file modifications, and git commands. Returns `{"should_block": bool, "context": "..."}`. Trivial sessions (< 3 tool calls, no file edits) skip capture entirely.
|
||||
- **Checklist for `/mem0:dream`:** 6-step progress tracker per Claude skill best practices for complex multi-step workflows.
|
||||
- **Checklist for `/mem0:onboard`:** 7-step progress tracker for onboarding wizard.
|
||||
- **Expanded hook matcher (all 3 configs):** `enforce_metadata_defaults.sh` now triggers on `add_memory`, `search_memories`, `get_memories`, `get_memory`, `update_memory`, and `delete_all_memories` (12 tool name variants covering both MCP naming conventions).
|
||||
|
||||
### Changed
|
||||
|
||||
- **Stop hook uses MCP-driven capture:** When meaningful work detected and no memories stored, returns `decision: "block"` asking Claude to call `add_memory` via MCP. One-shot flag prevents infinite loops. REST API capture runs in background as fallback.
|
||||
- **SessionStart banner uses raw text stdout:** Replaced JSON `additionalContext` with `cat <<BANNER` for reliable display per official hooks spec.
|
||||
- **`enforce_metadata_defaults.sh` rewritten:** Handler-based dispatch for 4 tool types. `add_memory` gets top-level identity + metadata defaults. `search_memories`/`get_memories` get filter identity injection. `delete_all_memories` gets top-level identity. Never overrides explicitly-passed identity.
|
||||
|
||||
## 0.2.4
|
||||
|
||||
### Fixed
|
||||
|
||||
- **PostToolUse matcher mismatch (`hooks.json:81`):** Changed from `mcp__mem0__` to `mcp__mem0__|mcp__plugin_mem0_mem0__`. Root cause of session stats recording nothing — 146 consecutive "no memory operations" entries. Unblocks `/mem0:stats` session line, stop-hook report, and `session_stats.py` tracking.
|
||||
- **File-read hook noise (`on_file_read.sh`):** Replaced bare-filename semantic search with `metadata.files` filter + score threshold (≥ 0.4). Falls back to basename search if metadata filter returns nothing. Eliminates irrelevant context injection on every Read.
|
||||
- **`/mem0:pin` uses v3-removed `immutable=True`:** Removed Step 3a entirely. Standardized on `metadata.pinned: true` (which `dream/SKILL.md` already respects during pruning). Fixed unconditional `...` appended to short pin confirmations.
|
||||
- **`/mem0:list-projects` undercounts (implicit null scoping):** Dual-query approach — runs both null-scoped and app-scoped `get_memories` calls, merges by ID. Handles legacy `metadata.project_id` and `metadata.project` fields.
|
||||
- **`/mem0:peek` free-text search on memory IDs:** Detects bare hex IDs (`^[a-f0-9]{8}$`) and `[mem0:<hex>]` citation refs, routes to `get_memory` direct lookup instead of semantic search.
|
||||
- **Dead `PostToolUseFailure` hook block:** Removed entirely — this hook event does not exist in Claude Code.
|
||||
|
||||
### Added
|
||||
|
||||
- **Session ID capture (`on_session_start.sh`):** Extracts `session_id` from Claude Code stdin JSON, persists to `/tmp/mem0_session_id_$USER`. Falls back to timestamp-based ID. Enables `run_id`-based session scoping.
|
||||
- **`run_id` injection (`enforce_metadata_defaults.sh`):** Reads session ID from temp file, injects as `run_id` into every `add_memory` call. Tags all memories with session identity for entity-scoped filtering.
|
||||
- **`min_score`, `metadata_filters`, `rerank`, `threshold` params (`_search.py`):** `search_memories()` now accepts `min_score: float` to filter low-relevance results, `metadata_filters: dict` for field-level filtering, `rerank: bool` for managed reranker, and `threshold: float` (default 0.3, up from platform default 0.1) for server-side relevance gating. Existing callers unaffected (new params have defaults).
|
||||
- **Rerank on tour/peek:** `/mem0:tour` and `/mem0:peek` search calls now pass `rerank=true` for better result ordering (+150–200ms latency, significantly improved precision).
|
||||
- **`/mem0:stats` session query via `run_id`:** Queries memories by `run_id` filter for API-backed session counts. Cross-checks against local stats file. Shows truncated session ID in output.
|
||||
|
||||
### Removed
|
||||
|
||||
- **`/mem0:protocol` skill:** Routing table fully superseded by individual skill descriptions (auto-trigger). Operational guidelines (search patterns, metadata rules) covered by `enforce_metadata_defaults.sh` hook and individual skill bodies.
|
||||
|
||||
### Changed
|
||||
|
||||
- **All 17 skill descriptions:** Rewritten per Claude skill best practices — each now includes what the skill does AND when to trigger it, with specific keywords for auto-discovery. Average length 200–270 chars (under 1024 max). Third person, action verbs.
|
||||
- **Onboarding auto-trigger (`on_session_start.sh`):** Replaced 3-state marker-file logic with memory-count detection. New project (0 memories) → prompts Claude to invoke `/mem0:onboard`. No marker files, no OAuth state. Simplified no-API-key path to single inactive banner.
|
||||
|
||||
## 0.2.3
|
||||
|
||||
### Added
|
||||
|
||||
- **Read hook (`on_file_read.sh`):** `PreToolUse(Read)` hook that searches mem0 for memories tagged with the file being opened and injects them as context. Skips non-code files, lockfiles, and `node_modules/`. Deduplicates repeated reads within a session.
|
||||
- **Shared search module (`_search.py`):** Wraps `POST /v3/memories/search/` into a reusable `search_memories()` call with `format_results_for_context()` for consistent `[type] content [mem0:id]` display. Used by all pre-fetch hooks.
|
||||
- **User settings (`load_settings.py`):** Loads config from `~/.mem0/settings.json` with 9 keys: `auto_save`, `auto_search`, `search_limit`, `retention_session_days`, `confidence_threshold`, `output_style`, `debug`, `skip_tools`, `capture_tools`. Supports `init` subcommand for first-run creation.
|
||||
- **`/mem0:forget` skill:** Standalone skill for deleting memories by search query or UUID with confirmation. Supports undo-last-N via `session_stats.py peek`.
|
||||
- **`/mem0:peek` skill:** Compact quick-search with one-liner output. Runs 2 parallel searches (broad + `decision`-filtered), deduplicates by ID.
|
||||
- **`/mem0:memory-reviewer` skill:** Read-only memory quality audit. Scans for near-duplicates (>60% noun overlap), contradictions, low-confidence entries, untagged memories, and stale entries (>180 days). Refers to `/mem0:dream` for remediation.
|
||||
- **`/mem0:context-loader` skill:** Pre-fetch agent that runs 2–4 parallel `search_memories` calls across query angles and type filters, deduplicates, outputs up to 10 memories. Silent on empty results.
|
||||
- **Compact memory output style (`output-styles/compact-memory.md`):** `[<type>] <content, max 80 chars> [mem0:<short_id>]` format used by `peek`, `tour`, and inline search display.
|
||||
- **`userConfig` in `.claude-plugin/plugin.json`:** `api_key` field (`sensitive: true`) enables key storage via `claude plugin configure mem0`.
|
||||
- **OAuth support:** `authorizationUrl` added to `.mcp.json` for OAuth flow alongside token-based auth.
|
||||
- **Tests:** `test_search.py`, `test_rubric_dedup.py`, `test_on_file_read.py`.
|
||||
|
||||
### Changed
|
||||
|
||||
- **Skills renamed:** All `mem0-*` prefixed skill directories renamed to shorter forms (e.g., `mem0-dream` → `dream`, `mem0-mcp` → `protocol`, `mem0-tour` → `tour`). 12 skills renamed total.
|
||||
- **Pre-fetch on bash errors:** `on_bash_output.sh` now performs actual `search_memories` calls via `_search.py` instead of emitting search query templates as text.
|
||||
- **Session-resume pre-fetch:** `on_user_prompt.sh` detects resume phrases ("where did we leave off", "continue from where") and pre-fetches `session_state` + `decision` memories.
|
||||
- **Remember-intent routing:** `on_user_prompt.sh` detects save phrases ("remember this", "don't forget that") and routes to `/mem0:remember` skill instead of raw `add_memory`.
|
||||
- **Rubric deduplication:** Search guidance rubric injected only on first user prompt per session via flag file.
|
||||
- **Namespace-agnostic tool matching:** `on_post_tool_use.sh` and `on_tool_failure.sh` now use wildcard suffix matching (`*__add_memory`) instead of hardcoded `mcp__mem0__` prefix.
|
||||
- **API key resolution:** `_identity.sh`/`_identity.py` now check `CLAUDE_PLUGIN_OPTION_API_KEY` (from `userConfig`) before legacy `CLAUDE_PLUGIN_OPTION_MEM0_API_KEY`.
|
||||
- **Session start:** Three-state no-key handling (first run → auto-onboard, OAuth mode → proceed, neither → inactive banner). Banner now shows `auth=api_key|oauth`.
|
||||
- **Hook timeouts:** `on_user_prompt.sh` and `on_bash_output.sh` raised from 5s to 12s.
|
||||
- **Compact prompts:** `on_task_completed.sh` and `on_stop.sh` replaced multi-step checklists with single-line directives (0–2 durable facts max).
|
||||
- **`/mem0:dream`:** Removed `--forget` (now standalone `forget` skill) and `--schedule` flags.
|
||||
- **`/mem0:health`:** Removed `--fix` auto-fix mode; output condensed to `PASS/FAIL CheckName Detail` one-liners.
|
||||
- **`/mem0:protocol` (was `mem0-mcp`):** Added 14-entry natural-language-to-skill routing table. _(Removed in 0.2.4 — superseded by skill descriptions.)_
|
||||
- **CLI config fallback removed:** `_identity.sh`/`_identity.py` no longer read `~/.mem0/config.json`; API key resolution is env-var-only.
|
||||
- **`auto_import.py`:** Added content-hash deduplication to skip files with identical content within a single import run.
|
||||
- **All skill descriptions:** Shortened to concise one-liners.
|
||||
|
||||
### Fixed
|
||||
|
||||
- **Namespace-agnostic tool name parsing in `on_tool_failure.sh`:** `${TOOL_NAME##*__}` correctly strips any MCP namespace prefix, not just `mcp__mem0__`.
|
||||
- **`_identity.py`/`_identity.sh`:** `CLAUDE_PLUGIN_OPTION_API_KEY` env var was not checked, causing key-not-found when using `userConfig`.
|
||||
- **Three previously failing tests** (`test_on_file_read.py`, `test_rubric_dedup.py`, `test_write_path.py`) fixed after hook changes.
|
||||
|
||||
### Removed
|
||||
|
||||
- **`/mem0:dream --forget` flag:** Extracted to standalone `forget` skill.
|
||||
- **`/mem0:dream --schedule` flag:** Use Claude Code's built-in `/schedule` command instead.
|
||||
- **`/mem0:health --fix` flag:** Auto-fix mode removed entirely; use `/mem0:dream` for remediation.
|
||||
- **CLI dependency for key management:** All `~/.mem0/config.json` fallback code removed.
|
||||
|
||||
## 0.2.2
|
||||
|
||||
### Fixed
|
||||
|
||||
- **Duplicate memory writes on compaction:** `on_pre_compact.py` was running as both primary and backup capture path. Now reads `session_stats` and skips if agent already stored 2+ memories. `on_stop.sh` and `on_session_end.sh` were both calling `on_pre_compact.py`, creating double captures — removed redundant calls.
|
||||
- **Verbose session-state blobs:** `on_pre_compact.py` `build_content()` was producing 5000+ char structured markdown. Now produces minimal 2-line summary (`Working on:`, `Files touched:`), relying on `infer=True` for extraction.
|
||||
- **Pre-compaction prompt rewrite:** Instruction changed from "store a single large `session_state` blob with `infer=False`" to "store 0–3 durable facts per session (15–50 words each), one per `add_memory` call, tagged by category."
|
||||
- **False-positive error detection:** `on_bash_output.sh` and `on_user_prompt.sh` error grep pattern was too broad, triggering on routine test/linter output. Now uses two-tier approach: high-signal patterns (`Traceback`, `panic:`, `FATAL:`) fire always; lower-signal (`Error:`, `Exception:`) require 2+ occurrences.
|
||||
- **Background `on_pre_commit.py` on every git commit:** `on_git_commit_capture.sh` was storing `commit_context` memories regardless of usefulness. Background call removed; hook now only performs memory search. `on_pre_commit.py` deleted.
|
||||
- **Post-commit prompt always firing:** `on_post_commit.sh` now gated behind `settings.commit_prompts: true` in `mem0.md` (defaults to off).
|
||||
- **Project ID lost after folder rename:** `_project.py` only looked up `project_map.json` by CWD path. Added remote-hash fallback: hashes `git remote.origin.url` to a 16-char key, self-heals map on hit.
|
||||
- **Subagent skip list hardcoded:** `on_subagent_stop.sh` now reads `settings.subagent_skip` from `mem0.md` instead of hardcoded `Explore|Plan`.
|
||||
- **Auto-import missed project-root files:** `auto_import.py` only searched CWD. Added `_git_root()` helper to also search git root when invoked from subdirectory.
|
||||
- **Concurrent `ensure_deps.sh` install race:** Multiple parallel sessions could corrupt the venv. Added lock directory with 60s spin-wait and `.install-failed` sentinel.
|
||||
- **Telemetry `distinct_id` used MD5:** Changed to SHA-256 (truncated 32 chars).
|
||||
- **Telemetry caller props could override system props:** Moved system fields after spread so they always win.
|
||||
- **Plugin version hardcoded in `telemetry.py`:** Replaced with `_load_plugin_version()` reading from `plugin.json`.
|
||||
- **Onboard marker race:** Marker now created in `on_session_start.sh` when prompt is first displayed, not after skill completes.
|
||||
|
||||
### Changed
|
||||
|
||||
- **`capture_compact_summary.py`:** `infer` changed from `False` to `True` so platform can extract structured facts.
|
||||
- **Chunking utilities extracted to `_chunking.py`:** `split_by_headers`, `split_by_hr_or_headers`, `filter_and_truncate` moved from `import_competing_tools.py` to shared module.
|
||||
- **`auto_import.py` now chunks Markdown files:** `.md` files split by `## ` headers before import instead of single blob.
|
||||
- **`enforce_metadata_defaults.sh`:** New `PreToolUse` hook on `add_memory` for all three editors. Injects default metadata (`confidence: 0.7`, `source: "auto_capture"`, `type: "task_learning"`) when agent omits them.
|
||||
- **`mem0.md` Settings section parsing:** `parse_mem0_config.py` now parses `Settings` section; added `--key <dotted.path>` CLI argument for programmatic lookup.
|
||||
- **Project config display condensed:** Session start shows compact summary line instead of raw JSON dump.
|
||||
|
||||
### Added
|
||||
|
||||
- `scripts/_chunking.py` — shared content-chunking utilities.
|
||||
- `scripts/enforce_metadata_defaults.sh` — metadata defaults injection hook.
|
||||
- `parse_mem0_config.py --key` — CLI accessor for individual `mem0.md` config keys.
|
||||
- **Native `MEMORY.md` detection:** `on_session_start.sh` detects Claude Code auto-memory and prompts to disable or run `/mem0:import`.
|
||||
- **`/mem0:list-projects` skill:** Discovers all project `app_id` scopes by paginating `get_memories` without an `app_id` filter.
|
||||
- **`/mem0:tour` cross-project mode** (`--all-projects`) and peek mode (query argument).
|
||||
- **`/mem0:stats` weekly digest mode** (`--weekly`).
|
||||
- **`/mem0:dream --forget` mode:** Search-confirm-delete flow with undo-last-write.
|
||||
- **`/mem0:import --tools` flag:** Import from competing AI tool configs.
|
||||
- `conftest.py` — `_clean_project_map` autouse fixture preventing cross-test pollution.
|
||||
|
||||
### Removed
|
||||
|
||||
- `scripts/on_pre_commit.py` — source of unwanted background writes on every commit.
|
||||
- **`/mem0:digest` skill** — merged into `/mem0:stats --weekly`.
|
||||
- **`/mem0:forget` skill** — merged into `/mem0:dream --forget`.
|
||||
- **`/mem0:import-tools` skill** — merged into `/mem0:import --tools`.
|
||||
- **`/mem0:peek` skill** — merged into `/mem0:tour <query>`.
|
||||
- `tests/test_pre_commit.py` — tests for deleted script.
|
||||
|
||||
## 0.2.1
|
||||
|
||||
### Added
|
||||
|
||||
- **11 new skills:** `/mem0:dream` (memory consolidation), `/mem0:export` (portable YAML-frontmatter export), `/mem0:import` (re-import exported memories), `/mem0:import-tools` (import from Cursor/Copilot/Cline/Continue configs), `/mem0:forget` (delete with confirmation), `/mem0:health` (diagnostic check — API key, MCP connectivity, read/write), `/mem0:peek` (compact quick-search), `/mem0:pin` (mark memory as high-priority), `/mem0:remember` (quick verbatim store with auto-classification), `/mem0:stats` (session + lifetime statistics), `/mem0:digest` (weekly memory summary).
|
||||
- **8 new hook scripts:** `on_bash_output.sh` (scan bash output for errors, surface `anti_pattern`/`bug_fix` memories), `on_git_commit_capture.sh` (detect git commit/merge/rebase, search relevant memories), `on_post_commit.sh` (prompt to save commit learnings), `on_post_compact.sh` (recovery prompt to reload context after compaction), `on_session_end.sh` (last-chance transcript capture with dedup marker), `on_subagent_stop.sh` (remind to capture learnings from non-Explore/Plan subagents), `on_tool_failure.sh` (classify MCP failures as auth/rate-limit/network, suggest recovery), `on_pre_commit.py` (capture staged changes via REST API).
|
||||
- **PostHog telemetry (`telemetry.py`):** Anonymous, fire-and-forget, 10% sampled. Uses stdlib `urllib` (no SDK dependency). Sends event type, platform, plugin version, anonymized identity. Never sends memory content or API keys. Opt-out via `MEM0_TELEMETRY=false`.
|
||||
- **10 new memory categories in `setup_coding_categories.py`:** `dependency_decisions`, `performance_findings`, `security_constraints`, `testing_patterns`, `data_model`, `api_contracts`, `deployment_runbook`, `team_norms`, `domain_glossary`, `experiment_results`.
|
||||
- **Dependency management (`ensure_deps.sh`):** Installs `mem0ai` into persistent venv at `${CLAUDE_PLUGIN_DATA}/venv`. Skips re-install if `requirements.txt` hash unchanged. Runs on `Setup(init|maintenance)` hook and every `SessionStart`.
|
||||
- **Competing tool importer (`import_competing_tools.py`):** Parses and uploads configs from `.cursorrules`, `.github/copilot-instructions.md`, `memory-bank/`, `.continue/rules.md`. Splits by Markdown headers/horizontal rules.
|
||||
- **Export file parser (`parse_export_file.py`):** Parses YAML-frontmatter Markdown format into JSON array.
|
||||
- **Config parser (`parse_mem0_config.py`):** Reads `mem0.md` and extracts `Retention` section into category-to-days mapping.
|
||||
- **Auto-onboarding:** `on_session_start.sh` detects first-time projects and triggers `/mem0:onboard` automatically.
|
||||
- **`mem0.md` config loading:** Session start parses `mem0.md` and injects project config into context.
|
||||
- **Inactive API key banner:** Shows `Mem0 Inactive` with `api_key=NOT_SET` instead of silently exiting.
|
||||
- **`requirements.txt`:** Declares `mem0ai` as plugin's Python dependency.
|
||||
- **Tests:** `test_coding_categories.py`, `test_import_competing_tools.py`, `test_parse_export_file.py`, `test_parse_mem0_config.py`, `test_pre_commit.py`, `test_session_stats.py`, `test_telemetry.py`, `test_write_path.py`.
|
||||
|
||||
### Changed
|
||||
|
||||
- **API scoping: `metadata.project_id` → `app_id`:** All scripts and skills now pass `project_id` as top-level `app_id` parameter instead of inside `metadata`. Affects `auto_import.py`, `capture_compact_summary.py`, `on_pre_compact.py`, all stop hooks, all skill instructions.
|
||||
- **API endpoint: v1 → v3:** `auto_import.py`, `capture_compact_summary.py`, `on_pre_compact.py` now call `/v3/memories/add/`.
|
||||
- **API key resolution:** `_identity.py` and `_identity.sh` now check `CLAUDE_PLUGIN_OPTION_MEM0_API_KEY` (Claude Code `userConfig` env var) as fallback after `MEM0_API_KEY`.
|
||||
- **`session_stats.py`:** Added per-category counters, rolling list of up to 50 recent memory IDs, `peek` subcommand for non-destructive stat reading.
|
||||
- **`setup_coding_categories.py`:** Now imports `mem0ai` from managed venv via `sys.path` injection.
|
||||
- **`on_stop_cursor.sh`:** Added `loop_count` guard to prevent re-entry loops.
|
||||
- **`on_stop.sh`:** Removed `set -e` so session-end reminder always emits even if `session_stats.py` fails. Added dedup marker (`~/.mem0/.captured_<session_id>`).
|
||||
- **`on_user_prompt.sh`:** Detects source file paths in prompt and adds `metadata.files contains` search filter. Handles no-API-key case gracefully.
|
||||
- **`/mem0:tour`:** Replaced 7 parallel type-filtered `search_memories` calls with single `get_memories(app_id=...)` + 3 broad searches (type filtering misses auto-categorized memories).
|
||||
- **`/mem0:onboard`:** Added SDK install step, changed MCP check to use ToolSearch, writes onboard marker to prevent re-triggering.
|
||||
- **`/mem0:mcp`:** Added 16-row category-to-query routing table, inline citations requirement, `branch` in metadata requirement.
|
||||
|
||||
### Fixed
|
||||
|
||||
- **`auto_import.py`, `capture_compact_summary.py`, `on_pre_compact.py`:** Were reading `MEM0_API_KEY` directly; now use `resolve_api_key()` so `CLAUDE_PLUGIN_OPTION_MEM0_API_KEY` is honored.
|
||||
- **`on_pre_compact.py`:** `resolve_project_id()` and `resolve_branch()` now receive `cwd` from hook input instead of `os.getcwd()`, fixing incorrect identification when hook fires in different directory.
|
||||
- **`on_stop_codex.sh`, `on_stop_cursor.sh`:** Missing `_identity.sh` source call; API key resolution via `userConfig` fallback was broken.
|
||||
- **`on_post_tool_use.sh`:** Input field corrected from `tool_result` to `tool_output` to match hook JSON schema.
|
||||
|
||||
## 0.2.0
|
||||
|
||||
### Added
|
||||
|
||||
- **Project-scoped memories:** Deterministic `project_id` from git remote (`_project.sh` / `_project.py`). Memories are now isolated per-repo via `metadata.project_id` on every `add_memory` and `search_memories` call. Same repo cloned twice → same `project_id`.
|
||||
- **Branch-aware tagging:** `metadata.branch` stamped on session-state and compact-summary memories. Enables branch-scoped recall (e.g. "what was I doing on feature/auth-rewrite?").
|
||||
- **Auto-import of project files:** SessionStart detects CLAUDE.md, AGENTS.md, .cursorrules, .windsurfrules, mem0.md — hashes them (SHA-256), imports changed files as `project_profile` memories. Idempotent across sessions.
|
||||
- **Active identity banner:** SessionStart now prints `user=X | project=Y | branch=Z | memories=N` instead of a silent bootstrap.
|
||||
- **Session-end report:** Stop hook prints `Session: wrote N memories, retrieved M. Categories touched: ...` and appends to `~/.mem0/session-log.md`.
|
||||
- **`/mem0:onboard` skill:** Post-install wizard — verifies API key, detects and imports project files, installs coding categories, prints setup summary. 30 seconds to value.
|
||||
- **`/mem0:tour` skill:** Shows all memories for the current project grouped by category. Proof-of-value demo.
|
||||
- **`/mem0:switch-project` skill:** Manual `project_id` override for monorepos and non-git directories. Persists to `~/.mem0/project_map.json`.
|
||||
- **Session stats tracker** (`session_stats.py`): Tracks memory adds/searches per session for the end-of-session report.
|
||||
|
||||
### Changed
|
||||
|
||||
- All hooks and `mem0-mcp/SKILL.md` now include `project_id` in every filter and metadata example.
|
||||
- SessionStart banner replaces the previous "## Mem0 Identity" block with a compact one-liner.
|
||||
- `on_pre_compact.py` and `capture_compact_summary.py` now include `project_id` and `branch` in stored metadata.
|
||||
|
||||
## 0.1.3
|
||||
|
||||
### Fixed
|
||||
|
||||
- **user_id resolution no longer derives from `MEM0_API_KEY`.** v0.1.2 changed the resolver to fall back to `"mem0-" + sha256(MEM0_API_KEY)[:12]` ahead of `$USER`, which silently moved every existing user to a new bucket on update. Memories written under the previous `$USER` value became unreachable from the plugin. Resolution is now back to `MEM0_USER_ID` → `$USER` → `"default"`.
|
||||
- Dropped the "regardless of which machine you're on" line from the SessionStart bootstrap, since cross-machine consolidation now requires setting `MEM0_USER_ID` explicitly.
|
||||
|
||||
### Notes for users upgrading from 0.1.2
|
||||
|
||||
- The `~/.mem0/identity.json` cache file is no longer read or written. Safe to delete.
|
||||
- If you wrote memories during the v0.1.2 window, they live under `mem0-<sha256(api_key)[:12]>`. To recover: temporarily `export MEM0_USER_ID=mem0-<hash>`, search/export, then unset.
|
||||
- Want a single bucket across machines (the original goal of #5076)? Set `MEM0_USER_ID` explicitly in your shell profile. The plugin will not auto-derive one.
|
||||
|
||||
## 0.1.2
|
||||
|
||||
### Added
|
||||
|
||||
- Deterministic `user_id` resolver (`_identity.sh` / `_identity.py`) — **reverted in 0.1.3, see above.**
|
||||
- SessionStart-compact handler (`capture_compact_summary.py`) that stores the post-compaction summary as a memory with `metadata.type=compact_summary`.
|
||||
- Coding-taxonomy setup script (`setup_coding_categories.py`) — one-shot `project.update(custom_categories=[...])` for `architecture_decisions`, `anti_patterns`, `task_learnings`, `tooling_setup`, `bug_fixes`, `coding_conventions`, `user_preferences`.
|
||||
- Opt-in hook logging via `MEM0_DEBUG=1` → `~/.mem0/hooks.log`.
|
||||
- `mem0-mcp` skill replacing the Claude-Code-specific `mem0-codex` skill.
|
||||
|
||||
### Fixed
|
||||
|
||||
- `session_id` now written to memory metadata (`on_pre_compact.py`).
|
||||
- SessionStart bootstrap exits silently when `MEM0_API_KEY` is unset.
|
||||
- `block_memory_write.sh` regex tightened to `MEMORY.md` / `.claude/memory/*` — no longer blocks `docs/memory/*.md`.
|
||||
- Removed duplicate PreCompact write path (kept agent-driven, dropped the parallel Python REST entry from `hooks.json` / `cursor-hooks.json`).
|
||||
- Hook-side captures (`session_state`, `compact_summary`) now set `expiration_date = today + 90 days`.
|
||||
|
||||
## 0.1.1
|
||||
|
||||
- Cursor plugin fully functional (`#4547`).
|
||||
- Codex plugin support and integration docs (`#4665`).
|
||||
- Codex lifecycle hooks via opt-in installer (`#4917`).
|
||||
- Removed invalid keys from Claude plugin config (`#4821`).
|
||||
|
||||
## 0.1.0
|
||||
|
||||
- Initial release: Mem0 plugin for Claude Code and Cursor (`#4518`).
|
||||
@@ -0,0 +1,305 @@
|
||||
# Mem0 Plugin for Claude Code, Claude Cowork, Cursor, Codex, OpenCode & Antigravity
|
||||
|
||||
Add persistent memory to your AI workflows. Store, retrieve, and manage memories across sessions using the Mem0 Platform. Works with **Claude Code** (CLI), **Claude Cowork** (desktop app), **Cursor**, **Codex**, **OpenCode**, and **Antigravity**.
|
||||
|
||||
## Quick path for agents
|
||||
|
||||
If you're an AI agent setting up Mem0 autonomously (no human dashboard signup available), run:
|
||||
|
||||
```bash
|
||||
mem0 init --agent --json
|
||||
```
|
||||
|
||||
This mints an evaluation API key in <5 seconds — no email, no OTP, no browser. The key is written to your config and exported as `MEM0_API_KEY` for the current shell. Use it immediately against the Mem0 Platform or the MCP server. The human owner can later run `mem0 init --email <their-email>` to claim ownership: memories transfer, the same API key keeps working, and the agent isn't disrupted.
|
||||
|
||||
Humans setting up Mem0 by hand should continue with Step 1 below.
|
||||
|
||||
## Step 1: Set your API key
|
||||
|
||||
> **You must complete this step before installing the plugin.**
|
||||
|
||||
1. Sign up at [app.mem0.ai](https://app.mem0.ai?utm_source=oss&utm_medium=mem0-plugin-readme) if you haven't already
|
||||
2. Go to [app.mem0.ai/dashboard/api-keys](https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=mem0-plugin-readme)
|
||||
3. Click **Create API Key** and copy the key (starts with `m0-`)
|
||||
4. Set the key using **one** of these methods:
|
||||
|
||||
**CLI** — add to your shell profile:
|
||||
|
||||
```bash
|
||||
# For zsh (default on macOS)
|
||||
echo 'export MEM0_API_KEY="m0-your-api-key"' >> ~/.zshrc
|
||||
source ~/.zshrc
|
||||
|
||||
# For bash
|
||||
echo 'export MEM0_API_KEY="m0-your-api-key"' >> ~/.bashrc
|
||||
source ~/.bashrc
|
||||
```
|
||||
|
||||
**Desktop app** — use the local environment editor:
|
||||
|
||||
Click the environment dropdown next to the prompt box → hover over **Local** → click the **gear icon** → add `MEM0_API_KEY` with your key. Values are stored encrypted on your machine.
|
||||
|
||||
> **Note:** The Desktop app does not inherit custom environment variables from shell profiles — it only reads `PATH`. You must use the local environment editor for Desktop.
|
||||
|
||||
5. Confirm it's set:
|
||||
|
||||
```bash
|
||||
echo $MEM0_API_KEY
|
||||
# Should print: m0-your-api-key
|
||||
```
|
||||
|
||||
## Step 2: Install the plugin
|
||||
|
||||
Choose one of the options below. All require `MEM0_API_KEY` to be set first (see above).
|
||||
|
||||
### Claude Code (CLI) / Claude Cowork (Desktop)
|
||||
|
||||
Claude Code and Claude Cowork share the same plugin system.
|
||||
|
||||
**CLI:**
|
||||
|
||||
```
|
||||
/plugin marketplace add mem0ai/mem0
|
||||
/plugin install mem0@mem0-plugins
|
||||
```
|
||||
|
||||
**Cowork desktop app:** Open the Cowork tab, click **Customize** in the sidebar, click **Browse plugins**, and install Mem0.
|
||||
|
||||
This installs the full plugin including the MCP server, lifecycle hooks (automatic memory capture), and the Mem0 SDK skill.
|
||||
|
||||
### Codex
|
||||
|
||||
**Option A — Direct MCP** (fastest, MCP only):
|
||||
|
||||
Codex reads MCP servers from `~/.codex/config.toml` as TOML. Add:
|
||||
|
||||
```toml
|
||||
[mcp_servers.mem0]
|
||||
url = "https://mcp.mem0.ai/mcp"
|
||||
bearer_token_env_var = "MEM0_API_KEY"
|
||||
```
|
||||
|
||||
Export `MEM0_API_KEY` in your shell and restart Codex. `codex mcp add` only supports stdio servers, so HTTP servers like Mem0's must be added via `config.toml` directly (or via the **Plugins → Connect to a custom MCP → Streamable HTTP** UI in the Codex app).
|
||||
|
||||
**Option B — Sideload the plugin** (full experience: MCP + skills + opt-in hooks):
|
||||
|
||||
Clone the repo and register the bundled marketplace with one CLI call:
|
||||
|
||||
```bash
|
||||
git clone https://github.com/mem0ai/mem0.git ~/codex-plugins/mem0-source
|
||||
codex plugin marketplace add ~/codex-plugins/mem0-source
|
||||
```
|
||||
|
||||
This points Codex at the repo's `.agents/plugins/marketplace.json`, which references `integrations/mem0-plugin/` as the local source. Restart Codex, run `/plugins`, and install **Mem0** from the **Mem0 Plugins** marketplace.
|
||||
|
||||
> **Don't combine with Option A.** The plugin manifest auto-registers `mem0` as an MCP server via `integrations/mem0-plugin/.codex-mcp.json` — adding a manual `[mcp_servers.mem0]` block would duplicate the registration.
|
||||
|
||||
**Optional — enable lifecycle hooks.** Codex doesn't auto-wire hooks from plugin manifests; it only reads `~/.codex/hooks.json` (or `<repo>/.codex/hooks.json`) ([docs](https://developers.openai.com/codex/hooks)). Run the bundled installer once to merge Mem0's entries:
|
||||
|
||||
```bash
|
||||
python3 ~/codex-plugins/mem0-source/integrations/mem0-plugin/scripts/install_codex_hooks.py
|
||||
```
|
||||
|
||||
This merges three entries into `~/.codex/hooks.json` with absolute paths pointing into your clone:
|
||||
|
||||
| Event | What it does |
|
||||
|-------|--------------|
|
||||
| `SessionStart` | Loads prior memories as bootstrap context |
|
||||
| `UserPromptSubmit` | Injects relevant memories into the prompt |
|
||||
| `Stop` | Reminds the agent to persist learnings at turn end |
|
||||
|
||||
Re-running the installer is idempotent (replaces the Mem0 entries rather than duplicating) and preserves any other hooks you have. To remove: `python3 .../install_codex_hooks.py --uninstall`. If you move or delete the clone directory, re-run the installer from the new location — the hooks file stores absolute paths.
|
||||
|
||||
Codex hooks also require the `codex_hooks` feature flag in `~/.codex/config.toml`:
|
||||
|
||||
```toml
|
||||
[features]
|
||||
codex_hooks = true
|
||||
```
|
||||
|
||||
The installer prints a reminder if the flag isn't set. Restart Codex after editing the config.
|
||||
|
||||
**Managing the plugin:**
|
||||
|
||||
```bash
|
||||
codex plugin marketplace upgrade # pull latest plugin versions
|
||||
codex plugin marketplace remove mem0-plugins # unregister the marketplace
|
||||
```
|
||||
|
||||
### Cursor
|
||||
|
||||
> **Already have `mem0` configured as an MCP server?** Remove the existing entry from your Cursor MCP settings before installing to avoid duplicate tools.
|
||||
|
||||
**Option A — One-click deeplink** (installs MCP server only):
|
||||
|
||||
[Install Mem0 MCP in Cursor](cursor://anysphere.cursor-deeplink/mcp/install?name=mem0&config=eyJtY3BTZXJ2ZXJzIjp7Im1lbTAiOnsidXJsIjoiaHR0cHM6Ly9tY3AubWVtMC5haS9tY3AvIiwiaGVhZGVycyI6eyJBdXRob3JpemF0aW9uIjoiVG9rZW4gJHtlbnY6TUVNMF9BUElfS0VZfSJ9fX19)
|
||||
|
||||
**Option B — Manual configuration** (MCP server only):
|
||||
|
||||
Add the following to your `.cursor/mcp.json`:
|
||||
|
||||
```json
|
||||
{
|
||||
"mcpServers": {
|
||||
"mem0": {
|
||||
"url": "https://mcp.mem0.ai/mcp/",
|
||||
"headers": {
|
||||
"Authorization": "Token ${env:MEM0_API_KEY}"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
**Option C — Cursor Marketplace** (full plugin with hooks and skills):
|
||||
|
||||
Install from the [Cursor Marketplace](https://cursor.com/marketplace) for the complete experience including lifecycle hooks and the Mem0 SDK skill.
|
||||
|
||||
### OpenCode
|
||||
|
||||
```bash
|
||||
bunx @mem0/opencode-plugin@latest install
|
||||
```
|
||||
|
||||
Or via OpenCode's built-in CLI: `opencode plugin @mem0/opencode-plugin`
|
||||
|
||||
Then add the MCP server to your `opencode.json` (project or global at `~/.config/opencode/opencode.json`):
|
||||
|
||||
```json
|
||||
{
|
||||
"mcp": {
|
||||
"mem0": {
|
||||
"type": "remote",
|
||||
"url": "https://mcp.mem0.ai/mcp/",
|
||||
"headers": {
|
||||
"Authorization": "Token {env:MEM0_API_KEY}"
|
||||
},
|
||||
"oauth": false
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
Restart OpenCode. The plugin installs hooks and skills automatically. Drop the `plugin` install if you only want MCP.
|
||||
|
||||
See [OpenCode integration docs](https://docs.mem0.ai/integrations/opencode) for full details.
|
||||
|
||||
### Antigravity (Google)
|
||||
|
||||
**Option A — degit** (recommended):
|
||||
|
||||
```bash
|
||||
# Install the plugin (MCP server, hooks, scripts)
|
||||
npx degit mem0ai/mem0/integrations/mem0-plugin ~/.gemini/config/plugins/mem0
|
||||
```
|
||||
|
||||
This installs the MCP server, lifecycle hooks, and shared scripts.
|
||||
|
||||
See [Antigravity integration docs](https://docs.mem0.ai/integrations/antigravity) for full details.
|
||||
|
||||
## Post-Installation: Run `/mem0:onboard`
|
||||
|
||||
After installing, start a new session and run:
|
||||
|
||||
```
|
||||
/mem0:onboard
|
||||
```
|
||||
|
||||
This runs the setup wizard which:
|
||||
1. Verifies your API key and MCP connection
|
||||
2. Detects and imports project files (`CLAUDE.md`, `AGENTS.md`, `.cursorrules`)
|
||||
3. Installs coding-optimized memory categories
|
||||
4. Shows your identity (user ID, project scope, branch)
|
||||
|
||||
The onboarding is idempotent — safe to re-run anytime. On first session in a new project (0 memories), Claude is prompted to run it automatically.
|
||||
|
||||
## Verify it works
|
||||
|
||||
After onboarding, confirm everything is connected:
|
||||
|
||||
1. Run `/mem0:health` to check connectivity
|
||||
2. Run `/mem0:stats` to see memory counts
|
||||
3. Try `/mem0:remember "we use TypeScript"` then `/mem0:tour` to see it stored
|
||||
|
||||
## Available Skills
|
||||
|
||||
The plugin includes 17 skills accessible via `/mem0:` commands:
|
||||
|
||||
| Command | Description |
|
||||
|---------|-------------|
|
||||
| `/mem0:remember` | Store a memory verbatim — decisions, preferences, conventions |
|
||||
| `/mem0:tour` | Browse all memories grouped by category |
|
||||
| `/mem0:peek` | Quick search with compact one-liner results |
|
||||
| `/mem0:stats` | Session and project memory statistics |
|
||||
| `/mem0:dream` | Consolidate memories — merge duplicates, resolve contradictions |
|
||||
| `/mem0:pin` | Protect critical memories from pruning |
|
||||
| `/mem0:forget` | Delete memories by search or ID |
|
||||
| `/mem0:health` | Diagnose connectivity, API key, and read/write |
|
||||
| `/mem0:export` | Export memories to portable Markdown |
|
||||
| `/mem0:import` | Import memories from export file or MEMORY.md |
|
||||
| `/mem0:list-projects` | List all projects with stored memories |
|
||||
| `/mem0:switch-project` | Override auto-detected project scope |
|
||||
| `/mem0:memory-reviewer` | Audit memory quality — duplicates, contradictions, stale |
|
||||
| `/mem0:context-loader` | Pre-load relevant memories for current task |
|
||||
|
||||
## What's included
|
||||
|
||||
| Component | Claude Code / Cowork | Cursor (Marketplace) | Cursor (Deeplink/Manual) | Codex (Sideload) | Codex (Direct MCP) | OpenCode (Full) | OpenCode (MCP) | Antigravity |
|
||||
|-----------|:--------------------:|:--------------------:|:------------------------:|:----------------:|:------------------:|:---------------:|:--------------:|:-----------:|
|
||||
| MCP Server | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
|
||||
| Lifecycle Hooks | Yes | Yes | No | Opt-in | No | Yes | No | Yes |
|
||||
| Mem0 SDK Skill | Yes | Yes | No | Yes | No | Yes | No | Yes |
|
||||
|
||||
- **MCP Server** — Connects to the Mem0 remote MCP server (`mcp.mem0.ai`), providing tools to add, search, update, and delete memories. No local dependencies required.
|
||||
- **Lifecycle Hooks** — Automatic memory capture at key points. Claude Code, Cursor, OpenCode, and Antigravity wire hooks natively when the full plugin is installed. Codex hooks are opt-in via a one-time installer (`scripts/install_codex_hooks.py`).
|
||||
- **Mem0 SDK Skill** — Guides the AI on how to integrate the Mem0 SDK (Python & TypeScript) into your applications.
|
||||
|
||||
## Updating the plugin
|
||||
|
||||
When the plugin updates (new version pulled from the marketplace, or a fresh local install), the MCP server connection in your existing session is left holding a stale handle and stops responding. **Restart your client to reconnect:**
|
||||
|
||||
- **Claude Code:** run `/restart` in the prompt, or close and reopen the CLI.
|
||||
- **Cursor:** quit and relaunch.
|
||||
- **Codex:** restart the editor session.
|
||||
- **OpenCode:** restart the session.
|
||||
- **Antigravity:** restart the session.
|
||||
|
||||
Your `MEM0_API_KEY` doesn't need to be re-entered — the auth header is re-read from your environment on the new session. The plugin's MCP config uses `${MEM0_API_KEY}` interpolation at session start, not at install time, so as long as the env var is set persistently (in your shell profile or `~/.claude/settings.json` `env` block), reconnection is automatic on restart.
|
||||
|
||||
If reconnection still fails after a restart, check that `MEM0_API_KEY` is reachable in the new shell (`echo $MEM0_API_KEY`) and confirm you're using a key that starts with `m0-` (from https://app.mem0.ai/dashboard/api-keys, not a legacy token).
|
||||
|
||||
## Coding-tuned categories (automatic)
|
||||
|
||||
mem0 auto-tags every memory with one or more `categories` from a project-level list. The default list is consumer-oriented (`food`, `hobbies`, `music` …) — useful for chat assistants, less so for code. **The plugin installs a coding-focused taxonomy automatically in the background on session start** — no prompt, no manual step. New memories then auto-tag against 17 development-oriented categories: `architecture_decisions`, `anti_patterns`, `task_learnings`, `tooling_setup`, `bug_fixes`, `coding_conventions`, `user_preferences`, `dependency_decisions`, `performance_findings`, `security_constraints`, `testing_patterns`, `data_model`, `api_contracts`, `deployment_runbook`, `team_norms`, `domain_glossary`, `experiment_results`.
|
||||
|
||||
The background setup is idempotent and runs once per account (cached in `~/.mem0/categories_setup.json`); it re-applies only if the taxonomy itself changes. To preview the taxonomy or force a refresh manually:
|
||||
|
||||
```bash
|
||||
# Dry-run -- prints current vs proposed, no changes:
|
||||
python integrations/mem0-plugin/scripts/setup_coding_categories.py
|
||||
|
||||
# Write explicitly:
|
||||
python integrations/mem0-plugin/scripts/setup_coding_categories.py --apply
|
||||
```
|
||||
|
||||
Requires the `mem0ai` Python SDK (`pip install mem0ai`) and `MEM0_API_KEY` set. `project.update(custom_categories=[...])` always replaces the full list.
|
||||
|
||||
## MCP Tools
|
||||
|
||||
Once installed, the following tools are available:
|
||||
|
||||
| Tool | Description |
|
||||
|------|-------------|
|
||||
| `add_memory` | Save text or conversation history for a user/agent |
|
||||
| `search_memories` | Semantic search across memories with filters |
|
||||
| `get_memories` | List memories with filters and pagination |
|
||||
| `get_memory` | Retrieve a specific memory by ID |
|
||||
| `update_memory` | Overwrite a memory's text by ID |
|
||||
| `delete_memory` | Delete a single memory by ID |
|
||||
| `delete_all_memories` | Bulk delete all memories in scope |
|
||||
| `delete_entities` | Delete a user/agent/app/run entity and its memories |
|
||||
| `list_entities` | List users/agents/apps/runs stored in Mem0 |
|
||||
|
||||
## License
|
||||
|
||||
Apache-2.0
|
||||
@@ -0,0 +1,104 @@
|
||||
{
|
||||
"hooks": {
|
||||
"SessionStart": [
|
||||
{
|
||||
"matcher": "*",
|
||||
"hooks": [
|
||||
{
|
||||
"name": "mem0-ensure-deps",
|
||||
"type": "command",
|
||||
"command": "ANTIGRAVITY_PLUGIN_ROOT=${extensionPath} CLAUDE_PLUGIN_ROOT=${extensionPath} bash ${extensionPath}/scripts/ensure_deps.sh 2>/dev/null || true",
|
||||
"timeout": 60
|
||||
},
|
||||
{
|
||||
"name": "mem0-session-start",
|
||||
"type": "command",
|
||||
"command": "ANTIGRAVITY_PLUGIN_ROOT=${extensionPath} CLAUDE_PLUGIN_ROOT=${extensionPath} bash ${extensionPath}/scripts/on_session_start.sh 2>/dev/null || true"
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
"UserPromptSubmit": [
|
||||
{
|
||||
"hooks": [
|
||||
{
|
||||
"name": "mem0-user-prompt",
|
||||
"type": "command",
|
||||
"command": "ANTIGRAVITY_PLUGIN_ROOT=${extensionPath} CLAUDE_PLUGIN_ROOT=${extensionPath} bash ${extensionPath}/scripts/on_user_prompt.sh 2>/dev/null || true",
|
||||
"timeout": 8
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
"PreToolUse": [
|
||||
{
|
||||
"matcher": "Write|Edit|MultiEdit",
|
||||
"hooks": [
|
||||
{
|
||||
"name": "mem0-block-memory-write",
|
||||
"type": "command",
|
||||
"command": "ANTIGRAVITY_PLUGIN_ROOT=${extensionPath} CLAUDE_PLUGIN_ROOT=${extensionPath} bash ${extensionPath}/scripts/block_memory_write.sh"
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"matcher": "mcp__mem0__.*|mcp__plugin_mem0_mem0__.*",
|
||||
"hooks": [
|
||||
{
|
||||
"name": "mem0-enforce-metadata",
|
||||
"type": "command",
|
||||
"command": "ANTIGRAVITY_PLUGIN_ROOT=${extensionPath} CLAUDE_PLUGIN_ROOT=${extensionPath} bash ${extensionPath}/scripts/enforce_metadata_defaults.sh",
|
||||
"timeout": 3
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"matcher": "Read",
|
||||
"hooks": [
|
||||
{
|
||||
"name": "mem0-file-context",
|
||||
"type": "command",
|
||||
"command": "ANTIGRAVITY_PLUGIN_ROOT=${extensionPath} CLAUDE_PLUGIN_ROOT=${extensionPath} bash ${extensionPath}/scripts/on_file_read.sh",
|
||||
"timeout": 5
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
"Stop": [
|
||||
{
|
||||
"hooks": [
|
||||
{
|
||||
"name": "mem0-session-summary",
|
||||
"type": "command",
|
||||
"command": "ANTIGRAVITY_PLUGIN_ROOT=${extensionPath} CLAUDE_PLUGIN_ROOT=${extensionPath} bash ${extensionPath}/scripts/on_stop.sh",
|
||||
"timeout": 30
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
"PostToolUse": [
|
||||
{
|
||||
"matcher": "mcp__mem0__.*|mcp__plugin_mem0_mem0__.*",
|
||||
"hooks": [
|
||||
{
|
||||
"name": "mem0-post-tool",
|
||||
"type": "command",
|
||||
"command": "ANTIGRAVITY_PLUGIN_ROOT=${extensionPath} CLAUDE_PLUGIN_ROOT=${extensionPath} bash ${extensionPath}/scripts/on_post_tool_use.sh",
|
||||
"timeout": 3
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"matcher": "Bash",
|
||||
"hooks": [
|
||||
{
|
||||
"name": "mem0-bash-output",
|
||||
"type": "command",
|
||||
"command": "ANTIGRAVITY_PLUGIN_ROOT=${extensionPath} CLAUDE_PLUGIN_ROOT=${extensionPath} bash ${extensionPath}/scripts/on_bash_output.sh",
|
||||
"timeout": 5
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,104 @@
|
||||
{
|
||||
"hooks": {
|
||||
"PreToolUse": [
|
||||
{
|
||||
"matcher": "Write|Edit|MultiEdit",
|
||||
"hooks": [
|
||||
{
|
||||
"type": "command",
|
||||
"command": "${PLUGIN_ROOT}/scripts/block_memory_write.sh",
|
||||
"timeout": 3
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"matcher": "mcp__mem0__add_memory|mcp__plugin_mem0_mem0__add_memory|mcp__mem0__search_memories|mcp__plugin_mem0_mem0__search_memories|mcp__mem0__get_memories|mcp__plugin_mem0_mem0__get_memories|mcp__mem0__delete_all_memories|mcp__plugin_mem0_mem0__delete_all_memories",
|
||||
"hooks": [
|
||||
{
|
||||
"type": "command",
|
||||
"command": "${PLUGIN_ROOT}/scripts/enforce_metadata_defaults.sh",
|
||||
"timeout": 3
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"matcher": "Read",
|
||||
"hooks": [
|
||||
{
|
||||
"type": "command",
|
||||
"command": "${PLUGIN_ROOT}/scripts/on_file_read.sh",
|
||||
"timeout": 5
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
"SessionStart": [
|
||||
{
|
||||
"matcher": "startup|resume|compact",
|
||||
"hooks": [
|
||||
{
|
||||
"type": "command",
|
||||
"command": "${PLUGIN_ROOT}/scripts/on_session_start.sh",
|
||||
"statusMessage": "Loading mem0 context..."
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
"UserPromptSubmit": [
|
||||
{
|
||||
"hooks": [
|
||||
{
|
||||
"type": "command",
|
||||
"command": "${PLUGIN_ROOT}/scripts/on_user_prompt.sh",
|
||||
"statusMessage": "Checking memory relevance...",
|
||||
"timeout": 12
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
"PostToolUse": [
|
||||
{
|
||||
"matcher": "mcp__mem0__.*|mcp__plugin_mem0_mem0__.*",
|
||||
"hooks": [
|
||||
{
|
||||
"type": "command",
|
||||
"command": "${PLUGIN_ROOT}/scripts/on_post_tool_use.sh",
|
||||
"timeout": 3
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"matcher": "Bash",
|
||||
"hooks": [
|
||||
{
|
||||
"type": "command",
|
||||
"command": "${PLUGIN_ROOT}/scripts/on_bash_output.sh",
|
||||
"timeout": 12
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
"Stop": [
|
||||
{
|
||||
"hooks": [
|
||||
{
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"type": "command",
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"command": "${PLUGIN_ROOT}/scripts/on_stop.sh",
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"timeout": 30
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}
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}
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],
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{
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{
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}
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]
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}
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]
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}
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}
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{
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{
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{
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}
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],
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"stop": [
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}
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{
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]
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}
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}
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}
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{
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||||
"statusMessage": "Installing mem0 SDK...",
|
||||
"timeout": 60
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||||
}
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||||
]
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},
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{
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"matcher": "startup|resume|compact",
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||||
"hooks": [
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{
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||||
"type": "command",
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"command": "${CLAUDE_PLUGIN_ROOT}/scripts/on_session_start.sh",
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"statusMessage": "Loading mem0 context..."
|
||||
}
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]
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}
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],
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{
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{
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"type": "command",
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"command": "${CLAUDE_PLUGIN_ROOT}/scripts/block_memory_write.sh"
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}
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},
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{
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"matcher": "mcp__mem0__add_memory|mcp__plugin_mem0_mem0__add_memory|mcp__mem0__search_memories|mcp__plugin_mem0_mem0__search_memories|mcp__mem0__get_memories|mcp__plugin_mem0_mem0__get_memories|mcp__mem0__delete_all_memories|mcp__plugin_mem0_mem0__delete_all_memories",
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{
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}
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},
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{
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"matcher": "Read",
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"command": "${CLAUDE_PLUGIN_ROOT}/scripts/on_file_read.sh",
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"timeout": 5
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}
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}
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{
|
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"hooks": [
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{
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"type": "command",
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||||
"command": "${CLAUDE_PLUGIN_ROOT}/scripts/on_post_tool_use.sh",
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||||
"timeout": 3
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}
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]
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},
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{
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"matcher": "Bash",
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{
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"type": "command",
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"command": "${CLAUDE_PLUGIN_ROOT}/scripts/on_bash_output.sh",
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"timeout": 5
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}
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]
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||||
}
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{
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{
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"type": "command",
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||||
"command": "${CLAUDE_PLUGIN_ROOT}/scripts/on_stop.sh",
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"timeout": 30
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}
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]
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}
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],
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"PreCompact": [
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{
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"hooks": [
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{
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"type": "command",
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"command": "${CLAUDE_PLUGIN_ROOT}/scripts/on_pre_compact.sh",
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"statusMessage": "Preparing pre-compaction summary..."
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}
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]
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}
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],
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"UserPromptSubmit": [
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{
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{
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||||
"type": "command",
|
||||
"command": "${CLAUDE_PLUGIN_ROOT}/scripts/on_user_prompt.sh",
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||||
"statusMessage": "Checking memory relevance...",
|
||||
"timeout": 8
|
||||
}
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||||
]
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}
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]
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}
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}
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<path d="M196.915 241.18C198.304 236.024 195.686 230.756 192.414 226.542C189.567 222.87 187.944 218.398 187.774 213.755C187.604 209.112 188.896 204.533 191.467 200.664C194.038 196.794 197.759 193.829 202.104 192.187C206.45 190.544 211.202 190.307 215.69 191.509C220.178 192.712 224.175 195.292 227.118 198.887C230.061 202.481 231.802 206.909 232.094 211.546C232.387 216.183 231.217 220.794 228.749 224.731C226.281 228.667 222.64 231.729 218.339 233.486C213.406 235.513 208.505 238.77 207.164 243.91C205.823 249.051 208.393 254.335 211.666 258.549C214.513 262.22 216.136 266.693 216.306 271.335C216.476 275.978 215.184 280.557 212.613 284.427C210.042 288.297 206.321 291.262 201.975 292.904C197.629 294.546 192.877 294.783 188.39 293.581C183.902 292.379 179.905 289.799 176.962 286.204C174.019 282.609 172.278 278.181 171.985 273.545C171.693 268.908 172.863 264.296 175.331 260.36C177.799 256.424 181.44 253.361 185.741 251.605C190.658 249.577 195.543 246.337 196.915 241.18Z" fill="white"/>
|
||||
<path d="M246.195 184.797C243.529 180.184 237.957 178.316 232.673 177.629C228.069 177.045 223.764 175.03 220.365 171.869C216.967 168.708 214.646 164.56 213.729 160.01C212.813 155.46 213.348 150.737 215.258 146.507C217.168 142.277 220.357 138.753 224.376 136.431C228.395 134.11 233.041 133.108 237.66 133.567C242.279 134.026 246.637 135.923 250.12 138.991C253.604 142.058 256.037 146.141 257.077 150.664C258.117 155.188 257.711 159.923 255.917 164.204C253.857 169.137 252.724 174.9 255.342 179.513C257.96 184.127 263.595 186.01 268.879 186.681C273.484 187.267 277.789 189.283 281.186 192.446C284.584 195.608 286.904 199.757 287.819 204.308C288.733 208.859 288.197 213.582 286.285 217.811C284.372 222.041 281.181 225.564 277.16 227.884C273.14 230.203 268.492 231.203 263.874 230.741C259.255 230.279 254.897 228.379 251.416 225.31C247.934 222.24 245.503 218.155 244.466 213.63C243.429 209.106 243.838 204.37 245.636 200.09C247.695 195.173 248.861 189.411 246.195 184.797Z" fill="white"/>
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<path d="M241.18 110.07C236.024 108.697 230.756 111.315 226.542 114.588C222.87 117.435 218.398 119.058 213.755 119.228C209.112 119.398 204.533 118.106 200.664 115.535C196.794 112.964 193.829 109.243 192.187 104.897C190.544 100.551 190.307 95.7994 191.509 91.3117C192.712 86.824 195.292 82.8268 198.887 79.8837C202.481 76.9405 206.909 75.2 211.546 74.9073C216.183 74.6147 220.794 75.7849 224.731 78.2527C228.667 80.7206 231.729 84.3617 233.486 88.6627C235.513 93.5955 238.754 98.4964 243.91 99.8374C249.066 101.178 254.335 98.6082 258.549 95.3356C262.22 92.4959 266.69 90.8798 271.328 90.7151C275.967 90.5503 280.54 91.8452 284.403 94.4172C288.267 96.9892 291.226 100.709 292.863 105.052C294.501 109.394 294.734 114.142 293.531 118.624C292.327 123.107 289.748 127.099 286.155 130.037C282.563 132.976 278.139 134.714 273.507 135.005C268.875 135.296 264.268 134.126 260.336 131.661C256.403 129.195 253.344 125.557 251.589 121.261C249.577 116.36 246.321 111.459 241.18 110.07Z" fill="white"/>
|
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<path d="M153.491 191.533C174.501 191.533 191.533 174.501 191.533 153.491C191.533 132.482 174.501 115.45 153.491 115.45C132.481 115.45 115.449 132.482 115.449 153.491C115.449 174.501 132.481 191.533 153.491 191.533Z" fill="white"/>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 13 KiB |
@@ -0,0 +1,10 @@
|
||||
{
|
||||
"mcpServers": {
|
||||
"mem0": {
|
||||
"serverUrl": "https://mcp.mem0.ai/mcp/",
|
||||
"headers": {
|
||||
"Authorization": "Token ${MEM0_API_KEY}"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"id": "mem0",
|
||||
"name": "mem0",
|
||||
"version": "0.1.1",
|
||||
"description": "Persistent semantic memory for Antigravity agents. Cross-session, user-level recall via the Mem0 Platform MCP server. 16 slash commands, lifecycle hooks for auto-capture and metadata enforcement.",
|
||||
"author": { "name": "Mem0", "email": "support@mem0.ai" },
|
||||
"publisher": "mem0ai",
|
||||
"homepage": "https://mem0.ai",
|
||||
"repository": "https://github.com/mem0ai/mem0",
|
||||
"license": "Apache-2.0",
|
||||
"keywords": ["memory", "persistence", "personalization", "mcp", "semantic-search"],
|
||||
"contextFileName": "AGENTS.md"
|
||||
}
|
||||
@@ -0,0 +1 @@
|
||||
mem0ai
|
||||
@@ -0,0 +1,75 @@
|
||||
"""Shared content-chunking utilities for mem0-plugin import scripts."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
MIN_CHUNK_CHARS = 50
|
||||
MAX_CHUNK_CHARS = 10_000
|
||||
|
||||
|
||||
def split_by_headers(content: str, header_prefix: str = "## ") -> list[str]:
|
||||
"""Split content by Markdown header lines (e.g. '## ').
|
||||
|
||||
The header line is included at the start of each chunk.
|
||||
Returns a list of non-empty chunk strings.
|
||||
"""
|
||||
chunks: list[str] = []
|
||||
current_lines: list[str] = []
|
||||
|
||||
for line in content.splitlines(keepends=True):
|
||||
if line.startswith(header_prefix) and current_lines:
|
||||
chunk = "".join(current_lines).strip()
|
||||
if chunk:
|
||||
chunks.append(chunk)
|
||||
current_lines = [line]
|
||||
else:
|
||||
current_lines.append(line)
|
||||
|
||||
if current_lines:
|
||||
chunk = "".join(current_lines).strip()
|
||||
if chunk:
|
||||
chunks.append(chunk)
|
||||
|
||||
return chunks
|
||||
|
||||
|
||||
def split_by_hr_or_headers(content: str) -> list[str]:
|
||||
"""Split content by '---' horizontal rules or '## ' headers.
|
||||
|
||||
Used for .continue/rules.md which may use either convention.
|
||||
"""
|
||||
import re
|
||||
|
||||
# Split on lines that are exactly "---" or start with "## "
|
||||
chunks: list[str] = []
|
||||
current_lines: list[str] = []
|
||||
|
||||
for line in content.splitlines(keepends=True):
|
||||
is_hr = re.match(r"^---\s*$", line)
|
||||
is_h2 = line.startswith("## ")
|
||||
|
||||
if (is_hr or is_h2) and current_lines:
|
||||
chunk = "".join(current_lines).strip()
|
||||
if chunk:
|
||||
chunks.append(chunk)
|
||||
current_lines = [] if is_hr else [line]
|
||||
else:
|
||||
current_lines.append(line)
|
||||
|
||||
if current_lines:
|
||||
chunk = "".join(current_lines).strip()
|
||||
if chunk:
|
||||
chunks.append(chunk)
|
||||
|
||||
return chunks
|
||||
|
||||
|
||||
def filter_and_truncate(chunks: list[str]) -> list[str]:
|
||||
"""Filter out chunks shorter than MIN_CHUNK_CHARS, truncate long chunks."""
|
||||
result: list[str] = []
|
||||
for chunk in chunks:
|
||||
if len(chunk) < MIN_CHUNK_CHARS:
|
||||
continue
|
||||
if len(chunk) > MAX_CHUNK_CHARS:
|
||||
chunk = chunk[:MAX_CHUNK_CHARS]
|
||||
result.append(chunk)
|
||||
return result
|
||||
@@ -0,0 +1,51 @@
|
||||
"""Shared formatting helpers for mem0 plugin hooks.
|
||||
|
||||
Constants and utilities used by file_context.py, session_timeline.py,
|
||||
and any future hook that displays memories.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
TYPE_ICONS = {
|
||||
"decision": "⚖️",
|
||||
"anti_pattern": "\U0001f534",
|
||||
"bug_fix": "\U0001f534",
|
||||
"convention": "\U0001f504",
|
||||
"task_learning": "\U0001f535",
|
||||
"user_preference": "\U0001f7e3",
|
||||
"session_summary": "\U0001f4cb",
|
||||
"session_state": "\U0001f4cb",
|
||||
"project_profile": "\U0001f4d6",
|
||||
"compact_summary": "\U0001f4cb",
|
||||
"auto_capture": "✅",
|
||||
"environmental": "🌐",
|
||||
"health_check": "🩺",
|
||||
}
|
||||
|
||||
|
||||
def format_age(memory: dict) -> str:
|
||||
"""Format how long ago a memory was created, e.g. '2h ago', '3d ago'."""
|
||||
created = memory.get("created_at", "")
|
||||
if not created:
|
||||
return ""
|
||||
try:
|
||||
from datetime import datetime, timezone
|
||||
|
||||
if created.endswith("Z"):
|
||||
created = created[:-1] + "+00:00"
|
||||
dt = datetime.fromisoformat(created)
|
||||
now = datetime.now(timezone.utc)
|
||||
delta = now - dt
|
||||
seconds = int(delta.total_seconds())
|
||||
if seconds < 3600:
|
||||
return f"{seconds // 60}m ago"
|
||||
if seconds < 86400:
|
||||
return f"{seconds // 3600}h ago"
|
||||
days = seconds // 86400
|
||||
if days == 1:
|
||||
return "1d ago"
|
||||
if days < 30:
|
||||
return f"{days}d ago"
|
||||
return f"{days // 30}mo ago"
|
||||
except Exception:
|
||||
return ""
|
||||
@@ -0,0 +1,104 @@
|
||||
"""Resolve mem0 identity: API key, user_id, and settings.
|
||||
|
||||
API key resolution (first non-empty wins):
|
||||
1. MEM0_API_KEY env var (explicit / shell profile)
|
||||
2. CLAUDE_PLUGIN_OPTION_API_KEY (injected by Claude Code userConfig)
|
||||
3. CLAUDE_PLUGIN_OPTION_MEM0_API_KEY (legacy userConfig)
|
||||
4. Extract from shell profile files (~/.zshrc, ~/.bashrc, etc.)
|
||||
Desktop app doesn't inherit shell env — this covers users who
|
||||
set MEM0_API_KEY in their profile but use the Desktop app.
|
||||
|
||||
User ID resolution:
|
||||
1. MEM0_USER_ID env var (explicit override)
|
||||
2. $USER, else "default"
|
||||
|
||||
Settings resolution:
|
||||
~/.mem0/settings.json (user-editable, falls back to defaults)
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import os
|
||||
import re
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
def _extract_key_from_shell_profiles() -> str:
|
||||
"""Extract MEM0_API_KEY from shell profile files.
|
||||
|
||||
The Desktop app only reads PATH from shell profiles — env vars like
|
||||
MEM0_API_KEY are not inherited. This handles the common
|
||||
``export MEM0_API_KEY=...`` pattern without sourcing the full profile.
|
||||
"""
|
||||
profiles = [".zshrc", ".bashrc", ".zprofile", ".bash_profile", ".profile"]
|
||||
pattern = re.compile(r'^\s*(?:export\s+)?MEM0_API_KEY=(.+)$')
|
||||
|
||||
for name in profiles:
|
||||
path = Path.home() / name
|
||||
if not path.is_file():
|
||||
continue
|
||||
try:
|
||||
for line in path.read_text(encoding="utf-8", errors="replace").splitlines():
|
||||
m = pattern.match(line)
|
||||
if not m:
|
||||
continue
|
||||
value = m.group(1).strip()
|
||||
value = re.sub(r'#.*$', '', value).strip()
|
||||
value = value.strip("\"'")
|
||||
if value and not value.startswith("$"):
|
||||
return value
|
||||
except OSError:
|
||||
continue
|
||||
return ""
|
||||
|
||||
|
||||
def resolve_api_key() -> str:
|
||||
key = os.environ.get("MEM0_API_KEY", "").strip()
|
||||
if key:
|
||||
return key
|
||||
key = os.environ.get("CLAUDE_PLUGIN_OPTION_API_KEY", "").strip()
|
||||
if key:
|
||||
return key
|
||||
key = os.environ.get("CLAUDE_PLUGIN_OPTION_MEM0_API_KEY", "").strip()
|
||||
if key:
|
||||
return key
|
||||
key = _extract_key_from_shell_profiles()
|
||||
if key:
|
||||
return key
|
||||
return ""
|
||||
|
||||
|
||||
def resolve_user_id() -> str:
|
||||
explicit = os.environ.get("MEM0_USER_ID", "").strip()
|
||||
if explicit:
|
||||
return explicit
|
||||
return os.environ.get("USER") or "default"
|
||||
|
||||
|
||||
def resolve_config() -> dict:
|
||||
"""Resolve settings from ~/.mem0/settings.json (primary) with env var overrides."""
|
||||
try:
|
||||
from load_settings import load_settings
|
||||
return load_settings()
|
||||
except ImportError:
|
||||
return {
|
||||
"auto_save": True,
|
||||
"auto_search": True,
|
||||
"search_limit": 10,
|
||||
"retention_session_days": 90,
|
||||
"confidence_threshold": 0.3,
|
||||
"debug": False,
|
||||
}
|
||||
|
||||
|
||||
try:
|
||||
from _project import resolve_branch, resolve_project_id, save_project_mapping
|
||||
except ImportError:
|
||||
def resolve_project_id(cwd: str | None = None) -> str:
|
||||
return os.path.basename(cwd or os.getcwd())
|
||||
|
||||
def resolve_branch(cwd: str | None = None) -> str:
|
||||
return "unknown"
|
||||
|
||||
def save_project_mapping(cwd: str, project_id: str) -> None:
|
||||
pass
|
||||
@@ -0,0 +1,87 @@
|
||||
# Source this file. Sets MEM0_API_KEY, MEM0_RESOLVED_USER_ID, and settings.
|
||||
#
|
||||
# API key resolution (first non-empty wins):
|
||||
# 1. MEM0_API_KEY env var (explicit / shell profile)
|
||||
# 2. CLAUDE_PLUGIN_OPTION_API_KEY (injected by Claude Code userConfig)
|
||||
# 3. CLAUDE_PLUGIN_OPTION_MEM0_API_KEY (legacy userConfig)
|
||||
# 4. Extract from shell profile files (~/.zshrc, ~/.bashrc, etc.)
|
||||
# Desktop app doesn't inherit shell env — this fallback covers users
|
||||
# who set MEM0_API_KEY in their profile but use the Desktop app.
|
||||
#
|
||||
# Settings: ~/.mem0/settings.json (user-editable, falls back to defaults)
|
||||
|
||||
_SCRIPT_DIR="$( cd "$(dirname "${BASH_SOURCE[0]:-$0}")" && pwd )"
|
||||
|
||||
# Resolve API key: env var > userConfig > shell profile extraction
|
||||
if [ -z "${MEM0_API_KEY:-}" ] && [ -n "${CLAUDE_PLUGIN_OPTION_API_KEY:-}" ]; then
|
||||
MEM0_API_KEY="$CLAUDE_PLUGIN_OPTION_API_KEY"
|
||||
export MEM0_API_KEY
|
||||
fi
|
||||
if [ -z "${MEM0_API_KEY:-}" ] && [ -n "${CLAUDE_PLUGIN_OPTION_MEM0_API_KEY:-}" ]; then
|
||||
MEM0_API_KEY="$CLAUDE_PLUGIN_OPTION_MEM0_API_KEY"
|
||||
export MEM0_API_KEY
|
||||
fi
|
||||
# Fallback: extract MEM0_API_KEY from shell profile files.
|
||||
# The Desktop app only reads PATH from shell profiles — env vars like
|
||||
# MEM0_API_KEY are not inherited. This grep-based extraction handles
|
||||
# the common `export MEM0_API_KEY=...` pattern without sourcing the
|
||||
# full profile (which could have side effects).
|
||||
if [ -z "${MEM0_API_KEY:-}" ]; then
|
||||
for _profile in "$HOME/.zshrc" "$HOME/.bashrc" "$HOME/.zprofile" "$HOME/.bash_profile" "$HOME/.profile"; do
|
||||
if [ -f "$_profile" ]; then
|
||||
_extracted=$(grep -E '^\s*(export\s+)?MEM0_API_KEY=' "$_profile" 2>/dev/null \
|
||||
| tail -1 \
|
||||
| sed 's/^[^=]*=//' \
|
||||
| sed "s/^[\"']//;s/[\"']$//" \
|
||||
| sed 's/#.*//' \
|
||||
| tr -d '[:space:]')
|
||||
# Only use literal values — skip variable references like ${OTHER_VAR}
|
||||
if [ -n "$_extracted" ] && [ "${_extracted#\$}" = "$_extracted" ]; then
|
||||
MEM0_API_KEY="$_extracted"
|
||||
export MEM0_API_KEY
|
||||
break
|
||||
fi
|
||||
fi
|
||||
done
|
||||
fi
|
||||
|
||||
_mem0_resolve_identity() {
|
||||
if [ -n "${MEM0_USER_ID:-}" ]; then
|
||||
printf '%s' "$MEM0_USER_ID"
|
||||
return
|
||||
fi
|
||||
printf '%s' "${USER:-default}"
|
||||
}
|
||||
|
||||
MEM0_RESOLVED_USER_ID="$(_mem0_resolve_identity)"
|
||||
export MEM0_RESOLVED_USER_ID
|
||||
|
||||
_MEM0_IDENTITY_ANNOTATION=""
|
||||
if [ -n "${MEM0_USER_ID:-}" ] && [ "$MEM0_USER_ID" != "${USER:-default}" ]; then
|
||||
_MEM0_IDENTITY_ANNOTATION=" (override; default: ${USER:-default})"
|
||||
fi
|
||||
export _MEM0_IDENTITY_ANNOTATION
|
||||
|
||||
# Load settings from ~/.mem0/settings.json
|
||||
if command -v python3 >/dev/null 2>&1; then
|
||||
_SETTINGS_JSON=$(PYTHONPATH="$_SCRIPT_DIR" python3 -c "from load_settings import load_settings; import json; print(json.dumps(load_settings()))" 2>/dev/null || echo "{}")
|
||||
MEM0_AUTO_SAVE=$(echo "$_SETTINGS_JSON" | python3 -c "import sys,json; print(str(json.load(sys.stdin).get('auto_save',True)).lower())" 2>/dev/null || echo "true")
|
||||
MEM0_AUTO_SEARCH=$(echo "$_SETTINGS_JSON" | python3 -c "import sys,json; print(str(json.load(sys.stdin).get('auto_search',True)).lower())" 2>/dev/null || echo "true")
|
||||
MEM0_SEARCH_LIMIT=$(echo "$_SETTINGS_JSON" | python3 -c "import sys,json; print(json.load(sys.stdin).get('search_limit',10))" 2>/dev/null || echo "10")
|
||||
MEM0_RETENTION_SESSION_DAYS=$(echo "$_SETTINGS_JSON" | python3 -c "import sys,json; print(json.load(sys.stdin).get('retention_session_days',90))" 2>/dev/null || echo "90")
|
||||
MEM0_CONFIDENCE_THRESHOLD=$(echo "$_SETTINGS_JSON" | python3 -c "import sys,json; print(json.load(sys.stdin).get('confidence_threshold',0.3))" 2>/dev/null || echo "0.3")
|
||||
MEM0_GLOBAL_SEARCH=$(echo "$_SETTINGS_JSON" | python3 -c "import sys,json; print(str(json.load(sys.stdin).get('global_search',False)).lower())" 2>/dev/null || echo "false")
|
||||
MEM0_DEBUG=$(echo "$_SETTINGS_JSON" | python3 -c "import sys,json; print(str(json.load(sys.stdin).get('debug',False)).lower())" 2>/dev/null || echo "false")
|
||||
else
|
||||
MEM0_AUTO_SAVE="true"
|
||||
MEM0_AUTO_SEARCH="true"
|
||||
MEM0_SEARCH_LIMIT="10"
|
||||
MEM0_RETENTION_SESSION_DAYS="90"
|
||||
MEM0_CONFIDENCE_THRESHOLD="0.3"
|
||||
MEM0_GLOBAL_SEARCH="false"
|
||||
MEM0_DEBUG="false"
|
||||
fi
|
||||
export MEM0_AUTO_SAVE MEM0_AUTO_SEARCH MEM0_SEARCH_LIMIT MEM0_RETENTION_SESSION_DAYS MEM0_CONFIDENCE_THRESHOLD MEM0_GLOBAL_SEARCH MEM0_DEBUG
|
||||
|
||||
# Also resolve project context
|
||||
. "$_SCRIPT_DIR/_project.sh"
|
||||
@@ -0,0 +1,175 @@
|
||||
"""Resolve mem0 project_id and branch.
|
||||
|
||||
Resolution priority (project_id):
|
||||
1. MEM0_PROJECT_ID env var (explicit override)
|
||||
2. ~/.mem0/project_map.json lookup by cwd
|
||||
2b. ~/.mem0/project_map.json lookup by remote hash (self-healing fallback)
|
||||
3. Git remote slug: strip protocol/prefix, strip .git, replace / and : with -
|
||||
e.g. git@github.com:mem0ai/mem0.git -> mem0ai-mem0
|
||||
4. Fallback: basename of cwd
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import hashlib
|
||||
import json
|
||||
import os
|
||||
import re
|
||||
import subprocess
|
||||
|
||||
|
||||
def resolve_project_id(cwd: str | None = None) -> str:
|
||||
if cwd is None:
|
||||
cwd = os.getcwd()
|
||||
|
||||
# 1. Explicit override
|
||||
explicit = os.environ.get("MEM0_PROJECT_ID", "").strip()
|
||||
if explicit:
|
||||
return explicit
|
||||
|
||||
# 2. project_map.json lookup
|
||||
map_path = os.path.expanduser("~/.mem0/project_map.json")
|
||||
if os.path.isfile(map_path):
|
||||
try:
|
||||
with open(map_path) as f:
|
||||
project_map = json.load(f)
|
||||
mapped = project_map.get(cwd, "").strip()
|
||||
if mapped:
|
||||
return mapped
|
||||
# 2b. Remote hash fallback (self-healing when folder is moved/renamed)
|
||||
remote_key = _remote_hash_key(cwd)
|
||||
if remote_key:
|
||||
mapped = project_map.get(remote_key, "").strip()
|
||||
if mapped:
|
||||
# Self-heal: write the new CWD key so future lookups are fast
|
||||
project_map[cwd] = mapped
|
||||
try:
|
||||
with open(map_path, "w") as f:
|
||||
json.dump(project_map, f, indent=2)
|
||||
except OSError:
|
||||
pass
|
||||
return mapped
|
||||
except (OSError, json.JSONDecodeError, AttributeError):
|
||||
pass
|
||||
|
||||
# 3. Git remote slug
|
||||
try:
|
||||
result = subprocess.run(
|
||||
["git", "remote", "get-url", "origin"],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
check=True,
|
||||
cwd=cwd,
|
||||
)
|
||||
remote_url = result.stdout.strip()
|
||||
if remote_url:
|
||||
slug = _remote_url_to_slug(remote_url)
|
||||
if slug:
|
||||
return slug
|
||||
except (subprocess.CalledProcessError, OSError):
|
||||
pass
|
||||
|
||||
# 4. Fallback: basename of cwd
|
||||
return os.path.basename(cwd) or "unknown"
|
||||
|
||||
|
||||
def resolve_branch(cwd: str | None = None) -> str:
|
||||
if cwd is None:
|
||||
cwd = os.getcwd()
|
||||
try:
|
||||
result = subprocess.run(
|
||||
["git", "branch", "--show-current"],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
check=True,
|
||||
cwd=cwd,
|
||||
)
|
||||
branch = result.stdout.strip()
|
||||
return branch if branch else "unknown"
|
||||
except (subprocess.CalledProcessError, OSError):
|
||||
return "unknown"
|
||||
|
||||
|
||||
def save_project_mapping(cwd: str, project_id: str) -> None:
|
||||
"""Write cwd -> project_id (and remote hash key -> project_id) into ~/.mem0/project_map.json."""
|
||||
mem0_dir = os.path.expanduser("~/.mem0")
|
||||
os.makedirs(mem0_dir, exist_ok=True)
|
||||
map_path = os.path.join(mem0_dir, "project_map.json")
|
||||
project_map: dict[str, str] = {}
|
||||
if os.path.isfile(map_path):
|
||||
try:
|
||||
with open(map_path) as f:
|
||||
project_map = json.load(f)
|
||||
except (OSError, json.JSONDecodeError):
|
||||
project_map = {}
|
||||
project_map[cwd] = project_id
|
||||
# Also write the remote hash key so the mapping survives folder moves/renames
|
||||
remote_key = _remote_hash_key(cwd)
|
||||
if remote_key:
|
||||
project_map[remote_key] = project_id
|
||||
with open(map_path, "w") as f:
|
||||
json.dump(project_map, f, indent=2)
|
||||
|
||||
|
||||
def _remote_hash_key(cwd: str | None = None) -> str:
|
||||
"""Return a stable key derived from the git remote URL.
|
||||
|
||||
Runs ``git config --get remote.origin.url`` in *cwd* and returns a string
|
||||
of the form ``remote:<sha256(url)[:16]>``. Returns an empty string when
|
||||
the directory is not a git repo or has no remote configured.
|
||||
"""
|
||||
if cwd is None:
|
||||
cwd = os.getcwd()
|
||||
try:
|
||||
result = subprocess.run(
|
||||
["git", "config", "--get", "remote.origin.url"],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
check=True,
|
||||
cwd=cwd,
|
||||
)
|
||||
url = result.stdout.strip()
|
||||
if not url:
|
||||
return ""
|
||||
digest = hashlib.sha256(url.encode()).hexdigest()[:16]
|
||||
return f"remote:{digest}"
|
||||
except (subprocess.CalledProcessError, OSError):
|
||||
return ""
|
||||
|
||||
|
||||
def _remote_url_to_slug(url: str) -> str:
|
||||
"""Convert a git remote URL to a deterministic slug.
|
||||
|
||||
Handles:
|
||||
- HTTPS: https://github.com/owner/repo.git
|
||||
- SSH: git@github.com:owner/repo.git
|
||||
- SSH: git@github.com-alias:owner/repo.git (custom host aliases)
|
||||
- ssh://: ssh://git@github.com/owner/repo.git
|
||||
- git://: git://github.com/owner/repo.git
|
||||
"""
|
||||
slug = url.strip()
|
||||
# Strip .git suffix
|
||||
if slug.endswith(".git"):
|
||||
slug = slug[:-4]
|
||||
# Strip protocol prefixes
|
||||
for prefix in ("https://", "http://", "ssh://", "git://"):
|
||||
if slug.startswith(prefix):
|
||||
slug = slug[len(prefix):]
|
||||
break
|
||||
else:
|
||||
# Handle git@ style (no protocol prefix matched)
|
||||
slug = re.sub(r"^git@", "", slug)
|
||||
# Replace the first colon (SSH host:path separator) with /
|
||||
slug = slug.replace(":", "/", 1)
|
||||
# Split on / and take last two components (owner, repo)
|
||||
parts = [p for p in slug.split("/") if p]
|
||||
if len(parts) >= 2:
|
||||
owner, repo = parts[-2], parts[-1]
|
||||
slug = f"{owner}-{repo}"
|
||||
elif parts:
|
||||
slug = parts[-1]
|
||||
else:
|
||||
return ""
|
||||
# Replace any remaining / and : with -
|
||||
slug = slug.replace("/", "-").replace(":", "-")
|
||||
return slug
|
||||
Executable
+77
@@ -0,0 +1,77 @@
|
||||
# Source this file. Sets MEM0_PROJECT_ID and MEM0_BRANCH.
|
||||
#
|
||||
# Resolution priority (project_id):
|
||||
# 1. MEM0_PROJECT_ID env var (explicit override)
|
||||
# 2. ~/.mem0/project_map.json lookup by $PWD (requires jq)
|
||||
# 3. Git remote slug: strip protocol/prefix, strip .git, replace / and : with -
|
||||
# e.g. git@github.com:mem0ai/mem0.git -> mem0ai-mem0
|
||||
# 4. Fallback: basename of $PWD
|
||||
#
|
||||
# Branch resolution:
|
||||
# git branch --show-current, fallback "unknown"
|
||||
|
||||
_mem0_resolve_project_id() {
|
||||
# 1. Explicit override
|
||||
if [ -n "${MEM0_PROJECT_ID:-}" ]; then
|
||||
printf '%s' "$MEM0_PROJECT_ID"
|
||||
return
|
||||
fi
|
||||
|
||||
# 2. project_map.json lookup by $PWD
|
||||
_mem0_map="$HOME/.mem0/project_map.json"
|
||||
if [ -f "$_mem0_map" ] && command -v jq >/dev/null 2>&1; then
|
||||
_mem0_mapped=$(jq -r --arg cwd "$PWD" '.[$cwd] // empty' "$_mem0_map" 2>/dev/null)
|
||||
if [ -n "$_mem0_mapped" ]; then
|
||||
printf '%s' "$_mem0_mapped"
|
||||
return
|
||||
fi
|
||||
fi
|
||||
|
||||
# 3. Git remote slug
|
||||
_mem0_remote_url=$(git remote get-url origin 2>/dev/null)
|
||||
if [ -n "$_mem0_remote_url" ]; then
|
||||
_mem0_slug="$_mem0_remote_url"
|
||||
# Strip .git suffix
|
||||
_mem0_slug="${_mem0_slug%.git}"
|
||||
# Strip protocol prefixes
|
||||
_mem0_slug="${_mem0_slug#https://}"
|
||||
_mem0_slug="${_mem0_slug#http://}"
|
||||
_mem0_slug="${_mem0_slug#ssh://}"
|
||||
_mem0_slug="${_mem0_slug#git://}"
|
||||
_mem0_slug="${_mem0_slug#git@}"
|
||||
# Replace first colon (SSH host:path separator) with /
|
||||
# shellcheck disable=SC2039
|
||||
_mem0_slug="${_mem0_slug/://}"
|
||||
# Keep only the last two path components (owner/repo)
|
||||
_mem0_owner=$(printf '%s' "$_mem0_slug" | awk -F'/' '{print $(NF-1)}')
|
||||
_mem0_repo=$(printf '%s' "$_mem0_slug" | awk -F'/' '{print $NF}')
|
||||
_mem0_slug="${_mem0_owner}-${_mem0_repo}"
|
||||
# Replace any remaining / and : with -
|
||||
# shellcheck disable=SC2039
|
||||
_mem0_slug="${_mem0_slug//\//-}"
|
||||
# shellcheck disable=SC2039
|
||||
_mem0_slug="${_mem0_slug//:/-}"
|
||||
if [ -n "$_mem0_slug" ]; then
|
||||
printf '%s' "$_mem0_slug"
|
||||
_MEM0_PERSIST_CWD="$PWD" _MEM0_PERSIST_SLUG="$_mem0_slug" python3 -c "
|
||||
import os, sys
|
||||
sys.path.insert(0, '$(dirname "${BASH_SOURCE[0]:-$0}")')
|
||||
from _project import save_project_mapping
|
||||
save_project_mapping(os.environ['_MEM0_PERSIST_CWD'], os.environ['_MEM0_PERSIST_SLUG'])
|
||||
" 2>/dev/null || true
|
||||
return
|
||||
fi
|
||||
fi
|
||||
|
||||
# 4. Fallback: basename of $PWD
|
||||
printf '%s' "$(basename "$PWD")"
|
||||
}
|
||||
|
||||
_mem0_resolve_branch() {
|
||||
git branch --show-current 2>/dev/null || printf 'unknown'
|
||||
}
|
||||
|
||||
MEM0_PROJECT_ID="$(_mem0_resolve_project_id)"
|
||||
MEM0_BRANCH="$(_mem0_resolve_branch)"
|
||||
export MEM0_PROJECT_ID
|
||||
export MEM0_BRANCH
|
||||
@@ -0,0 +1,84 @@
|
||||
"""Shared mem0 search API helper.
|
||||
|
||||
Wraps POST /v3/memories/search/ into a single function call.
|
||||
All pre-fetch hooks use this instead of duplicating urllib boilerplate.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import urllib.request
|
||||
|
||||
SEARCH_URL = "https://api.mem0.ai/v3/memories/search/"
|
||||
SEARCH_TIMEOUT = 5
|
||||
|
||||
|
||||
def _do_search(api_key: str, payload: dict) -> list[dict]:
|
||||
body = json.dumps(payload).encode()
|
||||
req = urllib.request.Request(
|
||||
SEARCH_URL,
|
||||
data=body,
|
||||
headers={"Authorization": f"Token {api_key}", "Content-Type": "application/json"},
|
||||
method="POST",
|
||||
)
|
||||
with urllib.request.urlopen(req, timeout=SEARCH_TIMEOUT) as r:
|
||||
data = json.loads(r.read())
|
||||
return data if isinstance(data, list) else data.get("results", [])
|
||||
|
||||
|
||||
def search_memories(
|
||||
api_key: str,
|
||||
user_id: str,
|
||||
project_id: str,
|
||||
query: str,
|
||||
metadata_type: str | None = None,
|
||||
metadata_filters: dict | None = None,
|
||||
top_k: int = 3,
|
||||
min_score: float = 0.0,
|
||||
rerank: bool = False,
|
||||
threshold: float = 0.3,
|
||||
global_search: bool = False,
|
||||
) -> list[dict]:
|
||||
if not api_key:
|
||||
return []
|
||||
|
||||
if global_search:
|
||||
filters: dict = {"OR": [{"user_id": "*"}]}
|
||||
else:
|
||||
base_clauses: list[dict] = [{"user_id": user_id}, {"app_id": project_id}]
|
||||
if metadata_type:
|
||||
base_clauses.append({"metadata": {"type": metadata_type}})
|
||||
if metadata_filters:
|
||||
for key, value in metadata_filters.items():
|
||||
base_clauses.append({"metadata": {key: value}})
|
||||
filters = {"AND": base_clauses}
|
||||
|
||||
base_payload: dict = {"query": query, "top_k": top_k, "threshold": threshold}
|
||||
if rerank:
|
||||
base_payload["rerank"] = True
|
||||
|
||||
try:
|
||||
payload = {**base_payload, "filters": filters}
|
||||
results = _do_search(api_key, payload)[:top_k]
|
||||
|
||||
if min_score > 0:
|
||||
results = [m for m in results if m.get("score", 0) >= min_score]
|
||||
return results
|
||||
except Exception:
|
||||
return []
|
||||
|
||||
|
||||
def format_results_for_context(
|
||||
memories: list[dict],
|
||||
heading: str = "Relevant memories",
|
||||
) -> str:
|
||||
if not memories:
|
||||
return ""
|
||||
lines = [f"### {heading}", ""]
|
||||
for m in memories:
|
||||
mid = m.get("id", "?")[:8]
|
||||
text = m.get("memory", "")[:200]
|
||||
cat = (m.get("metadata") or {}).get("type", "unknown")
|
||||
lines.append(f"- [{cat}] {text} [mem0:{mid}]")
|
||||
lines.append("")
|
||||
return "\n".join(lines)
|
||||
+210
@@ -0,0 +1,210 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Auto-capture recent conversation exchanges into mem0.
|
||||
|
||||
Runs in the background from UserPromptSubmit hook (every 3rd message).
|
||||
Reads the last few exchanges from the transcript, sends them to the
|
||||
mem0 API with infer=True so the platform extracts facts automatically.
|
||||
|
||||
Input: env vars (MEM0_API_KEY, MEM0_RESOLVED_USER_ID, MEM0_PROJECT_ID, etc.)
|
||||
argv[1] = transcript_path
|
||||
Output: stderr logs only (exit 0 always — must not block)
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import sys
|
||||
import urllib.error
|
||||
import urllib.request
|
||||
|
||||
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
|
||||
from _identity import resolve_api_key, resolve_user_id
|
||||
from _project import resolve_branch, resolve_project_id
|
||||
|
||||
log = logging.getLogger("mem0-auto-capture")
|
||||
log.setLevel(logging.DEBUG)
|
||||
_handler = logging.StreamHandler(sys.stderr)
|
||||
_handler.setFormatter(logging.Formatter("[mem0-auto-capture] %(message)s"))
|
||||
log.addHandler(_handler)
|
||||
|
||||
if os.environ.get("MEM0_DEBUG"):
|
||||
_log_dir = os.path.expanduser("~/.mem0")
|
||||
try:
|
||||
os.makedirs(_log_dir, exist_ok=True)
|
||||
_fh = logging.FileHandler(os.path.join(_log_dir, "hooks.log"))
|
||||
_fh.setFormatter(logging.Formatter("[mem0-auto-capture] %(asctime)s %(message)s"))
|
||||
log.addHandler(_fh)
|
||||
except OSError:
|
||||
pass
|
||||
|
||||
API_URL = "https://api.mem0.ai"
|
||||
TAIL_LINES = 200
|
||||
MAX_CONTENT_CHARS = 8000
|
||||
MIN_CONTENT_CHARS = 100
|
||||
|
||||
|
||||
def tail_lines(filepath: str, n: int) -> list[str]:
|
||||
try:
|
||||
with open(filepath, "rb") as f:
|
||||
f.seek(0, 2)
|
||||
file_size = f.tell()
|
||||
if file_size == 0:
|
||||
return []
|
||||
chunk_size = min(file_size, n * 4096)
|
||||
f.seek(max(0, file_size - chunk_size))
|
||||
data = f.read().decode("utf-8", errors="replace")
|
||||
return data.splitlines()[-n:]
|
||||
except OSError:
|
||||
return []
|
||||
|
||||
|
||||
def extract_recent_exchanges(lines: list[str], max_exchanges: int = 3) -> list[dict]:
|
||||
"""Extract the last N user+assistant message pairs from the transcript JSONL."""
|
||||
messages = []
|
||||
for line in lines:
|
||||
line = line.strip()
|
||||
if not line:
|
||||
continue
|
||||
try:
|
||||
entry = json.loads(line)
|
||||
except json.JSONDecodeError:
|
||||
continue
|
||||
|
||||
if entry.get("isCompactSummary"):
|
||||
continue
|
||||
|
||||
msg = entry.get("message", {})
|
||||
role = msg.get("role", "")
|
||||
if role not in ("user", "assistant"):
|
||||
continue
|
||||
|
||||
content = msg.get("content", "")
|
||||
if isinstance(content, list):
|
||||
parts = []
|
||||
for block in content:
|
||||
if isinstance(block, str):
|
||||
parts.append(block)
|
||||
elif isinstance(block, dict) and block.get("type") == "text":
|
||||
parts.append(block.get("text", ""))
|
||||
content = "\n".join(parts).strip()
|
||||
|
||||
if not content or len(content) < 20:
|
||||
continue
|
||||
|
||||
# Skip tool-call-only assistant messages
|
||||
if role == "assistant" and content.startswith("{"):
|
||||
continue
|
||||
|
||||
messages.append({"role": role, "content": content[:2000]})
|
||||
|
||||
# Take last N exchanges (pairs of user+assistant)
|
||||
if not messages:
|
||||
return []
|
||||
|
||||
result = messages[-(max_exchanges * 2):]
|
||||
return result
|
||||
|
||||
|
||||
def store_exchange(api_key: str, messages: list[dict], user_id: str,
|
||||
project_id: str, branch: str, session_id: str) -> bool:
|
||||
metadata = {
|
||||
"type": "auto_capture",
|
||||
"source": "auto_capture",
|
||||
"confidence": 0.7,
|
||||
}
|
||||
if branch:
|
||||
metadata["branch"] = branch
|
||||
if session_id:
|
||||
metadata["session_id"] = session_id
|
||||
|
||||
body = {
|
||||
"messages": messages,
|
||||
"user_id": user_id,
|
||||
"app_id": project_id,
|
||||
"metadata": metadata,
|
||||
"infer": True,
|
||||
}
|
||||
|
||||
data = json.dumps(body).encode("utf-8")
|
||||
req = urllib.request.Request(
|
||||
f"{API_URL}/v3/memories/add/",
|
||||
data=data,
|
||||
headers={
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Token {api_key}",
|
||||
},
|
||||
method="POST",
|
||||
)
|
||||
try:
|
||||
with urllib.request.urlopen(req, timeout=15) as resp:
|
||||
if resp.status in (200, 201):
|
||||
result = json.loads(resp.read())
|
||||
log.info("Auto-captured: event_id=%s status=%s",
|
||||
result.get("event_id", "?"), result.get("status", "?"))
|
||||
return True
|
||||
log.warning("API returned status %d", resp.status)
|
||||
return False
|
||||
except urllib.error.URLError as e:
|
||||
log.warning("API call failed: %s", e)
|
||||
return False
|
||||
|
||||
|
||||
def main():
|
||||
api_key = resolve_api_key()
|
||||
if not api_key:
|
||||
log.debug("MEM0_API_KEY not set, skipping")
|
||||
return
|
||||
|
||||
if len(sys.argv) < 2:
|
||||
log.debug("No transcript_path argument")
|
||||
return
|
||||
|
||||
transcript_path = sys.argv[1]
|
||||
if not transcript_path or not os.path.isfile(transcript_path):
|
||||
log.debug("Transcript not found: %s", transcript_path)
|
||||
return
|
||||
|
||||
user_id = resolve_user_id()
|
||||
project_id = resolve_project_id()
|
||||
branch = resolve_branch()
|
||||
session_id = ""
|
||||
sid_file = f"/tmp/mem0_session_id_{os.environ.get('USER', 'default')}"
|
||||
if os.path.isfile(sid_file):
|
||||
try:
|
||||
with open(sid_file) as f:
|
||||
session_id = f.read().strip()
|
||||
except OSError:
|
||||
pass
|
||||
|
||||
lines = tail_lines(transcript_path, TAIL_LINES)
|
||||
if not lines:
|
||||
log.debug("Transcript empty")
|
||||
return
|
||||
|
||||
messages = extract_recent_exchanges(lines, max_exchanges=4)
|
||||
if not messages:
|
||||
log.debug("No substantial exchanges found")
|
||||
return
|
||||
|
||||
total_chars = sum(len(m["content"]) for m in messages)
|
||||
if total_chars < MIN_CONTENT_CHARS:
|
||||
log.debug("Exchanges too short (%d chars), skipping", total_chars)
|
||||
return
|
||||
|
||||
log.info("Auto-capturing %d messages (%d chars)", len(messages), total_chars)
|
||||
if store_exchange(api_key, messages, user_id, project_id, branch, session_id):
|
||||
try:
|
||||
import session_stats
|
||||
session_stats.record_add("auto_capture")
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
try:
|
||||
main()
|
||||
except Exception as e:
|
||||
log.error("Unexpected error: %s", e)
|
||||
sys.exit(0)
|
||||
@@ -0,0 +1,374 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Auto-import declarative project files into mem0.
|
||||
|
||||
Runs in the background from the SessionStart hook (startup only).
|
||||
Imports CLAUDE.md, AGENTS.md, .cursorrules, .windsurfrules, mem0.md
|
||||
into mem0 as project profile memories, skipping unchanged files via
|
||||
SHA-256 hashing.
|
||||
|
||||
Input: MEM0_CWD env var (optional, defaults to os.getcwd())
|
||||
Output: stderr logs only (exit 0 always — must not block)
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import hashlib
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import sys
|
||||
import urllib.error
|
||||
import urllib.request
|
||||
|
||||
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
|
||||
from _chunking import filter_and_truncate, split_by_headers
|
||||
from _identity import resolve_api_key, resolve_user_id
|
||||
from _project import resolve_branch, resolve_project_id, save_project_mapping
|
||||
|
||||
log = logging.getLogger("mem0-auto-import")
|
||||
log.setLevel(logging.DEBUG)
|
||||
_handler = logging.StreamHandler(sys.stderr)
|
||||
_handler.setFormatter(logging.Formatter("[mem0-auto-import] %(message)s"))
|
||||
log.addHandler(_handler)
|
||||
|
||||
if os.environ.get("MEM0_DEBUG"):
|
||||
_log_dir = os.path.expanduser("~/.mem0")
|
||||
try:
|
||||
os.makedirs(_log_dir, exist_ok=True)
|
||||
_file_handler = logging.FileHandler(os.path.join(_log_dir, "hooks.log"))
|
||||
_file_handler.setFormatter(logging.Formatter("[mem0-auto-import] %(asctime)s %(message)s"))
|
||||
log.addHandler(_file_handler)
|
||||
except OSError:
|
||||
pass
|
||||
|
||||
API_URL = "https://api.mem0.ai"
|
||||
MAX_FILE_SIZE = 100_000 # skip files over 100 KB
|
||||
TARGET_FILES = ["CLAUDE.md", "AGENTS.md", ".cursorrules", ".windsurfrules", "mem0.md"]
|
||||
HASH_STORE = os.path.expanduser("~/.mem0/file_hashes.json")
|
||||
LOCK_FILE = os.path.expanduser("~/.mem0/auto_import.lock")
|
||||
|
||||
|
||||
def _acquire_lock() -> bool:
|
||||
"""Try to acquire a file lock. Returns False if another instance is running."""
|
||||
try:
|
||||
os.makedirs(os.path.dirname(LOCK_FILE), exist_ok=True)
|
||||
fd = os.open(LOCK_FILE, os.O_CREAT | os.O_EXCL | os.O_WRONLY)
|
||||
os.write(fd, str(os.getpid()).encode())
|
||||
os.close(fd)
|
||||
return True
|
||||
except FileExistsError:
|
||||
try:
|
||||
mtime = os.path.getmtime(LOCK_FILE)
|
||||
import time
|
||||
if time.time() - mtime > 120:
|
||||
os.unlink(LOCK_FILE)
|
||||
return _acquire_lock()
|
||||
except OSError:
|
||||
pass
|
||||
return False
|
||||
|
||||
|
||||
def _release_lock() -> None:
|
||||
try:
|
||||
os.unlink(LOCK_FILE)
|
||||
except OSError:
|
||||
pass
|
||||
|
||||
|
||||
def _git_root(cwd: str) -> str:
|
||||
"""Return the git repo root, or empty string if not in a repo."""
|
||||
import subprocess
|
||||
try:
|
||||
result = subprocess.run(
|
||||
["git", "rev-parse", "--show-toplevel"],
|
||||
cwd=cwd, capture_output=True, text=True, timeout=5,
|
||||
)
|
||||
if result.returncode == 0:
|
||||
return result.stdout.strip()
|
||||
except (OSError, subprocess.TimeoutExpired):
|
||||
pass
|
||||
return ""
|
||||
|
||||
|
||||
def sha256_file(path: str) -> str:
|
||||
"""Return the hex SHA-256 digest of a file."""
|
||||
h = hashlib.sha256()
|
||||
with open(path, "rb") as f:
|
||||
for chunk in iter(lambda: f.read(65536), b""):
|
||||
h.update(chunk)
|
||||
return h.hexdigest()
|
||||
|
||||
|
||||
def load_hashes() -> dict[str, str]:
|
||||
"""Load the hash store from disk; return empty dict on any error."""
|
||||
if not os.path.isfile(HASH_STORE):
|
||||
return {}
|
||||
try:
|
||||
with open(HASH_STORE) as f:
|
||||
return json.load(f)
|
||||
except (OSError, json.JSONDecodeError):
|
||||
return {}
|
||||
|
||||
|
||||
def save_hashes(hashes: dict[str, str]) -> None:
|
||||
"""Persist the hash store to disk."""
|
||||
mem0_dir = os.path.expanduser("~/.mem0")
|
||||
os.makedirs(mem0_dir, exist_ok=True)
|
||||
try:
|
||||
with open(HASH_STORE, "w") as f:
|
||||
json.dump(hashes, f, indent=2)
|
||||
except OSError as e:
|
||||
log.warning("Could not save hash store: %s", e)
|
||||
|
||||
|
||||
def already_imported(api_key: str, user_id: str, project_id: str, filename: str) -> bool:
|
||||
body = json.dumps({
|
||||
"query": filename,
|
||||
"filters": {
|
||||
"AND": [
|
||||
{"user_id": user_id},
|
||||
{"app_id": project_id},
|
||||
{"metadata": {"source": "auto-import"}},
|
||||
]
|
||||
},
|
||||
"top_k": 10,
|
||||
"threshold": 0.0,
|
||||
}).encode()
|
||||
req = urllib.request.Request(
|
||||
f"{API_URL}/v3/memories/search/",
|
||||
data=body,
|
||||
headers={"Content-Type": "application/json", "Authorization": f"Token {api_key}"},
|
||||
method="POST",
|
||||
)
|
||||
try:
|
||||
with urllib.request.urlopen(req, timeout=5) as r:
|
||||
data = json.loads(r.read())
|
||||
results = data if isinstance(data, list) else data.get("results", [])
|
||||
for result in results:
|
||||
meta = result.get("metadata", {}) if isinstance(result, dict) else {}
|
||||
file_field = meta.get("file", "")
|
||||
if file_field == filename or file_field.startswith(f"{filename}["):
|
||||
return True
|
||||
return False
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
|
||||
def _delete_stale_chunks(api_key: str, user_id: str, project_id: str, filename: str) -> int:
|
||||
"""Find and delete existing chunks for a file before re-import. Returns count deleted."""
|
||||
body = json.dumps({
|
||||
"query": filename,
|
||||
"filters": {
|
||||
"AND": [
|
||||
{"user_id": user_id},
|
||||
{"app_id": project_id},
|
||||
{"metadata": {"source": "auto-import"}},
|
||||
]
|
||||
},
|
||||
"top_k": 20,
|
||||
"threshold": 0.0,
|
||||
}).encode()
|
||||
req = urllib.request.Request(
|
||||
f"{API_URL}/v3/memories/search/",
|
||||
data=body,
|
||||
headers={"Content-Type": "application/json", "Authorization": f"Token {api_key}"},
|
||||
method="POST",
|
||||
)
|
||||
ids_to_delete = []
|
||||
try:
|
||||
with urllib.request.urlopen(req, timeout=10) as r:
|
||||
data = json.loads(r.read())
|
||||
results = data if isinstance(data, list) else data.get("results", [])
|
||||
for result in results:
|
||||
if not isinstance(result, dict):
|
||||
continue
|
||||
meta = result.get("metadata", {})
|
||||
file_field = meta.get("file", "")
|
||||
if file_field == filename or file_field.startswith(f"{filename}["):
|
||||
mid = result.get("id")
|
||||
if mid:
|
||||
ids_to_delete.append(mid)
|
||||
except Exception as e:
|
||||
log.warning("Failed to search for stale chunks of %s: %s", filename, e)
|
||||
return 0
|
||||
|
||||
deleted = 0
|
||||
for mid in ids_to_delete:
|
||||
try:
|
||||
del_req = urllib.request.Request(
|
||||
f"{API_URL}/v1/memories/{mid}/",
|
||||
headers={"Authorization": f"Token {api_key}"},
|
||||
method="DELETE",
|
||||
)
|
||||
with urllib.request.urlopen(del_req, timeout=10):
|
||||
deleted += 1
|
||||
except Exception as e:
|
||||
log.warning("Failed to delete stale chunk %s: %s", mid, e)
|
||||
|
||||
if deleted:
|
||||
log.info("Deleted %d stale chunk(s) for %s before re-import", deleted, filename)
|
||||
return deleted
|
||||
|
||||
|
||||
def post_memory(api_key: str, content: str, user_id: str, filename: str, project_id: str, branch: str = "") -> bool:
|
||||
"""POST a project profile memory to the Mem0 REST API."""
|
||||
metadata = {
|
||||
"type": "project_profile",
|
||||
"file": filename,
|
||||
"source": "auto-import",
|
||||
}
|
||||
if branch:
|
||||
metadata["branch"] = branch
|
||||
body = {
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": f"## Project Profile: {filename}\n\nProject: {project_id}\n\n{content}",
|
||||
}
|
||||
],
|
||||
"user_id": user_id,
|
||||
"app_id": project_id,
|
||||
"metadata": metadata,
|
||||
"infer": False,
|
||||
}
|
||||
|
||||
data = json.dumps(body).encode("utf-8")
|
||||
req = urllib.request.Request(
|
||||
f"{API_URL}/v3/memories/add/",
|
||||
data=data,
|
||||
headers={
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Token {api_key}",
|
||||
},
|
||||
method="POST",
|
||||
)
|
||||
|
||||
try:
|
||||
with urllib.request.urlopen(req, timeout=15) as resp:
|
||||
if resp.status in (200, 201):
|
||||
log.info("Imported %s (project=%s)", filename, project_id)
|
||||
return True
|
||||
log.warning("API returned status %d for %s", resp.status, filename)
|
||||
return False
|
||||
except urllib.error.URLError as e:
|
||||
log.warning("API call failed for %s: %s", filename, e)
|
||||
return False
|
||||
|
||||
|
||||
def main() -> None:
|
||||
api_key = resolve_api_key()
|
||||
if not api_key:
|
||||
log.debug("MEM0_API_KEY not set, skipping auto-import")
|
||||
return
|
||||
|
||||
cwd = os.environ.get("MEM0_CWD", "").strip() or os.getcwd()
|
||||
user_id = resolve_user_id()
|
||||
project_id = resolve_project_id(cwd)
|
||||
branch = resolve_branch(cwd)
|
||||
|
||||
save_project_mapping(cwd, project_id)
|
||||
|
||||
git_root = _git_root(cwd)
|
||||
search_dirs = [cwd]
|
||||
if git_root and os.path.realpath(git_root) != os.path.realpath(cwd):
|
||||
search_dirs.append(git_root)
|
||||
|
||||
log.debug("Auto-import started: cwd=%s git_root=%s project=%s user=%s branch=%s", cwd, git_root or "(none)", project_id, user_id, branch)
|
||||
|
||||
hashes = load_hashes()
|
||||
updated = False
|
||||
seen_content_hashes: set[str] = set()
|
||||
|
||||
for filename in TARGET_FILES:
|
||||
filepath = ""
|
||||
for search_dir in search_dirs:
|
||||
candidate = os.path.join(search_dir, filename)
|
||||
if os.path.isfile(candidate):
|
||||
filepath = candidate
|
||||
break
|
||||
|
||||
if not filepath:
|
||||
log.debug("Not found, skipping: %s", filename)
|
||||
continue
|
||||
|
||||
filepath = os.path.realpath(filepath)
|
||||
|
||||
try:
|
||||
file_size = os.path.getsize(filepath)
|
||||
except OSError:
|
||||
log.debug("Cannot stat %s, skipping", filename)
|
||||
continue
|
||||
|
||||
if file_size > MAX_FILE_SIZE:
|
||||
log.debug("Skipping %s: size %d exceeds %d bytes", filename, file_size, MAX_FILE_SIZE)
|
||||
continue
|
||||
|
||||
try:
|
||||
current_hash = sha256_file(filepath)
|
||||
except OSError as e:
|
||||
log.debug("Cannot hash %s: %s", filename, e)
|
||||
continue
|
||||
|
||||
if current_hash in seen_content_hashes:
|
||||
log.debug("Duplicate content, skipping: %s (same as earlier file)", filename)
|
||||
continue
|
||||
seen_content_hashes.add(current_hash)
|
||||
|
||||
hash_key = f"{project_id}:{branch}:{filename}" if branch else f"{project_id}:{filename}"
|
||||
if hashes.get(hash_key) == current_hash:
|
||||
if already_imported(api_key, user_id, project_id, filename):
|
||||
log.debug("Unchanged and still in mem0, skipping: %s", filename)
|
||||
continue
|
||||
log.info("Hash matches but memories missing server-side, re-importing: %s", filename)
|
||||
|
||||
elif already_imported(api_key, user_id, project_id, filename):
|
||||
log.debug("Already in mem0, updating hash store: %s", filename)
|
||||
hashes[hash_key] = current_hash
|
||||
updated = True
|
||||
continue
|
||||
|
||||
try:
|
||||
with open(filepath, encoding="utf-8", errors="replace") as f:
|
||||
content = f.read()
|
||||
except OSError as e:
|
||||
log.debug("Cannot read %s: %s", filename, e)
|
||||
continue
|
||||
|
||||
_delete_stale_chunks(api_key, user_id, project_id, filename)
|
||||
|
||||
is_markdown = filename.endswith(".md")
|
||||
if is_markdown:
|
||||
chunks = filter_and_truncate(split_by_headers(content))
|
||||
else:
|
||||
chunks = filter_and_truncate([content])
|
||||
|
||||
if not chunks:
|
||||
chunks = [content[:10000]]
|
||||
|
||||
success = True
|
||||
for i, chunk in enumerate(chunks):
|
||||
chunk_name = f"{filename}[{i+1}/{len(chunks)}]" if len(chunks) > 1 else filename
|
||||
if not post_memory(api_key, chunk, user_id, chunk_name, project_id, branch):
|
||||
success = False
|
||||
|
||||
if success:
|
||||
hashes[hash_key] = current_hash
|
||||
updated = True
|
||||
|
||||
if updated:
|
||||
save_hashes(hashes)
|
||||
else:
|
||||
log.debug("No files imported this run")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
if not _acquire_lock():
|
||||
log.debug("Another auto_import instance is running — skipping")
|
||||
sys.exit(0)
|
||||
try:
|
||||
main()
|
||||
except Exception as e:
|
||||
log.error("Unexpected error: %s", e)
|
||||
finally:
|
||||
_release_lock()
|
||||
sys.exit(0)
|
||||
@@ -0,0 +1,236 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Auto-configure mem0's coding-category taxonomy in the background.
|
||||
|
||||
Runs from the SessionStart hook (startup only), exactly like auto_import.py.
|
||||
mem0 auto-tags every memory with `categories`; by default that list is
|
||||
consumer-oriented (food, hobbies, ...), which is useless for code. This script
|
||||
replaces it with the coding-focused taxonomy defined in
|
||||
``setup_coding_categories.CODING_CATEGORIES`` so search and retrieval are tuned
|
||||
for development work — without the user ever being asked during onboarding.
|
||||
|
||||
Design (mirrors auto_import.py):
|
||||
- Resolve the API key; do nothing if it is absent.
|
||||
- Gate on a state file (``~/.mem0/categories_setup.json``) keyed by a hash of
|
||||
the API key -> a hash of the taxonomy. Categories are scoped to the mem0
|
||||
*project* tied to the API key (NOT to the local repo), so this only needs to
|
||||
run once per account, and re-runs only if the taxonomy itself changes.
|
||||
- Hold a lock file so concurrent sessions don't race.
|
||||
- Reuse the proven SDK path (``client.project.update``) via the plugin venv.
|
||||
- Always exit 0; log to stderr only. Must never block a session.
|
||||
|
||||
Run with no arguments (background) or in the foreground for onboarding to print
|
||||
a parseable status line.
|
||||
|
||||
Requires MEM0_API_KEY (or CLAUDE_PLUGIN_OPTION_API_KEY) and the mem0ai SDK,
|
||||
which ensure_deps.sh installs into ${CLAUDE_PLUGIN_DATA}/venv on session start.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import hashlib
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import sys
|
||||
import time
|
||||
|
||||
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
|
||||
# Importing setup_coding_categories also injects the plugin venv's site-packages
|
||||
# onto sys.path (its module-level bootstrap), so ``from mem0 import MemoryClient``
|
||||
# works even when this script is run with the system python3.
|
||||
from _identity import resolve_api_key # noqa: E402
|
||||
from setup_coding_categories import CODING_CATEGORIES, _categories_match # noqa: E402
|
||||
|
||||
log = logging.getLogger("mem0-auto-categories")
|
||||
log.setLevel(logging.DEBUG)
|
||||
_handler = logging.StreamHandler(sys.stderr)
|
||||
_handler.setFormatter(logging.Formatter("[mem0-auto-categories] %(message)s"))
|
||||
log.addHandler(_handler)
|
||||
|
||||
if os.environ.get("MEM0_DEBUG"):
|
||||
_log_dir = os.path.expanduser("~/.mem0")
|
||||
try:
|
||||
os.makedirs(_log_dir, exist_ok=True)
|
||||
_file_handler = logging.FileHandler(os.path.join(_log_dir, "hooks.log"))
|
||||
_file_handler.setFormatter(logging.Formatter("[mem0-auto-categories] %(asctime)s %(message)s"))
|
||||
log.addHandler(_file_handler)
|
||||
except OSError:
|
||||
pass
|
||||
|
||||
STATE_FILE = os.path.expanduser("~/.mem0/categories_setup.json")
|
||||
LOCK_FILE = os.path.expanduser("~/.mem0/categories_setup.lock")
|
||||
|
||||
|
||||
# --------------------------------------------------------------------------- #
|
||||
# Fingerprints #
|
||||
# --------------------------------------------------------------------------- #
|
||||
def categories_fingerprint(categories: list = CODING_CATEGORIES) -> str:
|
||||
"""Stable, order-independent 16-hex digest of the category taxonomy.
|
||||
|
||||
Reordering the categories yields the same fingerprint; adding, removing, or
|
||||
editing a category changes it (so the taxonomy re-applies on upgrade).
|
||||
"""
|
||||
pairs = sorted(
|
||||
(str(key), str(value))
|
||||
for entry in categories
|
||||
if isinstance(entry, dict)
|
||||
for key, value in entry.items()
|
||||
)
|
||||
payload = json.dumps(pairs, sort_keys=True, ensure_ascii=False)
|
||||
return hashlib.sha256(payload.encode("utf-8")).hexdigest()[:16]
|
||||
|
||||
|
||||
def apikey_fingerprint(api_key: str) -> str:
|
||||
"""Opaque 16-hex digest of the API key. Never stores the key itself."""
|
||||
return hashlib.sha256(api_key.encode("utf-8")).hexdigest()[:16]
|
||||
|
||||
|
||||
# --------------------------------------------------------------------------- #
|
||||
# State file #
|
||||
# --------------------------------------------------------------------------- #
|
||||
def load_state(path: str = STATE_FILE) -> dict:
|
||||
"""Load the apikey-fingerprint -> categories-fingerprint map; {} on any error."""
|
||||
if not os.path.isfile(path):
|
||||
return {}
|
||||
try:
|
||||
with open(path) as f:
|
||||
data = json.load(f)
|
||||
return data if isinstance(data, dict) else {}
|
||||
except (OSError, json.JSONDecodeError):
|
||||
return {}
|
||||
|
||||
|
||||
def save_state(state: dict, path: str = STATE_FILE) -> None:
|
||||
"""Persist the state map, creating the parent directory if needed."""
|
||||
parent = os.path.dirname(path)
|
||||
if parent:
|
||||
try:
|
||||
os.makedirs(parent, exist_ok=True)
|
||||
except OSError as e:
|
||||
log.warning("Could not create state dir: %s", e)
|
||||
return
|
||||
try:
|
||||
with open(path, "w") as f:
|
||||
json.dump(state, f, indent=2)
|
||||
except OSError as e:
|
||||
log.warning("Could not save categories state: %s", e)
|
||||
|
||||
|
||||
def is_applied(state: dict, key_fp: str, cat_fp: str) -> bool:
|
||||
"""True only when this API key has already had this exact taxonomy applied."""
|
||||
return state.get(key_fp) == cat_fp
|
||||
|
||||
|
||||
# --------------------------------------------------------------------------- #
|
||||
# SDK interaction (client injected for testability) #
|
||||
# --------------------------------------------------------------------------- #
|
||||
def make_client():
|
||||
"""Construct a MemoryClient. Imported lazily so this module loads without the SDK."""
|
||||
from mem0 import MemoryClient
|
||||
|
||||
return MemoryClient()
|
||||
|
||||
|
||||
def fetch_current_categories(client) -> list | None:
|
||||
"""Return the project's current custom_categories, or None if unavailable."""
|
||||
current = client.project.get(fields=["custom_categories"])
|
||||
if isinstance(current, dict):
|
||||
return current.get("custom_categories")
|
||||
return None
|
||||
|
||||
|
||||
def apply_categories(client, proposed: list = CODING_CATEGORIES) -> str:
|
||||
"""Install the coding taxonomy if it isn't already in place.
|
||||
|
||||
Returns "already-configured" when the project already matches (no write), or
|
||||
"applied" after a successful ``project.update``. Raises on API failure.
|
||||
"""
|
||||
current = fetch_current_categories(client)
|
||||
if _categories_match(current, proposed):
|
||||
return "already-configured"
|
||||
client.project.update(custom_categories=proposed)
|
||||
return "applied"
|
||||
|
||||
|
||||
# --------------------------------------------------------------------------- #
|
||||
# Lock (mirrors auto_import.py) #
|
||||
# --------------------------------------------------------------------------- #
|
||||
def _acquire_lock() -> bool:
|
||||
"""Try to acquire a file lock. Returns False if another instance is running."""
|
||||
try:
|
||||
os.makedirs(os.path.dirname(LOCK_FILE), exist_ok=True)
|
||||
fd = os.open(LOCK_FILE, os.O_CREAT | os.O_EXCL | os.O_WRONLY)
|
||||
os.write(fd, str(os.getpid()).encode())
|
||||
os.close(fd)
|
||||
return True
|
||||
except FileExistsError:
|
||||
try:
|
||||
if time.time() - os.path.getmtime(LOCK_FILE) > 120:
|
||||
os.unlink(LOCK_FILE)
|
||||
return _acquire_lock()
|
||||
except OSError:
|
||||
pass
|
||||
return False
|
||||
|
||||
|
||||
def _release_lock() -> None:
|
||||
try:
|
||||
os.unlink(LOCK_FILE)
|
||||
except OSError:
|
||||
pass
|
||||
|
||||
|
||||
# --------------------------------------------------------------------------- #
|
||||
# Entry point #
|
||||
# --------------------------------------------------------------------------- #
|
||||
def main() -> None:
|
||||
api_key = resolve_api_key()
|
||||
if not api_key:
|
||||
log.debug("MEM0_API_KEY not set, skipping coding-categories setup")
|
||||
return
|
||||
|
||||
key_fp = apikey_fingerprint(api_key)
|
||||
cat_fp = categories_fingerprint()
|
||||
|
||||
state = load_state()
|
||||
if is_applied(state, key_fp, cat_fp):
|
||||
log.debug("Coding categories already configured for this account (cached); skipping")
|
||||
return
|
||||
|
||||
os.environ["MEM0_API_KEY"] = api_key
|
||||
|
||||
try:
|
||||
client = make_client()
|
||||
except ImportError:
|
||||
log.debug("mem0ai SDK not ready yet (venv installing?); will retry next session")
|
||||
return
|
||||
except Exception as e:
|
||||
log.warning("Could not initialise MemoryClient: %s", e)
|
||||
return
|
||||
|
||||
try:
|
||||
result = apply_categories(client)
|
||||
except Exception as e:
|
||||
log.warning("Could not configure coding categories: %s", e)
|
||||
return
|
||||
|
||||
state[key_fp] = cat_fp
|
||||
save_state(state)
|
||||
|
||||
if result == "applied":
|
||||
log.info("Applied %d coding categories", len(CODING_CATEGORIES))
|
||||
else:
|
||||
log.info("Coding categories already configured")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
if not _acquire_lock():
|
||||
log.debug("Another auto_setup_categories instance is running — skipping")
|
||||
sys.exit(0)
|
||||
try:
|
||||
main()
|
||||
except Exception as e: # never block a session
|
||||
log.error("Unexpected error: %s", e)
|
||||
finally:
|
||||
_release_lock()
|
||||
sys.exit(0)
|
||||
+36
@@ -0,0 +1,36 @@
|
||||
#!/usr/bin/env bash
|
||||
# Hook: PreToolUse (matcher: Write|Edit)
|
||||
#
|
||||
# Blocks writes to MEMORY.md and auto-memory files, redirecting Claude
|
||||
# to use the mem0 MCP add_memory tool instead.
|
||||
#
|
||||
# Input: JSON on stdin with tool_name, tool_input
|
||||
# Output: stderr message (exit 2 = block)
|
||||
#
|
||||
# Exit codes:
|
||||
# 0 = allow the tool call
|
||||
# 2 = block the tool call (stderr is shown to Claude as feedback)
|
||||
|
||||
set -euo pipefail
|
||||
|
||||
if [ -n "${MEM0_DEBUG:-}" ]; then
|
||||
mkdir -p "$HOME/.mem0" && exec 2>>"$HOME/.mem0/hooks.log"
|
||||
fi
|
||||
|
||||
INPUT=$(cat)
|
||||
|
||||
FILE_PATH=$(echo "$INPUT" | jq -r '.tool_input.file_path // .tool_input.path // ""' 2>/dev/null || echo "")
|
||||
|
||||
if [ -z "$FILE_PATH" ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
case "$FILE_PATH" in
|
||||
*/.claude/*/MEMORY.md|*/.claude/memory/*)
|
||||
echo "BLOCKED: Do not write to $FILE_PATH. Use the mem0 MCP \`add_memory\` tool instead to persist memories. This project uses mem0 for all memory storage." >&2
|
||||
exit 2
|
||||
;;
|
||||
*)
|
||||
exit 0
|
||||
;;
|
||||
esac
|
||||
@@ -0,0 +1,33 @@
|
||||
#!/usr/bin/env bash
|
||||
# Hook: preToolUse (Cursor) — blocks writes to MEMORY.md
|
||||
#
|
||||
# Cursor variant of block_memory_write.sh. Returns JSON:
|
||||
# {"permission":"deny","agent_message":"..."} on block,
|
||||
# {"permission":"allow"} on pass.
|
||||
|
||||
set -uo pipefail
|
||||
|
||||
if [ -n "${MEM0_DEBUG:-}" ]; then
|
||||
mkdir -p "$HOME/.mem0" && exec 2>>"$HOME/.mem0/hooks.log"
|
||||
fi
|
||||
|
||||
INPUT=$(cat)
|
||||
|
||||
FILE_PATH=$(echo "$INPUT" | jq -r '.tool_input.file_path // .tool_input.path // ""' 2>/dev/null || echo "")
|
||||
|
||||
if [ -z "$FILE_PATH" ]; then
|
||||
jq -cn '{permission:"allow"}'
|
||||
exit 0
|
||||
fi
|
||||
|
||||
case "$FILE_PATH" in
|
||||
*/MEMORY.md|*/.claude/memory/*|*/.cursor/memory/*)
|
||||
jq -cn --arg msg "Do not write to $FILE_PATH. Use the mem0 MCP add_memory tool instead to persist memories." \
|
||||
'{permission:"deny", agent_message:$msg}'
|
||||
exit 0
|
||||
;;
|
||||
*)
|
||||
jq -cn '{permission:"allow"}'
|
||||
exit 0
|
||||
;;
|
||||
esac
|
||||
@@ -0,0 +1,197 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Capture the post-compaction summary into mem0.
|
||||
|
||||
PreCompact hooks fire BEFORE the summary is generated, so they can't
|
||||
store the actual compact-summary text. This script runs at
|
||||
SessionStart with source=compact, reads the transcript, finds the
|
||||
most recent entry flagged isCompactSummary=true, and stores it as a
|
||||
memory tagged metadata.type=compact_summary.
|
||||
|
||||
Input: JSON on stdin with transcript_path, session_id, source
|
||||
Output: stderr logs only (exit 0 always -- must not block)
|
||||
|
||||
Spawned in the background by on_session_start.sh; the user-facing
|
||||
bootstrap text continues without waiting on the network.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import sys
|
||||
import urllib.error
|
||||
import urllib.request
|
||||
from datetime import date, timedelta
|
||||
|
||||
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
|
||||
from _identity import resolve_api_key, resolve_user_id
|
||||
from _project import resolve_branch, resolve_project_id
|
||||
|
||||
log = logging.getLogger("mem0-compact-summary")
|
||||
log.setLevel(logging.DEBUG)
|
||||
_handler = logging.StreamHandler(sys.stderr)
|
||||
_handler.setFormatter(logging.Formatter("[mem0-compact-summary] %(message)s"))
|
||||
log.addHandler(_handler)
|
||||
|
||||
if os.environ.get("MEM0_DEBUG"):
|
||||
_log_dir = os.path.expanduser("~/.mem0")
|
||||
try:
|
||||
os.makedirs(_log_dir, exist_ok=True)
|
||||
_file_handler = logging.FileHandler(os.path.join(_log_dir, "hooks.log"))
|
||||
_file_handler.setFormatter(logging.Formatter("[mem0-compact-summary] %(asctime)s %(message)s"))
|
||||
log.addHandler(_file_handler)
|
||||
except OSError:
|
||||
pass
|
||||
|
||||
API_URL = "https://api.mem0.ai"
|
||||
MAX_TAIL_LINES = 2000
|
||||
MAX_SUMMARY_CHARS = 50000
|
||||
# Compact summaries describe a single session's state -- stale after a quarter.
|
||||
COMPACT_SUMMARY_EXPIRY_DAYS = 90
|
||||
|
||||
|
||||
def tail_lines(filepath: str, n: int) -> list[str]:
|
||||
try:
|
||||
with open(filepath, "rb") as f:
|
||||
f.seek(0, 2)
|
||||
file_size = f.tell()
|
||||
if file_size == 0:
|
||||
return []
|
||||
chunk_size = min(file_size, n * 4096)
|
||||
f.seek(max(0, file_size - chunk_size))
|
||||
data = f.read().decode("utf-8", errors="replace")
|
||||
return data.splitlines()[-n:]
|
||||
except OSError:
|
||||
return []
|
||||
|
||||
|
||||
def find_compact_summary(lines: list[str]) -> str:
|
||||
"""Walk transcript backwards, return text content of the most recent
|
||||
entry flagged isCompactSummary=true. Empty string if none found."""
|
||||
for line in reversed(lines):
|
||||
line = line.strip()
|
||||
if not line:
|
||||
continue
|
||||
try:
|
||||
entry = json.loads(line)
|
||||
except json.JSONDecodeError:
|
||||
continue
|
||||
if not entry.get("isCompactSummary"):
|
||||
continue
|
||||
|
||||
message = entry.get("message", {})
|
||||
content = message.get("content", [])
|
||||
if isinstance(content, str):
|
||||
return content[:MAX_SUMMARY_CHARS]
|
||||
if isinstance(content, list):
|
||||
parts = []
|
||||
for block in content:
|
||||
if isinstance(block, str):
|
||||
parts.append(block)
|
||||
elif isinstance(block, dict) and block.get("type") == "text":
|
||||
parts.append(block.get("text", ""))
|
||||
return "\n".join(parts).strip()[:MAX_SUMMARY_CHARS]
|
||||
return ""
|
||||
|
||||
|
||||
def store_summary(api_key: str, summary: str, user_id: str, session_id: str, project_id: str = "", branch: str = "") -> bool:
|
||||
expires = (date.today() + timedelta(days=COMPACT_SUMMARY_EXPIRY_DAYS)).isoformat()
|
||||
metadata = {
|
||||
"type": "compact_summary",
|
||||
"source": "session-start-compact",
|
||||
"session_id": session_id,
|
||||
}
|
||||
if branch:
|
||||
metadata["branch"] = branch
|
||||
body = {
|
||||
"messages": [{"role": "user", "content": summary}],
|
||||
"user_id": user_id,
|
||||
"app_id": project_id,
|
||||
"metadata": metadata,
|
||||
"infer": True,
|
||||
"expiration_date": expires,
|
||||
}
|
||||
|
||||
data = json.dumps(body).encode("utf-8")
|
||||
req = urllib.request.Request(
|
||||
f"{API_URL}/v3/memories/add/",
|
||||
data=data,
|
||||
headers={
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Token {api_key}",
|
||||
},
|
||||
method="POST",
|
||||
)
|
||||
try:
|
||||
with urllib.request.urlopen(req, timeout=15) as resp:
|
||||
if resp.status in (200, 201):
|
||||
log.info("Compact summary stored")
|
||||
return True
|
||||
log.warning("API returned status %d", resp.status)
|
||||
return False
|
||||
except urllib.error.URLError as e:
|
||||
log.warning("API call failed: %s", e)
|
||||
return False
|
||||
|
||||
|
||||
def main():
|
||||
api_key = resolve_api_key()
|
||||
if not api_key:
|
||||
log.debug("MEM0_API_KEY not set, skipping capture")
|
||||
return
|
||||
|
||||
try:
|
||||
hook_input = json.loads(sys.stdin.read())
|
||||
except (json.JSONDecodeError, OSError):
|
||||
log.debug("No valid JSON on stdin")
|
||||
return
|
||||
|
||||
transcript_path = hook_input.get("transcript_path", "")
|
||||
if not transcript_path:
|
||||
log.debug("No transcript_path provided")
|
||||
return
|
||||
|
||||
session_id = hook_input.get("session_id", "")
|
||||
cwd = hook_input.get("cwd") or None
|
||||
user_id = resolve_user_id()
|
||||
project_id = resolve_project_id(cwd)
|
||||
branch = resolve_branch(cwd)
|
||||
|
||||
lines = tail_lines(transcript_path, MAX_TAIL_LINES)
|
||||
if not lines:
|
||||
log.debug("Transcript empty or unreadable: %s", transcript_path)
|
||||
return
|
||||
|
||||
summary = find_compact_summary(lines)
|
||||
if not summary:
|
||||
log.debug("No isCompactSummary entry found")
|
||||
return
|
||||
|
||||
if len(summary.strip()) < 100:
|
||||
log.debug("Compact summary too short (%d chars) — skipping", len(summary.strip()))
|
||||
return
|
||||
|
||||
marker_dir = os.path.expanduser("~/.mem0")
|
||||
marker_file = os.path.join(marker_dir, f"compact_captured_{session_id}")
|
||||
if session_id and os.path.isfile(marker_file):
|
||||
log.info("Compact summary already captured for session %s — skipping", session_id)
|
||||
return
|
||||
|
||||
log.info("Capturing compact summary (%d chars)", len(summary))
|
||||
if store_summary(api_key, summary, user_id, session_id, project_id, branch):
|
||||
if session_id:
|
||||
try:
|
||||
os.makedirs(marker_dir, exist_ok=True)
|
||||
with open(marker_file, "w") as f:
|
||||
f.write("")
|
||||
except OSError:
|
||||
pass
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
try:
|
||||
main()
|
||||
except Exception as e:
|
||||
log.error("Unexpected error: %s", e)
|
||||
sys.exit(0)
|
||||
@@ -0,0 +1,264 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Capture a structured session summary on Stop hook.
|
||||
|
||||
Runs on every Stop (end of each assistant turn). Each invocation reads
|
||||
the transcript JSONL, extracts the latest assistant message and all
|
||||
files touched so far, then stores via mem0 API with infer=True. Uses
|
||||
run_id=session_id to scope infer dedup to the session, so the final
|
||||
stored summary reflects the most recent turn — not just the first.
|
||||
|
||||
Input: JSON on stdin with transcript_path, session_id, cwd, agent_id
|
||||
Output: stderr logs only (exit 0 always — must not block)
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import re
|
||||
import sys
|
||||
import urllib.error
|
||||
import urllib.request
|
||||
from datetime import date, timedelta
|
||||
|
||||
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
|
||||
from _identity import resolve_api_key, resolve_user_id
|
||||
from _project import resolve_branch, resolve_project_id
|
||||
|
||||
log = logging.getLogger("mem0-session-summary")
|
||||
log.setLevel(logging.DEBUG)
|
||||
_handler = logging.StreamHandler(sys.stderr)
|
||||
_handler.setFormatter(logging.Formatter("[mem0-session-summary] %(message)s"))
|
||||
log.addHandler(_handler)
|
||||
|
||||
if os.environ.get("MEM0_DEBUG"):
|
||||
_log_dir = os.path.expanduser("~/.mem0")
|
||||
try:
|
||||
os.makedirs(_log_dir, exist_ok=True)
|
||||
_fh = logging.FileHandler(os.path.join(_log_dir, "hooks.log"))
|
||||
_fh.setFormatter(logging.Formatter("[mem0-session-summary] %(asctime)s %(message)s"))
|
||||
log.addHandler(_fh)
|
||||
except OSError:
|
||||
pass
|
||||
|
||||
API_URL = "https://api.mem0.ai"
|
||||
MAX_TAIL_LINES = 3000
|
||||
MAX_SUMMARY_CHARS = 50000
|
||||
SUMMARY_EXPIRY_DAYS = 90
|
||||
|
||||
SYSTEM_TAG_RE = re.compile(
|
||||
r"<(?:system-reminder|private|claude-mem-context|persisted-output|system_instruction)>"
|
||||
r".*?"
|
||||
r"</(?:system-reminder|private|claude-mem-context|persisted-output|system_instruction)>",
|
||||
re.DOTALL,
|
||||
)
|
||||
|
||||
|
||||
def tail_lines(filepath: str, n: int) -> list[str]:
|
||||
try:
|
||||
with open(filepath, "rb") as f:
|
||||
f.seek(0, 2)
|
||||
file_size = f.tell()
|
||||
if file_size == 0:
|
||||
return []
|
||||
chunk_size = min(file_size, n * 4096)
|
||||
f.seek(max(0, file_size - chunk_size))
|
||||
data = f.read().decode("utf-8", errors="replace")
|
||||
return data.splitlines()[-n:]
|
||||
except OSError:
|
||||
return []
|
||||
|
||||
|
||||
def extract_last_assistant_message(lines: list[str]) -> str:
|
||||
"""Walk transcript backwards, return text content of the last assistant message."""
|
||||
for line in reversed(lines):
|
||||
line = line.strip()
|
||||
if not line:
|
||||
continue
|
||||
if '"type":"assistant"' not in line and '"type": "assistant"' not in line:
|
||||
continue
|
||||
try:
|
||||
entry = json.loads(line)
|
||||
except json.JSONDecodeError:
|
||||
continue
|
||||
if entry.get("type") != "assistant":
|
||||
continue
|
||||
message = entry.get("message", {})
|
||||
content = message.get("content", [])
|
||||
if isinstance(content, str):
|
||||
return content
|
||||
if isinstance(content, list):
|
||||
parts = []
|
||||
for block in content:
|
||||
if isinstance(block, str):
|
||||
parts.append(block)
|
||||
elif isinstance(block, dict) and block.get("type") == "text":
|
||||
parts.append(block.get("text", ""))
|
||||
return "\n".join(parts).strip()
|
||||
return ""
|
||||
|
||||
|
||||
def extract_files_touched(lines: list[str]) -> list[str]:
|
||||
"""Extract unique file paths from tool_use content blocks in transcript."""
|
||||
files = set()
|
||||
file_ext_re = re.compile(
|
||||
r"[a-zA-Z0-9_./-]+\.(?:py|ts|tsx|js|jsx|rs|go|rb|java|sh|yaml|yml|json|toml|md|sql|css|html)"
|
||||
)
|
||||
for line in lines:
|
||||
line = line.strip()
|
||||
if not line:
|
||||
continue
|
||||
if '"tool_use"' not in line and '"file_path"' not in line:
|
||||
continue
|
||||
try:
|
||||
entry = json.loads(line)
|
||||
except json.JSONDecodeError:
|
||||
continue
|
||||
content = entry.get("message", {}).get("content", [])
|
||||
if not isinstance(content, list):
|
||||
continue
|
||||
for block in content:
|
||||
if not isinstance(block, dict) or block.get("type") != "tool_use":
|
||||
continue
|
||||
inp = block.get("input", {})
|
||||
if not isinstance(inp, dict):
|
||||
continue
|
||||
fp = inp.get("file_path", "")
|
||||
if fp:
|
||||
files.add(fp)
|
||||
command = inp.get("command", "")
|
||||
if command:
|
||||
for match in file_ext_re.findall(command):
|
||||
files.add(match)
|
||||
return sorted(files)[:20]
|
||||
|
||||
|
||||
def strip_tags(text: str) -> str:
|
||||
return SYSTEM_TAG_RE.sub("", text).strip()
|
||||
|
||||
|
||||
def build_summary_prompt(assistant_msg: str, files: list[str]) -> str:
|
||||
"""Build a structured prompt that helps mem0's AI extract a good summary."""
|
||||
files_section = ""
|
||||
if files:
|
||||
file_list = ", ".join(files[:10])
|
||||
files_section = f"\n\nFiles touched during this session: {file_list}"
|
||||
|
||||
return (
|
||||
f"Session summary — store the following as a structured session summary.\n\n"
|
||||
f"What the assistant accomplished in this session:\n"
|
||||
f"{assistant_msg[:MAX_SUMMARY_CHARS]}"
|
||||
f"{files_section}\n\n"
|
||||
f"Extract and remember: what was requested, what was investigated, "
|
||||
f"key decisions made, what was completed, and what needs to happen next."
|
||||
)
|
||||
|
||||
|
||||
def store_summary(
|
||||
api_key: str,
|
||||
summary_prompt: str,
|
||||
user_id: str,
|
||||
session_id: str,
|
||||
project_id: str,
|
||||
branch: str,
|
||||
files: list[str],
|
||||
) -> bool:
|
||||
expires = (date.today() + timedelta(days=SUMMARY_EXPIRY_DAYS)).isoformat()
|
||||
metadata = {
|
||||
"type": "session_summary",
|
||||
"source": "stop-hook",
|
||||
"session_id": session_id,
|
||||
}
|
||||
if branch:
|
||||
metadata["branch"] = branch
|
||||
if files:
|
||||
metadata["files_touched"] = json.dumps(files[:20])
|
||||
|
||||
body = {
|
||||
"messages": [{"role": "user", "content": summary_prompt}],
|
||||
"user_id": user_id,
|
||||
"app_id": project_id,
|
||||
"run_id": session_id,
|
||||
"metadata": metadata,
|
||||
"infer": True,
|
||||
"expiration_date": expires,
|
||||
}
|
||||
|
||||
data = json.dumps(body).encode("utf-8")
|
||||
req = urllib.request.Request(
|
||||
f"{API_URL}/v3/memories/add/",
|
||||
data=data,
|
||||
headers={
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Token {api_key}",
|
||||
},
|
||||
method="POST",
|
||||
)
|
||||
try:
|
||||
with urllib.request.urlopen(req, timeout=15) as resp:
|
||||
if resp.status in (200, 201):
|
||||
log.info("Session summary stored")
|
||||
return True
|
||||
log.warning("API returned status %d", resp.status)
|
||||
return False
|
||||
except urllib.error.URLError as e:
|
||||
log.warning("API call failed: %s", e)
|
||||
return False
|
||||
|
||||
|
||||
def main():
|
||||
api_key = resolve_api_key()
|
||||
if not api_key:
|
||||
log.debug("MEM0_API_KEY not set, skipping")
|
||||
return
|
||||
|
||||
try:
|
||||
hook_input = json.loads(sys.stdin.read())
|
||||
except (json.JSONDecodeError, OSError):
|
||||
log.debug("No valid JSON on stdin")
|
||||
return
|
||||
|
||||
# Guard: skip subagent sessions (only root sessions get summaries)
|
||||
agent_id = hook_input.get("agent_id", "")
|
||||
if agent_id:
|
||||
log.debug("Subagent session (agent_id=%s), skipping", agent_id)
|
||||
return
|
||||
|
||||
transcript_path = hook_input.get("transcript_path", "")
|
||||
if not transcript_path:
|
||||
log.debug("No transcript_path provided")
|
||||
return
|
||||
|
||||
session_id = hook_input.get("session_id", "")
|
||||
cwd = hook_input.get("cwd") or None
|
||||
|
||||
user_id = resolve_user_id()
|
||||
project_id = resolve_project_id(cwd)
|
||||
branch = resolve_branch(cwd)
|
||||
|
||||
lines = tail_lines(transcript_path, MAX_TAIL_LINES)
|
||||
if not lines:
|
||||
log.debug("Transcript empty or unreadable: %s", transcript_path)
|
||||
return
|
||||
|
||||
assistant_msg = extract_last_assistant_message(lines)
|
||||
if not assistant_msg or len(assistant_msg.strip()) < 100:
|
||||
log.debug("Assistant message too short (%d chars) — skipping", len(assistant_msg.strip()))
|
||||
return
|
||||
|
||||
assistant_msg = strip_tags(assistant_msg)
|
||||
files = extract_files_touched(lines)
|
||||
|
||||
summary_prompt = build_summary_prompt(assistant_msg, files)
|
||||
|
||||
log.info("Capturing session summary (%d chars, %d files)", len(assistant_msg), len(files))
|
||||
store_summary(api_key, summary_prompt, user_id, session_id, project_id, branch, files)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
try:
|
||||
main()
|
||||
except Exception as e:
|
||||
log.error("Unexpected error: %s", e)
|
||||
sys.exit(0)
|
||||
@@ -0,0 +1,218 @@
|
||||
#!/usr/bin/env bash
|
||||
# PreToolUse hook for mem0 MCP tools.
|
||||
# Injects identity (user_id, app_id) and metadata defaults when the agent
|
||||
# omits them. Uses the hookSpecificOutput.updatedInput contract to modify
|
||||
# tool call parameters before execution.
|
||||
#
|
||||
# Handles:
|
||||
# add_memory — top-level user_id, app_id, metadata defaults
|
||||
# search_memories — user_id/app_id into filters.AND[]
|
||||
# get_memories — user_id/app_id into filters.AND[]
|
||||
# delete_all_memories — top-level user_id, app_id
|
||||
#
|
||||
# Hook contract:
|
||||
# exit 0 = allow. If stdout contains {"hookSpecificOutput": {"updatedInput": ...}},
|
||||
# the updatedInput replaces the tool's input parameters.
|
||||
# exit 2 = block (stderr shown as rejection reason).
|
||||
|
||||
set -uo pipefail
|
||||
|
||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
||||
source "$SCRIPT_DIR/_identity.sh" 2>/dev/null || true
|
||||
|
||||
INPUT=$(cat)
|
||||
|
||||
TOOL_NAME=$(echo "$INPUT" | jq -r '.tool_name // ""' 2>/dev/null)
|
||||
|
||||
# Determine which handler to use based on tool name
|
||||
HANDLER=""
|
||||
case "$TOOL_NAME" in
|
||||
mcp__mem0__add_memory|mcp__plugin_mem0_mem0__add_memory)
|
||||
HANDLER="add_memory" ;;
|
||||
mcp__mem0__search_memories|mcp__plugin_mem0_mem0__search_memories)
|
||||
HANDLER="search_memories" ;;
|
||||
mcp__mem0__get_memories|mcp__plugin_mem0_mem0__get_memories)
|
||||
HANDLER="get_memories" ;;
|
||||
mcp__mem0__delete_all_memories|mcp__plugin_mem0_mem0__delete_all_memories)
|
||||
HANDLER="delete_all" ;;
|
||||
*) exit 0 ;;
|
||||
esac
|
||||
|
||||
TOOL_INPUT=$(echo "$INPUT" | jq -r '.tool_input // "{}"' 2>/dev/null)
|
||||
|
||||
_PATCH_OUT="/tmp/mem0_enforce_$$"
|
||||
trap 'rm -f "$_PATCH_OUT"' EXIT
|
||||
_MEM0_TOOL_INPUT="$TOOL_INPUT" \
|
||||
_MEM0_USER_ID="${MEM0_RESOLVED_USER_ID:-}" \
|
||||
_MEM0_APP_ID="${MEM0_PROJECT_ID:-}" \
|
||||
_MEM0_GLOBAL_SEARCH="${MEM0_GLOBAL_SEARCH:-false}" \
|
||||
_MEM0_HANDLER="$HANDLER" \
|
||||
python3 <<'PYEOF' > "$_PATCH_OUT" 2>/dev/null || true
|
||||
import json, os, sys
|
||||
|
||||
raw = os.environ.get("_MEM0_TOOL_INPUT", "{}")
|
||||
try:
|
||||
inp = json.loads(raw)
|
||||
except Exception:
|
||||
sys.exit(0)
|
||||
|
||||
handler = os.environ.get("_MEM0_HANDLER", "")
|
||||
resolved_uid = os.environ.get("_MEM0_USER_ID", "")
|
||||
resolved_aid = os.environ.get("_MEM0_APP_ID", "")
|
||||
global_search = os.environ.get("_MEM0_GLOBAL_SEARCH", "false") == "true"
|
||||
changed = False
|
||||
|
||||
|
||||
def inject_top_level_identity(inp, uid, aid):
|
||||
"""Inject user_id/app_id as top-level params (for add_memory, delete_all)."""
|
||||
changed = False
|
||||
if uid and not inp.get("user_id"):
|
||||
inp["user_id"] = uid
|
||||
changed = True
|
||||
if aid and not inp.get("app_id"):
|
||||
inp["app_id"] = aid
|
||||
changed = True
|
||||
return changed
|
||||
|
||||
|
||||
def inject_filter_identity(inp, uid, aid):
|
||||
"""Inject user_id/app_id into filters.AND[] (for search/get_memories)."""
|
||||
changed = False
|
||||
if not uid and not aid:
|
||||
return False
|
||||
|
||||
filters = inp.get("filters")
|
||||
|
||||
if filters is None:
|
||||
# No filters at all — create from scratch
|
||||
and_clauses = []
|
||||
if uid:
|
||||
and_clauses.append({"user_id": uid})
|
||||
if aid:
|
||||
and_clauses.append({"app_id": aid})
|
||||
inp["filters"] = {"AND": and_clauses}
|
||||
return True
|
||||
|
||||
if not isinstance(filters, dict):
|
||||
return False
|
||||
|
||||
# Check if filters already contain user_id/app_id
|
||||
and_clauses = filters.get("AND")
|
||||
if and_clauses is None:
|
||||
# Filters exist but no AND — could be flat like {"user_id": "x"}
|
||||
has_uid = "user_id" in filters
|
||||
has_aid = "app_id" in filters
|
||||
if has_uid and has_aid:
|
||||
return False
|
||||
# Convert flat filters to AND format and add missing identity
|
||||
existing = []
|
||||
for k, v in list(filters.items()):
|
||||
existing.append({k: v})
|
||||
if uid and not has_uid:
|
||||
existing.append({"user_id": uid})
|
||||
changed = True
|
||||
if aid and not has_aid:
|
||||
existing.append({"app_id": aid})
|
||||
changed = True
|
||||
if changed:
|
||||
inp["filters"] = {"AND": existing}
|
||||
return changed
|
||||
|
||||
if not isinstance(and_clauses, list):
|
||||
return False
|
||||
|
||||
# AND array exists — check for existing user_id/app_id
|
||||
has_uid = any("user_id" in c for c in and_clauses if isinstance(c, dict))
|
||||
has_aid = any("app_id" in c for c in and_clauses if isinstance(c, dict))
|
||||
|
||||
if uid and not has_uid:
|
||||
and_clauses.append({"user_id": uid})
|
||||
changed = True
|
||||
if aid and not has_aid:
|
||||
and_clauses.append({"app_id": aid})
|
||||
changed = True
|
||||
|
||||
return changed
|
||||
|
||||
|
||||
if handler == "add_memory":
|
||||
changed = inject_top_level_identity(inp, resolved_uid, resolved_aid)
|
||||
|
||||
meta = inp.get("metadata") or {}
|
||||
|
||||
if "confidence" not in meta:
|
||||
meta["confidence"] = 0.7
|
||||
changed = True
|
||||
if "files" not in meta:
|
||||
meta["files"] = ["*"]
|
||||
changed = True
|
||||
if "source" not in meta:
|
||||
meta["source"] = "auto_capture"
|
||||
changed = True
|
||||
if "type" not in meta:
|
||||
meta["type"] = "task_learning"
|
||||
changed = True
|
||||
|
||||
if meta.get("confidence", 0) >= 1.0 and "infer" not in inp:
|
||||
inp["infer"] = False
|
||||
changed = True
|
||||
|
||||
# Track session in metadata instead of run_id.
|
||||
# run_id creates a separate entity partition in the v3 API,
|
||||
# making memories invisible to search/get_memories calls
|
||||
# that don't include a run_id filter.
|
||||
if "session_id" not in meta:
|
||||
sid = os.environ.get("MEM0_SESSION_ID", "")
|
||||
if not sid:
|
||||
session_file = "/tmp/mem0_session_id_" + os.environ.get("USER", "default")
|
||||
if os.path.isfile(session_file):
|
||||
try:
|
||||
with open(session_file) as f:
|
||||
sid = f.read().strip()
|
||||
except OSError:
|
||||
pass
|
||||
if sid:
|
||||
meta["session_id"] = sid
|
||||
changed = True
|
||||
|
||||
if changed:
|
||||
inp["metadata"] = meta
|
||||
|
||||
elif handler in ("search_memories", "get_memories"):
|
||||
if global_search:
|
||||
inp["filters"] = {"OR": [{"user_id": "*"}]}
|
||||
changed = True
|
||||
else:
|
||||
changed = inject_filter_identity(inp, resolved_uid, resolved_aid)
|
||||
|
||||
elif handler == "delete_all":
|
||||
changed = inject_top_level_identity(inp, resolved_uid, resolved_aid)
|
||||
|
||||
if changed:
|
||||
print(json.dumps(inp))
|
||||
PYEOF
|
||||
PATCHED=$(cat "$_PATCH_OUT" 2>/dev/null)
|
||||
rm -f "$_PATCH_OUT"
|
||||
|
||||
if [ -n "$PATCHED" ] && echo "$PATCHED" | jq empty 2>/dev/null; then
|
||||
jq -n --argjson updated "$PATCHED" '{
|
||||
"hookSpecificOutput": {
|
||||
"hookEventName": "PreToolUse",
|
||||
"permissionDecision": "allow",
|
||||
"updatedInput": $updated
|
||||
}
|
||||
}' 2>/dev/null || true
|
||||
fi
|
||||
|
||||
# Track session stats here because PostToolUse hooks don't fire for plugin MCP tools.
|
||||
case "$HANDLER" in
|
||||
add_memory)
|
||||
_CAT=$(echo "$TOOL_INPUT" | jq -r '.metadata.type // .metadata.category // ""' 2>/dev/null || echo "")
|
||||
python3 "$SCRIPT_DIR/session_stats.py" add "$_CAT" 2>/dev/null &
|
||||
;;
|
||||
search_memories|get_memories)
|
||||
python3 "$SCRIPT_DIR/session_stats.py" search 2>/dev/null &
|
||||
;;
|
||||
esac
|
||||
|
||||
exit 0
|
||||
+50
@@ -0,0 +1,50 @@
|
||||
#!/usr/bin/env bash
|
||||
# Install mem0ai SDK into a persistent venv inside CLAUDE_PLUGIN_DATA.
|
||||
# Runs on SessionStart; skips if requirements.txt hasn't changed.
|
||||
set -euo pipefail
|
||||
|
||||
PLUGIN_ROOT="${CLAUDE_PLUGIN_ROOT:-$(cd "$(dirname "$0")/.." && pwd)}"
|
||||
DATA_DIR="${CLAUDE_PLUGIN_DATA:-${HOME}/.mem0/plugin-data}"
|
||||
VENV_DIR="${DATA_DIR}/venv"
|
||||
REQ_SRC="${PLUGIN_ROOT}/requirements.txt"
|
||||
REQ_STAMP="${DATA_DIR}/requirements.txt"
|
||||
|
||||
mkdir -p "${DATA_DIR}"
|
||||
|
||||
LOCKDIR="${DATA_DIR}/.install-lock"
|
||||
|
||||
needs_install=false
|
||||
|
||||
if [ ! -f "${VENV_DIR}/bin/python3" ]; then
|
||||
needs_install=true
|
||||
elif ! diff -q "${REQ_SRC}" "${REQ_STAMP}" >/dev/null 2>&1; then
|
||||
needs_install=true
|
||||
fi
|
||||
|
||||
if [ "${needs_install}" = "true" ]; then
|
||||
if mkdir "${LOCKDIR}" 2>/dev/null; then
|
||||
# We acquired the lock — proceed with installation
|
||||
trap 'rmdir "${LOCKDIR}" 2>/dev/null || true' EXIT
|
||||
python3 -m venv "${VENV_DIR}" 2>/dev/null || python -m venv "${VENV_DIR}"
|
||||
"${VENV_DIR}/bin/pip" install --quiet --upgrade pip >/dev/null 2>&1 || true
|
||||
if "${VENV_DIR}/bin/pip" install --quiet -r "${REQ_SRC}" 2>/dev/null; then
|
||||
cp "${REQ_SRC}" "${REQ_STAMP}"
|
||||
rm -f "${DATA_DIR}/.install-failed"
|
||||
else
|
||||
rm -f "${REQ_STAMP}"
|
||||
touch "${DATA_DIR}/.install-failed"
|
||||
echo "mem0 plugin: failed to install Python dependencies" >&2
|
||||
exit 0
|
||||
fi
|
||||
else
|
||||
# Another process holds the lock — wait up to 60s for it to finish
|
||||
for i in $(seq 1 60); do
|
||||
[ ! -d "${LOCKDIR}" ] && break
|
||||
sleep 1
|
||||
done
|
||||
# Check if the other process's install failed
|
||||
if [ -f "${DATA_DIR}/.install-failed" ]; then
|
||||
echo "mem0 plugin: dependency installation failed (by another session)" >&2
|
||||
fi
|
||||
fi
|
||||
fi
|
||||
@@ -0,0 +1,133 @@
|
||||
#!/usr/bin/env python3
|
||||
"""File-context injection for PreToolUse/Read hook.
|
||||
|
||||
When Claude is about to read a file, this script searches mem0 for
|
||||
memories that reference that file path and returns a compact timeline
|
||||
of prior work. This gives Claude context like "last time you fixed a
|
||||
null pointer here" before it reads the file.
|
||||
|
||||
Modeled after claude-mem's file-context handler but adapted for mem0's
|
||||
cloud API architecture.
|
||||
|
||||
Input: file_path (positional arg), env vars for identity
|
||||
Output: JSON to stdout with hookSpecificOutput.additionalContext
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import os
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
|
||||
from _formatting import TYPE_ICONS, format_age
|
||||
from _identity import resolve_api_key, resolve_user_id
|
||||
from _project import resolve_project_id
|
||||
from _search import search_memories
|
||||
|
||||
FILE_READ_GATE_MIN_BYTES = 1500
|
||||
MAX_RESULTS = 5
|
||||
SEARCH_TIMEOUT = 5
|
||||
|
||||
|
||||
def gate_file(file_path: str, cwd: str) -> str | None:
|
||||
"""Return the resolved absolute path if the file passes gating, else None."""
|
||||
if not file_path:
|
||||
return None
|
||||
p = Path(file_path)
|
||||
if not p.is_absolute():
|
||||
p = Path(cwd) / p
|
||||
try:
|
||||
p = p.resolve()
|
||||
if not p.is_file():
|
||||
return None
|
||||
if p.stat().st_size < FILE_READ_GATE_MIN_BYTES:
|
||||
return None
|
||||
return str(p)
|
||||
except OSError:
|
||||
return None
|
||||
|
||||
|
||||
def relative_path(abs_path: str, cwd: str) -> str:
|
||||
try:
|
||||
return os.path.relpath(abs_path, cwd)
|
||||
except ValueError:
|
||||
return abs_path
|
||||
|
||||
|
||||
def format_timeline(memories: list[dict], file_path: str) -> str:
|
||||
"""Format memories into a compact timeline for context injection."""
|
||||
if not memories:
|
||||
return ""
|
||||
|
||||
rel = file_path
|
||||
lines = [
|
||||
f"Prior work on `{rel}` — {len(memories)} memories found.",
|
||||
"Need details? Use `search_memories` with the memory ID.",
|
||||
"",
|
||||
]
|
||||
|
||||
for m in memories:
|
||||
mid = m.get("id", "?")[:8]
|
||||
text = (m.get("memory", "") or "")[:150].replace("\n", " ").strip()
|
||||
meta = m.get("metadata") or {}
|
||||
cat = meta.get("type", "unknown")
|
||||
icon = TYPE_ICONS.get(cat, "❓")
|
||||
age = format_age(m)
|
||||
age_str = f" ({age})" if age else ""
|
||||
lines.append(f"- {icon} [{cat}]{age_str} {text} [mem0:{mid}]")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
def search_file_context(
|
||||
api_key: str, user_id: str, project_id: str, file_path: str, cwd: str
|
||||
) -> str:
|
||||
"""Search mem0 for memories related to a file path."""
|
||||
global_search = os.environ.get("MEM0_GLOBAL_SEARCH", "false") == "true"
|
||||
rel = relative_path(file_path, cwd)
|
||||
basename = os.path.basename(file_path)
|
||||
|
||||
query = f"{rel} {basename}" if rel != basename else rel
|
||||
results = search_memories(
|
||||
api_key, user_id, project_id, query,
|
||||
top_k=MAX_RESULTS, threshold=0.3,
|
||||
global_search=global_search,
|
||||
)
|
||||
|
||||
results = results[:MAX_RESULTS]
|
||||
|
||||
return format_timeline(results, rel)
|
||||
|
||||
|
||||
def main():
|
||||
if len(sys.argv) < 2:
|
||||
sys.exit(0)
|
||||
|
||||
file_path = sys.argv[1]
|
||||
cwd = sys.argv[2] if len(sys.argv) > 2 else os.getcwd()
|
||||
|
||||
api_key = resolve_api_key()
|
||||
if not api_key:
|
||||
sys.exit(0)
|
||||
|
||||
resolved = gate_file(file_path, cwd)
|
||||
if not resolved:
|
||||
sys.exit(0)
|
||||
|
||||
user_id = resolve_user_id()
|
||||
project_id = resolve_project_id(cwd)
|
||||
|
||||
timeline = search_file_context(api_key, user_id, project_id, resolved, cwd)
|
||||
if not timeline:
|
||||
sys.exit(0)
|
||||
|
||||
print(timeline, end="")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
try:
|
||||
main()
|
||||
except Exception:
|
||||
pass
|
||||
sys.exit(0)
|
||||
@@ -0,0 +1,299 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Import memories from competing AI tool configuration files into mem0.
|
||||
|
||||
Sub-commands (via sys.argv[1]):
|
||||
cursorrules [--path .cursorrules]
|
||||
copilot [--path .github/copilot-instructions.md]
|
||||
cline [--path memory-bank/]
|
||||
continue [--path .continue/rules.md]
|
||||
|
||||
Each sub-command reads configuration files from competing tools,
|
||||
splits them into chunks, and POSTs each chunk to the mem0 API as a
|
||||
project_profile memory.
|
||||
|
||||
Output: progress messages to stdout, errors to stderr
|
||||
Exit: 0 always
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import hashlib
|
||||
import json
|
||||
import os
|
||||
import sys
|
||||
import urllib.error
|
||||
import urllib.request
|
||||
|
||||
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
|
||||
from _chunking import (
|
||||
filter_and_truncate,
|
||||
split_by_headers,
|
||||
split_by_hr_or_headers,
|
||||
)
|
||||
from _identity import resolve_api_key, resolve_user_id
|
||||
from _project import resolve_branch, resolve_project_id
|
||||
|
||||
API_URL = "https://api.mem0.ai"
|
||||
HASH_STORE = os.path.expanduser("~/.mem0/import_hashes.json")
|
||||
|
||||
|
||||
def _load_hashes() -> dict[str, str]:
|
||||
if not os.path.isfile(HASH_STORE):
|
||||
return {}
|
||||
try:
|
||||
with open(HASH_STORE) as f:
|
||||
return json.load(f)
|
||||
except (OSError, json.JSONDecodeError):
|
||||
return {}
|
||||
|
||||
|
||||
def _save_hashes(hashes: dict[str, str]) -> None:
|
||||
os.makedirs(os.path.dirname(HASH_STORE), exist_ok=True)
|
||||
try:
|
||||
with open(HASH_STORE, "w") as f:
|
||||
json.dump(hashes, f, indent=2)
|
||||
except OSError:
|
||||
pass
|
||||
|
||||
|
||||
def _content_hash(content: str) -> str:
|
||||
return hashlib.sha256(content.encode("utf-8")).hexdigest()
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# API helpers
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def post_memory(api_key: str, content: str, user_id: str, project_id: str, branch: str, source: str) -> bool:
|
||||
"""POST a single memory chunk to the mem0 API."""
|
||||
metadata: dict = {
|
||||
"type": "project_profile",
|
||||
"source": source,
|
||||
}
|
||||
if branch:
|
||||
metadata["branch"] = branch
|
||||
|
||||
body = {
|
||||
"messages": [{"role": "user", "content": content}],
|
||||
"user_id": user_id,
|
||||
"app_id": project_id,
|
||||
"metadata": metadata,
|
||||
"infer": False,
|
||||
}
|
||||
data = json.dumps(body).encode("utf-8")
|
||||
req = urllib.request.Request(
|
||||
f"{API_URL}/v3/memories/add/",
|
||||
data=data,
|
||||
headers={
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Token {api_key}",
|
||||
},
|
||||
method="POST",
|
||||
)
|
||||
try:
|
||||
with urllib.request.urlopen(req, timeout=20) as resp:
|
||||
return resp.status in (200, 201)
|
||||
except urllib.error.URLError as e:
|
||||
print(f" [warn] API call failed: {e}", file=sys.stderr)
|
||||
return False
|
||||
|
||||
|
||||
def import_chunks(chunks: list[str], api_key: str, user_id: str, project_id: str, branch: str, source: str, hash_key: str = "") -> int:
|
||||
"""Import a list of content chunks; return number of successful imports.
|
||||
|
||||
Skips import if content hash matches a previous run for the same hash_key."""
|
||||
if hash_key:
|
||||
combined = "\n".join(chunks)
|
||||
current_hash = _content_hash(combined)
|
||||
hashes = _load_hashes()
|
||||
if hashes.get(hash_key) == current_hash:
|
||||
print(f"Already imported (unchanged) -- skipping: {hash_key}")
|
||||
return 0
|
||||
else:
|
||||
current_hash = ""
|
||||
hashes = {}
|
||||
|
||||
success = 0
|
||||
for chunk in chunks:
|
||||
if post_memory(api_key, chunk, user_id, project_id, branch, source):
|
||||
success += 1
|
||||
|
||||
if success > 0 and hash_key and current_hash:
|
||||
hashes[hash_key] = current_hash
|
||||
_save_hashes(hashes)
|
||||
|
||||
return success
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Sub-command implementations
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def _parse_path_arg(args: list[str], flag: str, default: str) -> str:
|
||||
"""Extract --path <value> from args list, falling back to default."""
|
||||
for i, arg in enumerate(args):
|
||||
if arg == flag and i + 1 < len(args):
|
||||
return args[i + 1]
|
||||
if arg.startswith(f"{flag}="):
|
||||
return arg[len(flag) + 1:]
|
||||
return default
|
||||
|
||||
|
||||
def cmd_cursorrules(args: list[str]) -> None:
|
||||
path = _parse_path_arg(args, "--path", ".cursorrules")
|
||||
source = "cursor-import"
|
||||
|
||||
api_key = resolve_api_key()
|
||||
user_id = resolve_user_id()
|
||||
project_id = resolve_project_id()
|
||||
branch = resolve_branch()
|
||||
|
||||
if not api_key:
|
||||
print("Error: MEM0_API_KEY not set", file=sys.stderr)
|
||||
return
|
||||
|
||||
if not os.path.isfile(path):
|
||||
print(f"File not found: {path}", file=sys.stderr)
|
||||
return
|
||||
|
||||
with open(path, encoding="utf-8", errors="replace") as f:
|
||||
content = f.read()
|
||||
|
||||
raw_chunks = split_by_headers(content, "## ")
|
||||
# Fall back to treating the whole file as one chunk if no headers found
|
||||
if not raw_chunks:
|
||||
raw_chunks = [content.strip()] if content.strip() else []
|
||||
|
||||
chunks = filter_and_truncate(raw_chunks)
|
||||
n = import_chunks(chunks, api_key, user_id, project_id, branch, source, hash_key=f"{project_id}:{source}:{path}")
|
||||
print(f"Imported {n} memories from {source} ({path})")
|
||||
|
||||
|
||||
def cmd_copilot(args: list[str]) -> None:
|
||||
path = _parse_path_arg(args, "--path", ".github/copilot-instructions.md")
|
||||
source = "copilot-import"
|
||||
|
||||
api_key = resolve_api_key()
|
||||
user_id = resolve_user_id()
|
||||
project_id = resolve_project_id()
|
||||
branch = resolve_branch()
|
||||
|
||||
if not api_key:
|
||||
print("Error: MEM0_API_KEY not set", file=sys.stderr)
|
||||
return
|
||||
|
||||
if not os.path.isfile(path):
|
||||
print(f"File not found: {path}", file=sys.stderr)
|
||||
return
|
||||
|
||||
with open(path, encoding="utf-8", errors="replace") as f:
|
||||
content = f.read()
|
||||
|
||||
raw_chunks = split_by_headers(content, "## ")
|
||||
if not raw_chunks:
|
||||
raw_chunks = [content.strip()] if content.strip() else []
|
||||
|
||||
chunks = filter_and_truncate(raw_chunks)
|
||||
n = import_chunks(chunks, api_key, user_id, project_id, branch, source, hash_key=f"{project_id}:{source}:{path}")
|
||||
print(f"Imported {n} memories from {source} ({path})")
|
||||
|
||||
|
||||
def cmd_cline(args: list[str]) -> None:
|
||||
dir_path = _parse_path_arg(args, "--path", "memory-bank/")
|
||||
source = "cline-import"
|
||||
|
||||
api_key = resolve_api_key()
|
||||
user_id = resolve_user_id()
|
||||
project_id = resolve_project_id()
|
||||
branch = resolve_branch()
|
||||
|
||||
if not api_key:
|
||||
print("Error: MEM0_API_KEY not set", file=sys.stderr)
|
||||
return
|
||||
|
||||
if not os.path.isdir(dir_path):
|
||||
print(f"Directory not found: {dir_path}", file=sys.stderr)
|
||||
return
|
||||
|
||||
md_files = sorted(
|
||||
f for f in os.listdir(dir_path) if f.endswith(".md")
|
||||
)
|
||||
if not md_files:
|
||||
print(f"No .md files found in {dir_path}", file=sys.stderr)
|
||||
return
|
||||
|
||||
total = 0
|
||||
for filename in md_files:
|
||||
filepath = os.path.join(dir_path, filename)
|
||||
with open(filepath, encoding="utf-8", errors="replace") as f:
|
||||
content = f.read().strip()
|
||||
if not content:
|
||||
continue
|
||||
chunks = filter_and_truncate([content])
|
||||
n = import_chunks(chunks, api_key, user_id, project_id, branch, source, hash_key=f"{project_id}:{source}:{filepath}")
|
||||
total += n
|
||||
|
||||
print(f"Imported {total} memories from {source} ({dir_path})")
|
||||
|
||||
|
||||
def cmd_continue(args: list[str]) -> None:
|
||||
path = _parse_path_arg(args, "--path", ".continue/rules.md")
|
||||
source = "continue-import"
|
||||
|
||||
api_key = resolve_api_key()
|
||||
user_id = resolve_user_id()
|
||||
project_id = resolve_project_id()
|
||||
branch = resolve_branch()
|
||||
|
||||
if not api_key:
|
||||
print("Error: MEM0_API_KEY not set", file=sys.stderr)
|
||||
return
|
||||
|
||||
if not os.path.isfile(path):
|
||||
print(f"File not found: {path}", file=sys.stderr)
|
||||
return
|
||||
|
||||
with open(path, encoding="utf-8", errors="replace") as f:
|
||||
content = f.read()
|
||||
|
||||
raw_chunks = split_by_hr_or_headers(content)
|
||||
if not raw_chunks:
|
||||
raw_chunks = [content.strip()] if content.strip() else []
|
||||
|
||||
chunks = filter_and_truncate(raw_chunks)
|
||||
n = import_chunks(chunks, api_key, user_id, project_id, branch, source, hash_key=f"{project_id}:{source}:{path}")
|
||||
print(f"Imported {n} memories from {source} ({path})")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Entry point
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
COMMANDS = {
|
||||
"cursorrules": cmd_cursorrules,
|
||||
"copilot": cmd_copilot,
|
||||
"cline": cmd_cline,
|
||||
"continue": cmd_continue,
|
||||
}
|
||||
|
||||
|
||||
def main() -> None:
|
||||
if len(sys.argv) < 2 or sys.argv[1] not in COMMANDS:
|
||||
available = ", ".join(COMMANDS.keys())
|
||||
print("Usage: import_competing_tools.py <subcommand> [--path <path>]", file=sys.stderr)
|
||||
print(f"Subcommands: {available}", file=sys.stderr)
|
||||
sys.exit(0)
|
||||
|
||||
subcommand = sys.argv[1]
|
||||
remaining_args = sys.argv[2:]
|
||||
COMMANDS[subcommand](remaining_args)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
try:
|
||||
main()
|
||||
except Exception as e:
|
||||
print(f"Unexpected error: {e}", file=sys.stderr)
|
||||
sys.exit(0)
|
||||
+162
@@ -0,0 +1,162 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Install Mem0 lifecycle hooks into ~/.codex/hooks.json.
|
||||
|
||||
Codex discovers hooks only at ~/.codex/hooks.json or <repo>/.codex/hooks.json,
|
||||
and has no plugin-host mechanism for auto-wiring hooks from an installed
|
||||
plugin. This installer reads the template at hooks/codex-hooks.json, rewrites
|
||||
the ${PLUGIN_ROOT} placeholder to the absolute install path of this
|
||||
plugin, then merges the entries into ~/.codex/hooks.json.
|
||||
|
||||
Re-running is idempotent: existing Mem0 entries (identified by the plugin
|
||||
directory name in the command string) are removed before fresh entries are
|
||||
added, so upgrades don't leave duplicates.
|
||||
|
||||
Usage:
|
||||
python3 install_codex_hooks.py # install or update
|
||||
python3 install_codex_hooks.py --uninstall # remove Mem0 entries
|
||||
|
||||
After installing, Codex requires the hooks feature flag in ~/.codex/config.toml:
|
||||
|
||||
[features]
|
||||
codex_hooks = true
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import json
|
||||
import platform
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
SCRIPT_DIR = Path(__file__).resolve().parent
|
||||
PLUGIN_ROOT = SCRIPT_DIR.parent
|
||||
|
||||
CODEX_DIR = Path.home() / ".codex"
|
||||
HOOKS_FILE = CODEX_DIR / "hooks.json"
|
||||
CONFIG_FILE = CODEX_DIR / "config.toml"
|
||||
|
||||
TEMPLATE_FILE = PLUGIN_ROOT / "hooks" / "codex-hooks.json"
|
||||
|
||||
# Substring we look for when identifying entries this installer owns.
|
||||
# Matches the plugin directory name, which stays stable across install paths.
|
||||
OWNER_MARKER = "mem0-plugin"
|
||||
|
||||
|
||||
def load_template() -> dict:
|
||||
raw = TEMPLATE_FILE.read_text()
|
||||
raw = raw.replace("${PLUGIN_ROOT}", str(PLUGIN_ROOT))
|
||||
return json.loads(raw)
|
||||
|
||||
|
||||
def load_existing() -> dict:
|
||||
if not HOOKS_FILE.exists():
|
||||
return {"hooks": {}}
|
||||
try:
|
||||
return json.loads(HOOKS_FILE.read_text())
|
||||
except (json.JSONDecodeError, OSError) as e:
|
||||
print(f"error: failed to read {HOOKS_FILE}: {e}", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
def is_owned_entry(entry: dict) -> bool:
|
||||
for hook in entry.get("hooks", []):
|
||||
if OWNER_MARKER in hook.get("command", ""):
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def strip_owned_entries(config: dict) -> dict:
|
||||
hooks = config.get("hooks", {}) or {}
|
||||
for event in list(hooks.keys()):
|
||||
hooks[event] = [e for e in hooks[event] if not is_owned_entry(e)]
|
||||
if not hooks[event]:
|
||||
del hooks[event]
|
||||
config["hooks"] = hooks
|
||||
return config
|
||||
|
||||
|
||||
def merge_template(config: dict, template: dict) -> dict:
|
||||
hooks = config.setdefault("hooks", {})
|
||||
for event, entries in template.get("hooks", {}).items():
|
||||
hooks.setdefault(event, []).extend(entries)
|
||||
return config
|
||||
|
||||
|
||||
def write_config(config: dict) -> None:
|
||||
CODEX_DIR.mkdir(parents=True, exist_ok=True)
|
||||
HOOKS_FILE.write_text(json.dumps(config, indent=2) + "\n")
|
||||
|
||||
|
||||
def feature_flag_enabled() -> bool:
|
||||
if not CONFIG_FILE.exists():
|
||||
return False
|
||||
content = CONFIG_FILE.read_text()
|
||||
for line in content.splitlines():
|
||||
stripped = line.split("#", 1)[0].strip().replace(" ", "")
|
||||
if stripped == "codex_hooks=true":
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def print_feature_flag_hint() -> None:
|
||||
print()
|
||||
print("Codex hooks feature flag is not enabled.")
|
||||
print(f"Add this to {CONFIG_FILE}:")
|
||||
print()
|
||||
print(" [features]")
|
||||
print(" codex_hooks = true")
|
||||
print()
|
||||
print("Then restart Codex.")
|
||||
|
||||
|
||||
def main() -> int:
|
||||
parser = argparse.ArgumentParser(description="Install or remove Mem0 Codex hooks.")
|
||||
parser.add_argument(
|
||||
"--uninstall",
|
||||
action="store_true",
|
||||
help="Remove Mem0 entries from ~/.codex/hooks.json and exit.",
|
||||
)
|
||||
args = parser.parse_args()
|
||||
|
||||
config = load_existing()
|
||||
|
||||
if args.uninstall:
|
||||
config = strip_owned_entries(config)
|
||||
write_config(config)
|
||||
print(f"Removed Mem0 hooks from {HOOKS_FILE}")
|
||||
return 0
|
||||
|
||||
# Codex lifecycle hooks register .sh paths directly in ~/.codex/hooks.json.
|
||||
# On native Windows .sh has no default handler, so Codex spawning a hook
|
||||
# triggers "Open With" dialogs (one OpenWith.exe per event). See #5243.
|
||||
if platform.system() == "Windows":
|
||||
print(
|
||||
"Codex lifecycle hooks register .sh scripts directly, which Windows\n"
|
||||
"cannot execute without a bash interpreter on PATH. Re-run this\n"
|
||||
"installer from WSL or Git Bash, or use Mem0 via MCP / Direct tools\n",
|
||||
file=sys.stderr,
|
||||
)
|
||||
return 2
|
||||
|
||||
if not TEMPLATE_FILE.exists():
|
||||
print(f"error: template not found at {TEMPLATE_FILE}", file=sys.stderr)
|
||||
return 1
|
||||
|
||||
template = load_template()
|
||||
config = strip_owned_entries(config)
|
||||
config = merge_template(config, template)
|
||||
write_config(config)
|
||||
|
||||
print(f"Installed Mem0 hooks into {HOOKS_FILE}")
|
||||
print(f"Plugin path: {PLUGIN_ROOT}")
|
||||
print("Events: PreToolUse, SessionStart, UserPromptSubmit, PostToolUse")
|
||||
|
||||
if not feature_flag_enabled():
|
||||
print_feature_flag_hint()
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -0,0 +1,50 @@
|
||||
"""Load plugin settings from ~/.mem0/settings.json.
|
||||
|
||||
Settings file is user-editable. Missing file or keys fall back to defaults.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
from pathlib import Path
|
||||
|
||||
SETTINGS_PATH = Path.home() / ".mem0" / "settings.json"
|
||||
|
||||
DEFAULTS = {
|
||||
"auto_save": True,
|
||||
"auto_search": True,
|
||||
"search_limit": 10,
|
||||
"retention_session_days": 90,
|
||||
"confidence_threshold": 0.3,
|
||||
"global_search": False,
|
||||
"debug": False,
|
||||
}
|
||||
|
||||
|
||||
def load_settings() -> dict:
|
||||
settings = dict(DEFAULTS)
|
||||
if SETTINGS_PATH.exists():
|
||||
try:
|
||||
with open(SETTINGS_PATH) as f:
|
||||
user = json.load(f)
|
||||
settings.update({k: v for k, v in user.items() if k in DEFAULTS})
|
||||
except (json.JSONDecodeError, OSError):
|
||||
pass
|
||||
return settings
|
||||
|
||||
|
||||
def create_default_settings() -> None:
|
||||
SETTINGS_PATH.parent.mkdir(parents=True, exist_ok=True)
|
||||
if not SETTINGS_PATH.exists():
|
||||
with open(SETTINGS_PATH, "w") as f:
|
||||
json.dump(DEFAULTS, f, indent=2)
|
||||
f.write("\n")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import sys
|
||||
if len(sys.argv) > 1 and sys.argv[1] == "init":
|
||||
create_default_settings()
|
||||
print(f"Created {SETTINGS_PATH}")
|
||||
else:
|
||||
print(json.dumps(load_settings()))
|
||||
+122
@@ -0,0 +1,122 @@
|
||||
#!/usr/bin/env bash
|
||||
# Hook: PostToolUse (matcher: Bash)
|
||||
#
|
||||
# Scans bash command output for stack traces and error patterns.
|
||||
# When found, injects a search rubric telling the agent to check mem0
|
||||
# for prior occurrences of the same error.
|
||||
#
|
||||
# This complements on_user_prompt.sh (which catches errors in the user's
|
||||
# typed message). This hook catches errors in COMMAND OUTPUT — e.g.,
|
||||
# when `npm test` or `python script.py` fails with a traceback.
|
||||
#
|
||||
# Input: JSON on stdin with tool_name, tool_input, tool_response
|
||||
# Output: Context injected into Claude's next response (exit 0)
|
||||
|
||||
set -uo pipefail
|
||||
|
||||
INPUT=$(cat)
|
||||
|
||||
TOOL_RESULT=$(echo "$INPUT" | jq -r '.tool_response // ""' 2>/dev/null || echo "")
|
||||
|
||||
# Skip short output (< 50 chars unlikely to contain a real stack trace)
|
||||
if [ ${#TOOL_RESULT} -lt 50 ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
# Skip git operations — not useful for error detection
|
||||
COMMAND=$(echo "$INPUT" | jq -r '.tool_input.command // ""' 2>/dev/null || echo "")
|
||||
case "$COMMAND" in
|
||||
*"git commit"*|*"git merge"*|*"git rebase"*)
|
||||
exit 0
|
||||
;;
|
||||
esac
|
||||
|
||||
# Detect stack traces and error patterns in command output
|
||||
HAS_ERROR=""
|
||||
if echo "$TOOL_RESULT" | grep -qE '(Traceback \(most recent call last\)|panic: |FATAL:|error\[E[0-9]+\])'; then
|
||||
HAS_ERROR="true"
|
||||
elif [ "$(echo "$TOOL_RESULT" | grep -cE '(Error:|Exception:)')" -ge 2 ]; then
|
||||
HAS_ERROR="true"
|
||||
fi
|
||||
|
||||
if [ -z "$HAS_ERROR" ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
||||
. "$SCRIPT_DIR/_identity.sh" 2>/dev/null || true
|
||||
|
||||
# Extract error class/message (first matching line)
|
||||
ERROR_LINE=$(echo "$TOOL_RESULT" | grep -iE '(Error:|Exception:|panic:|FAIL:|fatal:)' | head -1 | sed 's/^[[:space:]]*//' | cut -c1-120)
|
||||
|
||||
# Extract file paths from stack trace frames
|
||||
TRACE_FILES=$(echo "$TOOL_RESULT" | grep -oE '([a-zA-Z0-9_./-]+\.(py|ts|tsx|js|jsx|rs|go|rb|java|sh))(:[0-9]+)?' | head -5 | sort -u)
|
||||
|
||||
# Build file list for display
|
||||
FILE_DISPLAY=""
|
||||
if [ -n "$TRACE_FILES" ]; then
|
||||
FILE_DISPLAY=$(echo "$TRACE_FILES" | sed 's/^/ - /')
|
||||
fi
|
||||
|
||||
USER_ID="${MEM0_RESOLVED_USER_ID:-${USER:-default}}"
|
||||
|
||||
# Extract query (first 80 chars of error line)
|
||||
ERROR_QUERY=$(echo "$ERROR_LINE" | cut -c1-80)
|
||||
|
||||
# Telemetry (fire regardless of API key)
|
||||
python3 "$SCRIPT_DIR/telemetry.py" bash_error --error_detected 2>/dev/null &
|
||||
|
||||
# No API key — skip output entirely
|
||||
if [ -z "${MEM0_API_KEY:-}" ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
# Pre-fetch memories: anti_pattern and bug_fix searches
|
||||
RESULTS=$(PYTHONPATH="$SCRIPT_DIR" MEM0_SEARCH_QUERY="$ERROR_QUERY" MEM0_SEARCH_USER="$USER_ID" \
|
||||
MEM0_API_KEY="${MEM0_API_KEY}" MEM0_PROJECT_ID="${MEM0_PROJECT_ID:-unknown}" \
|
||||
python3 -c "
|
||||
import os, sys
|
||||
sys.path.insert(0, os.environ.get('PYTHONPATH', '.'))
|
||||
from _search import search_memories, format_results_for_context
|
||||
|
||||
api_key = os.environ.get('MEM0_API_KEY', '')
|
||||
user_id = os.environ.get('MEM0_SEARCH_USER', 'default')
|
||||
project_id = os.environ.get('MEM0_PROJECT_ID', 'unknown')
|
||||
query = os.environ.get('MEM0_SEARCH_QUERY', '')
|
||||
|
||||
r1 = search_memories(api_key, user_id, project_id, query, metadata_type='anti_pattern', top_k=3)
|
||||
r2 = search_memories(api_key, user_id, project_id, query, metadata_type='bug_fix', top_k=3)
|
||||
|
||||
seen = set()
|
||||
combined = []
|
||||
for m in r1 + r2:
|
||||
mid = m.get('id', '')
|
||||
if mid not in seen:
|
||||
seen.add(mid)
|
||||
combined.append(m)
|
||||
|
||||
print(format_results_for_context(combined, heading='Prior error memories'), end='')
|
||||
" 2>/dev/null || echo "")
|
||||
|
||||
# Build context string for JSON output
|
||||
CTX="Error detected in command output\n\n"
|
||||
CTX="${CTX}\`${COMMAND}\` produced an error:\n> ${ERROR_LINE}\n"
|
||||
|
||||
if [ -n "$FILE_DISPLAY" ]; then
|
||||
CTX="${CTX}\nFiles in stack trace:\n${FILE_DISPLAY}\n"
|
||||
fi
|
||||
|
||||
if [ -n "$RESULTS" ]; then
|
||||
CTX="${CTX}\n${RESULTS}\n"
|
||||
fi
|
||||
|
||||
CTX="${CTX}\nResolved errors are stored as anti_pattern or bug_fix memories for future reference."
|
||||
|
||||
jq -cn --arg ctx "$CTX" '{
|
||||
hookSpecificOutput: {
|
||||
hookEventName: "PostToolUse",
|
||||
additionalContext: $ctx
|
||||
}
|
||||
}' 2>/dev/null || true
|
||||
|
||||
exit 0
|
||||
+51
@@ -0,0 +1,51 @@
|
||||
#!/usr/bin/env bash
|
||||
# Hook: PreToolUse (matcher: Read)
|
||||
#
|
||||
# Injects prior work context before Claude reads a file. Searches mem0
|
||||
# for memories referencing the file path and returns a compact timeline.
|
||||
#
|
||||
# Modeled after claude-mem's file-context handler, adapted for mem0 cloud API.
|
||||
#
|
||||
# Input: JSON on stdin with tool_name, tool_input (file_path), cwd
|
||||
# Output: JSON with hookSpecificOutput.additionalContext + permissionDecision
|
||||
#
|
||||
# Must never block the Read — silent exit on any failure.
|
||||
|
||||
set -uo pipefail
|
||||
|
||||
INPUT=$(cat)
|
||||
|
||||
# Extract file path from tool_input
|
||||
FILE_PATH=$(echo "$INPUT" | jq -r '.tool_input.file_path // ""' 2>/dev/null || echo "")
|
||||
if [ -z "$FILE_PATH" ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
||||
|
||||
# Resolve API key (covers Desktop app users who set it in shell profile)
|
||||
if [ -z "${MEM0_API_KEY:-}" ]; then
|
||||
. "$SCRIPT_DIR/_identity.sh" 2>/dev/null || true
|
||||
fi
|
||||
if [ -z "${MEM0_API_KEY:-}" ]; then
|
||||
exit 0
|
||||
fi
|
||||
CWD=$(echo "$INPUT" | jq -r '.cwd // "."' 2>/dev/null || echo ".")
|
||||
|
||||
# Call the Python worker — it handles gating (file size, existence)
|
||||
TIMELINE=$(python3 "$SCRIPT_DIR/file_context.py" "$FILE_PATH" "$CWD" 2>/dev/null || echo "")
|
||||
|
||||
if [ -z "$TIMELINE" ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
# Return context injection with permissionDecision: allow
|
||||
jq -cn --arg ctx "$TIMELINE" '{
|
||||
hookSpecificOutput: {
|
||||
hookEventName: "PreToolUse",
|
||||
additionalContext: $ctx,
|
||||
permissionDecision: "allow"
|
||||
}
|
||||
}' 2>/dev/null || true
|
||||
|
||||
exit 0
|
||||
+41
@@ -0,0 +1,41 @@
|
||||
#!/usr/bin/env bash
|
||||
# Hook: preToolUse (matcher: Read) — Cursor variant
|
||||
#
|
||||
# Same as on_file_read.sh but uses CURSOR_PLUGIN_ROOT for path resolution
|
||||
# and sources Cursor-specific identity.
|
||||
|
||||
set -uo pipefail
|
||||
|
||||
INPUT=$(cat)
|
||||
|
||||
FILE_PATH=$(echo "$INPUT" | jq -r '.tool_input.file_path // ""' 2>/dev/null || echo "")
|
||||
if [ -z "$FILE_PATH" ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
if [ -z "${MEM0_API_KEY:-}" ]; then
|
||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
||||
. "$SCRIPT_DIR/_identity.sh" 2>/dev/null || true
|
||||
fi
|
||||
if [ -z "${MEM0_API_KEY:-}" ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
||||
CWD=$(echo "$INPUT" | jq -r '.cwd // "."' 2>/dev/null || echo ".")
|
||||
|
||||
TIMELINE=$(python3 "$SCRIPT_DIR/file_context.py" "$FILE_PATH" "$CWD" 2>/dev/null || echo "")
|
||||
|
||||
if [ -z "$TIMELINE" ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
jq -cn --arg ctx "$TIMELINE" '{
|
||||
hookSpecificOutput: {
|
||||
hookEventName: "PreToolUse",
|
||||
additionalContext: $ctx,
|
||||
permissionDecision: "allow"
|
||||
}
|
||||
}' 2>/dev/null || true
|
||||
|
||||
exit 0
|
||||
+36
@@ -0,0 +1,36 @@
|
||||
#!/usr/bin/env bash
|
||||
# Hook: PostToolUse — track mem0 MCP tool usage for session stats
|
||||
#
|
||||
# Fires after any tool call. We only care about mem0 MCP tools:
|
||||
# mcp__mem0__add_memory → record an add
|
||||
# mcp__mem0__search_memories → record a search
|
||||
#
|
||||
# Input: JSON on stdin with tool_name, tool_input, tool_response
|
||||
# Output: none (exit 0, non-blocking)
|
||||
|
||||
set -uo pipefail
|
||||
|
||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
||||
|
||||
INPUT=$(cat)
|
||||
TOOL_NAME=$(echo "$INPUT" | jq -r '.tool_name // ""' 2>/dev/null || echo "")
|
||||
|
||||
case "$TOOL_NAME" in
|
||||
*__add_memory)
|
||||
CATEGORY=$(echo "$INPUT" | jq -r '.tool_input.metadata.type // .tool_input.metadata.category // ""' 2>/dev/null || echo "")
|
||||
python3 "$SCRIPT_DIR/session_stats.py" add "$CATEGORY" 2>/dev/null || true
|
||||
python3 "$SCRIPT_DIR/telemetry.py" tool_use --tool=add_memory 2>/dev/null &
|
||||
;;
|
||||
*__search_memories|*__get_memories)
|
||||
python3 "$SCRIPT_DIR/session_stats.py" search 2>/dev/null || true
|
||||
python3 "$SCRIPT_DIR/telemetry.py" tool_use --tool=search_memories 2>/dev/null &
|
||||
;;
|
||||
*__delete_memory)
|
||||
python3 "$SCRIPT_DIR/telemetry.py" tool_use --tool=delete_memory 2>/dev/null &
|
||||
;;
|
||||
*__update_memory)
|
||||
python3 "$SCRIPT_DIR/telemetry.py" tool_use --tool=update_memory 2>/dev/null &
|
||||
;;
|
||||
esac
|
||||
|
||||
exit 0
|
||||
@@ -0,0 +1,15 @@
|
||||
#!/usr/bin/env bash
|
||||
# Hook: postToolUse (Cursor) — track mem0 MCP tool usage for session stats
|
||||
#
|
||||
# Wraps on_post_tool_use.sh. Cursor expects JSON output but PostToolUse
|
||||
# has no meaningful return value, so we output {} after tracking.
|
||||
|
||||
set -uo pipefail
|
||||
|
||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
||||
|
||||
# Run the shared tracker (output is ignored)
|
||||
"$SCRIPT_DIR/on_post_tool_use.sh" 2>/dev/null || true
|
||||
|
||||
echo '{}'
|
||||
exit 0
|
||||
+314
@@ -0,0 +1,314 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Capture session state via the Mem0 REST API.
|
||||
|
||||
Safety net for PreCompact and Stop hooks — reads the transcript JSONL,
|
||||
extracts structured session state, and stores it in Mem0 directly.
|
||||
|
||||
Used by:
|
||||
- PreCompact hook: Tags with "pre-compaction" (context about to be lost)
|
||||
- Stop hook: Tags with "session-end" (session ending, Claude can't respond)
|
||||
|
||||
Input: JSON on stdin with transcript_path, session_id, cwd
|
||||
Output: stderr logs only (exit 0 always — must not block)
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import sys
|
||||
import urllib.error
|
||||
import urllib.request
|
||||
from datetime import date, timedelta
|
||||
|
||||
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
|
||||
from _identity import resolve_api_key, resolve_user_id
|
||||
from _project import resolve_branch, resolve_project_id
|
||||
|
||||
log = logging.getLogger("mem0-capture")
|
||||
log.setLevel(logging.DEBUG)
|
||||
_handler = logging.StreamHandler(sys.stderr)
|
||||
_handler.setFormatter(logging.Formatter("[mem0-capture] %(message)s"))
|
||||
log.addHandler(_handler)
|
||||
|
||||
if os.environ.get("MEM0_DEBUG"):
|
||||
_log_dir = os.path.expanduser("~/.mem0")
|
||||
try:
|
||||
os.makedirs(_log_dir, exist_ok=True)
|
||||
_file_handler = logging.FileHandler(os.path.join(_log_dir, "hooks.log"))
|
||||
_file_handler.setFormatter(logging.Formatter("[mem0-capture] %(asctime)s %(message)s"))
|
||||
log.addHandler(_file_handler)
|
||||
except OSError:
|
||||
pass
|
||||
|
||||
API_URL = "https://api.mem0.ai"
|
||||
MAX_TAIL_LINES = 500
|
||||
MAX_USER_MESSAGES = 30
|
||||
MAX_BASH_COMMANDS = 20
|
||||
MAX_ASSISTANT_TEXT = 10000
|
||||
# session_state captures churn fast (active codebase, files in flight). Past
|
||||
# ~3 months they're stale noise. Durable facts (decisions, conventions) are
|
||||
# stored separately by the agent without an expiration_date.
|
||||
SESSION_STATE_EXPIRY_DAYS = 90
|
||||
|
||||
|
||||
def tail_lines(filepath: str, n: int) -> list[str]:
|
||||
"""Read last n lines of a file efficiently."""
|
||||
try:
|
||||
with open(filepath, "rb") as f:
|
||||
f.seek(0, 2)
|
||||
file_size = f.tell()
|
||||
if file_size == 0:
|
||||
return []
|
||||
chunk_size = min(file_size, n * 4096)
|
||||
f.seek(max(0, file_size - chunk_size))
|
||||
data = f.read().decode("utf-8", errors="replace")
|
||||
return data.splitlines()[-n:]
|
||||
except OSError:
|
||||
return []
|
||||
|
||||
|
||||
def parse_transcript(lines: list[str]) -> dict:
|
||||
"""Parse transcript JSONL lines and extract session state."""
|
||||
user_messages: list[str] = []
|
||||
files_modified: set[str] = set()
|
||||
bash_commands: list[str] = []
|
||||
last_assistant_text = ""
|
||||
|
||||
for line in lines:
|
||||
line = line.strip()
|
||||
if not line:
|
||||
continue
|
||||
try:
|
||||
entry = json.loads(line)
|
||||
except json.JSONDecodeError:
|
||||
continue
|
||||
|
||||
entry_type = entry.get("type")
|
||||
if entry_type not in ("user", "assistant"):
|
||||
continue
|
||||
if entry.get("isSidechain"):
|
||||
continue
|
||||
|
||||
message = entry.get("message", {})
|
||||
content_blocks = message.get("content", [])
|
||||
|
||||
if entry_type == "user":
|
||||
parts = []
|
||||
if isinstance(content_blocks, str):
|
||||
parts.append(content_blocks)
|
||||
elif isinstance(content_blocks, list):
|
||||
for block in content_blocks:
|
||||
if isinstance(block, str):
|
||||
parts.append(block)
|
||||
elif isinstance(block, dict) and block.get("type") == "text":
|
||||
parts.append(block.get("text", ""))
|
||||
text = "\n".join(parts).strip()
|
||||
if text and len(text) > 10 and not text.startswith("<"):
|
||||
user_messages.append(text)
|
||||
|
||||
elif entry_type == "assistant":
|
||||
for block in content_blocks:
|
||||
if not isinstance(block, dict):
|
||||
continue
|
||||
if block.get("type") == "text":
|
||||
text = block.get("text", "").strip()
|
||||
if text:
|
||||
last_assistant_text = text
|
||||
if block.get("type") == "tool_use":
|
||||
tool_name = block.get("name", "")
|
||||
tool_input = block.get("input", {})
|
||||
if tool_name in ("Write", "Edit"):
|
||||
fp = tool_input.get("file_path", "")
|
||||
if fp:
|
||||
files_modified.add(fp)
|
||||
elif tool_name == "Bash":
|
||||
cmd = tool_input.get("command", "")
|
||||
if cmd:
|
||||
bash_commands.append(cmd)
|
||||
|
||||
return {
|
||||
"user_messages": user_messages[-MAX_USER_MESSAGES:],
|
||||
"files_modified": sorted(files_modified),
|
||||
"bash_commands": bash_commands[-MAX_BASH_COMMANDS:],
|
||||
"last_assistant_text": last_assistant_text[:MAX_ASSISTANT_TEXT],
|
||||
}
|
||||
|
||||
|
||||
def build_content(state: dict, source: str) -> str:
|
||||
"""Build minimal context — only what's needed to resume work.
|
||||
|
||||
This is a FALLBACK safety net, not the primary capture path.
|
||||
The agent handles rich memory storage via on_pre_compact.sh prompts.
|
||||
This script only fires when the agent didn't store enough on its own.
|
||||
|
||||
Keep it short — mem0 infer=True will extract structured facts.
|
||||
"""
|
||||
parts = []
|
||||
|
||||
if state["files_modified"]:
|
||||
parts.append(f"Files touched: {', '.join(state['files_modified'][:15])}")
|
||||
|
||||
if state["bash_commands"]:
|
||||
git_cmds = [c for c in state["bash_commands"] if "git " in c]
|
||||
if git_cmds:
|
||||
parts.append(f"Git operations: {len(git_cmds)}")
|
||||
|
||||
return "\n".join(parts)
|
||||
|
||||
|
||||
def store_memory(api_key: str, content: str, user_id: str, source: str, session_id: str = "", project_id: str = "", branch: str = "") -> bool:
|
||||
"""Store session state as a memory via the Mem0 REST API."""
|
||||
expires = (date.today() + timedelta(days=SESSION_STATE_EXPIRY_DAYS)).isoformat()
|
||||
metadata = {
|
||||
"type": "session_state",
|
||||
"source": source,
|
||||
"session_id": session_id,
|
||||
}
|
||||
if branch:
|
||||
metadata["branch"] = branch
|
||||
body = {
|
||||
"messages": [
|
||||
{"role": "user", "content": content}
|
||||
],
|
||||
"user_id": user_id,
|
||||
"app_id": project_id,
|
||||
"metadata": metadata,
|
||||
"expiration_date": expires,
|
||||
"infer": True,
|
||||
}
|
||||
|
||||
data = json.dumps(body).encode("utf-8")
|
||||
req = urllib.request.Request(
|
||||
f"{API_URL}/v3/memories/add/",
|
||||
data=data,
|
||||
headers={
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Token {api_key}",
|
||||
},
|
||||
method="POST",
|
||||
)
|
||||
|
||||
try:
|
||||
with urllib.request.urlopen(req, timeout=15) as resp:
|
||||
if resp.status in (200, 201):
|
||||
log.info("Session state stored successfully")
|
||||
return True
|
||||
log.warning("API returned status %d", resp.status)
|
||||
return False
|
||||
except urllib.error.URLError as e:
|
||||
log.warning("API call failed: %s", e)
|
||||
return False
|
||||
|
||||
|
||||
def format_status(state: dict, source: str, stored: bool, skipped_reason: str = "") -> str:
|
||||
"""Build a clean, readable status line for terminal display."""
|
||||
files_count = len(state.get("files_modified", []))
|
||||
git_cmds = [c for c in state.get("bash_commands", []) if "git " in c]
|
||||
user_msgs = len(state.get("user_messages", []))
|
||||
|
||||
parts = []
|
||||
if files_count:
|
||||
parts.append(f"{files_count} file{'s' if files_count != 1 else ''} touched")
|
||||
if git_cmds:
|
||||
parts.append(f"{len(git_cmds)} git op{'s' if len(git_cmds) != 1 else ''}")
|
||||
if user_msgs:
|
||||
parts.append(f"{user_msgs} exchange{'s' if user_msgs != 1 else ''}")
|
||||
|
||||
activity = ", ".join(parts) if parts else "minimal activity"
|
||||
|
||||
if source == "pre-compaction":
|
||||
icon = "✨" # ✨
|
||||
label = "Pre-compaction snapshot"
|
||||
else:
|
||||
icon = "\U0001f4be" # 💾
|
||||
label = "Session-end snapshot"
|
||||
|
||||
if skipped_reason:
|
||||
return f"{icon} Mem0 {label} — {activity} — {skipped_reason}"
|
||||
elif stored:
|
||||
return f"{icon} Mem0 {label} — {activity} — saved to mem0"
|
||||
else:
|
||||
return f"{icon} Mem0 {label} — {activity} — nothing to capture"
|
||||
|
||||
|
||||
def main():
|
||||
source = "pre-compaction"
|
||||
show_status = False
|
||||
for arg in sys.argv[1:]:
|
||||
if arg.startswith("--source="):
|
||||
source = arg.split("=", 1)[1]
|
||||
elif arg == "--status":
|
||||
show_status = True
|
||||
|
||||
api_key = resolve_api_key()
|
||||
if not api_key:
|
||||
log.debug("MEM0_API_KEY not set, skipping capture")
|
||||
if show_status:
|
||||
print("✨ Mem0 — no API key, skipping capture")
|
||||
return
|
||||
|
||||
try:
|
||||
hook_input = json.loads(sys.stdin.read())
|
||||
except (json.JSONDecodeError, OSError):
|
||||
log.debug("No valid JSON on stdin")
|
||||
return
|
||||
|
||||
transcript_path = hook_input.get("transcript_path", "")
|
||||
if not transcript_path:
|
||||
log.debug("No transcript_path provided")
|
||||
return
|
||||
|
||||
session_id = hook_input.get("session_id", "")
|
||||
cwd = hook_input.get("cwd") or None
|
||||
user_id = resolve_user_id()
|
||||
project_id = resolve_project_id(cwd)
|
||||
branch = resolve_branch(cwd)
|
||||
|
||||
lines = tail_lines(transcript_path, MAX_TAIL_LINES)
|
||||
if not lines:
|
||||
log.debug("Transcript empty or unreadable: %s", transcript_path)
|
||||
return
|
||||
|
||||
state = parse_transcript(lines)
|
||||
|
||||
# Skip if agent already stored memories this session — avoid duplicate writes.
|
||||
stats_file = f"/tmp/mem0_session_stats_{os.environ.get('USER', 'default')}.json"
|
||||
try:
|
||||
with open(stats_file) as f:
|
||||
stats = json.load(f)
|
||||
if stats.get("adds", 0) >= 1:
|
||||
log.info("Agent stored %d memories this session — skipping fallback", stats["adds"])
|
||||
if show_status:
|
||||
print(format_status(state, source, False, f"agent already stored {stats['adds']} memor{'ies' if stats['adds'] != 1 else 'y'}"))
|
||||
return
|
||||
except (OSError, json.JSONDecodeError):
|
||||
pass
|
||||
|
||||
if not state["files_modified"]:
|
||||
log.debug("No files modified — skipping fallback capture")
|
||||
if show_status:
|
||||
print(format_status(state, source, False))
|
||||
return
|
||||
|
||||
content = build_content(state, source)
|
||||
if not content.strip():
|
||||
log.debug("No content to store")
|
||||
if show_status:
|
||||
print(format_status(state, source, False))
|
||||
return
|
||||
|
||||
log.info("Fallback capture: %d files modified", len(state["files_modified"]))
|
||||
stored = store_memory(api_key, content, user_id, source, session_id, project_id, branch)
|
||||
|
||||
if show_status:
|
||||
print(format_status(state, source, stored))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
try:
|
||||
main()
|
||||
except Exception as e:
|
||||
log.error("Unexpected error: %s", e)
|
||||
sys.exit(0)
|
||||
+23
@@ -0,0 +1,23 @@
|
||||
#!/usr/bin/env bash
|
||||
# Hook: PreCompact
|
||||
#
|
||||
# Fires BEFORE context compaction. Captures session state via REST API
|
||||
# in the background. Runs silently — no output to user.
|
||||
|
||||
set -uo pipefail
|
||||
|
||||
if [ -n "${MEM0_DEBUG:-}" ]; then
|
||||
mkdir -p "$HOME/.mem0" && exec 2>>"$HOME/.mem0/hooks.log"
|
||||
fi
|
||||
|
||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
||||
INPUT=$(cat)
|
||||
|
||||
python3 "$SCRIPT_DIR/telemetry.py" pre_compact 2>/dev/null &
|
||||
|
||||
# Capture in background, no stdout
|
||||
_TMP="/tmp/mem0_precompact_input_$$.json"
|
||||
printf '%s' "$INPUT" > "$_TMP" 2>/dev/null
|
||||
(python3 "$SCRIPT_DIR/on_pre_compact.py" --source=pre-compaction < "$_TMP" 2>/dev/null; rm -f "$_TMP") &
|
||||
|
||||
exit 0
|
||||
@@ -0,0 +1,19 @@
|
||||
#!/usr/bin/env bash
|
||||
# Hook: preCompact (Cursor)
|
||||
#
|
||||
# Wraps on_pre_compact.sh and converts plain-text output to Cursor's
|
||||
# expected JSON format: {"user_message":"<text>"}
|
||||
|
||||
set -uo pipefail
|
||||
|
||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
||||
|
||||
TEXT=$("$SCRIPT_DIR/on_pre_compact.sh" 2>/dev/null || echo "")
|
||||
|
||||
if [ -z "$TEXT" ]; then
|
||||
echo '{}'
|
||||
exit 0
|
||||
fi
|
||||
|
||||
jq -cn --arg msg "$TEXT" '{user_message:$msg}'
|
||||
exit 0
|
||||
+199
@@ -0,0 +1,199 @@
|
||||
#!/usr/bin/env bash
|
||||
set -uo pipefail
|
||||
|
||||
if [ -n "${MEM0_DEBUG:-}" ]; then
|
||||
mkdir -p "$HOME/.mem0" && exec 2>>"$HOME/.mem0/hooks.log"
|
||||
fi
|
||||
|
||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
||||
. "$SCRIPT_DIR/_identity.sh" 2>/dev/null || true
|
||||
|
||||
INPUT=$(cat)
|
||||
SOURCE=$(echo "$INPUT" | jq -r '.source // "startup"' 2>/dev/null || echo "startup")
|
||||
|
||||
if [ "$SOURCE" = "startup" ]; then
|
||||
python3 "$SCRIPT_DIR/session_stats.py" init 2>/dev/null || true
|
||||
rm -f /tmp/mem0_recent_reads_${USER}_* 2>/dev/null || true
|
||||
fi
|
||||
PYTHONPATH="$SCRIPT_DIR" python3 "$SCRIPT_DIR/load_settings.py" init 2>/dev/null || true
|
||||
rm -f "/tmp/mem0_rubric_injected_${USER}" 2>/dev/null || true
|
||||
rm -f /tmp/mem0_rubric_* 2>/dev/null || true
|
||||
rm -f "/tmp/mem0_msg_count_${USER:-default}" 2>/dev/null || true
|
||||
MEM0_SESSION_ID=$(echo "$INPUT" | jq -r '.session_id // ""' 2>/dev/null || echo "")
|
||||
if [ -z "$MEM0_SESSION_ID" ]; then
|
||||
MEM0_SESSION_ID="ses_$(date +%s)_$$"
|
||||
fi
|
||||
printf '%s' "$MEM0_SESSION_ID" > "/tmp/mem0_session_id_${USER}"
|
||||
export MEM0_SESSION_ID
|
||||
|
||||
# Persist identity to Claude's env so Bash tool calls, MCP config, and other hooks see them
|
||||
if [ -n "${CLAUDE_ENV_FILE:-}" ]; then
|
||||
echo "export MEM0_SESSION_ID=\"$MEM0_SESSION_ID\"" >> "$CLAUDE_ENV_FILE"
|
||||
echo "export MEM0_RESOLVED_USER_ID=\"${MEM0_RESOLVED_USER_ID:-$USER}\"" >> "$CLAUDE_ENV_FILE"
|
||||
echo "export MEM0_PROJECT_ID=\"${MEM0_PROJECT_ID:-unknown}\"" >> "$CLAUDE_ENV_FILE"
|
||||
echo "export MEM0_BRANCH=\"${MEM0_BRANCH:-unknown}\"" >> "$CLAUDE_ENV_FILE"
|
||||
if [ -n "${MEM0_API_KEY:-}" ]; then
|
||||
echo "export MEM0_API_KEY=\"$MEM0_API_KEY\"" >> "$CLAUDE_ENV_FILE"
|
||||
fi
|
||||
fi
|
||||
|
||||
if [ -z "${MEM0_API_KEY:-}" ]; then
|
||||
_UID="${MEM0_RESOLVED_USER_ID:-${USER:-default}}"
|
||||
_PID="${MEM0_PROJECT_ID:-unknown}"
|
||||
_BR="${MEM0_BRANCH:-unknown}"
|
||||
cat <<BANNER
|
||||
## Mem0 — Setup Required
|
||||
|
||||
\`user=${_UID} | project=${_PID} | branch=${_BR} | auth=none\`
|
||||
|
||||
IMPORTANT: In your FIRST response, display this exact status line as your opening line:
|
||||
|
||||
\`\`\`
|
||||
Mem0 — Setup Required | user=${_UID} | project=${_PID} | branch=${_BR} | auth=none
|
||||
\`\`\`
|
||||
|
||||
MEM0_API_KEY is not set. To configure:
|
||||
- **Reinstall the plugin**: Uninstall and reinstall — Claude Code will prompt for your API key during setup (stored securely in keychain)
|
||||
- **Desktop app**: Click the environment dropdown next to the prompt box → hover over **Local** → click the **gear icon** → add \`MEM0_API_KEY=m0-...\`
|
||||
- **CLI**: Add \`export MEM0_API_KEY=m0-...\` to your shell profile (~/.zshrc or ~/.bashrc)
|
||||
- Get a key at https://app.mem0.ai/dashboard/api-keys
|
||||
|
||||
Then invoke the \`mem0:onboard\` skill to complete setup.
|
||||
BANNER
|
||||
exit 0
|
||||
fi
|
||||
|
||||
_DATA_DIR="${CLAUDE_PLUGIN_DATA:-$HOME/.mem0/plugin-data}"
|
||||
_INSTALL_WARN=""
|
||||
if [ -f "${_DATA_DIR}/.install-failed" ]; then
|
||||
_INSTALL_WARN="mem0 SDK installation failed. Run: ${CLAUDE_PLUGIN_ROOT:-$SCRIPT_DIR/..}/scripts/ensure_deps.sh"
|
||||
fi
|
||||
|
||||
MEM0_COUNT="?"
|
||||
if command -v python3 >/dev/null 2>&1; then
|
||||
MEM0_COUNT=$(python3 -c "
|
||||
import json, os, urllib.request, urllib.error
|
||||
api_key = os.environ.get('MEM0_API_KEY', '')
|
||||
user_id = os.environ.get('MEM0_RESOLVED_USER_ID', 'default')
|
||||
app_id = os.environ.get('MEM0_PROJECT_ID', '')
|
||||
global_search = os.environ.get('MEM0_GLOBAL_SEARCH', 'false') == 'true'
|
||||
|
||||
def get_count(filters):
|
||||
body = json.dumps({'filters': filters}).encode()
|
||||
req = urllib.request.Request(
|
||||
'https://api.mem0.ai/v3/memories/?page=1&page_size=1',
|
||||
headers={'Authorization': f'Token {api_key}', 'Content-Type': 'application/json'},
|
||||
data=body, method='POST',
|
||||
)
|
||||
with urllib.request.urlopen(req, timeout=5) as r:
|
||||
data = json.loads(r.read())
|
||||
if isinstance(data, dict) and 'count' in data:
|
||||
return data['count']
|
||||
if isinstance(data, list):
|
||||
return len(data)
|
||||
return 0
|
||||
|
||||
try:
|
||||
if global_search:
|
||||
filters = {'OR': [{'user_id': '*'}]}
|
||||
else:
|
||||
filters = {'AND': [{'user_id': user_id}, {'app_id': app_id}]}
|
||||
total = get_count(filters)
|
||||
print(total)
|
||||
except Exception:
|
||||
print('?')
|
||||
" 2>/dev/null || echo "?")
|
||||
fi
|
||||
|
||||
_UID="${MEM0_RESOLVED_USER_ID:-${USER:-default}}"
|
||||
_ANN="${_MEM0_IDENTITY_ANNOTATION:-}"
|
||||
_PID="${MEM0_PROJECT_ID:-unknown}"
|
||||
_BR="${MEM0_BRANCH:-unknown}"
|
||||
_GS="${MEM0_GLOBAL_SEARCH:-false}"
|
||||
|
||||
if [ "$_GS" = "true" ]; then
|
||||
_SCOPE_LABEL="scope=global"
|
||||
_SCOPE_INSTR="Global search is ON — searches return all memories across all users and projects. Writes still use user_id: \`${_UID}\`, app_id: \`${_PID}\`."
|
||||
else
|
||||
_SCOPE_LABEL="project=${_PID}"
|
||||
_SCOPE_INSTR="Always include \`user_id\` + \`app_id\` in every \`search_memories\` filter and \`add_memory\` call:
|
||||
- user_id: \`${_UID}\`
|
||||
- app_id: \`${_PID}\` (project scope — passed as top-level \`app_id\`, NOT in metadata)"
|
||||
fi
|
||||
|
||||
cat <<BANNER
|
||||
## Mem0 Active
|
||||
|
||||
\`user=${_UID}${_ANN} | ${_SCOPE_LABEL} | branch=${_BR} | memories=${MEM0_COUNT}\`
|
||||
|
||||
IMPORTANT: In your FIRST response, display this exact status line as your opening line:
|
||||
|
||||
\`\`\`
|
||||
Mem0 Active | user=${_UID}${_ANN} | ${_SCOPE_LABEL} | branch=${_BR} | memories=${MEM0_COUNT}
|
||||
\`\`\`
|
||||
|
||||
${_SCOPE_INSTR}
|
||||
|
||||
After completing any task, decision, or meaningful exchange, proactively store learnings via \`add_memory\`. Do NOT wait until the session ends — store memories incrementally as work progresses. Focus on: decisions made, bugs fixed, patterns discovered, user preferences, or task outcomes. Aim for 1–3 memories per substantial interaction.
|
||||
|
||||
BANNER
|
||||
|
||||
if [ -n "$_INSTALL_WARN" ]; then
|
||||
echo "$_INSTALL_WARN"
|
||||
fi
|
||||
|
||||
MEM0_CWD_RESOLVED=$(echo "$INPUT" | jq -r '.cwd // "."' 2>/dev/null || echo ".")
|
||||
if command -v python3 >/dev/null 2>&1; then
|
||||
MEM0_PROJECT_CONFIG=$(python3 "$SCRIPT_DIR/parse_mem0_config.py" --full "$MEM0_CWD_RESOLVED" 2>/dev/null || echo "{}")
|
||||
if [ -n "$MEM0_PROJECT_CONFIG" ] && [ "$MEM0_PROJECT_CONFIG" != "{}" ]; then
|
||||
_CONFIG_KEYS=$(echo "$MEM0_PROJECT_CONFIG" | python3 -c "import sys,json; d=json.load(sys.stdin); print(len(d))" 2>/dev/null || echo "?")
|
||||
echo "mem0.md loaded (${_CONFIG_KEYS} sections configured)."
|
||||
fi
|
||||
fi
|
||||
|
||||
if [ "$SOURCE" = "startup" ]; then
|
||||
if [ "$MEM0_COUNT" = "0" ]; then
|
||||
echo "New project with 0 memories. Invoke the mem0:onboard skill to import project files. Coding categories install automatically in the background."
|
||||
else
|
||||
echo "Search mem0 for recent decisions and task learnings before responding. Run 2 parallel searches: one for decision type, one for task_learning type."
|
||||
|
||||
# Inject compact recent activity timeline (non-blocking, 5s timeout)
|
||||
# Use perl alarm as portable timeout (macOS lacks GNU timeout)
|
||||
_TIMELINE=$(MEM0_CWD="$MEM0_CWD_RESOLVED" perl -e 'alarm 5; exec @ARGV' python3 "$SCRIPT_DIR/session_timeline.py" 2>/dev/null || echo "")
|
||||
if [ -n "$_TIMELINE" ]; then
|
||||
echo ""
|
||||
echo "$_TIMELINE"
|
||||
fi
|
||||
fi
|
||||
|
||||
_PROJ_KEY=$(printf '%s' "$MEM0_CWD_RESOLVED" | tr '/' '-')
|
||||
_MEMORY_MD="$HOME/.claude/projects/${_PROJ_KEY}/memory/MEMORY.md"
|
||||
if [ -f "$_MEMORY_MD" ] && [ -s "$_MEMORY_MD" ]; then
|
||||
echo "Native MEMORY.md detected at ${_MEMORY_MD}. Add autoMemoryEnabled:false to settings.json or run /mem0:import."
|
||||
fi
|
||||
|
||||
MEM0_CWD="$MEM0_CWD_RESOLVED" \
|
||||
python3 "$SCRIPT_DIR/auto_import.py" 2>/dev/null &
|
||||
|
||||
# Configure the coding-category taxonomy in the background (idempotent, never blocks).
|
||||
# Prefer the venv python since this path needs the mem0ai SDK.
|
||||
_VENV_PY="${CLAUDE_PLUGIN_DATA:-$HOME/.mem0/plugin-data}/venv/bin/python3"
|
||||
if [ -x "$_VENV_PY" ]; then
|
||||
MEM0_CWD="$MEM0_CWD_RESOLVED" "$_VENV_PY" "$SCRIPT_DIR/auto_setup_categories.py" 2>/dev/null &
|
||||
else
|
||||
MEM0_CWD="$MEM0_CWD_RESOLVED" python3 "$SCRIPT_DIR/auto_setup_categories.py" 2>/dev/null &
|
||||
fi
|
||||
|
||||
elif [ "$SOURCE" = "resume" ]; then
|
||||
echo "Session resumed. Search mem0 for session_state and decision memories to pick up where you left off. Run 2 parallel searches."
|
||||
|
||||
elif [ "$SOURCE" = "compact" ]; then
|
||||
echo "Context compacted. Search mem0 for session_state and decision memories to recover context. Run 2 parallel searches."
|
||||
if [ "${MEM0_AUTO_SAVE:-true}" != "false" ]; then
|
||||
printf '%s' "$INPUT" | python3 "$SCRIPT_DIR/capture_compact_summary.py" 2>/dev/null &
|
||||
fi
|
||||
fi
|
||||
|
||||
python3 "$SCRIPT_DIR/telemetry.py" session_start --source="$SOURCE" --memory_count="${MEM0_COUNT:-0}" 2>/dev/null &
|
||||
|
||||
exit 0
|
||||
@@ -0,0 +1,19 @@
|
||||
#!/usr/bin/env bash
|
||||
# Hook: sessionStart (Cursor)
|
||||
#
|
||||
# Wraps on_session_start.sh and converts plain-text output to Cursor's
|
||||
# expected JSON format: {"additional_context":"<text>"}
|
||||
|
||||
set -uo pipefail
|
||||
|
||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
||||
|
||||
TEXT=$("$SCRIPT_DIR/on_session_start.sh" 2>/dev/null || echo "")
|
||||
|
||||
if [ -z "$TEXT" ]; then
|
||||
echo '{}'
|
||||
exit 0
|
||||
fi
|
||||
|
||||
jq -cn --arg ctx "$TEXT" '{additional_context:$ctx}'
|
||||
exit 0
|
||||
Executable
+55
@@ -0,0 +1,55 @@
|
||||
#!/usr/bin/env bash
|
||||
# Hook: Stop
|
||||
#
|
||||
# Captures a structured session summary when a Claude Code session ends.
|
||||
# Parses the transcript, extracts the last assistant message and files
|
||||
# touched, then stores via mem0 API with infer=True for AI extraction.
|
||||
#
|
||||
# Guards:
|
||||
# - Skips subagent sessions (agent_id present)
|
||||
# - Skips if no API key
|
||||
# - Skips if no transcript_path
|
||||
# - Dedup via marker file
|
||||
#
|
||||
# Input: JSON on stdin with transcript_path, session_id, agent_id, cwd
|
||||
# Output: Nothing to stdout (background capture). Always exits 0.
|
||||
|
||||
set -uo pipefail
|
||||
|
||||
if [ -n "${MEM0_DEBUG:-}" ]; then
|
||||
mkdir -p "$HOME/.mem0" && exec 2>>"$HOME/.mem0/hooks.log"
|
||||
fi
|
||||
|
||||
INPUT=$(cat)
|
||||
|
||||
# Guard: skip subagent sessions
|
||||
AGENT_ID=$(echo "$INPUT" | jq -r '.agent_id // ""' 2>/dev/null || echo "")
|
||||
if [ -n "$AGENT_ID" ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
# Resolve identity if needed
|
||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
||||
. "$SCRIPT_DIR/_identity.sh" 2>/dev/null || true
|
||||
|
||||
# Honor auto_save=false in ~/.mem0/settings.json
|
||||
if [ "${MEM0_AUTO_SAVE:-true}" = "false" ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
if [ -z "${MEM0_API_KEY:-}" ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
TRANSCRIPT_PATH=$(echo "$INPUT" | jq -r '.transcript_path // ""' 2>/dev/null || echo "")
|
||||
if [ -z "$TRANSCRIPT_PATH" ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
# Run capture in the background — fires every turn now, so avoid blocking
|
||||
echo "$INPUT" | python3 "$SCRIPT_DIR/capture_session_summary.py" 2>/dev/null &
|
||||
|
||||
# Telemetry
|
||||
python3 "$SCRIPT_DIR/telemetry.py" session_stop 2>/dev/null &
|
||||
|
||||
exit 0
|
||||
+36
@@ -0,0 +1,36 @@
|
||||
#!/usr/bin/env bash
|
||||
# Hook: stop — Cursor variant
|
||||
#
|
||||
# Same as on_stop.sh but uses CURSOR_PLUGIN_ROOT and Cursor-specific
|
||||
# identity resolution.
|
||||
|
||||
set -uo pipefail
|
||||
|
||||
if [ -n "${MEM0_DEBUG:-}" ]; then
|
||||
mkdir -p "$HOME/.mem0" && exec 2>>"$HOME/.mem0/hooks.log"
|
||||
fi
|
||||
|
||||
INPUT=$(cat)
|
||||
|
||||
AGENT_ID=$(echo "$INPUT" | jq -r '.agent_id // ""' 2>/dev/null || echo "")
|
||||
if [ -n "$AGENT_ID" ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
||||
. "$SCRIPT_DIR/_identity.sh" 2>/dev/null || true
|
||||
|
||||
if [ -z "${MEM0_API_KEY:-}" ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
TRANSCRIPT_PATH=$(echo "$INPUT" | jq -r '.transcript_path // ""' 2>/dev/null || echo "")
|
||||
if [ -z "$TRANSCRIPT_PATH" ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
echo "$INPUT" | python3 "$SCRIPT_DIR/capture_session_summary.py" 2>/dev/null || true
|
||||
|
||||
python3 "$SCRIPT_DIR/telemetry.py" session_stop 2>/dev/null &
|
||||
|
||||
exit 0
|
||||
+201
@@ -0,0 +1,201 @@
|
||||
#!/usr/bin/env bash
|
||||
# Hook: UserPromptSubmit
|
||||
#
|
||||
# Fires on every user message. Instead of pre-searching mem0 with the
|
||||
# raw prompt, this injects a decision rubric telling the agent when
|
||||
# and how to search itself. The agent has more context than this
|
||||
# script does -- let it decide.
|
||||
#
|
||||
# Input: JSON on stdin (prompt, session_id, cwd, transcript_path)
|
||||
# Output: Decision rubric injected into Claude's context (exit 0)
|
||||
|
||||
# Intentionally omit -e so the script always exits 0 even if jq fails --
|
||||
# must never block the user's prompt.
|
||||
set -uo pipefail
|
||||
|
||||
if [ -n "${MEM0_DEBUG:-}" ]; then
|
||||
mkdir -p "$HOME/.mem0" && exec 2>>"$HOME/.mem0/hooks.log"
|
||||
fi
|
||||
|
||||
INPUT=$(cat)
|
||||
PROMPT=$(echo "$INPUT" | jq -r '.prompt // ""' 2>/dev/null || echo "")
|
||||
|
||||
# Acknowledgements and short replies don't warrant memory context
|
||||
if [ ${#PROMPT} -lt 20 ]; then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
||||
# shellcheck source=_identity.sh
|
||||
. "$SCRIPT_DIR/_identity.sh" 2>/dev/null || true
|
||||
|
||||
# Rubric dedup: only inject full rubric once per session.
|
||||
# Key on session ID to avoid cross-session interference.
|
||||
SESSION_ID=$(echo "$INPUT" | jq -r '.session_id // ""' 2>/dev/null || echo "")
|
||||
if [ -z "$SESSION_ID" ]; then
|
||||
_SID_FILE="/tmp/mem0_session_id_${USER:-default}"
|
||||
[ -f "$_SID_FILE" ] && SESSION_ID=$(cat "$_SID_FILE" 2>/dev/null) || true
|
||||
fi
|
||||
if [ -z "$SESSION_ID" ]; then
|
||||
SESSION_ID="default_${USER:-unknown}"
|
||||
fi
|
||||
RUBRIC_DIR="${MEM0_RUBRIC_DIR:-/tmp}"
|
||||
RUBRIC_FLAG="$RUBRIC_DIR/mem0_rubric_${SESSION_ID}"
|
||||
RUBRIC_ALREADY_SHOWN=""
|
||||
if [ -f "$RUBRIC_FLAG" ]; then
|
||||
RUBRIC_ALREADY_SHOWN="true"
|
||||
fi
|
||||
|
||||
# Track message count for periodic memory-save nudges.
|
||||
# Every 5th substantial message, remind the agent to store learnings.
|
||||
MSG_COUNT_FILE="/tmp/mem0_msg_count_${USER:-default}"
|
||||
MSG_COUNT=0
|
||||
if [ -f "$MSG_COUNT_FILE" ]; then
|
||||
MSG_COUNT=$(cat "$MSG_COUNT_FILE" 2>/dev/null || echo "0")
|
||||
fi
|
||||
MSG_COUNT=$((MSG_COUNT + 1))
|
||||
printf '%s' "$MSG_COUNT" > "$MSG_COUNT_FILE" 2>/dev/null || true
|
||||
NEEDS_SAVE_NUDGE=""
|
||||
if [ $((MSG_COUNT % 5)) -eq 0 ] && [ "$MSG_COUNT" -gt 0 ]; then
|
||||
NEEDS_SAVE_NUDGE="true"
|
||||
fi
|
||||
|
||||
# Detect stack traces and error patterns in the prompt (no API needed)
|
||||
HAS_ERROR=""
|
||||
if echo "$PROMPT" | grep -qE '(Traceback|panic:)'; then
|
||||
HAS_ERROR="true"
|
||||
elif echo "$PROMPT" | grep -qE '^\s*fatal: '; then
|
||||
HAS_ERROR="true"
|
||||
elif [ "$(echo "$PROMPT" | grep -cE '(Error:|Exception:|FAIL:)')" -ge 2 ]; then
|
||||
HAS_ERROR="true"
|
||||
fi
|
||||
|
||||
# Detect file paths in the prompt (no API needed)
|
||||
FILE_PATHS=$(echo "$PROMPT" | grep -oE '([a-zA-Z0-9_./-]+\.(py|ts|tsx|js|jsx|rs|go|rb|java|sh|yaml|yml|json|toml|md|sql|css|html))\b' 2>/dev/null | head -5 || echo "")
|
||||
|
||||
# Detect session-resume patterns
|
||||
HAS_RESUME=""
|
||||
if echo "$PROMPT" | grep -qiE '(where (did )?(we|I) (leave|left) off|continue (from )?(where|last)|what were we (working|doing)|pick up where|resume (from |where)|what.s the (current|latest) (state|status)|catch me up|where are we)'; then
|
||||
HAS_RESUME="true"
|
||||
fi
|
||||
|
||||
# Detect explicit memory-save intent
|
||||
HAS_REMEMBER=""
|
||||
if echo "$PROMPT" | grep -qiE '(remember (this|that)|save (this|that) (fact|info|memory|note)|store (this|that)|don.t forget (this|that)|keep (this|that) in (mind|memory))'; then
|
||||
HAS_REMEMBER="true"
|
||||
fi
|
||||
|
||||
# Telemetry (background, fire-and-forget)
|
||||
_TELEM_ARGS=""
|
||||
[ -n "$HAS_ERROR" ] && _TELEM_ARGS="$_TELEM_ARGS --error_detected"
|
||||
[ -n "$FILE_PATHS" ] && _TELEM_ARGS="$_TELEM_ARGS --file_paths_detected"
|
||||
[ -n "$HAS_RESUME" ] && _TELEM_ARGS="$_TELEM_ARGS --resume_detected"
|
||||
[ -n "$HAS_REMEMBER" ] && _TELEM_ARGS="$_TELEM_ARGS --remember_detected"
|
||||
python3 "$SCRIPT_DIR/telemetry.py" user_prompt $_TELEM_ARGS 2>/dev/null &
|
||||
|
||||
# No API key — emit detections only, skip search rubric
|
||||
if [ -z "${MEM0_API_KEY:-}" ]; then
|
||||
_PROMPT_CTX=""
|
||||
if [ -n "$HAS_ERROR" ]; then
|
||||
_PROMPT_CTX="Error detected in prompt. Set MEM0_API_KEY to search past debugging context."
|
||||
fi
|
||||
if [ -n "$FILE_PATHS" ]; then
|
||||
_PROMPT_CTX="${_PROMPT_CTX:+${_PROMPT_CTX}\n}File paths detected: ${FILE_PATHS}"
|
||||
fi
|
||||
if [ -n "$_PROMPT_CTX" ]; then
|
||||
jq -cn --arg ctx "$_PROMPT_CTX" '{
|
||||
hookSpecificOutput: {
|
||||
hookEventName: "UserPromptSubmit",
|
||||
additionalContext: $ctx
|
||||
}
|
||||
}'
|
||||
fi
|
||||
exit 0
|
||||
fi
|
||||
USER_ID="$MEM0_RESOLVED_USER_ID"
|
||||
|
||||
_PROMPT_CTX=""
|
||||
|
||||
if [ -n "$HAS_RESUME" ]; then
|
||||
RESUME_RESULTS=$(PYTHONPATH="$SCRIPT_DIR" MEM0_SEARCH_USER="$USER_ID" python3 -c "
|
||||
import os, sys
|
||||
sys.path.insert(0, os.environ.get('PYTHONPATH', '.'))
|
||||
from _search import search_memories, format_results_for_context
|
||||
|
||||
api_key = os.environ.get('MEM0_API_KEY', '')
|
||||
user_id = os.environ.get('MEM0_SEARCH_USER', 'default')
|
||||
project_id = os.environ.get('MEM0_PROJECT_ID', 'unknown')
|
||||
|
||||
state = search_memories(api_key, user_id, project_id, 'session state current task', metadata_type='session_state', top_k=3)
|
||||
decisions = search_memories(api_key, user_id, project_id, 'recent decisions and learnings', metadata_type='decision', top_k=3)
|
||||
|
||||
all_r = state + decisions
|
||||
seen = set()
|
||||
unique = []
|
||||
for m in all_r:
|
||||
mid = m.get('id', '')
|
||||
if mid not in seen:
|
||||
seen.add(mid)
|
||||
unique.append(m)
|
||||
|
||||
if unique:
|
||||
print(format_results_for_context(unique, heading='Session context recovered from mem0'))
|
||||
print()
|
||||
print('These memories provide context for resuming work.')
|
||||
else:
|
||||
print('No session state found in mem0.')
|
||||
" 2>/dev/null || echo "")
|
||||
|
||||
if [ -n "$RESUME_RESULTS" ]; then
|
||||
_PROMPT_CTX="${RESUME_RESULTS}"
|
||||
fi
|
||||
fi
|
||||
|
||||
if [ -n "$HAS_REMEMBER" ]; then
|
||||
_PROMPT_CTX="${_PROMPT_CTX:+${_PROMPT_CTX}\n}Remember intent detected. The /mem0:remember skill auto-classifies, sets confidence=1.0, and stores verbatim."
|
||||
fi
|
||||
|
||||
if [ -z "$RUBRIC_ALREADY_SHOWN" ]; then
|
||||
_PROMPT_CTX="${_PROMPT_CTX:+${_PROMPT_CTX}\n}Mem0 searches apply when user references past work, decision questions, errors, or non-trivial tasks. Queries use noun-phrases, 2-4 parallel calls with different metadata.type filters, and include user_id + app_id."
|
||||
touch "$RUBRIC_FLAG" 2>/dev/null || true
|
||||
fi
|
||||
|
||||
if [ -n "$HAS_ERROR" ]; then
|
||||
_PROMPT_CTX="${_PROMPT_CTX:+${_PROMPT_CTX}\n}Error detected in prompt. Prior occurrences are available in mem0 via anti_pattern and task_learning type filters."
|
||||
fi
|
||||
|
||||
if [ -n "$FILE_PATHS" ]; then
|
||||
_PROMPT_CTX="${_PROMPT_CTX:+${_PROMPT_CTX}\n}File paths detected: ${FILE_PATHS}"
|
||||
fi
|
||||
|
||||
# Auto-capture: directly call mem0 API in background every 3rd message.
|
||||
# At MSG_COUNT=3 the 3rd response isn't in the transcript yet (hook fires
|
||||
# before Claude responds), so we capture 4 exchanges instead of 3. The
|
||||
# overlapping window ensures the next batch (MSG_COUNT=6) picks up the
|
||||
# exchange that was incomplete in the previous batch.
|
||||
TRANSCRIPT_PATH=$(echo "$INPUT" | jq -r '.transcript_path // ""' 2>/dev/null || echo "")
|
||||
if [ "${MEM0_AUTO_SAVE:-true}" != "false" ] && [ $((MSG_COUNT % 3)) -eq 0 ] && [ "$MSG_COUNT" -gt 0 ] && [ -n "$TRANSCRIPT_PATH" ]; then
|
||||
python3 "$SCRIPT_DIR/auto_capture.py" "$TRANSCRIPT_PATH" 2>/dev/null &
|
||||
fi
|
||||
|
||||
# Prompt-based nudge as fallback when auto-capture hasn't run yet.
|
||||
_ADDS=0
|
||||
_STATS_FILE="/tmp/mem0_session_stats_${USER:-default}.json"
|
||||
if [ -f "$_STATS_FILE" ]; then
|
||||
_ADDS=$(python3 -c "import json; print(json.load(open('$_STATS_FILE')).get('adds',0))" 2>/dev/null || echo "0")
|
||||
fi
|
||||
|
||||
if [ "$MSG_COUNT" -ge 3 ] && [ "$_ADDS" -lt "$((MSG_COUNT / 3))" ]; then
|
||||
_PROMPT_CTX="${_PROMPT_CTX:+${_PROMPT_CTX}\n}After responding, store any new decisions, learnings, or preferences from this exchange via add_memory. Keep it to 1 sentence per memory."
|
||||
fi
|
||||
|
||||
if [ -n "$_PROMPT_CTX" ]; then
|
||||
jq -cn --arg ctx "$_PROMPT_CTX" '{
|
||||
hookSpecificOutput: {
|
||||
hookEventName: "UserPromptSubmit",
|
||||
additionalContext: $ctx
|
||||
}
|
||||
}'
|
||||
fi
|
||||
|
||||
exit 0
|
||||
@@ -0,0 +1,19 @@
|
||||
#!/usr/bin/env bash
|
||||
# Hook: beforeSubmitPrompt (Cursor)
|
||||
#
|
||||
# Wraps on_user_prompt.sh and converts plain-text output to Cursor's
|
||||
# expected JSON format: {"continue":true,"user_message":"<text>"}
|
||||
|
||||
set -uo pipefail
|
||||
|
||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
||||
|
||||
TEXT=$("$SCRIPT_DIR/on_user_prompt.sh" 2>/dev/null || echo "")
|
||||
|
||||
if [ -z "$TEXT" ]; then
|
||||
jq -cn '{continue:true}'
|
||||
exit 0
|
||||
fi
|
||||
|
||||
jq -cn --arg msg "$TEXT" '{continue:true, user_message:$msg}'
|
||||
exit 0
|
||||
@@ -0,0 +1,150 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Parse a mem0 export file and output JSON.
|
||||
|
||||
Input: path to a mem0-export-*.md file (sys.argv[1])
|
||||
Output: JSON array of memory records to stdout
|
||||
Exit: 0 always
|
||||
|
||||
Each block in the file is delimited by lines containing exactly "---".
|
||||
Blocks have a YAML-like frontmatter section (key: value lines) followed
|
||||
by a blank line and the memory content text.
|
||||
|
||||
Example block format:
|
||||
---
|
||||
id: abc123
|
||||
created_at: 2024-01-01T00:00:00Z
|
||||
type: task_learnings
|
||||
confidence: 0.9
|
||||
branch: main
|
||||
files: src/foo.py, src/bar.py
|
||||
categories: coding_conventions, task_learnings
|
||||
---
|
||||
The actual memory content text goes here.
|
||||
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import re
|
||||
import sys
|
||||
|
||||
|
||||
def parse_blocks(content: str) -> list[dict]:
|
||||
"""Split content on '---' boundaries and parse each block.
|
||||
|
||||
Returns a list of dicts with keys:
|
||||
id, type, confidence, branch, files (list), categories (list), content (str)
|
||||
|
||||
Blocks with empty content are skipped.
|
||||
Missing optional fields default to "" (scalar) or [] (list fields).
|
||||
"""
|
||||
# Normalise line endings
|
||||
content = content.replace("\r\n", "\n").replace("\r", "\n")
|
||||
|
||||
# Split on lines that are exactly "---"
|
||||
raw_blocks = re.split(r"(?m)^---\s*$", content)
|
||||
|
||||
# After splitting on "---", the structure for each memory is:
|
||||
# raw_blocks[0] = preamble (before first ---, typically empty)
|
||||
# raw_blocks[1] = frontmatter for block 1
|
||||
# raw_blocks[2] = content for block 1
|
||||
# raw_blocks[3] = frontmatter for block 2
|
||||
# raw_blocks[4] = content for block 2
|
||||
# ...
|
||||
# So frontmatter blocks are at odd indices (1, 3, 5, ...) and
|
||||
# content blocks at even indices (2, 4, 6, ...).
|
||||
|
||||
results: list[dict] = []
|
||||
|
||||
# Pair up frontmatter + content starting at index 1
|
||||
i = 1
|
||||
while i < len(raw_blocks):
|
||||
frontmatter_raw = raw_blocks[i]
|
||||
content_raw = raw_blocks[i + 1] if i + 1 < len(raw_blocks) else ""
|
||||
|
||||
# Parse the frontmatter key-value pairs
|
||||
fm = _parse_frontmatter(frontmatter_raw)
|
||||
|
||||
# Strip leading/trailing whitespace from content
|
||||
memory_content = content_raw.strip()
|
||||
|
||||
# Skip blocks with empty content
|
||||
if not memory_content:
|
||||
i += 2
|
||||
continue
|
||||
|
||||
record = {
|
||||
"id": fm.get("id", ""),
|
||||
"type": fm.get("type", ""),
|
||||
"confidence": fm.get("confidence", ""),
|
||||
"branch": fm.get("branch", ""),
|
||||
"files": _parse_list_field(fm.get("files", "")),
|
||||
"categories": _parse_list_field(fm.get("categories", "")),
|
||||
"content": memory_content,
|
||||
}
|
||||
|
||||
# Include created_at if present
|
||||
if "created_at" in fm:
|
||||
record["created_at"] = fm["created_at"]
|
||||
|
||||
results.append(record)
|
||||
i += 2
|
||||
|
||||
return results
|
||||
|
||||
|
||||
def _parse_frontmatter(text: str) -> dict[str, str]:
|
||||
"""Parse simple 'key: value' lines from frontmatter text.
|
||||
|
||||
Only the first colon is used as the delimiter — values may contain colons.
|
||||
Lines not matching 'key: value' are ignored.
|
||||
"""
|
||||
result: dict[str, str] = {}
|
||||
for line in text.splitlines():
|
||||
line = line.strip()
|
||||
if not line:
|
||||
continue
|
||||
match = re.match(r"^([A-Za-z_][A-Za-z0-9_]*)\s*:\s*(.*)$", line)
|
||||
if match:
|
||||
key = match.group(1).strip()
|
||||
value = match.group(2).strip()
|
||||
result[key] = value
|
||||
return result
|
||||
|
||||
|
||||
def _parse_list_field(value: str) -> list[str]:
|
||||
"""Split a comma-separated value into a list, stripping whitespace.
|
||||
|
||||
Returns [] for empty/whitespace-only input.
|
||||
"""
|
||||
if not value or not value.strip():
|
||||
return []
|
||||
return [item.strip() for item in value.split(",") if item.strip()]
|
||||
|
||||
|
||||
def main() -> None:
|
||||
if len(sys.argv) < 2:
|
||||
print("Usage: parse_export_file.py <path-to-export-file>", file=sys.stderr)
|
||||
print("[]")
|
||||
sys.exit(0)
|
||||
|
||||
filepath = sys.argv[1]
|
||||
try:
|
||||
if filepath == "-":
|
||||
content = sys.stdin.read()
|
||||
else:
|
||||
with open(filepath, encoding="utf-8", errors="replace") as f:
|
||||
content = f.read()
|
||||
except OSError as e:
|
||||
print(f"Error reading file: {e}", file=sys.stderr)
|
||||
print("[]")
|
||||
sys.exit(0)
|
||||
|
||||
records = parse_blocks(content)
|
||||
print(json.dumps(records, ensure_ascii=False, indent=2))
|
||||
sys.exit(0)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,284 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Parse mem0.md project configuration file.
|
||||
|
||||
Reads the optional ``mem0.md`` file in a project directory and extracts
|
||||
retention policies from a ``## Retention`` section.
|
||||
|
||||
Retention format (inside the section):
|
||||
<category>: <N>d — keep for N days
|
||||
<category>: forever — never prune (returned as None)
|
||||
|
||||
Usage (CLI):
|
||||
python3 parse_mem0_config.py [<cwd>]
|
||||
|
||||
Prints a JSON object mapping category names to day counts (int) or null
|
||||
(forever) on stdout. Prints ``{}`` when no mem0.md or no ## Retention
|
||||
section is found.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import os
|
||||
import re
|
||||
import sys
|
||||
|
||||
|
||||
def find_mem0_config(cwd: str) -> str | None:
|
||||
"""Look for ``mem0.md`` in *cwd*.
|
||||
|
||||
Returns the absolute path to ``mem0.md`` if found, else ``None``.
|
||||
"""
|
||||
candidate = os.path.join(cwd, "mem0.md")
|
||||
return candidate if os.path.isfile(candidate) else None
|
||||
|
||||
|
||||
def parse_retention(content: str) -> dict[str, int | None]:
|
||||
"""Parse the ``## Retention`` section of *content*.
|
||||
|
||||
Scans for a heading that matches ``## Retention`` (case-insensitive),
|
||||
then reads lines until the next ``##``-level heading or end of string.
|
||||
|
||||
Each non-blank, non-comment line inside the section is expected to be::
|
||||
|
||||
<category>: <N>d → days=N (int)
|
||||
<category>: forever → days=None
|
||||
|
||||
Malformed lines are silently skipped.
|
||||
|
||||
Args:
|
||||
content: Full text of a mem0.md file.
|
||||
|
||||
Returns:
|
||||
Dict mapping category name (str) to day count (int) or ``None``
|
||||
(forever). Empty dict when no ``## Retention`` section is found.
|
||||
"""
|
||||
# Find the ## Retention section (allow any amount of trailing whitespace /
|
||||
# extra words, but the heading must start with "## Retention").
|
||||
section_match = re.search(
|
||||
r"^##\s+Retention[^\n]*\n(.*?)(?=^##\s|\Z)",
|
||||
content,
|
||||
flags=re.MULTILINE | re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
if not section_match:
|
||||
return {}
|
||||
|
||||
section_text = section_match.group(1)
|
||||
policies: dict[str, int | None] = {}
|
||||
|
||||
for line in section_text.splitlines():
|
||||
# Strip comments and whitespace
|
||||
line = re.sub(r"#.*$", "", line).strip()
|
||||
if not line:
|
||||
continue
|
||||
|
||||
# Match "<category>: <value>"
|
||||
line_match = re.match(r"^([^:]+):\s*(.+)$", line)
|
||||
if not line_match:
|
||||
continue
|
||||
|
||||
category = line_match.group(1).strip()
|
||||
value = line_match.group(2).strip().lower()
|
||||
|
||||
if value == "forever":
|
||||
policies[category] = None
|
||||
else:
|
||||
days_match = re.match(r"^(\d+)d$", value)
|
||||
if days_match:
|
||||
policies[category] = int(days_match.group(1))
|
||||
# else: malformed value — skip silently
|
||||
|
||||
return policies
|
||||
|
||||
|
||||
def parse_section_kv(content: str, heading: str) -> dict[str, str]:
|
||||
"""Parse a key-value section from mem0.md.
|
||||
|
||||
Looks for ``## <heading>`` (case-insensitive) and reads ``key: value``
|
||||
lines until the next ``##``-level heading or end of string.
|
||||
"""
|
||||
pattern = rf"^##\s+{re.escape(heading)}[^\n]*\n(.*?)(?=^##\s|\Z)"
|
||||
match = re.search(pattern, content, flags=re.MULTILINE | re.DOTALL | re.IGNORECASE)
|
||||
if not match:
|
||||
return {}
|
||||
|
||||
result: dict[str, str] = {}
|
||||
for line in match.group(1).splitlines():
|
||||
line = re.sub(r"#.*$", "", line).strip()
|
||||
if not line:
|
||||
continue
|
||||
m = re.match(r"^([^:]+):\s*(.+)$", line)
|
||||
if m:
|
||||
result[m.group(1).strip()] = m.group(2).strip()
|
||||
return result
|
||||
|
||||
|
||||
def parse_section_list(content: str, heading: str) -> list[str]:
|
||||
"""Parse a list section from mem0.md.
|
||||
|
||||
Looks for ``## <heading>`` and reads ``- item`` or bare lines.
|
||||
"""
|
||||
pattern = rf"^##\s+{re.escape(heading)}[^\n]*\n(.*?)(?=^##\s|\Z)"
|
||||
match = re.search(pattern, content, flags=re.MULTILINE | re.DOTALL | re.IGNORECASE)
|
||||
if not match:
|
||||
return []
|
||||
|
||||
items: list[str] = []
|
||||
for line in match.group(1).splitlines():
|
||||
line = re.sub(r"#.*$", "", line).strip()
|
||||
line = re.sub(r"^[-*]\s+", "", line).strip()
|
||||
if line:
|
||||
items.append(line)
|
||||
return items
|
||||
|
||||
|
||||
def parse_ignore_patterns(content: str) -> list[str]:
|
||||
"""Parse the ``## Ignore`` section of *content*.
|
||||
|
||||
Each non-blank line is a glob pattern (e.g., ``node_modules``, ``*.lock``).
|
||||
Lines starting with ``#`` are comments and skipped.
|
||||
"""
|
||||
pattern = r"^##\s+Ignore[^\n]*\n(.*?)(?=^##\s|\Z)"
|
||||
match = re.search(pattern, content, flags=re.MULTILINE | re.DOTALL | re.IGNORECASE)
|
||||
if not match:
|
||||
return []
|
||||
|
||||
patterns: list[str] = []
|
||||
for line in match.group(1).splitlines():
|
||||
line = line.strip()
|
||||
if not line or line.startswith("#"):
|
||||
continue
|
||||
line = re.sub(r"^[-*]\s+", "", line).strip()
|
||||
if line:
|
||||
patterns.append(line)
|
||||
return patterns
|
||||
|
||||
|
||||
def load_full_config(cwd: str | None = None) -> dict:
|
||||
"""Load all config sections from mem0.md.
|
||||
|
||||
Returns a dict with keys: retention, search, categories, identity,
|
||||
ignore, project_id.
|
||||
Each is populated only if the corresponding ``##`` section exists.
|
||||
"""
|
||||
if cwd is None:
|
||||
cwd = os.getcwd()
|
||||
|
||||
config_path = find_mem0_config(cwd)
|
||||
if config_path is None:
|
||||
return {}
|
||||
|
||||
try:
|
||||
with open(config_path, encoding="utf-8") as fh:
|
||||
content = fh.read()
|
||||
except OSError:
|
||||
return {}
|
||||
|
||||
config: dict = {}
|
||||
|
||||
retention = parse_retention(content)
|
||||
if retention:
|
||||
config["retention"] = retention
|
||||
|
||||
search = parse_section_kv(content, "Search")
|
||||
if search:
|
||||
config["search"] = search
|
||||
|
||||
categories = parse_section_list(content, "Categories")
|
||||
if categories:
|
||||
config["categories"] = categories
|
||||
config["default_categories"] = categories
|
||||
|
||||
identity = parse_section_kv(content, "Identity")
|
||||
if identity:
|
||||
config["identity"] = identity
|
||||
if "project_id" in identity:
|
||||
config["project_id"] = identity["project_id"]
|
||||
|
||||
ignore = parse_ignore_patterns(content)
|
||||
if ignore:
|
||||
config["ignore"] = ignore
|
||||
|
||||
settings = parse_section_kv(content, "Settings")
|
||||
if settings:
|
||||
config["settings"] = settings
|
||||
|
||||
return config
|
||||
|
||||
|
||||
def load_retention_policies(cwd: str | None = None) -> dict[str, int | None]:
|
||||
"""Load retention policies from the mem0.md in *cwd*.
|
||||
|
||||
Combines :func:`find_mem0_config` and :func:`parse_retention` into a
|
||||
single convenience function.
|
||||
"""
|
||||
if cwd is None:
|
||||
cwd = os.getcwd()
|
||||
|
||||
config_path = find_mem0_config(cwd)
|
||||
if config_path is None:
|
||||
return {}
|
||||
|
||||
try:
|
||||
with open(config_path, encoding="utf-8") as fh:
|
||||
content = fh.read()
|
||||
except OSError:
|
||||
return {}
|
||||
|
||||
return parse_retention(content)
|
||||
|
||||
|
||||
def main() -> int:
|
||||
"""CLI entry point.
|
||||
|
||||
With ``--full``, prints the complete config. Without it, prints only
|
||||
retention policies (backward-compatible).
|
||||
|
||||
With ``--key <dotted.path>``, prints the scalar value at that path in the
|
||||
full config (e.g. ``--key settings.commit_prompts``). Prints an empty
|
||||
string when the key is absent. Exits 1 only on unexpected errors.
|
||||
"""
|
||||
full_mode = "--full" in sys.argv
|
||||
|
||||
# Extract --key <value>
|
||||
key_path: str | None = None
|
||||
raw_args = sys.argv[1:]
|
||||
filtered_args: list[str] = []
|
||||
i = 0
|
||||
while i < len(raw_args):
|
||||
if raw_args[i] == "--key" and i + 1 < len(raw_args):
|
||||
key_path = raw_args[i + 1]
|
||||
i += 2
|
||||
elif raw_args[i].startswith("--key="):
|
||||
key_path = raw_args[i][len("--key="):]
|
||||
i += 1
|
||||
elif raw_args[i].startswith("--"):
|
||||
i += 1 # skip other flags like --full
|
||||
else:
|
||||
filtered_args.append(raw_args[i])
|
||||
i += 1
|
||||
|
||||
cwd = filtered_args[0] if filtered_args else os.getcwd()
|
||||
|
||||
if key_path is not None:
|
||||
config = load_full_config(cwd)
|
||||
# Traverse dotted path
|
||||
value: object = config
|
||||
for part in key_path.split("."):
|
||||
if not isinstance(value, dict):
|
||||
value = None
|
||||
break
|
||||
value = value.get(part)
|
||||
print(value if value is not None else "")
|
||||
return 0
|
||||
|
||||
if full_mode:
|
||||
config = load_full_config(cwd)
|
||||
else:
|
||||
config = load_retention_policies(cwd)
|
||||
print(json.dumps(config))
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -0,0 +1,138 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Session stats tracker for mem0 plugin.
|
||||
|
||||
Tracks memory adds/searches per session.
|
||||
Uses /tmp/mem0_session_stats_$USER.json (single file per user, reset on init).
|
||||
|
||||
Usage:
|
||||
python session_stats.py init # reset for new session
|
||||
python session_stats.py add <category> # record a memory write
|
||||
python session_stats.py search # record a search
|
||||
python session_stats.py report # print summary, clean up temp file
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import os
|
||||
import sys
|
||||
from datetime import datetime
|
||||
|
||||
STATS_FILE = f"/tmp/mem0_session_stats_{os.environ.get('USER', 'default')}.json"
|
||||
|
||||
|
||||
def _load() -> dict:
|
||||
if os.path.isfile(STATS_FILE):
|
||||
try:
|
||||
with open(STATS_FILE) as f:
|
||||
return json.load(f)
|
||||
except (json.JSONDecodeError, OSError):
|
||||
pass
|
||||
return {
|
||||
"adds": 0,
|
||||
"searches": 0,
|
||||
"categories": [],
|
||||
"category_counts": {},
|
||||
"started": datetime.now().isoformat(),
|
||||
}
|
||||
|
||||
|
||||
def _save(stats: dict) -> None:
|
||||
with open(STATS_FILE, "w") as f:
|
||||
json.dump(stats, f)
|
||||
|
||||
|
||||
MAX_RECENT_IDS = 50
|
||||
|
||||
|
||||
def init() -> None:
|
||||
_save({
|
||||
"adds": 0,
|
||||
"searches": 0,
|
||||
"categories": [],
|
||||
"category_counts": {},
|
||||
"recent_ids": [],
|
||||
"started": datetime.now().isoformat(),
|
||||
})
|
||||
|
||||
|
||||
def record_add(category: str = "", memory_id: str = "") -> None:
|
||||
stats = _load()
|
||||
stats["adds"] = stats.get("adds", 0) + 1
|
||||
if category:
|
||||
if category not in stats.get("categories", []):
|
||||
stats.setdefault("categories", []).append(category)
|
||||
counts = stats.setdefault("category_counts", {})
|
||||
counts[category] = counts.get(category, 0) + 1
|
||||
if memory_id:
|
||||
recent = stats.setdefault("recent_ids", [])
|
||||
recent.append({"id": memory_id, "category": category, "ts": datetime.now().isoformat()})
|
||||
if len(recent) > MAX_RECENT_IDS:
|
||||
stats["recent_ids"] = recent[-MAX_RECENT_IDS:]
|
||||
_save(stats)
|
||||
|
||||
|
||||
def record_search() -> None:
|
||||
stats = _load()
|
||||
stats["searches"] = stats.get("searches", 0) + 1
|
||||
_save(stats)
|
||||
|
||||
|
||||
def peek() -> str:
|
||||
"""Return current stats as JSON without clearing the file."""
|
||||
stats = _load()
|
||||
return json.dumps(stats)
|
||||
|
||||
|
||||
def report() -> str:
|
||||
stats = _load()
|
||||
adds = stats.get("adds", 0)
|
||||
searches = stats.get("searches", 0)
|
||||
categories = stats.get("categories", [])
|
||||
|
||||
if adds == 0 and searches == 0:
|
||||
return ""
|
||||
|
||||
parts = []
|
||||
category_counts = stats.get("category_counts", {})
|
||||
if category_counts:
|
||||
breakdown = ", ".join(f"{c} {n}" for c, n in sorted(category_counts.items(), key=lambda x: -x[1]))
|
||||
parts.append(f"Session: wrote {adds} memories ({breakdown}), retrieved {searches}")
|
||||
else:
|
||||
parts.append(f"Session: wrote {adds} memories, retrieved {searches}")
|
||||
if categories:
|
||||
parts.append(f"Categories touched: {', '.join(categories)}")
|
||||
|
||||
return ". ".join(parts) + "."
|
||||
|
||||
|
||||
def main() -> int:
|
||||
if len(sys.argv) < 2:
|
||||
print("Usage: session_stats.py [init|add|search|report]", file=sys.stderr)
|
||||
return 1
|
||||
|
||||
cmd = sys.argv[1]
|
||||
if cmd == "init":
|
||||
init()
|
||||
elif cmd == "add":
|
||||
category = sys.argv[2] if len(sys.argv) > 2 else ""
|
||||
memory_id = sys.argv[3] if len(sys.argv) > 3 else ""
|
||||
record_add(category, memory_id)
|
||||
elif cmd == "search":
|
||||
record_search()
|
||||
elif cmd == "peek":
|
||||
print(peek())
|
||||
elif cmd == "report":
|
||||
result = report()
|
||||
if result:
|
||||
print(result)
|
||||
else:
|
||||
print("Session: no memory operations.")
|
||||
else:
|
||||
print(f"Unknown command: {cmd}", file=sys.stderr)
|
||||
return 1
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -0,0 +1,106 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Fetch recent memories and format a compact timeline for SessionStart.
|
||||
|
||||
Searches mem0 cloud API for the most recent memories in the project
|
||||
and formats them as a compact activity timeline injected below the
|
||||
existing SessionStart banner.
|
||||
|
||||
Input: env vars for identity (MEM0_API_KEY, MEM0_RESOLVED_USER_ID, etc.)
|
||||
Output: Compact timeline text to stdout (empty if nothing found)
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import os
|
||||
import sys
|
||||
import urllib.request
|
||||
|
||||
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
|
||||
from _formatting import TYPE_ICONS, format_age
|
||||
from _identity import resolve_api_key, resolve_user_id
|
||||
from _project import resolve_project_id
|
||||
|
||||
API_URL = "https://api.mem0.ai"
|
||||
MAX_RECENT = 10
|
||||
MAX_SUMMARIES = 3
|
||||
FETCH_TIMEOUT = 5
|
||||
|
||||
|
||||
def fetch_recent_memories(api_key: str, user_id: str, project_id: str) -> list[dict]:
|
||||
"""Fetch the most recent memories for this project via GET list endpoint."""
|
||||
global_search = os.environ.get("MEM0_GLOBAL_SEARCH", "false") == "true"
|
||||
|
||||
if global_search:
|
||||
filters = {"OR": [{"user_id": "*"}]}
|
||||
else:
|
||||
filters = {"AND": [{"user_id": user_id}, {"app_id": project_id}]}
|
||||
|
||||
body = json.dumps({"filters": filters}).encode()
|
||||
req = urllib.request.Request(
|
||||
f"{API_URL}/v3/memories/?page=1&page_size={MAX_RECENT}",
|
||||
data=body,
|
||||
headers={
|
||||
"Authorization": f"Token {api_key}",
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
method="POST",
|
||||
)
|
||||
try:
|
||||
with urllib.request.urlopen(req, timeout=FETCH_TIMEOUT) as r:
|
||||
result = json.loads(r.read())
|
||||
if isinstance(result, dict) and "results" in result:
|
||||
return result["results"][:MAX_RECENT]
|
||||
if isinstance(result, list):
|
||||
return result[:MAX_RECENT]
|
||||
return []
|
||||
except Exception:
|
||||
return []
|
||||
|
||||
|
||||
def format_timeline(memories: list[dict]) -> str:
|
||||
"""Format memories into a compact recent activity timeline."""
|
||||
if not memories:
|
||||
return ""
|
||||
|
||||
lines = ["### Recent Activity", ""]
|
||||
|
||||
for m in memories:
|
||||
mid = m.get("id", "?")[:8]
|
||||
text = (m.get("memory", "") or "")[:120].replace("\n", " ").strip()
|
||||
meta = m.get("metadata") or {}
|
||||
cat = meta.get("type", "unknown")
|
||||
icon = TYPE_ICONS.get(cat, "❓")
|
||||
age = format_age(m)
|
||||
age_str = f" ({age})" if age else ""
|
||||
lines.append(f"- {icon} [{cat}]{age_str} {text} [mem0:{mid}]")
|
||||
|
||||
lines.append("")
|
||||
lines.append("Search mem0 for details on any of these, or for past decisions and task learnings relevant to the current task.")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
def main():
|
||||
api_key = resolve_api_key()
|
||||
if not api_key:
|
||||
return
|
||||
|
||||
user_id = resolve_user_id()
|
||||
project_id = resolve_project_id(os.environ.get("MEM0_CWD"))
|
||||
|
||||
memories = fetch_recent_memories(api_key, user_id, project_id)
|
||||
if not memories:
|
||||
return
|
||||
|
||||
timeline = format_timeline(memories)
|
||||
if timeline:
|
||||
print(timeline, end="")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
try:
|
||||
main()
|
||||
except Exception:
|
||||
pass
|
||||
sys.exit(0)
|
||||
@@ -0,0 +1,236 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Replace mem0's default category taxonomy with one tuned for coding workflows.
|
||||
|
||||
mem0 auto-tags every memory with one or more `categories`. By default the list
|
||||
is consumer-oriented (food, hobbies, music, ...), which is meaningless for code.
|
||||
This script replaces the project's category list with a coding-focused one.
|
||||
|
||||
Uses the mem0ai SDK (client.project.update). The SDK is installed into a
|
||||
persistent venv at ${CLAUDE_PLUGIN_DATA}/venv by the ensure_deps.sh hook.
|
||||
|
||||
Usage:
|
||||
python setup_coding_categories.py # dry-run: show current vs proposed
|
||||
python setup_coding_categories.py --apply # actually call project.update()
|
||||
|
||||
Requires MEM0_API_KEY (or CLAUDE_PLUGIN_OPTION_MEM0_API_KEY).
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import json
|
||||
import os
|
||||
import sys
|
||||
|
||||
_script_dir = os.path.dirname(os.path.abspath(__file__))
|
||||
sys.path.insert(0, _script_dir)
|
||||
from _identity import resolve_api_key # noqa: E402
|
||||
|
||||
_plugin_root = os.environ.get("CLAUDE_PLUGIN_ROOT", os.path.join(_script_dir, ".."))
|
||||
_data_dir = os.environ.get("CLAUDE_PLUGIN_DATA", os.path.join(os.path.expanduser("~"), ".mem0", "plugin-data"))
|
||||
_venv_site = os.path.join(_data_dir, "venv", "lib")
|
||||
if os.path.isdir(_venv_site):
|
||||
for d in sorted(os.listdir(_venv_site)):
|
||||
sp = os.path.join(_venv_site, d, "site-packages")
|
||||
if os.path.isdir(sp) and sp not in sys.path:
|
||||
sys.path.insert(1, sp)
|
||||
|
||||
CODING_CATEGORIES = [
|
||||
{
|
||||
"architecture_decisions": (
|
||||
"Design choices, system structure, technology selection, trade-offs evaluated, "
|
||||
"and architectural patterns adopted in the project."
|
||||
)
|
||||
},
|
||||
{
|
||||
"anti_patterns": (
|
||||
"Approaches that failed, debugging dead-ends, common mistakes to avoid, "
|
||||
"and lessons learned from things that didn't work."
|
||||
)
|
||||
},
|
||||
{
|
||||
"task_learnings": (
|
||||
"Strategies and approaches that succeeded for specific tasks, including tooling "
|
||||
"tricks, workflow shortcuts, and effective problem-solving patterns."
|
||||
)
|
||||
},
|
||||
{
|
||||
"tooling_setup": (
|
||||
"Development environment, build tools, dependencies, package managers, deploy "
|
||||
"pipelines, and configuration steps for the project."
|
||||
)
|
||||
},
|
||||
{
|
||||
"bug_fixes": (
|
||||
"Specific bug fixes with root cause analysis, the fix applied, and how the bug "
|
||||
"was diagnosed -- useful for recognising similar issues later."
|
||||
)
|
||||
},
|
||||
{
|
||||
"coding_conventions": (
|
||||
"Code style, naming patterns, file organisation, error-handling conventions, "
|
||||
"and team agreements about how code is written in this project."
|
||||
)
|
||||
},
|
||||
{
|
||||
"user_preferences": (
|
||||
"User's stated preferences for tools, libraries, languages, formatting, "
|
||||
"and ways of working."
|
||||
)
|
||||
},
|
||||
{
|
||||
"dependency_decisions": (
|
||||
"Why specific libraries, frameworks, or package versions were chosen or replaced, "
|
||||
"including the alternatives considered and the reasoning behind the selection."
|
||||
)
|
||||
},
|
||||
{
|
||||
"performance_findings": (
|
||||
"Profiling results, bottlenecks identified, optimisations applied, and measurable "
|
||||
"improvements achieved -- useful for avoiding regressions and guiding future work."
|
||||
)
|
||||
},
|
||||
{
|
||||
"security_constraints": (
|
||||
"Security requirements, authentication and authorisation rules, data-handling "
|
||||
"constraints, compliance obligations, and known threat mitigations in effect."
|
||||
)
|
||||
},
|
||||
{
|
||||
"testing_patterns": (
|
||||
"Test strategies, frameworks chosen, coverage targets, fixture patterns, mocking "
|
||||
"approaches, and how the test suite is structured for this project."
|
||||
)
|
||||
},
|
||||
{
|
||||
"data_model": (
|
||||
"Schema definitions, database column semantics, domain object relationships, "
|
||||
"field constraints, and how data flows between storage and application layers."
|
||||
)
|
||||
},
|
||||
{
|
||||
"api_contracts": (
|
||||
"API endpoint shapes, request and response schemas, authentication requirements, "
|
||||
"versioning policy, and any breaking-change commitments or deprecation timelines."
|
||||
)
|
||||
},
|
||||
{
|
||||
"deployment_runbook": (
|
||||
"How to build, release, deploy, and roll back the project. CI/CD pipeline steps, "
|
||||
"environment-specific configuration, and on-call runbook entries."
|
||||
)
|
||||
},
|
||||
{
|
||||
"team_norms": (
|
||||
"Team working agreements, PR review etiquette, branching strategy, on-call "
|
||||
"rotation, and other social or process conventions the team has agreed on."
|
||||
)
|
||||
},
|
||||
{
|
||||
"domain_glossary": (
|
||||
"Domain-specific terms, abbreviations, and acronyms with their precise meanings "
|
||||
"in this project -- prevents misunderstandings across code, docs, and discussion."
|
||||
)
|
||||
},
|
||||
{
|
||||
"experiment_results": (
|
||||
"Results from A/B tests, feature-flag experiments, spikes, or proof-of-concept "
|
||||
"work -- what was tried, what was measured, and what conclusion was reached."
|
||||
)
|
||||
},
|
||||
]
|
||||
|
||||
|
||||
def _print_categories(label: str, cats):
|
||||
print(f"=== {label} ===")
|
||||
if cats:
|
||||
print(json.dumps(cats, indent=2))
|
||||
else:
|
||||
print("(none / using mem0 defaults)")
|
||||
print()
|
||||
|
||||
|
||||
def _categories_match(current: list | None, proposed: list) -> bool:
|
||||
"""Compare categories by key sets, tolerating order differences and extra API fields."""
|
||||
if not current:
|
||||
return False
|
||||
current_keys = {k for d in current if isinstance(d, dict) for k in d}
|
||||
proposed_keys = {k for d in proposed if isinstance(d, dict) for k in d}
|
||||
if current_keys != proposed_keys:
|
||||
return False
|
||||
current_map = {k: v for d in current if isinstance(d, dict) for k, v in d.items()}
|
||||
proposed_map = {k: v for d in proposed if isinstance(d, dict) for k, v in d.items()}
|
||||
return all(
|
||||
current_map.get(k, "").strip() == v.strip()
|
||||
for k, v in proposed_map.items()
|
||||
)
|
||||
|
||||
|
||||
def main() -> int:
|
||||
ap = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
|
||||
ap.add_argument(
|
||||
"--apply",
|
||||
action="store_true",
|
||||
help="Actually call project.update(). Without this flag, runs in dry-run mode.",
|
||||
)
|
||||
args = ap.parse_args()
|
||||
|
||||
api_key = resolve_api_key()
|
||||
if not api_key:
|
||||
print("ERROR: MEM0_API_KEY is not set. Export it or configure it via plugin userConfig.", file=sys.stderr)
|
||||
return 1
|
||||
os.environ["MEM0_API_KEY"] = api_key
|
||||
|
||||
try:
|
||||
from mem0 import MemoryClient
|
||||
except ImportError:
|
||||
print(
|
||||
"ERROR: mem0ai SDK not found. The plugin's ensure_deps.sh hook should\n"
|
||||
"install it automatically on session start. Try restarting Claude Code,\n"
|
||||
"or run manually: pip install mem0ai",
|
||||
file=sys.stderr,
|
||||
)
|
||||
return 1
|
||||
|
||||
try:
|
||||
client = MemoryClient()
|
||||
except Exception as e:
|
||||
print(
|
||||
f"ERROR initialising MemoryClient: {e}\n"
|
||||
"Most commonly this is an invalid MEM0_API_KEY -- check the key at "
|
||||
"https://app.mem0.ai/dashboard/api-keys",
|
||||
file=sys.stderr,
|
||||
)
|
||||
return 1
|
||||
|
||||
try:
|
||||
current = client.project.get(fields=["custom_categories"])
|
||||
current_cats = current.get("custom_categories") if isinstance(current, dict) else None
|
||||
except Exception as e:
|
||||
print(f"ERROR fetching current categories: {e}", file=sys.stderr)
|
||||
return 1
|
||||
|
||||
_print_categories("Current project categories", current_cats)
|
||||
_print_categories("Proposed coding categories", CODING_CATEGORIES)
|
||||
|
||||
if not args.apply:
|
||||
print("Dry-run only -- no changes made. Re-run with --apply to write.")
|
||||
return 0
|
||||
|
||||
if _categories_match(current_cats, CODING_CATEGORIES):
|
||||
print("Categories already match -- skipping update.")
|
||||
return 0
|
||||
|
||||
print("Applying coding categories...")
|
||||
try:
|
||||
response = client.project.update(custom_categories=CODING_CATEGORIES)
|
||||
except Exception as e:
|
||||
print(f"ERROR applying update: {e}", file=sys.stderr)
|
||||
return 1
|
||||
|
||||
print("Done.", response if response else "")
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -0,0 +1,156 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Lightweight fire-and-forget telemetry for the mem0 plugin.
|
||||
|
||||
Sends anonymous usage events to PostHog using the same project key and
|
||||
endpoint as the mem0 Python SDK and CLI. No posthog library dependency —
|
||||
uses stdlib urllib directly (same pattern as cli/python telemetry_sender.py).
|
||||
|
||||
CLI usage (called from hooks as a background subprocess):
|
||||
python3 telemetry.py <event_type> [--memory_count=N] [--categories_count=N]
|
||||
[--error_detected] [--file_paths_detected]
|
||||
[--source=<src>] [--tool=<name>]
|
||||
|
||||
Opt-out: set MEM0_TELEMETRY=false (or 0/no/off) to disable all telemetry.
|
||||
|
||||
Never sends: user content, memory content, API keys, raw user/project IDs.
|
||||
Only sends: event type, platform, plugin version, anonymized hashes, counts.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import hashlib
|
||||
import json
|
||||
import os
|
||||
import platform
|
||||
import sys
|
||||
import urllib.error
|
||||
import urllib.request
|
||||
|
||||
|
||||
def _load_plugin_version() -> str:
|
||||
try:
|
||||
plugin_json = os.path.join(os.path.dirname(__file__), "..", ".claude-plugin", "plugin.json")
|
||||
with open(plugin_json) as f:
|
||||
return json.load(f).get("version", "unknown")
|
||||
except (OSError, json.JSONDecodeError, KeyError):
|
||||
return "unknown"
|
||||
|
||||
PLUGIN_VERSION = _load_plugin_version()
|
||||
|
||||
POSTHOG_API_KEY = "phc_hgJkUVJFYtmaJqrvf6CYN67TIQ8yhXAkWzUn9AMU4yX"
|
||||
POSTHOG_HOST = "https://us.i.posthog.com/i/v0/e/"
|
||||
REQUEST_TIMEOUT = 2
|
||||
|
||||
SAMPLE_RATE = 1.0
|
||||
|
||||
|
||||
def _sha256(value: str) -> str:
|
||||
return hashlib.sha256(value.encode("utf-8")).hexdigest()
|
||||
|
||||
|
||||
def _distinct_id() -> str:
|
||||
"""Stable anonymous ID: SHA-256 of API key if available, else SHA-256 of username."""
|
||||
api_key = os.environ.get("MEM0_API_KEY") or os.environ.get("CLAUDE_PLUGIN_OPTION_MEM0_API_KEY") or ""
|
||||
if api_key:
|
||||
return hashlib.sha256(api_key.encode()).hexdigest()[:32]
|
||||
user_id = os.environ.get("MEM0_RESOLVED_USER_ID") or os.environ.get("USER") or "unknown"
|
||||
return _sha256(user_id)
|
||||
|
||||
|
||||
def detect_platform() -> str:
|
||||
if os.environ.get("PLUGIN_ROOT"):
|
||||
return "codex"
|
||||
if os.environ.get("CLAUDECODE") or os.environ.get("CLAUDE_PLUGIN_ROOT"):
|
||||
return "claude-code"
|
||||
if os.environ.get("CURSOR_PLUGIN_ROOT"):
|
||||
return "cursor"
|
||||
if os.environ.get("WINDSURF_PLUGIN_ROOT"):
|
||||
return "windsurf"
|
||||
return "plugin"
|
||||
|
||||
|
||||
def is_enabled() -> bool:
|
||||
return os.environ.get("MEM0_TELEMETRY", "true").lower() not in ("false", "0", "no", "off")
|
||||
|
||||
|
||||
def build_posthog_payload(event_name: str, properties: dict | None = None) -> dict:
|
||||
project_id = os.environ.get("MEM0_PROJECT_ID") or "unknown"
|
||||
return {
|
||||
"api_key": POSTHOG_API_KEY,
|
||||
"distinct_id": _distinct_id(),
|
||||
"event": event_name,
|
||||
"properties": {
|
||||
**(properties or {}),
|
||||
"source": "plugin",
|
||||
"platform": detect_platform(),
|
||||
"plugin_version": PLUGIN_VERSION,
|
||||
"project_hash": _sha256(project_id),
|
||||
"os": sys.platform,
|
||||
"os_version": platform.version(),
|
||||
"sample_rate": SAMPLE_RATE,
|
||||
"$process_person_profile": False,
|
||||
"$lib": "posthog-python",
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def send(payload: dict) -> None:
|
||||
data = json.dumps(payload).encode("utf-8")
|
||||
req = urllib.request.Request(
|
||||
POSTHOG_HOST,
|
||||
data=data,
|
||||
headers={"Content-Type": "application/json"},
|
||||
)
|
||||
try:
|
||||
with urllib.request.urlopen(req, timeout=REQUEST_TIMEOUT):
|
||||
pass
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
|
||||
def emit(event_type: str, properties: dict | None = None) -> None:
|
||||
if not is_enabled():
|
||||
return
|
||||
send(build_posthog_payload(f"plugin.{event_type}", properties))
|
||||
|
||||
|
||||
def main() -> int:
|
||||
if not is_enabled():
|
||||
return 0
|
||||
if len(sys.argv) < 2:
|
||||
return 1
|
||||
|
||||
event_type = sys.argv[1]
|
||||
properties: dict = {}
|
||||
|
||||
for arg in sys.argv[2:]:
|
||||
if arg.startswith("--memory_count="):
|
||||
try:
|
||||
properties["memory_count"] = int(arg.split("=", 1)[1])
|
||||
except ValueError:
|
||||
pass
|
||||
elif arg.startswith("--categories_count="):
|
||||
try:
|
||||
properties["categories_count"] = int(arg.split("=", 1)[1])
|
||||
except ValueError:
|
||||
pass
|
||||
elif arg == "--error_detected":
|
||||
properties["error_detected"] = True
|
||||
elif arg == "--file_paths_detected":
|
||||
properties["file_paths_detected"] = True
|
||||
elif arg.startswith("--source="):
|
||||
properties["source_detail"] = arg.split("=", 1)[1]
|
||||
elif arg.startswith("--tool="):
|
||||
properties["tool"] = arg.split("=", 1)[1]
|
||||
elif arg.startswith("--files_count="):
|
||||
try:
|
||||
properties["files_count"] = int(arg.split("=", 1)[1])
|
||||
except ValueError:
|
||||
pass
|
||||
|
||||
emit(event_type, properties)
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -0,0 +1,48 @@
|
||||
---
|
||||
name: context-loader
|
||||
description: Searches and injects relevant memories into context before starting work on a task. Use when beginning a new task, switching context, or when project history, past decisions, or coding conventions need to be loaded.
|
||||
---
|
||||
|
||||
# Context Loader
|
||||
|
||||
Pre-fetches relevant memories to prime context before working on a task.
|
||||
|
||||
## When to use
|
||||
|
||||
- Session start (invoke manually or auto-triggered by skill description matching)
|
||||
- User starts work on a specific feature or file set
|
||||
- Complex multi-step task begins
|
||||
- User says "what do we know about X" or "context for X"
|
||||
|
||||
## Steps
|
||||
|
||||
1. **Extract topics** from current message/task. Identify: file paths, module names, feature areas, error patterns.
|
||||
|
||||
2. **Run 2-4 parallel `search_memories` calls** with different angles:
|
||||
|
||||
| Query angle | Filter | Purpose |
|
||||
|---|---|---|
|
||||
| Feature/module name | `{"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}, {"metadata": {"type": "decision"}}]}` | Architecture decisions |
|
||||
| File paths mentioned | `{"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}, {"metadata": {"type": "convention"}}]}` | Coding patterns |
|
||||
| Error keywords (if any) | `{"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}, {"metadata": {"type": "anti_pattern"}}]}` | Known pitfalls |
|
||||
| Broad project context | `{"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}]}` | Catch-all |
|
||||
|
||||
3. **Deduplicate** results by memory ID across all search responses.
|
||||
|
||||
4. **Output compact context block** (max 10 memories):
|
||||
|
||||
```
|
||||
context-loader: loaded <N> memories for "<task summary>"
|
||||
- [decision] <content> [mem0:<short_id>]
|
||||
- [convention] <content> [mem0:<short_id>]
|
||||
- [anti_pattern] <content> [mem0:<short_id>]
|
||||
```
|
||||
|
||||
5. If **zero results**: output nothing. Don't announce empty context.
|
||||
|
||||
## Constraints
|
||||
|
||||
- **Read-only** — never modify or delete memories
|
||||
- **Max 10 memories** returned (most relevant only)
|
||||
- **Silent on empty** — only surfaces findings if relevant context exists
|
||||
- Skip memories already visible in current session context
|
||||
@@ -0,0 +1,232 @@
|
||||
---
|
||||
name: dream
|
||||
description: Consolidates stored memories by merging duplicates, resolving contradictions, and pruning stale entries. Use when memory count is high, search results feel noisy or repetitive, or periodic cleanup is needed to maintain memory quality.
|
||||
---
|
||||
|
||||
# Mem0 Dream — Memory Consolidation
|
||||
|
||||
This skill performs a memory consolidation pass: it fetches all project memories,
|
||||
identifies near-duplicates, flags contradictions, and prunes stale entries based on
|
||||
configured retention policies. All proposed changes are shown as a diff for user
|
||||
approval before anything is modified.
|
||||
|
||||
**IMPORTANT: Execute steps strictly in order (1 → 2 → 3 → 4 → 5 → 6). Each step depends on the previous one. Do NOT run steps in parallel or skip ahead.**
|
||||
|
||||
## Step 1: Load Retention Policies
|
||||
|
||||
Determine the active retention policy by running the parser script. Use the
|
||||
appropriate `PLUGIN_ROOT` variable for the current platform (`${CLAUDE_PLUGIN_ROOT}`,
|
||||
`${CODEX_PLUGIN_ROOT}`, or `${CURSOR_PLUGIN_ROOT}`):
|
||||
|
||||
```bash
|
||||
python3 "<PLUGIN_ROOT>/scripts/parse_mem0_config.py" "<cwd>"
|
||||
```
|
||||
|
||||
Parse the JSON output (a dict of `category → days | null`). If the script fails
|
||||
or returns `{}`, fall back to these built-in defaults:
|
||||
|
||||
| `metadata.type` | Default retention |
|
||||
|---|---|
|
||||
| `session_state` | 90 days |
|
||||
| `compact_summary` | 90 days |
|
||||
| all others | no pruning |
|
||||
|
||||
Store the resolved policies for use in Step 3.
|
||||
|
||||
---
|
||||
|
||||
## Step 2: Fetch ALL Project Memories
|
||||
|
||||
Call `get_memories` to retrieve every memory for the active project:
|
||||
|
||||
```python
|
||||
get_memories(
|
||||
filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<active_project_id>"}]},
|
||||
page_size=200,
|
||||
)
|
||||
```
|
||||
|
||||
If the response indicates more pages exist, paginate until all memories are fetched.
|
||||
Collect the full list before proceeding. If zero memories are found, print:
|
||||
|
||||
```
|
||||
No memories found for project <project_id>. Nothing to consolidate.
|
||||
```
|
||||
|
||||
…and stop.
|
||||
|
||||
---
|
||||
|
||||
## Step 3: Analyze — Find Issues
|
||||
|
||||
Work entirely in-memory; do not modify anything yet.
|
||||
|
||||
Group memories by `metadata.type` (use `"unknown"` when the field is absent).
|
||||
For each group, identify the following:
|
||||
|
||||
### 3a. Near-duplicate pairs (merge candidates)
|
||||
|
||||
Two memories are near-duplicates when they express the same fact or decision but
|
||||
phrased differently (e.g., "Use PostgreSQL for auth" and "Auth DB is PostgreSQL").
|
||||
|
||||
Heuristics — two memories are near-duplicates if **all** of these hold:
|
||||
- Similarity threshold: estimated cosine similarity > 0.9 (use noun/keyword overlap as proxy — if >60% of significant nouns overlap, treat as >0.9 similarity).
|
||||
- Same `metadata.type`.
|
||||
- Neither memory is pinned (`metadata.pinned != true`).
|
||||
|
||||
For each qualifying pair, draft a merged version that is more complete and specific
|
||||
than either original.
|
||||
|
||||
### 3b. Contradictions
|
||||
|
||||
Two memories contradict when they assert opposing facts about the same topic
|
||||
(e.g., "Deploy to ECS" vs. "Deploy to Vercel").
|
||||
|
||||
Identify the likely winner: the more recent memory with higher confidence wins.
|
||||
Store both IDs and their content for user review.
|
||||
|
||||
### 3c. Prune candidates
|
||||
|
||||
A memory is a prune candidate when **any** of the following is true:
|
||||
|
||||
1. Its `metadata.type` has a retention policy and the memory is older than the
|
||||
configured number of days (compare `created_at` to today).
|
||||
2. Its confidence score is below 0.3 AND it contains no information unique to
|
||||
this project (no file paths, identifiers, or domain-specific nouns).
|
||||
|
||||
**Always skip memories where `metadata.pinned == true`**, regardless of age or
|
||||
confidence.
|
||||
|
||||
---
|
||||
|
||||
## Step 4: Print Diff Report
|
||||
|
||||
Print a structured diff to the terminal before making any changes. Use exactly
|
||||
this format:
|
||||
|
||||
```
|
||||
## dream — consolidation report
|
||||
|
||||
Merges (<N>):
|
||||
[mem0:<id1>] + [mem0:<id2>] → "<merged content, 100 chars>"
|
||||
|
||||
Conflicts (<N>):
|
||||
[mem0:<idA>] vs [mem0:<idB>] — "<topic>" [A/B/skip]
|
||||
|
||||
Prune (<N>):
|
||||
[mem0:<id>] — <type>, <age>d old
|
||||
|
||||
Proposed: <N> merges, <N> prunes, <N> conflicts. Apply? [Y/n]
|
||||
```
|
||||
|
||||
If there are zero items in any category, omit that section entirely.
|
||||
|
||||
If there are zero total proposals (no merges, no prunes, no conflicts), print:
|
||||
|
||||
```
|
||||
Dream complete. No duplicate, contradictory, or stale memories found.
|
||||
```
|
||||
|
||||
…and stop.
|
||||
|
||||
---
|
||||
|
||||
## Step 5: Wait for User Input and Apply
|
||||
|
||||
### 5a. Contradictions
|
||||
|
||||
For each `CONFLICT` pair in the report, wait for the user to type `A`, `B`, or
|
||||
`skip` (case-insensitive). If they enter nothing (empty), treat as `skip`.
|
||||
|
||||
Record the winner for each pair before proceeding to the final apply confirmation.
|
||||
|
||||
### 5b. Final confirmation
|
||||
|
||||
After all conflict resolutions are collected, prompt:
|
||||
|
||||
```
|
||||
Apply? [Y/n]
|
||||
```
|
||||
|
||||
If the user types `n` or `no` (case-insensitive), print `Cancelled. No changes made.`
|
||||
and stop.
|
||||
|
||||
If the user confirms (`Y`, `yes`, or empty / Enter), apply all changes in this order:
|
||||
|
||||
#### Merges
|
||||
|
||||
For each approved merge pair:
|
||||
1. `delete_memory(<id1>)`
|
||||
2. `delete_memory(<id2>)`
|
||||
3. `add_memory` with:
|
||||
- `text="<merged content>"`
|
||||
- `user_id=<active_user_id>`
|
||||
- `app_id=<active_project_id>` (top-level, not in metadata)
|
||||
- `metadata={"type": "<original type>", "branch": "<active_branch>", "confidence": <higher of the two original scores>, "source": "mem0-dream"}`
|
||||
- `infer=False`
|
||||
|
||||
#### Contradictions (resolved)
|
||||
|
||||
For each resolved conflict where the user chose A or B:
|
||||
- Delete the loser (the non-chosen memory): `delete_memory(memory_id=<loser_id>)`
|
||||
|
||||
Contradictions where the user chose `skip` are left untouched.
|
||||
|
||||
#### Prunes
|
||||
|
||||
For each prune candidate:
|
||||
- `delete_memory(<memory_id>)`
|
||||
|
||||
---
|
||||
|
||||
## Step 6: Print Summary
|
||||
|
||||
After all changes are applied, print:
|
||||
|
||||
```
|
||||
Dream complete — merged: <N>, pruned: <N>, conflicts resolved: <N>, skipped: <N>
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Auto mode
|
||||
|
||||
When invoked with `--auto` (e.g., `/mem0:dream --auto`), run non-interactively:
|
||||
|
||||
- **Merges**: applied automatically (no contradiction, both are compatible).
|
||||
- **Prunes**: applied automatically (age/confidence-based, no ambiguity).
|
||||
- **Contradictions**: skipped — they require human judgment.
|
||||
|
||||
### Concurrency guard
|
||||
|
||||
Before doing any work, check for a lock file at `/tmp/mem0_dream_auto.lock`:
|
||||
- If the lock file exists and is less than 10 minutes old, print `[mem0-dream --auto] Another run in progress — skipping.` and stop.
|
||||
- Otherwise, create the lock file (write the current timestamp). Delete it when done (in all exit paths).
|
||||
|
||||
### Execution
|
||||
|
||||
In auto mode:
|
||||
1. Load policies and fetch memories (Steps 1–3) as normal.
|
||||
2. Apply merges and prunes silently without printing the diff or prompting.
|
||||
3. Print a compact summary:
|
||||
```
|
||||
[mem0-dream --auto] project=<id> merged=<N> pruned=<N> conflicts_skipped=<N>
|
||||
```
|
||||
4. If contradictions were detected but skipped, check if a `mem0-dream-auto` reminder already exists before storing one:
|
||||
- Search for existing reminders: `search_memories(query="mem0-dream contradictions manual review", filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<active_project_id>"}, {"metadata": {"source": "mem0-dream-auto"}}]}, top_k=1)`
|
||||
- If a result exists with similarity > 0.9, skip storing the reminder (one already exists).
|
||||
- If no match, store the reminder:
|
||||
```python
|
||||
add_memory(
|
||||
text="mem0-dream detected <N> contradiction(s) requiring manual review. Run /mem0:dream to resolve them interactively.",
|
||||
user_id="<active_user_id>",
|
||||
app_id="<active_project_id>",
|
||||
metadata={"type": "task_learning", "source": "mem0-dream-auto", "branch": "<active_branch>"},
|
||||
infer=False,
|
||||
)
|
||||
```
|
||||
|
||||
## See also
|
||||
|
||||
- `/mem0:forget` — targeted deletion of specific memories (search + confirm + delete)
|
||||
- `/mem0:health --deep` — quick quality scan without applying changes
|
||||
@@ -0,0 +1,76 @@
|
||||
---
|
||||
name: export
|
||||
description: Exports all project memories to a portable Markdown file for backup or migration. Use when backing up memories, migrating to another project, sharing memory state with teammates, or archiving before cleanup.
|
||||
---
|
||||
|
||||
# Mem0 Export
|
||||
|
||||
Export all memories for the current project to a portable Markdown file.
|
||||
|
||||
## Execution
|
||||
|
||||
### Step 1: Resolve identity
|
||||
|
||||
Determine the active identity:
|
||||
- `user_id` from `MEM0_USER_ID` env var, else `$USER`, else `"default"`
|
||||
- `project_id` (used as `app_id`) from `MEM0_PROJECT_ID` env var, or via the project resolver
|
||||
|
||||
### Step 2: Fetch all memories
|
||||
|
||||
Call `get_memories` with:
|
||||
- `filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<active_project_id>"}]}`
|
||||
- `page_size=200`
|
||||
|
||||
If the response is paginated (i.e. the result contains a `next` cursor or the count equals `page_size`), continue fetching pages until all memories are retrieved.
|
||||
|
||||
### Step 3: Format each memory as a YAML-frontmatter block
|
||||
|
||||
For each memory record, produce a block in this exact format:
|
||||
|
||||
```
|
||||
---
|
||||
id: <memory.id>
|
||||
created_at: <memory.created_at>
|
||||
type: <memory.metadata.type or "">
|
||||
confidence: <memory.metadata.confidence or "">
|
||||
branch: <memory.metadata.branch or "">
|
||||
files: <memory.metadata.files joined with ", " or "">
|
||||
categories: <memory.categories joined with ", " or "">
|
||||
---
|
||||
<memory.memory or memory content string>
|
||||
|
||||
```
|
||||
|
||||
Notes:
|
||||
- The `---` delimiters must be on their own lines with no extra whitespace.
|
||||
- `files` and `categories` are written as comma-separated values on a single line.
|
||||
- Leave a blank line after the content before the next `---` (for readability).
|
||||
- If a field is missing or null, write an empty string (not "null").
|
||||
|
||||
### Step 4: Write the export file
|
||||
|
||||
Determine the output filename:
|
||||
|
||||
```
|
||||
mem0-export-<project_id>-<YYYY-MM-DD>.md
|
||||
```
|
||||
|
||||
Where `<YYYY-MM-DD>` is today's date in UTC.
|
||||
|
||||
Write all formatted blocks to this file using the Write tool (or equivalent). The file is written to the current working directory.
|
||||
|
||||
### Step 5: Print summary
|
||||
|
||||
```
|
||||
Exported <N> memories to <filename>
|
||||
```
|
||||
|
||||
Where `<N>` is the total number of memory blocks written.
|
||||
|
||||
## Error Handling
|
||||
|
||||
- If `get_memories` returns an error or zero memories, print:
|
||||
```
|
||||
No memories found for project <project_id>. Nothing exported.
|
||||
```
|
||||
- If the write fails, report the error to the user.
|
||||
@@ -0,0 +1,71 @@
|
||||
---
|
||||
name: forget
|
||||
description: Deletes memories by search query or memory ID with confirmation before removal. Use when removing outdated decisions, incorrect memories, sensitive data, or cleaning up after experiments. Also handles undo of recent additions.
|
||||
---
|
||||
|
||||
# Mem0 Forget
|
||||
|
||||
Delete specific memories from mem0.
|
||||
|
||||
## Execution
|
||||
|
||||
### Step 1: Parse input
|
||||
|
||||
The user provides either:
|
||||
- A search query: `/mem0:forget auth module decisions`
|
||||
- A memory ID: `/mem0:forget <memory_id>`
|
||||
|
||||
If no argument, ask: "What should I forget? Provide a search query or memory ID."
|
||||
|
||||
### Step 2: Find memories
|
||||
|
||||
**If memory ID provided** (looks like a UUID or hex string):
|
||||
- Call `get_memory` with the ID to verify it exists.
|
||||
- Show: `Found: "<memory content first 120 chars>" (created <date>)`
|
||||
|
||||
**If search query provided:**
|
||||
- Call `search_memories` with:
|
||||
- `query=<user's query>`
|
||||
- `filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<project_id>"}]}`
|
||||
- `top_k=10`
|
||||
- Show numbered list:
|
||||
```
|
||||
Found <N> memories matching "<query>":
|
||||
1. <content, 120 chars> (type: <type>, created: <date>) [ID: <short_id>]
|
||||
2. ...
|
||||
```
|
||||
|
||||
### Step 3: Confirm
|
||||
|
||||
Ask: "Delete which memories? Enter numbers (e.g., 1,3,5), 'all', or 'cancel'."
|
||||
|
||||
For a single memory ID, ask: "Delete this memory? [y/N]"
|
||||
|
||||
**Never delete without confirmation.** This is destructive.
|
||||
|
||||
### Step 4: Delete
|
||||
|
||||
For each confirmed memory, call `delete_memory` with the memory ID.
|
||||
|
||||
### Step 5: Report
|
||||
|
||||
```
|
||||
Deleted <N> memories.
|
||||
```
|
||||
|
||||
If any deletions failed, report which ones and why.
|
||||
|
||||
## Undo recent writes
|
||||
|
||||
If the user says "undo last N memories" or "undo last write":
|
||||
|
||||
1. Read session stats to get recently written memory IDs:
|
||||
```bash
|
||||
SCRIPT_DIR="${CLAUDE_PLUGIN_ROOT:-${CODEX_PLUGIN_ROOT:-${CURSOR_PLUGIN_ROOT:-}}}/scripts"
|
||||
python3 "$SCRIPT_DIR/session_stats.py" peek
|
||||
```
|
||||
2. Parse the `recent_ids` array from the JSON output. Each entry has `id`, `category`, `ts`.
|
||||
3. Show the last N entries (default 1) and ask for confirmation.
|
||||
4. Delete confirmed entries via `delete_memory`.
|
||||
|
||||
If `recent_ids` is empty, tell the user: "No recent memory IDs tracked this session. Try `/mem0:tour` to browse recent memories, or `/mem0:forget <search query>` to find specific ones."
|
||||
@@ -0,0 +1,160 @@
|
||||
---
|
||||
name: health
|
||||
description: Diagnoses mem0 connectivity, API key validity, and memory read/write functionality. Use when memory operations fail, searches return empty, add_memory errors occur, MCP connection drops, or to verify the plugin is working correctly.
|
||||
---
|
||||
|
||||
# Mem0 Health Check
|
||||
|
||||
Run a diagnostic check on the mem0 plugin. Useful for troubleshooting.
|
||||
|
||||
## Execution
|
||||
|
||||
Run ALL checks, then display a single summary. Do not stop on the first failure.
|
||||
|
||||
### Check 1: API key
|
||||
|
||||
```bash
|
||||
_KEY="${MEM0_API_KEY:-${CLAUDE_PLUGIN_OPTION_MEM0_API_KEY:-}}"
|
||||
[ -n "$_KEY" ] && echo "${_KEY:0:6}..." || echo "NOT_SET"
|
||||
```
|
||||
|
||||
- If `NOT_SET`: FAIL — "No API key configured"
|
||||
- If set: PASS — the command already prints only the first 6 chars
|
||||
|
||||
### Check 2: Identity resolution
|
||||
|
||||
Resolve identity using the plugin's own resolver scripts to match what hooks use:
|
||||
|
||||
```bash
|
||||
SCRIPT_DIR="${CLAUDE_PLUGIN_ROOT:-${CODEX_PLUGIN_ROOT:-${CURSOR_PLUGIN_ROOT:-}}}/scripts"
|
||||
source "$SCRIPT_DIR/_identity.sh" 2>/dev/null
|
||||
echo "user_id=${MEM0_RESOLVED_USER_ID:-}"
|
||||
echo "project_id=${MEM0_PROJECT_ID:-}"
|
||||
echo "branch=${MEM0_BRANCH:-}"
|
||||
```
|
||||
|
||||
If `CLAUDE_PLUGIN_ROOT` is not available, fall back to:
|
||||
- `user_id`: from `MEM0_USER_ID` or `$USER`
|
||||
- `project_id`: from `MEM0_PROJECT_ID` or check `~/.mem0/project_map.json` for `$PWD`
|
||||
- `branch`: from `git branch --show-current`
|
||||
|
||||
PASS if all three are non-empty. WARN if any falls back to defaults.
|
||||
|
||||
### Check 3: MCP server connectivity
|
||||
|
||||
Call `search_memories` with:
|
||||
- `query="health check"`
|
||||
- `filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<active_project_id>"}]}`
|
||||
- `top_k=1`
|
||||
|
||||
- If returns successfully (even empty): PASS
|
||||
- If errors: FAIL — show the error message
|
||||
|
||||
### Check 4: Memory write capability
|
||||
|
||||
Call `add_memory` with:
|
||||
- `text="Health check probe — safe to delete."`
|
||||
- `user_id=<active_user_id>`
|
||||
- `app_id=<active_project_id>`
|
||||
- `metadata={"type": "health_check", "probe": true}`
|
||||
- `infer=False`
|
||||
|
||||
The response returns `event_id` (v3 writes are async). Call `get_event_status(event_id=<event_id>)` to check processing.
|
||||
|
||||
- If status is `SUCCEEDED`: PASS — extract the memory ID from the event result, then call `delete_memory` with that ID to clean up.
|
||||
- If status is `PENDING` after 5 seconds: PASS (write accepted, processing delayed)
|
||||
- If errors: FAIL — show the error.
|
||||
|
||||
### Check 5: Session stats tracker
|
||||
|
||||
Check if the session stats file exists and is readable:
|
||||
|
||||
```bash
|
||||
STATS_FILE="/tmp/mem0_session_stats_${USER}.json"
|
||||
if [ -f "$STATS_FILE" ] && python3 -c "import json; json.load(open('$STATS_FILE'))" 2>/dev/null; then
|
||||
echo "OK"
|
||||
else
|
||||
echo "FAIL"
|
||||
fi
|
||||
```
|
||||
|
||||
This file is created by the SessionStart hook and updated by PostToolUse hooks throughout the session. If it doesn't exist, the session hooks may not have fired yet — try sending a message first, then recheck.
|
||||
|
||||
### Display
|
||||
|
||||
```
|
||||
## mem0 health
|
||||
|
||||
PASS API Key m0-dVe...
|
||||
PASS Identity user=kartik, project=mem0, branch=main
|
||||
PASS MCP Connection 142ms
|
||||
PASS Write/Read write + delete OK
|
||||
PASS Session Tracker stats file active
|
||||
|
||||
All checks passed.
|
||||
```
|
||||
|
||||
If any check fails, add a `## Troubleshooting` section with specific fix steps for each failure.
|
||||
|
||||
## Extended mode: Memory Quality Analysis
|
||||
|
||||
When invoked with `--deep` (e.g., `/mem0:health --deep`), run the standard 5 checks above **plus** a memory quality scan.
|
||||
|
||||
### Quality Check 1: Duplicates
|
||||
|
||||
Call `get_memories` with `filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<active_project_id>"}]}`, `page_size=200`. Compare all pairs within the same `metadata.type` group for high textual overlap (shared nouns/keywords > 60%). Report:
|
||||
|
||||
```
|
||||
Potential duplicates: <N> pairs
|
||||
[mem0:<id1>] ≈ [mem0:<id2>] — both about "<shared topic>"
|
||||
```
|
||||
|
||||
### Quality Check 2: Stale memories
|
||||
|
||||
Flag memories where:
|
||||
- `metadata.type` is `session_state` or `compact_summary` AND older than 90 days
|
||||
- `metadata.confidence` < 0.3 AND older than 30 days
|
||||
|
||||
```
|
||||
Stale candidates: <N>
|
||||
[mem0:<id>] — session_state, 142d old
|
||||
```
|
||||
|
||||
### Quality Check 2b: Low-confidence memories
|
||||
|
||||
Flag memories where `metadata.confidence` < 0.5 (regardless of age). Report separately from stale:
|
||||
|
||||
```
|
||||
Low-confidence memories: <N>
|
||||
[mem0:<id>] — confidence=0.3, "<content preview>"
|
||||
```
|
||||
|
||||
### Quality Check 3: Contradictions
|
||||
|
||||
Within each `metadata.type` group, flag pairs that assert opposing facts about the same topic. Use semantic judgment — look for negation patterns, conflicting tool/framework choices, or reversed decisions.
|
||||
|
||||
```
|
||||
Possible contradictions: <N>
|
||||
[mem0:<idA>] vs [mem0:<idB>] — conflicting on "<topic>"
|
||||
```
|
||||
|
||||
### Quality Check 4: Orphan memories
|
||||
|
||||
Memories with no `metadata.type` set, or with `metadata.type` not in the 17 known coding categories. These were likely written without proper tagging.
|
||||
|
||||
```
|
||||
Untagged/orphan memories: <N>
|
||||
```
|
||||
|
||||
### Quality summary
|
||||
|
||||
```
|
||||
## Memory Quality
|
||||
|
||||
Duplicates: <N> · Stale: <N> · Contradictions: <N> · Orphans: <N>
|
||||
```
|
||||
|
||||
If all counts are 0: `Memory quality: clean.`
|
||||
If any non-zero: append `Run /mem0:dream to fix.`
|
||||
|
||||
To fix issues found by `--deep`, run `/mem0:dream` for automated consolidation (merges, prunes, conflict resolution).
|
||||
@@ -0,0 +1,177 @@
|
||||
---
|
||||
name: import
|
||||
description: Imports memories from an exported Markdown file or MEMORY.md into the current project. Use when migrating from another project, restoring from backup, importing Claude Code native MEMORY.md content, or setting up a new project with existing knowledge.
|
||||
---
|
||||
|
||||
# Mem0 Import
|
||||
|
||||
Import memories from a mem0 export file into the current project.
|
||||
|
||||
## Execution
|
||||
|
||||
### Step 1: Determine the export file to import
|
||||
|
||||
If the user provided a filename as an argument to `/mem0:import <filename>`, use that file.
|
||||
|
||||
Otherwise, list `.md` files in the current directory whose names contain `mem0-export`:
|
||||
|
||||
```bash
|
||||
ls -1 *.md 2>/dev/null | grep mem0-export || echo "No export files found"
|
||||
```
|
||||
|
||||
If multiple files are found, ask the user which one to import. If none are found, print:
|
||||
```
|
||||
No mem0-export files found in the current directory.
|
||||
Run /mem0:export first, or provide the filename: /mem0:import <path-to-file>
|
||||
```
|
||||
|
||||
### Step 2: Parse the export file
|
||||
|
||||
Determine the plugin root. Use the appropriate variable for the current platform:
|
||||
- Claude Code: `${CLAUDE_PLUGIN_ROOT}`
|
||||
- Codex: `${CODEX_PLUGIN_ROOT}`
|
||||
- Cursor: `${CURSOR_PLUGIN_ROOT}`
|
||||
|
||||
Run the parser script to extract memory records as JSON:
|
||||
|
||||
```bash
|
||||
python3 "<PLUGIN_ROOT>/scripts/parse_export_file.py" "<path-to-export-file>"
|
||||
```
|
||||
|
||||
This outputs a JSON array where each element has:
|
||||
- `id` — original memory ID (for reference only; a new ID will be assigned on import)
|
||||
- `type` — metadata type
|
||||
- `confidence` — metadata confidence value
|
||||
- `branch` — metadata branch
|
||||
- `files` — list of associated files
|
||||
- `categories` — list of categories
|
||||
- `content` — the memory text
|
||||
|
||||
If the script fails or outputs `[]`, print:
|
||||
```
|
||||
Failed to parse <filename> or file contains no valid memory blocks.
|
||||
```
|
||||
and stop.
|
||||
|
||||
### Step 3: Resolve identity
|
||||
|
||||
Determine the active identity:
|
||||
- `user_id` from `MEM0_USER_ID` env var, else `$USER`, else `"default"`
|
||||
- `project_id` (used as `app_id`) from `MEM0_PROJECT_ID` env var, or via the project resolver
|
||||
|
||||
### Step 4: Import each memory
|
||||
|
||||
For each record in the parsed JSON array, call `add_memory` with:
|
||||
|
||||
- `text="<record.content>"`
|
||||
- `user_id=<active_user_id>`
|
||||
- `app_id=<active_project_id>`
|
||||
- `metadata={`
|
||||
- `"type": "<record.type>"` (if non-empty)
|
||||
- `"confidence": "<record.confidence>"` (if non-empty)
|
||||
- `"branch": "<record.branch>"` (if non-empty)
|
||||
- `"files": <record.files>` (the list, if non-empty)
|
||||
- `"source": "import"`
|
||||
- `}`
|
||||
- `infer=False`
|
||||
|
||||
Notes:
|
||||
- Do NOT pass the original `id` — the platform assigns a new ID.
|
||||
- Skip records where `content` is empty (the parser already filters these, but be defensive).
|
||||
- Continue importing even if individual records fail; track the count of successes.
|
||||
|
||||
### Step 5: Print results
|
||||
|
||||
```
|
||||
Imported <N> memories into project <project_id>
|
||||
```
|
||||
|
||||
Where `<N>` is the number of successfully imported memories.
|
||||
|
||||
If any failed:
|
||||
```
|
||||
Imported <N>/<total> memories into project <project_id> (<failed> failed)
|
||||
```
|
||||
|
||||
## Importing from competing AI tools (`--tools`)
|
||||
|
||||
When invoked with `--tools` (e.g., `/mem0:import --tools`), detect and import
|
||||
from competing AI tool configuration files:
|
||||
|
||||
### Supported tools
|
||||
|
||||
| Tool | File/directory |
|
||||
|------|---------------|
|
||||
| Cursor | `.cursorrules` |
|
||||
| GitHub Copilot | `.github/copilot-instructions.md` |
|
||||
| Cline | `memory-bank/` (directory of `.md` files) |
|
||||
| Continue | `.continue/rules.md` |
|
||||
|
||||
### T1: Detect
|
||||
|
||||
```bash
|
||||
test -f .cursorrules && echo "cursor: .cursorrules"
|
||||
test -f .github/copilot-instructions.md && echo "copilot: .github/copilot-instructions.md"
|
||||
test -d memory-bank/ && echo "cline: memory-bank/"
|
||||
test -f .continue/rules.md && echo "continue: .continue/rules.md"
|
||||
```
|
||||
|
||||
### T2: Ask user
|
||||
|
||||
List found files, ask which to import (numbers, comma-separated, or "all").
|
||||
If none found:
|
||||
```
|
||||
No competing tool configuration files found.
|
||||
Checked: .cursorrules, .github/copilot-instructions.md, memory-bank/, .continue/rules.md
|
||||
```
|
||||
|
||||
### T3: Run import
|
||||
|
||||
For each selected tool:
|
||||
```bash
|
||||
python3 "<PLUGIN_ROOT>/scripts/import_competing_tools.py" <tool> --path <file>
|
||||
```
|
||||
|
||||
Tools: `cursorrules`, `copilot`, `cline`, `continue`.
|
||||
|
||||
### T4: Report
|
||||
|
||||
```
|
||||
Imported <N> memories into <project_id> (cursor: <N>, copilot: <N>)
|
||||
```
|
||||
|
||||
Notes: `infer=False`, tagged `metadata.source=<tool>-import`, sections <50 chars
|
||||
skipped, chunks >10k chars truncated, safe to re-run (deduplication handles it).
|
||||
|
||||
---
|
||||
|
||||
## Importing Claude Code's native MEMORY.md
|
||||
|
||||
When invoked with a path to Claude Code's native `MEMORY.md` file (typically
|
||||
`~/.claude/projects/<proj-key>/memory/MEMORY.md`), or when `on_session_start.sh`
|
||||
detects native auto-memory and the user chooses to import:
|
||||
|
||||
1. Read the file. It contains newline-separated memory entries (one fact per line,
|
||||
sometimes with `- ` bullet prefix).
|
||||
2. Split by non-empty lines. Each line becomes one memory.
|
||||
3. Skip lines shorter than 20 characters or lines that are just headers (`#`).
|
||||
4. For each line, call `add_memory` with:
|
||||
- `text="<line>"`
|
||||
- `user_id=<active_user_id>`
|
||||
- `app_id=<active_project_id>`
|
||||
- `metadata={"type": "task_learning", "source": "memory-md-import", "confidence": 0.8}`
|
||||
- `infer=False`
|
||||
5. Report: `Imported <N> memories from MEMORY.md into project <project_id>`
|
||||
6. Suggest disabling native auto-memory:
|
||||
```
|
||||
To avoid duplicate memory systems, add to ~/.claude/settings.json:
|
||||
"autoMemoryEnabled": false
|
||||
```
|
||||
|
||||
This handles the cold-start gap when a user has been using Claude Code's native
|
||||
memory and switches to mem0.
|
||||
|
||||
## Error Handling
|
||||
|
||||
- If the parser script is not found at `<PLUGIN_ROOT>/scripts/parse_export_file.py`, print an error and stop.
|
||||
- If `add_memory` calls fail consistently (e.g. auth error), report the issue and stop early.
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user