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refactor: update memory skill loader, plugin config, and add privacy docs (#4905)

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Kartik
2026-04-22 17:15:19 +05:30
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parent 32b74e18b7
commit f5dc825d47
21 changed files with 1734 additions and 189 deletions
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docs/changelog/openclaw.mdx
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@@ -4,6 +4,27 @@ description: "Release notes for the OpenClaw plugin and agent harness."
mode: "wide"
---
<Update label="2026-04-21" description="v1.0.8">
**New Features:**
- **OSS Onboarding Wizard:** New guided 4-step interactive setup for open-source mode — walks through LLM provider, embedding provider, vector store, and user ID selection with prefilled defaults
- **Agent-Friendly CLI:** Added `--json` flag to all 16 CLI commands for machine-readable output. Agents can call `openclaw mem0 help --json` to discover every command and flag
- **Non-Interactive OSS Setup:** Added `--mode open-source` with `--oss-llm`, `--oss-embedder`, `--oss-vector` flags for fully automated OSS configuration without prompts
- **JSON Helpers Module:** New `cli/json-helpers.ts` with `jsonOut`, `jsonErr`, and `redactSecrets` utilities for consistent structured output
**Improvements:**
- **Init Flow Redesigned:** Replaced 3-option flat menu with 2-level structure: Platform (email login or API key) and Open Source (guided wizard)
- **Provider Selection:** LLM providers: OpenAI, Ollama, Anthropic. Embedding providers: OpenAI, Ollama. Vector stores: Qdrant, PGVector
- **Input Prefill:** All prompts with defaults (base URL, user ID) now prefill the input field instead of showing defaults in brackets
- **Smart Reuse:** When LLM and embedder use the same provider, API key and base URL are automatically reused from the LLM step
- **Default Model:** Updated default LLM model to `gpt-5-mini`
- **Manifest Compliance:** Removed undocumented fields, aligned env var declarations between SKILL.md and manifest, fixed `configSchema.required` for clean installs
**Tests:**
- 404 tests across 15 test files (+3 new: `json-helpers.test.ts`, `oss-wizard.test.ts`, `cli-commands.test.ts`)
</Update>
<Update label="2026-04-20" description="v1.0.7">
**New Features:**
docs/integrations/openclaw.mdx
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@@ -16,7 +16,7 @@ The plugin provides:
2. **Auto-Capture** — After the agent responds, the exchange is sent to Mem0 which decides what's worth keeping
3. **Agent Tools** — Eight tools for explicit memory operations during conversations
Both auto-recall and auto-capture run silently with no manual configuration required.
Both auto-recall and auto-capture are opt-in (`autoRecall: true`, `autoCapture: true` in config). Once enabled, they run silently with no manual intervention required.
## Requirements
@@ -147,7 +147,81 @@ OpenClaw treats memory plugins as an exclusive slot. Installing the plugin alone
### Open-Source Mode (Self-hosted)
No Mem0 key needed. Requires `OPENAI_API_KEY` for default embeddings/LLM.
No Mem0 key needed. Defaults use OpenAI (`gpt-5-mini` for LLM, `text-embedding-3-small` for embeddings) — requires `OPENAI_API_KEY`. For a fully local setup, use Ollama for both.
#### Option 1: Interactive Wizard (Recommended)
Run the guided 4-step wizard:
```bash
openclaw mem0 init --mode open-source
```
The wizard walks you through:
<Steps>
<Step title="LLM provider">
Choose OpenAI (`gpt-5-mini`), Ollama (`llama3.1:8b`, fully local), or Anthropic (`claude-sonnet-4-5-20250514`). Provide an API key or base URL as needed.
</Step>
<Step title="Embedding provider">
Choose OpenAI (`text-embedding-3-small`) or Ollama (`nomic-embed-text`, local). If the same provider was chosen for LLM, the API key and URL are reused automatically.
</Step>
<Step title="Vector store">
Choose Qdrant (`http://localhost:6333`) or PGVector (PostgreSQL). Connectivity is verified before proceeding.
</Step>
<Step title="User ID">
Set your memory namespace identifier.
</Step>
</Steps>
#### Option 2: Non-Interactive Setup
For CI/CD, scripts, or agent-driven setup — pass all options as flags:
```bash
# Fully local with Ollama + Qdrant
openclaw mem0 init --mode open-source \
--oss-llm ollama --oss-embedder ollama --oss-vector qdrant
# OpenAI + Qdrant
openclaw mem0 init --mode open-source \
--oss-llm openai --oss-llm-key <key> \
--oss-embedder openai --oss-embedder-key <key> \
--oss-vector qdrant
# Anthropic LLM + OpenAI embeddings + PGVector
openclaw mem0 init --mode open-source \
--oss-llm anthropic --oss-llm-key <key> \
--oss-embedder openai --oss-embedder-key <key> \
--oss-vector pgvector --oss-vector-user postgres --oss-vector-password secret
```
Add `--json` for machine-readable output (useful when an LLM agent is driving the setup).
<Accordion title="All --oss-* flags">
| Flag | Description |
|------|-------------|
| `--oss-llm <provider>` | `openai`, `ollama`, or `anthropic` |
| `--oss-llm-key <key>` | API key for LLM provider |
| `--oss-llm-model <model>` | Override default LLM model |
| `--oss-llm-url <url>` | Base URL (Ollama only) |
| `--oss-embedder <provider>` | `openai` or `ollama` |
| `--oss-embedder-key <key>` | API key for embedder |
| `--oss-embedder-model <model>` | Override default embedder model |
| `--oss-embedder-url <url>` | Base URL (Ollama only) |
| `--oss-vector <provider>` | `qdrant` or `pgvector` |
| `--oss-vector-url <url>` | Qdrant server URL (default: `http://localhost:6333`) |
| `--oss-vector-host <host>` | PGVector host |
| `--oss-vector-port <port>` | PGVector port |
| `--oss-vector-user <user>` | PGVector user |
| `--oss-vector-password <pw>` | PGVector password |
| `--oss-vector-dbname <db>` | PGVector database name |
| `--oss-vector-dims <n>` | Override embedding dimensions |
</Accordion>
#### Option 3: Manual Config
Minimal config — uses OpenAI defaults:
```json5
{
@@ -168,7 +242,7 @@ No Mem0 key needed. Requires `OPENAI_API_KEY` for default embeddings/LLM.
}
```
Sensible defaults work out of the box. To customize the embedder, vector store, or LLM:
To customize providers:
```json5
{
@@ -184,8 +258,8 @@ Sensible defaults work out of the box. To customize the embedder, vector store,
"userId": "your-user-id",
"oss": {
"embedder": { "provider": "openai", "config": { "model": "text-embedding-3-small" } },
"vectorStore": { "provider": "qdrant", "config": { "host": "localhost", "port": 6333 } },
"llm": { "provider": "openai", "config": { "model": "gpt-4o" } }
"vectorStore": { "provider": "qdrant", "config": { "url": "http://localhost:6333" } },
"llm": { "provider": "openai", "config": { "model": "gpt-5-mini" } }
}
}
}
@@ -225,6 +299,8 @@ The `memory_search` and `memory_list` tools accept a `scope` parameter (`"sessio
## CLI Commands
All commands support `--json` for machine-readable output — useful when an LLM agent drives the CLI programmatically. Run `openclaw mem0 help --json` to discover every command and flag.
```bash
# Search all memories (long-term + session)
openclaw mem0 search "what languages does the user know"
@@ -238,6 +314,10 @@ openclaw mem0 search "what languages does the user know" --scope session
# List all memories
openclaw mem0 list
openclaw mem0 list --user-id alice --top-k 20
# JSON output (any command)
openclaw mem0 search "preferences" --json
openclaw mem0 status --json
```
## Configuration Options
@@ -248,8 +328,8 @@ openclaw mem0 list --user-id alice --top-k 20
|-----|------|---------|-------------|
| `mode` | `"platform"` \| `"open-source"` | `"platform"` | Which backend to use |
| `userId` | `string` | OS username | Scope memories per user |
| `autoRecall` | `boolean` | `true` | Inject memories before each turn |
| `autoCapture` | `boolean` | `true` | Store facts after each turn |
| `autoRecall` | `boolean` | `false` | Inject memories before each turn (opt-in) |
| `autoCapture` | `boolean` | `false` | Store facts after each turn (opt-in) |
| `topK` | `number` | `5` | Max memories per recall |
| `searchThreshold` | `number` | `0.3` | Min similarity (0–1) |
@@ -275,7 +355,7 @@ openclaw mem0 list --user-id alice --top-k 20
| `oss.historyDbPath` | `string` | — | SQLite path for memory edit history |
| `oss.disableHistory` | `boolean` | `false` | Disable memory edit history tracking |
Everything inside `oss` is optional — defaults use OpenAI embeddings (`text-embedding-3-small`), in-memory vector store, and OpenAI LLM.
Everything inside `oss` is optional — defaults use OpenAI embeddings (`text-embedding-3-small`), in-memory vector store, and OpenAI LLM (`gpt-5-mini`).
## Plugin Management
@@ -338,6 +418,64 @@ If `openclaw plugins update` fails:
openclaw plugins install @mem0/openclaw-mem0
```
## Privacy & Security
### Data Flow
| Mode | Where data goes | Storage |
|------|----------------|---------|
| **Platform** | Conversations sent to `api.mem0.ai` for extraction and storage | Mem0 cloud |
| **Open-source** | Embeddings generated via configured provider (default: OpenAI API). Vectors stored locally. | `~/.mem0/vector_store.db` (SQLite) |
### Enabling Auto-Capture and Auto-Recall
Auto-capture and auto-recall are disabled by default (opt-in). To enable either or both:
```json5
{
"plugins": {
"entries": {
"openclaw-mem0": {
"config": {
"autoCapture": true, // send conversations to Mem0 for extraction
"autoRecall": true // inject relevant memories into context
}
}
}
}
}
```
Without these enabled, the agent can still use memory tools (`memory_add`, `memory_search`, etc.) explicitly — only the automatic background behavior is off.
### Credential Protection
The plugin never stores API keys, tokens, or secrets as memories. Five independent layers enforce this:
1. **Triage gate** — The extraction prompt rejects values matching known credential patterns (`sk-`, `m0-`, `ghp_`, `AKIA`, `Bearer`, `password=`, `token=`, `secret=`)
2. **Dream cleanup** — Periodic memory consolidation deletes any memories that slipped through containing credential patterns
3. **Extraction instructions** — Default extraction rules explicitly instruct the model to store only that a credential was configured, never the value
4. **Configurable patterns** — Add custom credential patterns via `skills.triage.credentialPatterns`
5. **CLI redaction** — `openclaw mem0 config show` redacts sensitive fields (`apiKey`, `oss.*.config.apiKey`)
### API Key Storage
Plugin config is stored in `~/.openclaw/openclaw.json` with file permissions `0o600` (owner-read-only). For production deployments, use environment variable references (`${MEM0_API_KEY}`) or SecretRef objects instead of plaintext keys.
### Telemetry
Anonymous usage telemetry (PostHog) is enabled by default to help improve the plugin. No conversation content or memory values are included — only event counts (recall, capture, tool usage, CLI commands).
To opt out, set the environment variable:
```bash
export MEM0_TELEMETRY=false
```
### System Prompt Context
The plugin injects memory-related instructions into the agent's system context via OpenClaw's `prependSystemContext` mechanism. This includes the memory triage protocol and recalled memories. This is the standard OpenClaw plugin SDK pattern for memory backends — no user-facing prompts are modified.
## Key Features
1. **Zero Configuration** — Auto-recall and auto-capture work out of the box with no prompting required