gabrielstein-mem0
789122bbea
The Python sync/async MemoryClient and the TS MemoryClient were silently switching their PostHog distinct_id from an anonymous on-disk UUID to the user's email post-ping, without sending the merge instruction. PostHog ended up tracking each user as 2-3 disconnected personas (OSS UUID, CLI anon UUID, email), and only ~4 $create_alias events fired across ~300K users. The Python CLI does this correctly today; this change ports the same pattern to MemoryClient. - mem0/memory/setup.py: make setup_config() idempotent so it backfills a top-level user_id for CLI-first users (the CLI writes telemetry.anonymous_id, not user_id, which left OSS telemetry silently dropped). Add read_anon_ids() and mark_aliased() helpers. - mem0/memory/telemetry.py: add AnonymousTelemetry.capture_identify() that posts a PostHog $identify event with $anon_distinct_id. Add "$identify" to _LIFECYCLE_EVENTS so it bypasses the 90% sampling drop. - mem0/client/main.py: at the end of __init__ for both MemoryClient and AsyncMemoryClient, fire $identify for each unaliased anon ID and persist telemetry.aliased_to so the alias only happens once per (anon_id, email) pair, ever. All telemetry calls swallow exceptions. - mem0-ts/src/client/telemetry.ts: mirror with captureIdentify(). - mem0-ts/src/client/config.ts (new): node-only readMem0AnonIds() and markMem0Aliased() using async dynamic imports of fs/path/os, gated on process.versions.node so browsers no-op cleanly. - mem0-ts/src/client/mem0.ts: call _maybeAliasAnonToEmail() inside _initializeClient after ping resolves the email. Tests cover the matrix (OSS-only, CLI-only, both, already-aliased) plus failure modes (malformed JSON, read-only fs, posthog errors, browser env). Telemetry never raises.
Mem0 - The Memory Layer for Your AI Apps
Mem0 is a self-improving memory layer for LLM applications, enabling personalized AI experiences that save costs and delight users. We offer both cloud and open-source solutions to cater to different needs.
See the complete OSS Docs. See the complete Platform API Reference.
1. Installation
For the open-source version, you can install the Mem0 package using npm:
npm i mem0ai
2. API Key Setup
For the cloud offering, sign in to Mem0 Platform to obtain your API Key.
3. Client Features
Cloud Offering
The cloud version provides a comprehensive set of features, including:
- Memory Operations: Perform CRUD operations on memories.
- Search Capabilities: Search for relevant memories using advanced filters.
- Memory History: Track changes to memories over time.
- Error Handling: Robust error handling for API-related issues.
- Async/Await Support: All methods return promises for easy integration.
Open-Source Offering
The open-source version includes the following top features:
- Memory Management: Add, update, delete, and retrieve memories.
- Vector Store Integration: Supports various vector store providers for efficient memory retrieval.
- LLM Support: Integrates with multiple LLM providers for generating responses.
- Customizable Configuration: Easily configure memory settings and providers.
- SQLite Storage: Use SQLite for memory history management.
4. Memory Operations
Mem0 provides a simple and customizable interface for performing memory operations. You can create long-term and short-term memories, search for relevant memories, and manage memory history.
5. Error Handling
The MemoryClient throws errors for any API-related issues. You can catch and handle these errors effectively.
6. Using with async/await
All methods of the MemoryClient return promises, allowing for seamless integration with async/await syntax.
7. Testing the Client
To test the MemoryClient in a Node.js environment, you can create a simple script to verify the functionality of memory operations.
Getting Help
If you have any questions or need assistance, please reach out to us:
- Email: founders@mem0.ai
- Join our discord community
- GitHub Issues: Report bugs or request features