JDSS/mem0

Files

T

Soumil Rathi 59880a6f8f feat: TS SDK v3 port, graph store removal, client v3 API migration

TypeScript SDK v3 pipeline (full parity with Python):
- Single-pass additive extraction with ADDITIVE_EXTRACTION_PROMPT
- Hybrid search (semantic + BM25 + entity boost) with additive scoring
- 8-phase batch pipeline (batch embed, persist, entity linking)
- New utils: scoring.ts, lemmatization.ts (natural), entity_extraction.ts (compromise)
- keywordSearch() on 8 vector stores (3 full: PGVector, Memory, Azure AI Search)
- Message persistence in SQLiteManager (rolling window of 10)
- Entity store as second vector collection
- MAX_BATCH=100 chunking guard on OpenAI/Azure embedBatch
- Updated default LLM model to gpt-4.1-nano-2025-04-14
- compromise + natural added as peer dependencies

Graph store removal (Python + TypeScript):
- Removed Neo4j, Memgraph, Kuzu, Neptune, Apache AGE integrations
- Deleted 18 graph-related files across both SDKs
- Removed GraphStoreFactory, GraphStoreConfig, graph_store config field
- Removed "relations" key from all API responses
- Removed graph optional dependency group from pyproject.toml
- Removed neo4j-driver from TS peerDependencies
- Simplified add/search/delete/reset (no more parallel graph operations)

Client SDK v3 API migration:
- add() endpoint: /v1/memories/ -> /v3/memories/ (async response)
- search() endpoint: /v2/memories/search/ -> /v3/memories/search/
- Removed output_format injection and v1.1 unwrapping logic
- Applied to both Python (sync + async) and TypeScript clients

Review feedback fixes:
- Removed deprecated custom_update_memory_prompt from MemoryConfig
- Added MAX_BATCH=100 chunking to Python + TS embed_batch
- Moved all inline imports to top level in main.py
- Cleaned up GraphStoreError dead code from exceptions.py

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-04-13 10:45:40 -07:00

.env.example

feat: add optional API key authentication to REST API server (#4442 )

2026-03-20 16:15:25 +05:30

dev.Dockerfile

feat: add development docker compose (#2411 )

2025-04-01 16:19:30 +05:30

docker-compose.yaml

Update docker compose (#3258 )

2025-08-05 15:40:14 -07:00

Dockerfile

Update docs for running REST API Server (#2241 )

2025-02-21 01:26:57 -08:00

main.py

feat: TS SDK v3 port, graph store removal, client v3 API migration

2026-04-13 10:45:40 -07:00

Makefile

Update docs for running REST API Server (#2241 )

2025-02-21 01:26:57 -08:00

README.md

Update docs for running REST API Server (#2241 )

2025-02-21 01:26:57 -08:00

requirements.txt

fix(server): add missing psycopg-pool dependency (#4374 )

2026-04-03 20:04:05 +05:30

README.md

Mem0 REST API Server

Mem0 provides a REST API server (written using FastAPI). Users can perform all operations through REST endpoints. The API also includes OpenAPI documentation, accessible at /docs when the server is running.

Features

Create memories: Create memories based on messages for a user, agent, or run.
Retrieve memories: Get all memories for a given user, agent, or run.
Search memories: Search stored memories based on a query.
Update memories: Update an existing memory.
Delete memories: Delete a specific memory or all memories for a user, agent, or run.
Reset memories: Reset all memories for a user, agent, or run.
OpenAPI Documentation: Accessible via /docs endpoint.

Running the server

Follow the instructions in the docs to run the server.