Files
mem0/pyproject.toml
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

163 lines
2.8 KiB
TOML

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "mem0ai"
version = "1.0.11"
description = "Long-term memory for AI Agents"
authors = [
{ name = "Mem0", email = "support@mem0.ai" }
]
readme = "README.md"
license = "Apache-2.0"
license-files = ["LICENSE"]
requires-python = ">=3.9,<4.0"
dependencies = [
"qdrant-client>=1.12.0",
"pydantic>=2.7.3",
"openai>=1.90.0",
"posthog>=4.5.0",
"pytz>=2024.1",
"sqlalchemy>=2.0.31",
"protobuf>=5.29.6,<7.0.0",
]
[project.optional-dependencies]
nlp = [
"spacy>=3.7.0",
]
vector_stores = [
"vecs>=0.4.0",
"chromadb>=0.4.24",
"cassandra-driver>=3.29.0",
"weaviate-client>=4.4.0,<4.15.0",
"pinecone<=7.3.0",
"pinecone-text>=0.10.0",
"faiss-cpu>=1.7.4",
"upstash-vector>=0.6.0",
"azure-search-documents>=11.4.0b8",
"psycopg>=3.2.8",
"psycopg-pool>=3.2.6,<4.0.0",
"pymongo>=4.13.2",
"pymochow>=2.2.9",
"pymysql>=1.1.0",
"dbutils>=3.0.3",
"valkey>=6.0.0",
"databricks-sdk>=0.63.0",
"azure-identity>=1.24.0",
"redis>=5.0.0,<6.0.0",
"redisvl>=0.1.0,<1.0.0",
"elasticsearch>=8.0.0,<9.0.0",
"pymilvus>=2.4.0,<2.6.0",
"langchain-aws>=0.2.23",
]
llms = [
"groq>=0.3.0",
"together>=0.2.10",
"litellm>=1.74.0",
"openai>=1.90.0",
"ollama>=0.3.0",
"vertexai>=0.1.0",
"google-generativeai>=0.3.0",
"google-genai>=1.0.0",
]
extras = [
"boto3>=1.34.0",
"langchain-community>=0.0.0",
"sentence-transformers>=5.0.0",
"elasticsearch>=8.0.0,<9.0.0",
"opensearch-py>=2.0.0",
"fastembed>=0.3.1",
]
test = [
"pytest>=8.2.2",
"pytest-mock>=3.14.0",
"pytest-asyncio>=0.23.7",
]
dev = [
"ruff>=0.6.5",
"isort>=5.13.2",
"pytest>=8.2.2",
]
[tool.pytest.ini_options]
pythonpath = ["."]
[tool.hatch.build]
include = [
"mem0/**/*.py",
]
exclude = [
"**/*",
"!mem0/**/*.py",
]
[tool.hatch.build.targets.wheel]
packages = ["mem0"]
only-include = ["mem0"]
[tool.hatch.envs.dev_py_3_9]
python = "3.9"
features = [
"test",
"vector_stores",
"llms",
"extras",
]
[tool.hatch.envs.dev_py_3_10]
python = "3.10"
features = [
"test",
"vector_stores",
"llms",
"extras",
]
[tool.hatch.envs.dev_py_3_11]
python = "3.11"
features = [
"test",
"vector_stores",
"llms",
"extras",
]
[tool.hatch.envs.dev_py_3_12]
python = "3.12"
features = [
"test",
"vector_stores",
"llms",
"extras",
]
[tool.hatch.envs.default.scripts]
format = [
"ruff format",
]
format-check = [
"ruff format --check",
]
lint = [
"ruff check",
]
lint-fix = [
"ruff check --fix",
]
test = [
"pytest tests/ {args}",
]
[tool.ruff]
line-length = 120
exclude = ["embedchain/", "openmemory/"]
[tool.ruff.lint.isort]
known-first-party = ["mem0", "mem0_cli"]
[tool.isort]
profile = "black"
known_first_party = ["mem0", "mem0_cli"]