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Mem0 Python SDK (v2.0.12)

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@whysosaket whysosaket released this 13 Jul 16:49
v2.0.12
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Mem0 Python SDK (v2.0.12)

New Features:

  • Memory (OSS): Accept text in Memory.update() and AsyncMemory.update(). data still works but is now deprecated, so prefer text in new code (#6044)

Bug Fixes:

  • Core: Coerce non-string entity IDs (user_id, agent_id, run_id) instead of crashing on .strip(), so passing an integer ID no longer raises AttributeError (#6206)
  • Core: Stop requiring langchain-core for the default async procedural memory path. The optional dependency is now only imported when you pass a custom LangChain LLM, matching the sync behavior (#6209)
  • Client: Encode dynamic URL path segments so IDs containing special characters no longer produce malformed requests (#5963)
  • LLMs: Skip temperature and top_p for newer Anthropic models that reject sampling parameters. Detection is automatic per model family and version, and the new enable_sampling_parameters config flag overrides it (#6211)
  • Vector Stores: Stop writing internal OutputData model fields as properties on Weaviate update() (#6149)
  • Vector Stores: Improve wildcard search handling in Milvus (#6187)
  • Vector Stores: Keep env-resolved Upstash Vector credentials after config validation. An env-var-only config previously passed validation and then failed to build (#5811)
  • Vector Stores: Restore the previous payload when a Neptune Analytics vector upsert fails inside update(), so a partial write can no longer leave the payload and embedding out of sync (#5824)

Changes:

  • LLMs: The Together default model is now MiniMaxAI/MiniMax-M3 (was mistralai/Mixtral-8x7B-Instruct-v0.1) (#6049)
  • LLMs: The xAI default model is now grok-4.3 (was grok-2-latest) (#6115)
  • Embeddings: The Together default embedding model is now intfloat/multilingual-e5-large-instruct at 1024 dimensions (was togethercomputer/m2-bert-80M-8k-retrieval at 768). If you use the Together embedder without pinning model, existing vectors were written at the old dimension: either re-embed them, or pin model and embedding_dims to the old values (#5989)
  • Rerankers: The Cohere default rerank model is now rerank-v3.5 (was rerank-english-v3.0) (#6055)

Security:

  • Vector Stores: Fix SQL and Cypher injection vulnerabilities in the PGVector, Azure MySQL, and Neptune providers (#4878)
  • Vector Stores: Validate Elasticsearch filter keys and values to prevent term query injection (#5980)
  • Dependencies: Require transformers>=5.3.0 to remediate GHSA-29pf-2h5f-8g72 (CVE-2026-4372) (#6110)
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