v2.0.11

mem0ai/mem0v2.0.11Jul 1, 2026by whysosaket

AI Summary

Python SDK release fixing embedding batch mismatches and adding security hardening for vector stores.

Key Highlights

Fixed OpenAI and Azure OpenAI embedder batch count mismatch
Fixed silent LLM extraction failures by re-raising them
Fixed SQL injection vulnerabilities in PGVector, Azure MySQL, and Databricks
Added filter validation for OpenSearch and Azure AI Search

Full Release Notes

## Mem0 Python SDK (v2.0.11)

**Bug Fixes:**
- **Embeddings:** Guard against an `embed_batch` count mismatch in the OpenAI and Azure OpenAI embedders ([#5966](https://github.com/mem0ai/mem0/pull/5966))
- **Memory:** Re-raise LLM extraction failures instead of silently returning `[]` ([#5878](https://github.com/mem0ai/mem0/pull/5878))
- **Vector Stores:** Normalize vectors for the cosine distance strategy in FAISS ([#5960](https://github.com/mem0ai/mem0/pull/5960))

**Security:**
- **Vector Stores:** Validate OpenSearch filter values to prevent term query injection ([#5986](https://github.com/mem0ai/mem0/pull/5986))
- **Vector Stores:** Validate value types and escape quotes in Azure AI Search OData filters ([#5983](https://github.com/mem0ai/mem0/pull/5983))
- **Vector Stores:** Validate Databricks catalog/schema/table identifiers to prevent SQL injection ([#5988](https://github.com/mem0ai/mem0/pull/5988))
- **Graph:** Escape Neptune filter values in openCypher queries to prevent injection ([#5982](https://github.com/mem0ai/mem0/pull/5982))