Release notes from mem0
Articles about Release notes from mem0
Mem0 Node SDK (v3.3.1)
Bug Fixes: Config (OSS): ConfigManager no longer injects OpenAI's default baseURL and model into non-OpenAI LLM providers. The defaults now apply only to openai and openai_structured, so a DeepSeek, xAI, or other provider config without an explicit baseURL or model falls back to that provider's own defaults and env vars (DEEPSEEK_API_BASE, XAI_API_BASE, ...) instead of pointing at OpenAI with an OpenAI model name (#7350) Vector Stores: Turbopuffer filters now apply every operator (eq, ne, gt, gte, lt, lte, in, nin).
Mem0 Python SDK (v2.2.1)
Bug Fixes: Core: add() (Memory and AsyncMemory) no longer reports records the vector store rejected as successful ADD events. Only records that were actually inserted are written to history, entity-linked, and returned. If none of the extracted memories could be inserted, add() now raises VectorStoreError instead of returning memories that were never stored (#7066) Core: Restore the context-manager protocol on Memory (with Memory() as m:) and AsyncMemory (async with AsyncMemory() as m:), which closes the instance on exit (#7354)
Mem0 DeepSeek Plugin (v0.3.2)
Improvements: Search: The search_memory tool description no longer asks the agent to search proactively before answering anything that may depend on earlier context. It now asks for a search before repeating investigation or when earlier decisions, fixes, commands, or results may help (#7420) Automatic recall: Injected memories are introduced as "Mem0 found these relevant memories from earlier work:". The old heading called them a shallow first pass and told the agent to search again with mem0_memory, a tool DeepSeek does not have (#7420)
Mem0 Pi Agent Plugin (v0.3.2)
Improvements: Search: The memory policy, mem0_memory tool description, and prompt guidelines no longer ask the agent to search before answering anything that may depend on earlier context or to run several searches per question. They now ask for a search before repeating investigation or when earlier decisions, fixes, commands, or results may help (#7420) Skills: context-loader makes one search instead of 2-4 parallel searches, and uses the search skill description from the other coding-agent plugins (#7420)
Mem0 OpenClaw Plugin (v1.2.1)
Improvements: Search: The memory_search tool description no longer asks the agent to search proactively or to run several searches for multi-part questions. It now asks for a search before repeating investigation or when earlier decisions, fixes, commands, or results may help. Recall strategies (smart, always, manual) are unchanged (#7420)
Mem0 OpenCode Plugin (v0.4.1)
Improvements: Search: The search_memories tool description no longer asks the agent to search proactively or to run several searches for multi-part questions. It now asks for a search before repeating investigation or when earlier decisions, fixes, commands, or results may help, the same wording as the other coding-agent plugins (#7420) Session context: Removed two system-context lines that told the agent to run 2 parallel searches before responding and 2-4 parallel searches for non-trivial tasks (#7420)
Mem0 Node SDK (v3.3.0)
New Features: Client: Add User Profiles to MemoryClient: getProfile(), generateProfile(), getProfileSettings(), updateProfileSettings(), sampleProfiles(), and getProfileJob(). A profile is a structured, always-current JSON summary of one user, shaped by a JSON Schema you configure per project and filled by an LLM from that user's memories. Generation is asynchronous. Every job POST carries an Idempotency-Key; to retry a lost request without starting a second job, pass the same idempotencyKey on each attempt (#7340)
Mem0 Python SDK (v2.2.0)
New Features: Client: Add User Profiles to MemoryClient and AsyncMemoryClient: get_profile(), generate_profile(), get_profile_settings(), update_profile_settings(), sample_profiles(), and get_profile_job(). A profile is a structured, always-current JSON summary of one user, shaped by a JSON Schema you configure per project and filled by an LLM from that user's memories. Generation is asynchronous. Every job POST carries an Idempotency-Key;
Vercel AI SDK Provider (v3.0.3)
Improvements: Client: Inherits the three surface-identity headers (X-Mem0-Source, X-Application, X-Mem0-Client) from the TypeScript SDK bump, so platform calls made through the Vercel AI SDK provider are now correctly attributed (#7326)
Mem0 Python SDK (v2.1.0)
Improvements: Client: Requests now carry three surface-identity headers so the platform can tell which product made a call. X-Mem0-Source names the surface and X-Application the host app it runs inside, both set-once so a wrapper that already declared its identity keeps it. X-Mem0-Client is append-only and carries name/version per layer, outermost first, so a plugin calling this SDK reports the whole chain rather than only the last speaker.