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ts-v3.1.0

mem0ai/mem0ts-v3.1.0Jul 13, 2026by whysosaket

AI Summary

Major Node SDK release introducing extensive provider support and lazy-loading to optimize bundle size.

Key Highlights

  • Massive provider expansion: 17 new vector stores, 5 new LLMs, 4 new embedders, and reranking support
  • Implemented lazy-loading for providers to reduce bundle size
  • Introduced `text` parameter support in Memory.update()
  • Added new LLM providers including AWS Bedrock and xAI

New Features

  • Rerankers support (Cohere, ZeroEntropy, cross-encoder, LLM-based)
  • New Vector Stores (Pinecone, Weaviate, Milvus, Chroma, MongoDB, Elasticsearch, OpenSearch, Databricks, Neptune, S3, Azure MySQL, Vertex AI, Turbopuffer, Upstash, Valkey, Cassandra, Baidu Mochow)
  • New LLMs (AWS Bedrock, xAI, Together, vLLM, Sarvam)
  • New Embeddings (Vertex AI, HuggingFace, FastEmbed, Together)
  • Accept `text` parameter in Memory.update()

Full Release Notes

## Mem0 Node SDK (v3.1.0)

The largest provider release for the TypeScript OSS SDK so far: 17 new vector stores, 5 new LLM providers, 4 new embedders, and reranking support. Importing `mem0ai/oss` no longer pulls in any provider SDK, so you only install what you actually configure.

**New Features:**
- **Rerankers:** Add reranking to the OSS SDK with four providers (Cohere, ZeroEntropy, cross-encoder, and LLM-based), plus per-search rerank via a `rerank` option on `search()` ([#6055](https://github.com/mem0ai/mem0/pull/6055))
- **Memory (OSS):** Accept `text` in `Memory.update()`. `data` still works but is now deprecated, so prefer `text` in new code ([#6044](https://github.com/mem0ai/mem0/pull/6044))
- **Vector Stores:** Add Pinecone ([#5802](https://github.com/mem0ai/mem0/pull/5802)), Weaviate ([#5800](https://github.com/mem0ai/mem0/pull/5800)), Milvus ([#5889](https://github.com/mem0ai/mem0/pull/5889)), Chroma ([#6145](https://github.com/mem0ai/mem0/pull/6145)), MongoDB ([#5793](https://github.com/mem0ai/mem0/pull/5793)), Elasticsearch ([#5866](https://github.com/mem0ai/mem0/pull/5866)), and OpenSearch ([#5810](https://github.com/mem0ai/mem0/pull/5810))
- **Vector Stores:** Add Databricks ([#5824](https://github.com/mem0ai/mem0/pull/5824)), AWS Neptune Analytics ([#5797](https://github.com/mem0ai/mem0/pull/5797)), S3 Vectors ([#5822](https://github.com/mem0ai/mem0/pull/5822)), Azure MySQL ([#5827](https://github.com/mem0ai/mem0/pull/5827)), and Google Vertex AI Vector Search ([#5791](https://github.com/mem0ai/mem0/pull/5791))
- **Vector Stores:** Add Turbopuffer ([#5801](https://github.com/mem0ai/mem0/pull/5801)), Upstash Vector ([#5811](https://github.com/mem0ai/mem0/pull/5811)), Valkey ([#5826](https://github.com/mem0ai/mem0/pull/5826)), Cassandra ([#5823](https://github.com/mem0ai/mem0/pull/5823)), and Baidu Mochow ([#5790](https://github.com/mem0ai/mem0/pull/5790))
- **LLMs:** Add AWS Bedrock ([#5890](https://github.com/mem0ai/mem0/pull/5890)), xAI Grok ([#6115](https://github.com/mem0ai/mem0/pull/6115)), Together ([#6049](https://github.com/mem0ai/mem0/pull/6049)), vLLM ([#5805](https://github.com/mem0ai/mem0/pull/5805)), and Sarvam ([#6130](https://github.com/mem0ai/mem0/pull/6130))
- **Embeddings:** Add Vertex AI ([#5882](https://github.com/mem0ai/mem0/pull/5882)), HuggingFace ([#6027](https://github.com/mem0ai/mem0/pull/6027)), FastEmbed ([#5862](https://github.com/mem0ai/mem0/pull/5862)), and Together ([#5989](https://github.com/mem0ai/mem0/pull/5989))

**Improvements:**
- **Packaging:** Lazy-load optional provider SDKs so importing `mem0ai/oss` never requires them. Provider packages are now resolved on first use, so an app that only configures OpenAI and Qdrant does not need the other provider SDKs installed ([#6280](https://github.com/mem0ai/mem0/pull/6280))

**Bug Fixes:**
- **Memory (OSS):** Re-raise LLM extraction transport failures instead of returning `[]`, so a network error during extraction surfaces as an error rather than a silently empty result ([#6102](https://github.com/mem0ai/mem0/pull/6102))
- **Vector Stores:** Prevent an unhandled promise rejection in the Supabase and Redis constructors ([#6111](https://github.com/mem0ai/mem0/pull/6111))
- **Client:** Encode dynamic URL path segments so IDs containing special characters no longer produce malformed requests ([#5963](https://github.com/mem0ai/mem0/pull/5963))

**Security:**
- **Dependencies:** Patch the `fast-xml-parser` and `tar` transitive CVEs ([#6160](https://github.com/mem0ai/mem0/pull/6160))