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v2.0.14 Feature

This release adds 1 notable feature for engineering teams evaluating rollout.

✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Topics

agents ai ai-agents application chatbots chatgpt
+7 more
genai llm long-term-memory memory memory-management python state-management

Summary

AI summary

Adds Oracle AI Vector Search provider with connection pooling and multiple index options.

Full changelog

New Features:

  • Vector Stores: Add an Oracle AI Vector Search provider (oracledb) with connection pooling, HNSW/IVF indexes, JSON metadata filtering, and six selectable distance metrics (#5358)

Bug Fixes:

  • Vector Stores: Translate a "*" filter value in OpenSearch into an exists query for every key, not just identity keys. It was previously ignored or matched literally against the string "*", so a wildcard filter returned nothing (#6522)
  • Vector Stores: Re-raise errors from OpenSearch search() instead of returning [], so a transport, auth, or index misconfiguration surfaces instead of looking like zero matches. keyword_search() still degrades on failure, since it is a best-effort BM25 signal (#6519)
  • Vector Stores: Guard the text field in Milvus update() behind the _has_bm25_schema check, matching insert(), so updating a memory in a collection without the BM25 text/sparse schema no longer fails (#5705)

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Universal memory layer for AI Agents

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Beta — feedback welcome: [email protected]