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Releases: redis/agent-memory-server

0.9.1

11 Jul 20:38
@abrookins abrookins
server/0.9.1
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Full Changelog: server/0.9.0...server/0.9.1

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abrookins
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0.9.0

11 Jul 07:11
@abrookins abrookins
server/0.9.0
fa5b0d5
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0.9.0

Memory Evolution

  • Working Memory (formerly Short-term Memory):

    • Renamed from "short-term memory" to "working memory" to better reflect its purpose
    • Enhanced with automatic promotion system that moves structured memories to long-term storage in background
    • Added support for arbitrary JSON data storage alongside memory structures
    • Improved automatic conversation summarization in working memory, based on token limits

  • Long-term Memory Promotion:

    • Implemented seamless flow from working memory to long-term memory via background task processing
    • Agent only has to think about working memory, long-term memory is managed automatically (but can be managed manually, too)
    • Use any LangChain VectorStore subclass for long-term storage, defaults to RedisVectorStore
    • Structured memories are automatically promoted with vector embeddings and metadata indexing
    • Deduplication and compaction systems for long-term memory management
    • Background task worker system using for reliable, scalable memory processing

Client SDK and Tooling

  • Working and long-term memory available as tools for LLM integration (LLM can choose to persist a long-term memory or search for long-term memories, etc.)
  • Higher-level tools support sending in a user's input and getting back a context-enriched prompt, via /v1/memory/prompt endpoint
  • Support for namespace isolation, user separation, and session management

Search and Retrieval

  • Vector-based similarity search using OpenAI embeddings
  • Rich filtering system by session, namespace, topics, entities, timestamps
  • Hybrid search combining semantic similarity with metadata filtering
  • RedisVL integration for high-performance vector operations with Redis

Enhanced Memory Classification:

  • Semantic memories for facts and preferences
  • Episodic memories for time-bound events with event dates (requires a timeframe)
  • Message memories for long-term conversation records (optional)
  • Automatic topic modeling and entity recognition either using BERTopic or a configured LLM
  • Rich metadata extraction and indexing

Authentication and Security

  • OAuth2/JWT Bearer token authentication with JWKS validation
  • Multi-provider support (Auth0, AWS Cognito, Okta, Azure AD)
  • Role-based access control using JWT claims
  • Development mode with configurable auth bypass

Operational Features

  • Comprehensive CLI Interface:
    • Commands for server management (api, mcp, task-worker)
    • Database operations (rebuild-index)
    • Background task scheduling and management
    • Health monitoring and diagnostics
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