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62 changes: 62 additions & 0 deletions CHANGELOG.md
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# Changelog

All notable changes to this project will be documented in this file.

The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

## [0.9.0] - 2025-07-11

*Changes from the initial release:*

### Architecture 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


## [0.0.1]

### Initial Release - 2025-04-07
- Initial release with basic short-term and long-term memory functionality
2 changes: 1 addition & 1 deletion agent-memory-client/agent_memory_client/__init__.py
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memory management capabilities for AI agents and applications.
"""

__version__ = "0.9.0b7"
__version__ = "0.9.0"

from .client import MemoryAPIClient, MemoryClientConfig, create_memory_client
from .exceptions import (
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2 changes: 1 addition & 1 deletion agent_memory_server/__init__.py
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"""Redis Agent Memory Server - A memory system for conversational AI."""

__version__ = "0.9.0b7"
__version__ = "0.9.0"