Merge pull request #22 from redis/feature/write-a-new

Write a changelog for 0.9 release

Author: abrookins

CHANGELOG.md

@@ -0,0 +1,62 @@
+# 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

agent-memory-client/agent_memory_client/__init__.py

@@ -5,7 +5,7 @@
 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 (

agent_memory_server/__init__.py

@@ -1,3 +1,3 @@
 """Redis Agent Memory Server - A memory system for conversational AI."""
 
-__version__ = "0.9.0b7"
+__version__ = "0.9.0"