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* Setting up * Readme * Add redis tests path to all-tests * First pass integration * Keep provider convention * First pass integration * add redis integration tests * update README.md * Add basic sample for redis integration * Add partitioning, add partition-aware tests, improve sample script * Fix code quality check * Try to resolve pytest check * Try to identify if pytest is the cause of failed checks * Re-enable tests * Rename redis test file * Removing some tests to narrow down issue * Revert, no difference * Delete temp files * Starting refactor of RedisProvider * Build dynamic schema builder, still need to do dynamic embedding model config * Add scope control * Complete first pass functionality with OpenAI + HF vectors -> Tests, Samples, Demo to follow * Fix code quality * attempt to identify rootcause of failed test * attempt to identify rootcause of failed test * Attempt to resolve code quality fail * Update pyproject.toml for foundry to pin azure-ai-projects == 1.1.0b3,azure-ai-agents == 1.2.0b3 * Add tests for redisprovider * Remove invalid tests * Add API key handling for openai vectorizer * Update uv.locl * Use master uv.lock * Begin sample file, add lazy index creation, fix faulty override * Index drop and reinit depends on drop_redis_index not overwrite * Add samples, threading included, escaped queries, verify threading works, sample README.md * Refactor filters * Opinionated vars * Allow filter expression combination * Try inline stubs for mypy * Address mypy errors * Better docstrings, tweaks for feedback * Tweak example 3 in redis_threads.py sample * adjust confusing name * Enrich docstrings * Add descriptions and comments to samples, externalize vectorizer choice, remove nltk and sentencetransformers dependnecy * Add descriptions and comments to samples, externalize vectorizer choice, remove nltk and sentencetransformers dependnecy * Incorporate initial feedback from dmytrostruk * Fix uv.lock * Attempt to resolve conflict * Use remote .tomls * Sanity check * fix tests * Remove hardcoded API key from samples * Fix incorrect env var * Make add and redis_search private * Fix tests relying on private funcs * Expand tests * Explainer comments to each test * Add a 'get_conversation_history' function to RedisProvider - This just returns messages in sequential order. Added 'created_at_*' timestamps to facilitate sequential recovery. function has to be manually invoked by user * Add agent-framework-redis to python/pyproject.toml * Remove get_conversation_history * improve redis context provider with pydantic techniques and safe index handling patterns * add RedisChatMessageStore * remove integration test :( * fix mypy error * Remove unused params * Redo schema validation to be order-invariant, handle attrs (previously throwing errors due to strict ==) * Expand explanation * Add ChatMessageStore example * Fix comments in redis_conversation.py * Resolving uv.lock conflict, update to match main * Fix test in redis provider * Apply suggestion from @ekzhu * Update python/packages/main/pyproject.toml --------- Co-authored-by: Tyler Hutcherson <tyler.hutcherson@redis.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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Get Started with Microsoft Agent Framework Redis
Please install this package as the extra for agent-framework:
pip install agent-framework[redis]
Components
Memory Context Provider
The RedisProvider enables persistent context & memory capabilities for your agents, allowing them to remember user preferences and conversation context across sessions and threads.
Basic Usage Examples
Review the set of getting started examples for using the Redis context provider.
Redis Chat Message Store
The RedisChatMessageStore provides persistent conversation storage using Redis Lists, enabling chat history to survive application restarts and support distributed applications.
Key Features
- Persistent Storage: Messages survive application restarts
- Thread Isolation: Each conversation thread has its own Redis key
- Message Limits: Configurable automatic trimming of old messages
- Serialization Support: Full compatibility with Agent Framework thread serialization
- Production Ready: Connection pooling, error handling, and performance optimized
Basic Usage Examples
See the complete Redis chat message store examples including:
- User session management
- Conversation persistence across restarts
- Thread serialization and deserialization
- Automatic message trimming
- Error handling patterns
Installing and running Redis
You have 3 options to set-up Redis:
Option A: Local Redis with Docker
docker run --name redis -p 6379:6379 -d redis:8.0.3
Option B: Redis Cloud
Get a free db at https://redis.io/cloud/
Option C: Azure Managed Redis
Here's a quickstart guide to create Azure Managed Redis for as low as $12 monthly: https://learn.microsoft.com/en-us/azure/redis/quickstart-create-managed-redis