base work

.gitignore

@@ -207,6 +207,7 @@ temp*/
 
 # AI
 .claude/
+.kiro/
 .omc/
 .omx/
 WARP.md

python/AGENTS.md

@@ -82,6 +82,7 @@ python/
 ### Storage & Memory
 - [mem0](packages/mem0/AGENTS.md) - Mem0 memory integration
 - [redis](packages/redis/AGENTS.md) - Redis storage
+- [valkey](packages/valkey/AGENTS.md) - Valkey storage and vector search
 
 ### Infrastructure
 - [copilotstudio](packages/copilotstudio/AGENTS.md) - Microsoft Copilot Studio

python/PACKAGE_STATUS.md

@@ -41,6 +41,7 @@ Status is grouped into these buckets:
 | `agent-framework-orchestrations` | `python/packages/orchestrations` | `beta` |
 | `agent-framework-purview` | `python/packages/purview` | `beta` |
 | `agent-framework-redis` | `python/packages/redis` | `beta` |
+| `agent-framework-valkey` | `python/packages/valkey` | `alpha` |
 
 ## Deprecated / removed packages
 

python/packages/valkey/AGENTS.md

@@ -0,0 +1,23 @@
+# Valkey Package (agent-framework-valkey)
+
+Valkey-based storage for agent conversations and context.
+
+## Main Classes
+
+- **`ValkeyChatMessageStore`** - Persistent chat history provider using Valkey
+- **`ValkeyContextProvider`** - Context provider with Valkey-backed vector search retrieval
+
+## Usage
+
+```python
+from agent_framework_valkey import ValkeyContextProvider, ValkeyChatMessageStore
+
+context_provider = ValkeyContextProvider(host="localhost", port=6379, user_id="u1")
+message_store = ValkeyChatMessageStore(host="localhost", port=6379)
+```
+
+## Import Path
+
+```python
+from agent_framework_valkey import ValkeyContextProvider, ValkeyChatMessageStore
+```

python/packages/valkey/LICENSE

@@ -0,0 +1,21 @@
+    MIT License
+
+    Copyright (c) Microsoft Corporation.
+
+    Permission is hereby granted, free of charge, to any person obtaining a copy
+    of this software and associated documentation files (the "Software"), to deal
+    in the Software without restriction, including without limitation the rights
+    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+    copies of the Software, and to permit persons to whom the Software is
+    furnished to do so, subject to the following conditions:
+
+    The above copyright notice and this permission notice shall be included in all
+    copies or substantial portions of the Software.
+
+    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+    SOFTWARE

python/packages/valkey/README.md

@@ -0,0 +1,115 @@
+# Get Started with Microsoft Agent Framework Valkey
+
+Please install this package via pip:
+
+```bash
+pip install agent-framework-valkey --pre
+```
+
+## Server Requirements
+
+The `ValkeyChatMessageStore` works with any Valkey (or Redis OSS) server — it only uses basic key-value operations.
+
+The `ValkeyContextProvider` requires the **valkey-search** module (>= 1.2) for its `FT.CREATE` / `FT.SEARCH` commands. This module ships with **valkey-bundle >= 9.1.0** and is also available in managed cloud offerings (AWS ElastiCache for Valkey, GCP Memorystore for Valkey).
+
+For local development and testing, use `valkey-bundle 9.1.0-rc1`:
+
+```bash
+docker run -d --name valkey -p 6379:6379 valkey/valkey-bundle:9.1.0-rc1
+```
+
+## Components
+
+### Valkey Context Provider
+
+The `ValkeyContextProvider` enables persistent context and memory capabilities for your agents,
+allowing them to remember user preferences and conversation context across sessions and threads.
+It uses Valkey's native vector search capabilities (`FT.CREATE` / `FT.SEARCH`) for semantic
+retrieval of past conversation context.
+
+#### Basic Usage
+
+```python
+from agent_framework_valkey import ValkeyContextProvider
+
+# Text-only search (no embeddings required)
+context_provider = ValkeyContextProvider(
+    host="localhost",
+    port=6379,
+    user_id="user-123",
+)
+
+# With vector search (requires an embedding function)
+async def my_embed_fn(text: str) -> list[float]:
+    # Your embedding logic here
+    ...
+
+context_provider = ValkeyContextProvider(
+    host="localhost",
+    port=6379,
+    user_id="user-123",
+    embed_fn=my_embed_fn,
+    vector_field_name="embedding",
+    vector_dims=1536,
+)
+```
+
+### Valkey Chat Message Store
+
+The `ValkeyChatMessageStore` provides persistent conversation storage using Valkey Lists,
+enabling chat history to survive application restarts and support distributed applications.
+
+#### Key Features
+
+- **Persistent Storage**: Messages survive application restarts
+- **Session Isolation**: Each conversation session has its own Valkey key
+- **Message Limits**: Configurable automatic trimming of old messages
+- **Lightweight**: Uses only basic Valkey key-value operations (no search module required)
+- **valkey-glide**: Built on the official Valkey Python client
+
+#### Basic Usage
+
+```python
+from agent_framework_valkey import ValkeyChatMessageStore
+
+store = ValkeyChatMessageStore(
+    host="localhost",
+    port=6379,
+    max_messages=100,
+)
+```
+
+## Installing and Running Valkey
+
+### Option A: Local Valkey with Docker
+
+For basic chat history storage (no search needed):
+
+```bash
+docker run --name valkey -p 6379:6379 -d valkey/valkey:8.1
+```
+
+For full functionality including the `ValkeyContextProvider` (requires valkey-search):
+
+```bash
+docker run --name valkey -p 6379:6379 -d valkey/valkey-bundle:9.1.0-rc1
+```
+
+### Option B: AWS ElastiCache for Valkey
+
+Create a serverless or node-based [ElastiCache for Valkey](https://docs.aws.amazon.com/AmazonElastiCache/latest/dg/WhatIs.html) cluster.
+
+### Option C: Google Cloud Memorystore for Valkey
+
+Create a [Memorystore for Valkey](https://cloud.google.com/memorystore/docs/valkey) instance.
+
+## Why Valkey?
+
+Valkey is an open-source, Linux Foundation project that is protocol-compatible with Redis
+for core operations. It provides:
+
+- **Open governance**: Community-driven development under the Linux Foundation
+- **Performance**: Single-digit millisecond latency with high recall for vector search
+- **Scaling**: Linear scaling with cluster mode support
+- **Cloud support**: Managed services from AWS, GCP, and other providers
+- **Migration path**: Drop-in replacement for Redis deployments

python/packages/valkey/agent_framework_valkey/__init__.py

@@ -0,0 +1,27 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Valkey integration for Microsoft Agent Framework.
+
+This module re-exports objects from:
+- agent-framework-valkey
+
+Supported classes:
+- ValkeyContextProvider
+- ValkeyChatMessageStore
+"""
+
+import importlib.metadata
+
+from ._chat_message_store import ValkeyChatMessageStore
+from ._context_provider import ValkeyContextProvider
+
+try:
+    __version__ = importlib.metadata.version(__name__)
+except importlib.metadata.PackageNotFoundError:
+    __version__ = "0.0.0"  # Fallback for development mode
+
+__all__ = [
+    "ValkeyChatMessageStore",
+    "ValkeyContextProvider",
+    "__version__",
+]