feat: Add AgentCore Session Manager Documentation

docs/community/session-managers/agentcore-memory.md

@@ -0,0 +1,149 @@
+# AgentCore Memory Session Manager
+
+{{ community_contribution_banner }}
+
+The [AgentCore Memory Session Manager](https://github.com/aws/bedrock-agentcore-sdk-python/tree/main/src/bedrock_agentcore/memory/integrations/strands) leverages Amazon Bedrock AgentCore Memory to provide advanced memory capabilities with intelligent retrieval for Strands Agents. It supports both short-term memory (STM) for conversation persistence and long-term memory (LTM) with multiple strategies for learning user preferences, facts, and session summaries.
+
+## Installation
+
+```bash
+pip install 'bedrock-agentcore[strands-agents]'
+```
+
+## Usage
+
+### Basic Setup (Short-Term Memory)
+
+```python
+from strands import Agent
+from bedrock_agentcore.memory import MemoryClient
+from bedrock_agentcore.memory.integrations.strands.config import AgentCoreMemoryConfig
+from bedrock_agentcore.memory.integrations.strands.session_manager import AgentCoreMemorySessionManager
+from datetime import datetime
+
+# Create a basic memory for short-term functionality
+client = MemoryClient(region_name="us-east-1")
+basic_memory = client.create_memory(
+    name="BasicTestMemory",
+    description="Basic memory for testing short-term functionality"
+)
+
+# Configure memory
+agentcore_memory_config = AgentCoreMemoryConfig(
+    memory_id=basic_memory.get('id'),
+    session_id=f"session_{datetime.now().strftime('%Y%m%d%H%M%S')}",
+    actor_id=f"user_{datetime.now().strftime('%Y%m%d%H%M%S')}"
+)
+
+# Create session manager
+session_manager = AgentCoreMemorySessionManager(
+    agentcore_memory_config=agentcore_memory_config,
+    region_name="us-east-1"
+)
+
+# Create agent
+agent = Agent(
+    system_prompt="You are a helpful assistant. Use all you know about the user to provide helpful responses.",
+    session_manager=session_manager,
+)
+
+# Use the agent - conversations are persisted with intelligent retrieval
+agent("I like sushi with tuna")
+agent("What should I buy for lunch today?")  # Agent remembers preferences
+```
+
+### Advanced Setup (Long-Term Memory)
+
+For more sophisticated memory capabilities, create a memory with multiple strategies:
+
+```python
+from bedrock_agentcore.memory.integrations.strands.config import RetrievalConfig
+
+# Create comprehensive memory with all built-in strategies
+comprehensive_memory = client.create_memory_and_wait(
+    name="ComprehensiveAgentMemory",
+    description="Full-featured memory with all built-in strategies",
+    strategies=[
+        {
+            "summaryMemoryStrategy": {
+                "name": "SessionSummarizer",
+                "namespaces": ["/summaries/{actorId}/{sessionId}"]
+            }
+        },
+        {
+            "userPreferenceMemoryStrategy": {
+                "name": "PreferenceLearner",
+                "namespaces": ["/preferences/{actorId}"]
+            }
+        },
+        {
+            "semanticMemoryStrategy": {
+                "name": "FactExtractor",
+                "namespaces": ["/facts/{actorId}"]
+            }
+        }
+    ]
+)
+
+# Configure with multiple namespace retrieval
+config = AgentCoreMemoryConfig(
+    memory_id=comprehensive_memory.get('id'),
+    session_id=f"session_{datetime.now().strftime('%Y%m%d%H%M%S')}",
+    actor_id=f"user_{datetime.now().strftime('%Y%m%d%H%M%S')}",
+    retrieval_config={
+        "/preferences/{actorId}": RetrievalConfig(
+            top_k=5,
+            relevance_score=0.7
+        ),
+        "/facts/{actorId}": RetrievalConfig(
+            top_k=10,
+            relevance_score=0.3
+        ),
+        "/summaries/{actorId}/{sessionId}": RetrievalConfig(
+            top_k=5,
+            relevance_score=0.5
+        )
+    }
+)
+
+session_manager = AgentCoreMemorySessionManager(config, region_name='us-east-1')
+agent = Agent(session_manager=session_manager)
+```
+
+## Configuration
+
+### Memory Strategies
+
+AgentCore Memory supports three built-in strategies:
+
+1. **summaryMemoryStrategy**: Automatically summarizes conversation sessions for efficient context retrieval
+2. **userPreferenceMemoryStrategy**: Learns and stores user preferences across sessions
+3. **semanticMemoryStrategy**: Extracts and stores factual information from conversations
+
+### AgentCoreMemoryConfig Parameters
+
+- `memory_id`: ID of the Bedrock AgentCore Memory resource
+- `session_id`: Unique identifier for the conversation session
+- `actor_id`: Unique identifier for the user/actor
+- `retrieval_config`: Dictionary mapping namespaces to RetrievalConfig objects
+
+### RetrievalConfig Parameters
+
+- `top_k`: Number of top results to retrieve (default: 5)
+- `relevance_score`: Minimum relevance threshold (0.0-1.0)
+
+### Namespace Patterns
+
+- `/preferences/{actorId}`: User-specific preferences across sessions
+- `/facts/{actorId}`: User-specific factual information
+- `/summaries/{actorId}/{sessionId}`: Session-specific conversation summaries
+
+## Important Notes
+
+> **Session Limitations:** Currently, only **one** agent per session is supported when using AgentCoreMemorySessionManager. Creating multiple agents with the same session will show a warning.
+
+## Resources
+
+- **GitHub**: [bedrock-agentcore-sdk-python](https://github.com/aws/bedrock-agentcore-sdk-python/)
+- **Documentation**: [Strands Integration Examples](https://github.com/aws/bedrock-agentcore-sdk-python/tree/main/src/bedrock_agentcore/memory/integrations/strands)
+- **Issues**: Report bugs and feature requests in the [bedrock-agentcore-sdk-python repository](https://github.com/aws/bedrock-agentcore-sdk-python/issues/new/choose)

docs/user-guide/concepts/agents/session-management.md

@@ -209,6 +209,15 @@ The [`SessionMessage`](../../../api-reference/types.md#strands.types.session.Ses
 
 These data models work together to provide a complete representation of an agent's state and conversation history. The session management system handles serialization and deserialization of these models, including special handling for binary data using base64 encoding.
 
+## Third-Party Session Managers
+
+The following third-party session managers extend Strands with additional storage and memory capabilities:
+
+| Session Manager | Provider | Description | Documentation |
+|-----------------|----------|-------------|---------------|
+| AgentCoreMemorySessionManager | Amazon | Advanced memory with intelligent retrieval using Amazon Bedrock AgentCore Memory. Supports both short-term memory (STM) and long-term memory (LTM) with strategies for user preferences, facts, and session summaries. | [View Documentation](../../../community/session-managers/agentcore-memory.md) |
+| **Contribute Your Own** | Community | Have you built a session manager? Share it with the community! | [Learn How](../../../community/community-packages.md) |
+
 ## Custom Session Repositories
 
 For advanced use cases, you can implement your own session storage backend by creating a custom session repository:

mkdocs.yml

@@ -157,6 +157,8 @@ nav:
         - Cohere: community/model-providers/cohere.md
         - CLOVA Studio: community/model-providers/clova-studio.md
         - Fireworks AI: community/model-providers/fireworksai.md
+      - Session Managers:
+          - Amazon AgentCore Memory: community/session-managers/agentcore-memory.md
 
   - Contribute ❤️: https://github.com/strands-agents/sdk-python/blob/main/CONTRIBUTING.md
   - API Reference: