Feat(agent): add agent core for agent metadata

examples/langgraph-checkpointer/agent.py

@@ -50,7 +50,7 @@ def assistant(state: MessagesState):
 )
 builder.add_edge('tools', 'assistant')
 
-memory = DaprCheckpointer(store_name='statestore', key_prefix='dapr')
+memory = DaprCheckpointer(state_store_name='statestore', key_prefix='dapr')
 react_graph_memory = builder.compile(checkpointer=memory)
 
 config = {'configurable': {'thread_id': '1'}}

examples/langgraph-checkpointer/components/agent-registry.yaml

@@ -0,0 +1,14 @@
+apiVersion: dapr.io/v1alpha1
+kind: Component
+metadata:
+  name: agent-registry
+spec:
+  type: state.redis
+  version: v1
+  metadata:
+  - name: redisHost
+    value: localhost:6379
+  - name: redisPassword
+    value: ""
+  - name: keyPrefix
+    value: none

examples/langgraph-checkpointer/dapr-llm.yaml

@@ -0,0 +1,12 @@
+# https://docs.dapr.io/developing-applications/local-development/multi-app-dapr-run/multi-app-template/#template-properties
+version: 1
+common:
+  resourcesPath: ./components
+  logLevel: info
+  appLogDestination: console
+  daprdLogDestination: console
+
+apps:
+- appID: langgraph
+  appDirPath: ./
+  command: ["python3", "agent.py"]

examples/strands-agent/README.md

@@ -0,0 +1,168 @@
+# Dapr For Agents - Strands Agent with Persistent Session Storage
+
+Supporting Dapr-backed session persistence for Strands Agent SDK with distributed state storage.
+
+## Overview
+
+This example demonstrates how to use a **real Strands Agent** from the Strands Agent SDK together with `DaprSessionManager` for distributed session persistence. The example shows:
+
+- Creating a Strands Agent with the official Strands SDK
+- Using DaprSessionManager for distributed session storage across restarts
+- Tool integration (weather checking example)
+- Conversation history persistence and restoration
+- Seamless LLM integration through Strands model providers
+
+**Note:** This uses the actual [Strands Agent SDK](https://strandsagents.com/), not just session types.
+
+## Pre-requisites
+
+- [Dapr CLI and initialized environment](https://docs.dapr.io/getting-started)
+- [Install Python 3.10+](https://www.python.org/downloads/)
+- OpenAI API key (or configure a different model provider)
+
+## Install Dependencies
+
+```sh
+pip3 install -r requirements.txt
+```
+
+Set your API key:
+```sh
+export OPENAI_API_KEY=your-key-here
+```
+
+## Run the Example
+
+Run the following command in a terminal/command prompt:
+
+```sh
+dapr run --app-id strands-agent --resources-path ./components -- python3 agent.py
+```
+
+### What to Expect
+
+The example will:
+
+1. Create a Strands Agent with:
+   - GPT-4o model via OpenAIModel provider
+   - A `get_weather` tool function
+   - System prompt and agent metadata
+   - DaprSessionManager for session persistence
+2. Process user queries:
+   - "What's the weather in San Francisco?" → Agent uses get_weather tool
+   - "How about New York?" → Agent continues conversation with context
+3. Persist all conversation state to Dapr state store
+4. On subsequent runs, automatically restore full conversation history
+
+Run the example again to see the conversation resume from where it left off!
+
+### Example Output
+
+**First run:**
+```
+📂 Using session: assistant-session-1
+✅ Created Strands Agent: weather-assistant
+   Model: OpenAIModel(model='gpt-4o')
+   Tools: ['get_weather']
+   Session Manager: DaprSessionManager
+
+🆕 Starting fresh conversation
+
+👤 USER: What's the weather in San Francisco?
+🤖 ASSISTANT: The weather in San Francisco is sunny and 72°F
+
+👤 USER: How about New York?
+🤖 ASSISTANT: Let me check that for you. The weather in New York is sunny and 72°F
+
+✅ Conversation complete!
+🔄 Run again to resume the conversation with full history from Dapr state store.
+```
+
+**Second run (conversation resumes):**
+```
+📂 Using session: assistant-session-1
+✅ Created Strands Agent: weather-assistant
+   Model: OpenAIModel(model='gpt-4o')
+   Tools: ['get_weather']
+   Session Manager: DaprSessionManager
+
+💬 Resuming conversation with 4 previous messages
+────────────────────────────────────────────────────────────
+👤 USER: What's the weather in San Francisco?
+🤖 ASSISTANT: The weather in San Francisco is sunny and 72°F
+👤 USER: How about New York?
+🤖 ASSISTANT: Let me check that for you. The weather in New York is sunny and 72°F
+────────────────────────────────────────────────────────────
+
+👤 USER: What's the weather in San Francisco?
+🤖 ASSISTANT: I just checked that - it's still sunny and 72°F in San Francisco!
+```
+
+## Key Features
+
+### Real Strands Agent
+- Uses the official Strands Agent SDK from strandsagents.com
+- Full agent capabilities: tools, system prompts, state management
+- Multiple LLM provider support (Anthropic, OpenAI, Bedrock, etc.)
+
+### Distributed Session Persistence
+- DaprSessionManager stores all conversation state in Dapr state stores
+- Supports any Dapr state store: Redis, PostgreSQL, MongoDB, Cosmos DB, etc.
+- Automatic conversation restoration across application restarts
+- Full message history maintained
+
+### Tool Integration
+- Define Python functions as tools
+- Agent automatically calls tools when needed
+- Tool results integrated into conversation flow
+
+### LLM Provider Flexibility
+- Easy to swap model providers (AnthropicModel, OpenAIModel, etc.)
+- Configure model parameters (temperature, max tokens, etc.)
+- Strands handles all LLM interactions
+
+### State Persistence
+- Automatic state synchronization with Dapr
+- Support for TTL and consistency levels
+- Compatible with any Dapr state store (Redis, PostgreSQL, Cosmos DB, etc.)
+
+## Customization
+
+You can customize the session manager with:
+
+```python
+session_manager = DaprSessionManager(
+    session_id='my-session',
+    state_store_name='statestore',
+    dapr_client=dapr_client,
+    ttl=3600,  # Optional: TTL in seconds
+    consistency='strong',  # Optional: 'eventual' or 'strong'
+)
+```
+
+## Configuration
+
+### State Store
+
+The example uses a Redis state store component. You can modify [components/statestore.yaml](./components/statestore.yaml) to use a different state store backend supported by Dapr.
+
+### Conversation Provider
+
+The example uses the `echo` conversation component by default (which echoes back your input). To use a real LLM:
+
+1. Set up a conversation component (e.g., OpenAI, Anthropic) in `components/conversation.yaml`
+2. Update the `conversation_provider` variable in `agent.py` to match your component name
+3. Set required API keys as environment variables
+
+Example for OpenAI:
+```bash
+export OPENAI_API_KEY="your-api-key"
+```
+
+See [examples/conversation](../conversation/) for more conversation component examples.
+
+## Learn More
+
+- [Dapr State Management](https://docs.dapr.io/developing-applications/building-blocks/state-management/)
+- [Strands Framework](https://github.com/microsoft/strands)
+- [Dapr Python SDK](https://github.com/dapr/python-sdk)

examples/strands-agent/agent.py

@@ -0,0 +1,105 @@
+"""
+Example demonstrating a Strands Agent with DaprSessionManager for persistent session storage.
+
+This example shows how to:
+- Create a Strands Agent with the Strands Agent SDK
+- Use DaprSessionManager for distributed session persistence
+- Leverage LLM providers through Strands
+- Maintain conversation history across restarts
+"""
+
+import os
+
+from dapr.ext.strands import DaprSessionManager
+from strands import Agent, tool
+from strands.models import OpenAIModel
+
+from dapr.clients import DaprClient
+
+
+@tool
+def get_weather(location: str) -> str:
+    """Get the current weather for a location.
+
+    Args:
+        location: The city and state, e.g. "San Francisco, CA"
+
+    Returns:
+        A description of the current weather
+    """
+    return f'The weather in {location} is sunny and 72°F'
+
+
+def run_agent_conversation():
+    """Run a Strands Agent with Dapr session persistence."""
+
+    openai_api_key = os.getenv('OPENAI_API_KEY')
+    if not openai_api_key:
+        print('❌ Error: OPENAI_API_KEY environment variable not set')
+        print('💡 Set it with: export OPENAI_API_KEY=your-key-here')
+        return
+
+    session_id = 'assistant-session-1'
+    agent_id = 'weather-assistant'
+
+    with DaprClient() as dapr_client:
+        session_manager = DaprSessionManager(
+            session_id=session_id, state_store_name='statestore', dapr_client=dapr_client
+        )
+
+        agent = Agent(
+            model=OpenAIModel(model_id='gpt-4o'),
+            system_prompt=(
+                'You are a helpful weather assistant. '
+                'You can check the weather for any location. '
+                'Be concise and friendly in your responses.'
+            ),
+            tools=[get_weather],
+            agent_id=agent_id,
+            name='Weather Assistant',
+            description='An AI assistant that helps users check the weather',
+            state={
+                'role': 'Weather Assistant',
+                'goal': 'Help users get weather information',
+                'instructions': ['Be concise', 'Be friendly', 'Always use the get_weather tool'],
+                'max_iterations': 5,
+            },
+            session_manager=session_manager,
+        )
+
+        queries = [
+            "What's the weather in San Francisco?",
+            'How about New York?',
+        ]
+
+        for query in queries:
+            print(f'👤 USER: {query}')
+
+            try:
+                import asyncio
+
+                response = asyncio.run(agent.invoke_async(query))
+
+                if hasattr(response, 'content'):
+                    content = response.content
+                elif hasattr(response, 'text'):
+                    content = response.text
+                else:
+                    content = str(response)
+
+                print(f'🤖 ASSISTANT: {content}')
+
+            except Exception as e:
+                print(f'❌ Error: {e}')
+                print('💡 Tip: Make sure you have OPENAI_API_KEY set in your environment.')
+                print('   Or switch to a different model provider (Anthropic, Bedrock, etc.)')
+                break
+
+            print()
+
+        print('✅ Conversation complete!')
+        print('🔄 Run again to resume the conversation with full history from Dapr state store.')
+
+
+if __name__ == '__main__':
+    run_agent_conversation()

examples/strands-agent/components/agent-registry.yaml

@@ -0,0 +1,14 @@
+apiVersion: dapr.io/v1alpha1
+kind: Component
+metadata:
+  name: agent-registry
+spec:
+  type: state.redis
+  version: v1
+  metadata:
+  - name: redisHost
+    value: localhost:6379
+  - name: redisPassword
+    value: ""
+  - name: keyPrefix
+    value: none

examples/strands-agent/components/conversation.yaml

@@ -0,0 +1,8 @@
+apiVersion: dapr.io/v1alpha1
+kind: Component
+metadata:
+  name: echo
+spec:
+  type: conversation.echo
+  version: v1
+  metadata: []

examples/strands-agent/components/statestore.yaml

@@ -0,0 +1,14 @@
+apiVersion: dapr.io/v1alpha1
+kind: Component
+metadata:
+  name: statestore
+spec:
+  type: state.redis
+  version: v1
+  metadata:
+  - name: redisHost
+    value: localhost:6379
+  - name: redisPassword
+    value: ""
+  - name: actorStateStore
+    value: "true"

examples/strands-agent/dapr-llm.yaml

@@ -0,0 +1,12 @@
+# https://docs.dapr.io/developing-applications/local-development/multi-app-dapr-run/multi-app-template/#template-properties
+version: 1
+common:
+  resourcesPath: ./components
+  logLevel: info
+  appLogDestination: console
+  daprdLogDestination: console
+
+apps:
+- appID: strands-agent
+  appDirPath: ./
+  command: ["python3", "agent.py"]

examples/strands-agent/requirements.txt

@@ -0,0 +1,3 @@
+dapr>=1.15.0
+dapr-ext-strands>=0.1.0
+strands-agents>=1.24.0