# Strands Agent with Bedrock AgentCore Integration | Information | Details | |---------------------|------------------------------------------------------------------------------| | Agent type | Synchronous | | Agentic Framework | Strands | | LLM model | Anthropic Claude 3 Haiku | | Components | AgentCore Runtime | | Example complexity | Easy | | SDK used | Amazon BedrockAgentCore Python SDK | These example demonstrate how to integrate a Strands agents with AWS Bedrock AgentCore, enabling you to deploy your agent as a managed service. You can use the `agentcore` CLI to configure and launch these agents. ## Prerequisites - Python 3.10+ - [uv](https://github.com/astral-sh/uv) - Fast Python package installer and resolver - AWS account with Bedrock Agentcore access ## Setup Instructions ### 1. Create a Python Environment with uv ```bash # Install uv if you don't have it already # Create and activate a virtual environment uv venv source .venv/bin/activate # On Windows: .venv\Scripts\activate ``` ### 2. Install Requirements ```bash uv pip install -r requirements.txt ``` ### 3. Understanding the Agent Code The `strands_agent_file_system.py` file contains a simple Strands agent with file system capabilities, integrated with Bedrock AgentCore: ```python import os os.environ["BYPASS_TOOL_CONSENT"]="true" from strands import Agent from strands_tools import file_read, file_write, editor # Initialize Strands agent with file system tools agent = Agent(tools=[file_read, file_write, editor]) # Integrate with Bedrock AgentCore from bedrock_agentcore.runtime import BedrockAgentCoreApp app = BedrockAgentCoreApp() @app.entrypoint def agent_invocation(payload, context): """Handler for agent invocation""" user_message = payload.get("prompt", "No prompt found in input, please guide customer to create a json payload with prompt key") result = agent(user_message) return {"result": result.message} app.run() ``` ### 4. Configure and Launch with Bedrock AgentCore Toolkit ```bash # Configure your agent for deployment agentcore configure -e strands_agent_file_system.py # Deploy your agent agentcore launch ``` ### 5. Testing Your Agent Once deployed, you can test your agent using: ```bash agentcore invoke '{"prompt":"hello"}' ```