bedrock-agentcore-starter-toolkit

import os from bedrock_agentcore.runtime import BedrockAgentCoreApp def my_agent_logic(request): """ Processes an incoming request for the AI agent. """ prompt = request.get("prompt", "Hello from AgentCore!") # Simulate agent processing or integrate with an LLM response_content = f"The agent received your prompt: '{prompt}'." return {"response": response_content} app = BedrockAgentCoreApp() @app.entrypoint def production_agent(request): """ The entrypoint function for the Bedrock AgentCore Runtime. This function wraps your core agent logic. """ return my_agent_logic(request) if __name__ == "__main__": # This block allows local testing of the agent logic. # For deployment, the `agentcore` CLI interacts with this file. print("Starting local AgentCore development server...") print("Access at http://localhost:8080/invocations") app.run() # To deploy and invoke via the CLI, run these commands in your terminal: # 1. Save the above Python code to a file, e.g., `my_agent.py`. # 2. Configure your agent: `agentcore configure --entrypoint my_agent.py --name my-bedrock-agent --region us-east-1` # (Ensure AWS credentials are configured, e.g., via `aws configure`) # 3. Launch the agent: `agentcore launch` # 4. Invoke the deployed agent: `agentcore invoke '{"prompt": "Tell me a fun fact about Python."}'`