agent-framework

import asyncio import os from agent_framework.azure import AzureOpenAIResponsesClient from azure.identity import AzureCliCredential # from dotenv import load_dotenv # Uncomment and install if using .env file locally async def main(): # Load environment variables from .env file if uncommented above # load_dotenv() # Ensure AZURE_AI_PROJECT_ENDPOINT and AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME are set # and you are authenticated via Azure CLI (e.g., `az login`) project_endpoint = os.environ.get("AZURE_AI_PROJECT_ENDPOINT", "https://your-project.services.ai.azure.com") deployment_name = os.environ.get("AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME", "gpt-4o") if not all([project_endpoint, deployment_name]): print("Please set AZURE_AI_PROJECT_ENDPOINT and AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME environment variables.") print("Ensure you have authenticated via Azure CLI (`az login`).") return # Create an Azure CLI credential for authentication credential = AzureCliCredential() # Initialize the Azure OpenAI Responses client client = AzureOpenAIResponsesClient( project_endpoint=project_endpoint, deployment_name=deployment_name, credential=credential, ) # Create an agent with instructions agent = client.as_agent( name="HelloAgent", instructions="You are a friendly assistant. Keep your answers brief.", ) # Run the agent print("Agent: Thinking...") result = await agent.run("What is the capital of France?") print(f"Agent: {result}") # Example of streaming response (optional) # print("\nAgent (streaming): Thinking...") # async for token in agent.run("Tell me a short story about a brave knight.", stream=True): # print(token, end="", flush=True) # print() if __name__ == "__main__": asyncio.run(main())