agent-framework-orchestrations

import asyncio import os from dotenv import load_dotenv from agent_framework import Agent from agent_framework.foundry import FoundryChatClient from agent_framework.orchestrations import SequentialBuilder from azure.identity import AzureCliCredential load_dotenv() # Load environment variables from .env file async def main(): # Ensure environment variables are set for FoundryChatClient foundry_endpoint = os.environ.get("FOUNDRY_PROJECT_ENDPOINT", "") model_deployment_name = os.environ.get("AZURE_AI_MODEL_DEPLOYMENT_NAME", "") if not foundry_endpoint or not model_deployment_name: print("Please set FOUNDRY_PROJECT_ENDPOINT and AZURE_AI_MODEL_DEPLOYMENT_NAME environment variables.") print("Also ensure you are authenticated via 'az login' if using AzureCliCredential.") return # 1) Create a chat client (e.g., FoundryChatClient for Azure AI Foundry) try: client = FoundryChatClient( project_endpoint=foundry_endpoint, model=model_deployment_name, credential=AzureCliCredential(), ) except Exception as e: print(f"Failed to create FoundryChatClient: {e}") print("Ensure 'az login' is performed and environment variables are correctly configured.") return # 2) Define your agents writer = Agent( client=client, instructions="You are a concise copywriter. Provide a single, punchy marketing sentence based on the prompt.", name="writer", ) reviewer = Agent( client=client, instructions="You are a thoughtful reviewer. Give brief feedback on the previous assistant message.", name="reviewer", ) # 3) Build a sequential workflow (writer -> reviewer) workflow = SequentialBuilder(participants=[writer, reviewer]).build() # 4) Run the workflow print("\n--- Running Sequential Workflow ---") async for event in workflow.run_stream("Write a tagline for a budget-friendly eBike."): if event.type == "output": print("\nFinal Conversation History:") for message in event.data: print(f" {message.role.capitalize()}: {message.content}") if __name__ == "__main__": asyncio.run(main())