chore: import upstream snapshot with attribution

python/samples/03-workflows/declarative/student_teacher/main.py

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+# Copyright (c) Microsoft. All rights reserved.
+
+"""
+Run the student-teacher (MathChat) workflow sample.
+
+Usage:
+    python main.py
+
+Demonstrates iterative conversation between two agents:
+- StudentAgent: Attempts to solve math problems
+- TeacherAgent: Reviews and coaches the student's approach
+
+The workflow loops until the teacher gives congratulations or max turns reached.
+
+Prerequisites:
+    - Azure OpenAI deployment with chat completion capability
+    - Environment variables:
+        FOUNDRY_PROJECT_ENDPOINT: Your Azure AI Foundry Agent Service (V2) project endpoint
+        FOUNDRY_MODEL: Your model deployment name
+"""
+
+import asyncio
+import os
+from pathlib import Path
+
+from agent_framework import Agent
+from agent_framework.declarative import WorkflowFactory
+from agent_framework.foundry import FoundryChatClient
+from azure.identity import AzureCliCredential
+from dotenv.main import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+
+STUDENT_INSTRUCTIONS = """You are a curious math student working on understanding mathematical concepts.
+When given a problem:
+1. Think through it step by step
+2. Make reasonable attempts, but it's okay to make mistakes
+3. Show your work and reasoning
+4. Ask clarifying questions when confused
+5. Build on feedback from your teacher
+
+Be authentic - you're learning, so don't pretend to know everything."""
+
+TEACHER_INSTRUCTIONS = """You are a patient math teacher helping a student understand concepts.
+When reviewing student work:
+1. Acknowledge what they did correctly
+2. Gently point out errors without giving away the answer
+3. Ask guiding questions to help them discover mistakes
+4. Provide hints that lead toward understanding
+5. When the student demonstrates clear understanding, respond with "CONGRATULATIONS"
+   followed by a summary of what they learned
+
+Focus on building understanding, not just getting the right answer."""
+
+
+async def main() -> None:
+    """Run the student-teacher workflow with real Azure AI agents."""
+    # Create chat client
+    client = FoundryChatClient(
+        project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+        model=os.environ["FOUNDRY_MODEL"],
+        credential=AzureCliCredential(),
+    )
+
+    # Create student and teacher agents
+    student_agent = Agent(
+        client=client,
+        name="StudentAgent",
+        instructions=STUDENT_INSTRUCTIONS,
+    )
+
+    teacher_agent = Agent(
+        client=client,
+        name="TeacherAgent",
+        instructions=TEACHER_INSTRUCTIONS,
+    )
+
+    # Create factory with agents
+    factory = WorkflowFactory(
+        agents={
+            "StudentAgent": student_agent,
+            "TeacherAgent": teacher_agent,
+        }
+    )
+
+    workflow_path = Path(__file__).parent / "workflow.yaml"
+    workflow = factory.create_workflow_from_yaml_path(workflow_path)
+
+    print(f"Loaded workflow: {workflow.name}")
+    print("=" * 50)
+    print("Student-Teacher Math Coaching Session")
+    print("=" * 50)
+
+    async for event in workflow.run("How would you compute the value of PI?", stream=True):
+        if event.type == "output":
+            print(f"{event.data}", flush=True, end="")
+
+    print("\n" + "=" * 50)
+    print("Session Complete")
+    print("=" * 50)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())