chore: import upstream snapshot with attribution

python/samples/03-workflows/_start-here/step3_streaming.py

@@ -0,0 +1,96 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+import os
+
+from agent_framework import Agent, AgentResponseUpdate, Message, WorkflowBuilder
+from agent_framework.foundry import FoundryChatClient
+from azure.identity import AzureCliCredential
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+"""
+Step 3: Agents in a workflow with streaming
+
+This sample creates two agents: a Writer agent creates or edits content, and a Reviewer agent which
+evaluates and provides feedback.
+
+Purpose:
+Show how to create agents from FoundryChatClient and use them directly in a workflow. Demonstrate
+how agents can be used in a workflow.
+
+Prerequisites:
+- FOUNDRY_PROJECT_ENDPOINT must be your Azure AI Foundry Agent Service (V2) project endpoint.
+- FOUNDRY_MODEL must be the deployment name of a model in your Foundry project.
+- Authentication via azure-identity. Use AzureCliCredential and run az login before executing the sample.
+- Basic familiarity with WorkflowBuilder, executors, edges, events, and streaming runs.
+"""
+
+
+async def main():
+    """Build the two node workflow and run it with streaming to observe events."""
+    # Create the Azure chat client. AzureCliCredential uses your current az login.
+    client = FoundryChatClient(
+        project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+        model=os.environ["FOUNDRY_MODEL"],
+        credential=AzureCliCredential(),
+    )
+    writer_agent = Agent(
+        client=client,
+        instructions=(
+            "You are an excellent content writer. You create new content and edit contents based on the feedback."
+        ),
+        name="writer",
+    )
+
+    reviewer_agent = Agent(
+        client=client,
+        instructions=(
+            "You are an excellent content reviewer."
+            "Provide actionable feedback to the writer about the provided content."
+            "Provide the feedback in the most concise manner possible."
+        ),
+        name="reviewer",
+    )
+
+    # Build the workflow using the fluent builder.
+    # Set the start node via constructor and connect an edge from writer to reviewer.
+    workflow = WorkflowBuilder(start_executor=writer_agent).add_edge(writer_agent, reviewer_agent).build()
+
+    # Track the last author to format streaming output.
+    last_author: str | None = None
+
+    # Run the workflow with the user's initial message and stream events as they occur.
+    async for event in workflow.run(
+        Message("user", ["Create a slogan for a new electric SUV that is affordable and fun to drive."]),
+        stream=True,
+    ):
+        # The outputs of the workflow are whatever the agents produce. So the events are expected to
+        # contain `AgentResponseUpdate` from the agents in the workflow.
+        if event.type == "output" and isinstance(event.data, AgentResponseUpdate):
+            update = event.data
+            author = update.author_name
+            if author != last_author:
+                if last_author is not None:
+                    print()  # Newline between different authors
+                print(f"{author}: {update.text}", end="", flush=True)
+                last_author = author
+            else:
+                print(update.text, end="", flush=True)
+
+    """
+    writer: "Electrify Your Journey: Affordable Fun Awaits!"
+    reviewer: Feedback:
+
+    1. **Clarity**: Consider simplifying the message. "Affordable Fun" could be more direct.
+    2. **Emotional Appeal**: Emphasize the thrill of driving more. Try using words that evoke excitement.
+    3. **Unique Selling Proposition**: Highlight the electric aspect more boldly.
+
+    Example revision: "Charge Your Adventure: Affordable SUVs for Fun-Loving Drivers!"
+    """
+
+
+if __name__ == "__main__":
+    asyncio.run(main())