Python: Add sample on how to share a thread between agents in a workflow (#3405)

* Add sample on how to share a thread between agents in a workflow * Fix sample * Fix formatting * Comments * comment
2026-06-16 21:04:09 +08:00 · 2026-01-30 10:07:58 -08:00
parent ff7041b990
commit 0fcf075ea7
3 changed files with 206 additions and 94 deletions
@@ -0,0 +1,103 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+
+from agent_framework import (
+    AgentExecutorRequest,
+    AgentExecutorResponse,
+    ChatMessageStore,
+    WorkflowBuilder,
+    WorkflowContext,
+    WorkflowRunState,
+    executor,
+)
+from agent_framework.azure import AzureAIProjectAgentProvider
+from azure.identity.aio import AzureCliCredential
+
+"""
+Sample: Agents with a shared thread in a workflow
+
+A Writer agent generates content, then a Reviewer agent critiques it, sharing a common message thread.
+
+Purpose:
+Show how to use a shared thread between multiple agents in a workflow.
+By default, agents have individual threads, but sharing a thread allows them to share all messages.
+
+Notes:
+- Not all agents can share threads; usually only the same type of agents can share threads.
+
+Demonstrate:
+- Creating multiple agents with Azure AI Agent Service (V2 API).
+- Setting up a shared thread between agents.
+
+Prerequisites:
+- Azure AI Agent Service configured, along with the required environment variables.
+- Authentication via azure-identity. Use AzureCliCredential and run az login before executing the sample.
+- Basic familiarity with agents, workflows, and executors in the agent framework.
+"""
+
+
+@executor(id="intercept_agent_response")
+async def intercept_agent_response(
+    agent_response: AgentExecutorResponse, ctx: WorkflowContext[AgentExecutorRequest]
+) -> None:
+    """This executor intercepts the agent response and sends a request without messages.
+
+    This essentially prevents duplication of messages in the shared thread. Without this
+    executor, the response will be added to the thread as input of the next agent call.
+    """
+    await ctx.send_message(AgentExecutorRequest(messages=[]))
+
+
+async def main() -> None:
+    async with (
+        AzureCliCredential() as credential,
+        AzureAIProjectAgentProvider(credential=credential) as provider,
+    ):
+        writer = await provider.create_agent(
+            instructions=(
+                "You are a concise copywriter. Provide a single, punchy marketing sentence based on the prompt."
+            ),
+            name="writer",
+        )
+
+        reviewer = await provider.create_agent(
+            instructions=("You are a thoughtful reviewer. Give brief feedback on the previous assistant message."),
+            name="reviewer",
+        )
+
+        shared_thread = writer.get_new_thread()
+        # Set the message store to store messages in memory.
+        shared_thread.message_store = ChatMessageStore()
+
+        workflow = (
+            WorkflowBuilder()
+            .register_agent(factory_func=lambda: writer, name="writer", agent_thread=shared_thread)
+            .register_agent(factory_func=lambda: reviewer, name="reviewer", agent_thread=shared_thread)
+            .register_executor(
+                factory_func=lambda: intercept_agent_response,
+                name="intercept_agent_response",
+            )
+            .add_chain(["writer", "intercept_agent_response", "reviewer"])
+            .set_start_executor("writer")
+            .build()
+        )
+
+        result = await workflow.run(
+            "Write a tagline for a budget-friendly eBike.",
+            # Keyword arguments will be passed to each agent call.
+            # Setting store=False to avoid storing messages in the service for this example.
+            options={"store": False},
+        )
+        # The final state should be IDLE since the workflow no longer has messages to
+        # process after the reviewer agent responds.
+        assert result.get_final_state() == WorkflowRunState.IDLE
+
+        # The shared thread now contains the conversation between the writer and reviewer. Print it out.
+        print("=== Shared Thread Conversation ===")
+        for message in shared_thread.message_store.messages:
+            print(f"{message.author_name or message.role}: {message.text}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())