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# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------
"""
DESCRIPTION:
This sample demonstrates how to use agent operations with an event handler in streaming from
the Azure Agents service using a synchronous client.
USAGE:
python sample_agents_stream_eventhandler.py
Before running the sample:
pip install azure-ai-agents azure-identity
Set these environment variables with your own values:
1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
page of your Azure AI Foundry portal.
2) MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in
the "Models + endpoints" tab in your Azure AI Foundry project.
"""
import os
from azure.ai.agents import AgentsClient
from azure.identity import DefaultAzureCredential
from azure.ai.agents.models import (
AgentEventHandler,
MessageDeltaChunk,
ThreadMessage,
ThreadRun,
RunStep,
)
from typing import Any, Optional
agents_client = AgentsClient(
endpoint=os.environ["PROJECT_ENDPOINT"],
credential=DefaultAzureCredential(),
)
# [START stream_event_handler]
# With AgentEventHandler[str], the return type for each event functions is optional string.
class MyEventHandler(AgentEventHandler[str]):
def on_message_delta(self, delta: "MessageDeltaChunk") -> Optional[str]:
return f"Text delta received: {delta.text}"
def on_thread_message(self, message: "ThreadMessage") -> Optional[str]:
return f"ThreadMessage created. ID: {message.id}, Status: {message.status}"
def on_thread_run(self, run: "ThreadRun") -> Optional[str]:
return f"ThreadRun status: {run.status}"
def on_run_step(self, step: "RunStep") -> Optional[str]:
return f"RunStep type: {step.type}, Status: {step.status}"
def on_error(self, data: str) -> Optional[str]:
return f"An error occurred. Data: {data}"
def on_done(self) -> Optional[str]:
return "Stream completed."
def on_unhandled_event(self, event_type: str, event_data: Any) -> Optional[str]:
return f"Unhandled Event Type: {event_type}, Data: {event_data}"
# [END stream_event_handler]
with agents_client:
# Create an agent and run stream with event handler
agent = agents_client.create_agent(
model=os.environ["MODEL_DEPLOYMENT_NAME"], name="my-agent", instructions="You are a helpful agent"
)
print(f"Created agent, agent ID {agent.id}")
thread = agents_client.threads.create()
print(f"Created thread, thread ID {thread.id}")
message = agents_client.messages.create(thread_id=thread.id, role="user", content="Hello, tell me a joke")
print(f"Created message, message ID {message.id}")
# [START create_stream]
with agents_client.runs.stream(thread_id=thread.id, agent_id=agent.id, event_handler=MyEventHandler()) as stream:
for event_type, event_data, func_return in stream:
print(f"Received data.")
print(f"Streaming receive Event Type: {event_type}")
print(f"Event Data: {str(event_data)[:100]}...")
print(f"Event Function return: {func_return}\n")
# [END create_stream]
agents_client.delete_agent(agent.id)
print("Deleted agent")
messages = agents_client.messages.list(thread_id=thread.id)
for msg in messages:
if msg.text_messages:
last_text = msg.text_messages[-1]
print(f"{msg.role}: {last_text.text.value}")
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