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# Copyright (c) Microsoft. All rights reserved.
import asyncio
from typing import cast
from agent_framework import Agent
from agent_framework.openai import OpenAIChatClient, OpenAIChatOptions, OpenAIContinuationToken
from dotenv import load_dotenv
# Load environment variables from .env file
load_dotenv()
"""Background Responses Sample.
This sample demonstrates long-running agent operations using the OpenAI
Responses API ``background`` option. Two patterns are shown:
1. **Non-streaming polling** start a background run, then poll with the
``continuation_token`` until the operation completes.
2. **Streaming with resumption** start a background streaming run, simulate
an interruption, and resume from the last ``continuation_token``.
Prerequisites:
- Set the ``OPENAI_API_KEY`` environment variable.
- A model that benefits from background execution (e.g. ``o3``).
"""
# 1. Create the agent with an OpenAI Responses client.
agent = Agent(
name="researcher",
instructions="You are a helpful research assistant. Be concise.",
client=OpenAIChatClient(model="o3"),
)
async def non_streaming_polling() -> None:
"""Demonstrate non-streaming background run with polling."""
print("=== Non-Streaming Polling ===\n")
session = agent.create_session()
# 2. Start a background run — returns immediately.
response = await agent.run(
messages="Briefly explain the theory of relativity in two sentences.",
session=session,
options=OpenAIChatOptions(background=True),
)
print(f"Initial status: continuation_token={'set' if response.continuation_token else 'None'}")
# 3. Poll until the operation completes.
poll_count = 0
while response.continuation_token is not None:
poll_count += 1
await asyncio.sleep(2)
response = await agent.run(
session=session,
options=OpenAIChatOptions(continuation_token=cast(OpenAIContinuationToken, response.continuation_token)),
)
print(f" Poll {poll_count}: continuation_token={'set' if response.continuation_token else 'None'}")
# 4. Done — print the final result.
print(f"\nResult ({poll_count} poll(s)):\n{response.text}\n")
async def streaming_with_resumption() -> None:
"""Demonstrate streaming background run with simulated interruption and resumption."""
print("=== Streaming with Resumption ===\n")
session = agent.create_session()
# 2. Start a streaming background run.
last_token = None
stream = agent.run(
messages="Briefly list three benefits of exercise.",
stream=True,
session=session,
options=OpenAIChatOptions(background=True),
)
# 3. Read some chunks, then simulate an interruption.
chunk_count = 0
print("First stream (before interruption):")
async for update in stream:
last_token = update.continuation_token
if update.text:
print(update.text, end="", flush=True)
chunk_count += 1
if chunk_count >= 3:
print("\n [simulated interruption]")
break
# 4. Resume from the last continuation token.
if last_token is not None:
print("Resumed stream:")
stream = agent.run(
stream=True,
session=session,
options=OpenAIChatOptions(continuation_token=cast(OpenAIContinuationToken, last_token)),
)
async for update in stream:
if update.text:
print(update.text, end="", flush=True)
print("\n")
async def main() -> None:
await non_streaming_polling()
await streaming_with_resumption()
if __name__ == "__main__":
asyncio.run(main())
"""
Sample output:
=== Non-Streaming Polling ===
Initial status: continuation_token=set
Poll 1: continuation_token=set
Poll 2: continuation_token=None
Result (2 poll(s)):
The theory of relativity, developed by Albert Einstein, consists of special
relativity (1905), which shows that the laws of physics are the same for all
non-accelerating observers and that the speed of light is constant, and general
relativity (1915), which describes gravity as the curvature of spacetime caused
by mass and energy.
=== Streaming with Resumption ===
First stream (before interruption):
Here are three
[simulated interruption]
Resumed stream:
key benefits of regular exercise:
1. **Improved cardiovascular health** ...
2. **Better mental health** ...
3. **Stronger muscles and bones** ...
"""