Integrate OpenAI Agents SDK with Acontext for session persistence and task extraction
Converter.items_to_messages() to convert to Acontext-compatible format.
acontext create my-agent-project --template-path "python/openai-agent-basic"
curl -fsSL https://install.acontext.io | shRun agent with Acontext
Complete example
import asyncio
import os
from agents import Agent, Runner, OpenAIChatCompletionsModel, AsyncOpenAI, function_tool
from agents.models.chatcmpl_converter import Converter
from acontext import AcontextClient
client = AcontextClient(
api_key=os.getenv("ACONTEXT_API_KEY"),
)
# If you're using self-hosted Acontext:
# client = AcontextClient(
# base_url="http://localhost:8029/api/v1",
# api_key="sk-ac-your-root-api-bearer-token",
# )
@function_tool
def get_weather(city: str) -> str:
"""Returns weather info for the specified city."""
return f"The weather in {city} is sunny"
agent = Agent(
name="Assistant",
instructions="You are a helpful assistant",
model=OpenAIChatCompletionsModel(
model="gpt-4o-mini",
openai_client=AsyncOpenAI(),
),
tools=[get_weather],
)
async def main():
session = client.sessions.create()
# Run agent
result = await Runner.run(agent, "Plan a 3-day trip to Finland")
# Continue conversation
user_msg_2 = {"role": "user", "content": "Check the weather there"}
new_input = result.to_input_list() + [user_msg_2]
result = await Runner.run(agent, new_input)
# Convert and store to Acontext
messages = Converter.items_to_messages(result.to_input_list())
for msg in messages:
client.sessions.store_message(session_id=session.id, blob=msg, format="openai")
# Extract tasks
client.sessions.flush(session.id)
tasks = client.sessions.get_tasks(session.id)
for task in tasks.items:
print(f"Task: {task.data.task_description} | Status: {task.status}")
if __name__ == "__main__":
asyncio.run(main())
from helper import message_to_input_items
messages = client.sessions.get_messages(session_id, format="openai")
# Convert back to Responses API format
conversation = []
for msg in messages.items:
items = message_to_input_items(msg)
conversation.extend(items)
conversation.append({"role": "user", "content": "Continue"})
result = await Runner.run(agent, conversation)