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Python: Bump Python package versions for 1.13.0 release (#7443)
* Bump Python package versions for 1.13.0 release

Bump all 37 Python package projects because the CHANGELOG-driven release includes cross-package feature-usage telemetry, with core and root advancing to 1.13.0, OpenAI to 1.12.0, patch bumps for other stable packages, and 260730 stamps for alpha and beta packages. No optional beta cohort bump was applied; every prerelease package changed. Raise core floors conservatively across co-released packages.

Copilot-Session: e234a28b-c2fd-4ff4-a51d-3d8917936541

* Align co-released Python package dependencies

Update the four hosting adapter pins to the co-released agent-framework-hosting alpha and raise the Azure Functions Durable Task floor to the co-released beta.

Copilot-Session: e234a28b-c2fd-4ff4-a51d-3d8917936541

* Minimize Python release lockfile updates

Regenerate uv.lock with the pre-commit hook pinned uv version so the release changes only workspace package versions while preserving platform markers and agentlightning 0.3.0.

Copilot-Session: e234a28b-c2fd-4ff4-a51d-3d8917936541

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Copilot-Session: e234a28b-c2fd-4ff4-a51d-3d8917936541
2026-07-30 22:47:07 +00:00
..

Get Started with Microsoft Agent Framework Durable Task

PyPI

Please install this package via pip:

pip install agent-framework-durabletask --pre

Durable Task Integration

The durable task integration lets you host Microsoft Agent Framework agents using the Durable Task framework so they can persist state, replay conversation history, and recover from failures automatically.

Basic Usage Example

from agent_framework import Agent
from agent_framework.openai import OpenAIChatCompletionClient
from agent_framework_durabletask import DurableAIAgentWorker
from durabletask.worker import TaskHubGrpcWorker

# Create the worker
worker = TaskHubGrpcWorker(host_address="localhost:4001")
agent_worker = DurableAIAgentWorker(worker)

chat_client = OpenAIChatCompletionClient()
my_agent = Agent(client=chat_client, name="assistant")
agent_worker.add_agent(my_agent)

For more details, review the Python README and the samples directory.