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Evan Mattson
3a463b8bf6
* Python: bump package versions for 1.2.1 release PATCH bump (1.2.0 -> 1.2.1) for the released cohort. The release window covers two PRs, no new public APIs: - agent-framework-core: prevent inner_exception from being lost in AgentFrameworkException (#5167) - samples: add requirements.txt and .env.example to the a2a/ hosting sample for pip-based setup (#5510) Per lockstep convention, all 21 beta packages stamp 1.0.0b260428 and all 3 alpha packages stamp 1.0.0a260428, regardless of per-package code churn. Every non-core package floor on agent-framework-core is raised to >=1.2.1 to keep cohort signaling consistent. Date stamp reflects the local (Asia) cut date 2026-04-28. * Python: silence pyright unknown-type warnings in hosted-env detection `azure.ai.agentserver.core` is probed at runtime via `importlib.util.find_spec` and is not a declared dependency. The existing `# pyright: ignore[reportMissingImports]` suppresses the missing-import warning, but at `lowest-direct` resolution pyright still reports the imported symbol (`AgentConfig`) and its members (`from_env`, `is_hosted`) as unknown, breaking `validate-dependency-bounds-test` for `packages/core`. Extend the existing ignore to cover `reportUnknownVariableType` on the import and `reportUnknownMemberType` on the call site so the bounds check returns to green. Behavior is unchanged. Latent since #5455 (shipped in 1.2.0). * Python: raise agent-framework-gemini lower bound to google-genai>=1.65.0 The Gemini chat client references several `google.genai.types` symbols (`FileSearch`, `ThinkingLevel`, `SearchTypes`, `McpServer`, `StreamableHttpTransport`, plus call-site keyword args `mcp_servers` and `search_types`) that are not present at the lower bound of `google-genai>=1.0.0`. At `lowest-direct` resolution this caused `validate-dependency-bounds-test` to fail for `packages/gemini` with eleven `reportAttributeAccessIssue` / `reportUnknownVariableType` errors. Walking the upstream `google.genai.types` API: - `GoogleMaps`, `AuthConfig`: present from 1.40.0 - `FileSearch`: introduced in 1.49.0 - `ThinkingLevel`: introduced in 1.55.0 - `SearchTypes`, `McpServer`, `StreamableHttpTransport`: introduced in 1.65.0 Bump the lower bound to 1.65.0 — the minimum version that exposes every symbol the package actually uses. Keep the `<2.0.0` upper cap unchanged. With this bump `validate-dependency-bounds-test` passes for both lower and upper resolution scenarios across all 27 workspace packages. Latent since #4847 (Gemini package introduction in 1.1.0); aggravated by subsequent feature additions that pulled in newer `types.*` symbols. * Python: add dependabot bumps to 1.2.1 CHANGELOG Catalog the 15 dependabot dependency updates that merged on `upstream/main` between python-1.2.0 and the 1.2.1 cut window under a new Changed section: - Workspace dev/runtime deps: `rich`, `prek`, `python-multipart`, `pyasn1`, `pytest` (ag-ui, devui, lab), `uv` (lab) - Frontend deps: `vite` (devui, chatkit), `postcss` (devui, chatkit, handoff), `picomatch` (devui, handoff) CHANGELOG-only — no source or pyproject.toml changes. PRs themselves merged upstream independently of this release branch and will be brought in via the PR merge.
3a463b8bf6
·
2026-04-28 18:23:26 +09:00
History
Get Started with Microsoft Agent Framework Durable Task
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.