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Python: Add Python feature lifecycle decorators for released APIs (#4975)

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* Add Python feature lifecycle decorators

Introduce reusable experimental and release-candidate decorators for released packages, migrate the Skills APIs to the new staged metadata and warning system, and add lifecycle guidance plus samples.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Fix Python CI follow-ups

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Address PR review feedback

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Preserve protocol runtime checks

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
This commit is contained in:
Eduard van Valkenburg
2026-03-31 21:40:08 +02:00
committed by GitHub
Unverified
parent 9c9d81d8b6
commit 55b6e7a9f4
19 changed files with 1220 additions and 60 deletions
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python/samples/02-agents/skills/code_defined_skill/code_defined_skill.py
+8 -7
View File
@@ -3,6 +3,11 @@
import asyncio
import json
import os
# Uncomment this filter to suppress the experimental Skills warning before
# using the sample's Skills APIs.
# import warnings # isort: skip
# warnings.filterwarnings("ignore", message=r"\[SKILLS\].*", category=FutureWarning)
from textwrap import dedent
from typing import Any
@@ -89,7 +94,7 @@ def conversion_policy(**kwargs: Any) -> Any:
Args:
**kwargs: Runtime keyword arguments from ``agent.run()``.
For example, ``agent.run(..., precision=2)``
For example, ``agent.run(..., function_invocation_kwargs={"precision": 2})``
makes ``kwargs["precision"]`` available here.
"""
precision = kwargs.get("precision", 4)
@@ -137,15 +142,11 @@ async def main() -> None:
credential=AzureCliCredential(),
)
# Create the skills provider with the code-defined skill
skills_provider = SkillsProvider(
skills=[unit_converter_skill],
)
# Create the skills provider with the code-defined skill and pass it to the agent
async with Agent(
client=client,
instructions="You are a helpful assistant that can convert units.",
context_providers=[skills_provider],
context_providers=[SkillsProvider(skills=[unit_converter_skill])],
) as agent:
print("Converting units")
print("-" * 60)