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Eduard van Valkenburg 5e056b672e Python: [BREAKING] Python: Provider-leading client design & OpenAI package extraction (#4818)
* Python: Provider-leading client design & OpenAI package extraction

Major refactoring of the Python Agent Framework client architecture:

- Extract OpenAI clients into new `agent-framework-openai` package
- Core package no longer depends on openai, azure-identity, azure-ai-projects
- Rename clients for discoverability: OpenAIResponsesClient → OpenAIChatClient,
  OpenAIChatClient → OpenAIChatCompletionClient
- Unify `model_id`/`deployment_name`/`model_deployment_name` → `model` param
- New FoundryChatClient for Azure AI Foundry Responses API
- New FoundryAgent/FoundryAgentClient for connecting to pre-configured Foundry agents
- Remove OpenAIBase/OpenAIConfigMixin from non-deprecated client MRO
- Deprecate AzureOpenAI* clients, AzureAIClient, OpenAIAssistantsClient
- Reorganize samples: azure_openai+azure_ai+azure_ai_agent → azure/
- ADR-0020: Provider-Leading Client Design

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

* fix: missing Agent imports in samples, .model_id → .model in foundry_local sample

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

* fix: CI failures — mypy errors, coverage targets, sample imports

- azure-ai mypy: add type ignores for TypedDict total=, model arg, forward ref
- Coverage: replace core.azure/openai targets with openai package target
- project_provider: add type annotation for opts dict

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

* fix: populate openai .pyi stub, fix broken README links, coverage targets

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

* fixes

* updated observabilitty

* reset azure init.pyi

* fix errors

* updated adr number

* fix foundry local

* fixed not renamed docstrings and comments, and added deprecated markers to old classes

* fix tests and pyprojects

* fix test vars

* updated function tests

* update durable

* updated test setup for functions

* Fix Foundry auth in workflow samples

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

* Stabilize Python integration workflows

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

* Update hosting samples for Foundry

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

* Trigger full CI rerun

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

* Trigger CI rerun again

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

* trigger rerun

* trigger rerun

* fix for litellm

* undo durabletask changes

* Move Foundry APIs into foundry namespace

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

* Fix Foundry pyproject formatting

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

* Split provider samples by Foundry surface

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

* Restore hosting sample requirements

Also fix the Foundry Local sample link after the provider sample move.

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

* updated tests

* udpated foundry integration tests

* removed dist from azurefunctions tests

* Use separate Foundry clients for concurrent agents

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

* fix client setup in azfunc and durable

* disabled two tests

* updated setup for some function and durable tests

* improved azure openai setup with new clients

* ignore deprecated

* fixes

* skip 11

* remove openai assistants int tests

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
5e056b672e · 2026-03-25 09:56:29 +00:00
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Mixed Skills — Code Skills and File Skills

This sample demonstrates how to combine code-defined skills and file-based skills in a single agent using a SkillScriptRunner callable and SkillsProvider.

Concepts

Concept Description
Code skill A Skill created in Python with @skill.script decorators for in-process callable functions and @skill.resource for dynamic content
File skill A skill discovered from a SKILL.md file on disk, with reference documents and executable script files
script_runner A callable (sync or async) satisfying the SkillScriptRunner protocol — required when file skills have scripts
SkillsProvider Registers both code-defined and file-based skills in a single provider

Skills in This Sample

volume-converter (code skill)

Defined entirely in Python code using decorators:

  • @skill.resourceconversion-table: gallons↔liters conversion factors
  • @skill.scriptconvert: converts a value using a multiplication factor

Code scripts run in-process — no subprocess or external runner needed.

unit-converter (file skill)

Discovered from skills/unit-converter/SKILL.md:

  • Reference: references/CONVERSION_TABLES.md — supported unit conversions and their factors
  • Script: scripts/convert.py — converts a value using a multiplication factor (e.g. miles to kilometers)

File scripts are executed as local Python subprocesses via the script_runner callback.

How It Works

┌─────────────────────────────────────────────────────────────┐
│  SkillsProvider(                                             │
│      skill_paths="./skills",              # file skills      │
│      skills=[volume_converter_skill],    # code skills      │
│      script_runner=runner,                                    │
│  )                                                           │
└─────────────┬───────────────────────────────────────────────┘
              │
              ▼
┌─────────────────────────────────────────────────────────────┐
│  script_runner(skill, script, args)                          │
│                                                             │
│  • Code scripts (@skill.script) → in-process call           │
│  • File scripts (scripts/*.py) → subprocess via             │
│    the callback function                                    │
└─────────────────────────────────────────────────────────────┘

Prerequisites

Set environment variables (or create a .env file):

AZURE_AI_PROJECT_ENDPOINT=https://your-project.openai.azure.com/
AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME=gpt-4o-mini

Authenticate with Azure CLI:

az login

Running the Sample

cd python
uv run samples/02-agents/skills/mixed_skills/mixed_skills.py

Directory Structure

mixed_skills/
├── mixed_skills.py                # Main sample — wires code + file skills together
├── README.md
└── skills/
    └── unit-converter/            # File-based skill (discovered from SKILL.md)
        ├── SKILL.md
        ├── references/
        │   └── CONVERSION_TABLES.md
        └── scripts/
            └── convert.py

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