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Eduard van Valkenburg 6acab3d1d6 Python: [BREAKING] Standardize model selection on model (#4999)
* Refactor Anthropic model option and provider clients

Rename the Anthropic client model option from model_id to model, add provider-specific Anthropic wrappers for Foundry, Bedrock, and Vertex, and expose them through the Anthropic, Foundry, Amazon, and Google namespaces. Update core option handling, docs, samples, and tests accordingly.

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

* Fix Anthropic skills sample typing

Cast the Anthropic beta client to Any in the skills sample so the pre-commit sample pyright check no longer fails on beta skills and files endpoints that are not exposed by the current SDK stubs.

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

* undo sample mypy

* Retry CI after transient external failures

Retrigger PR validation after an unrelated Copilot review workflow SAML failure and a transient external tau2 git fetch failure in the Windows Python test setup.

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

* Address review feedback on model option merging

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

* Address Anthropic compatibility review feedback

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

* moved all to `model`

* fixes for azure ai search

* Python: standardize remaining sample env var names

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

* Python: fix foundry-local pyright compatibility

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

* updated env vars in cicd

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Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
6acab3d1d6 · 2026-04-01 19:00:18 +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):

FOUNDRY_PROJECT_ENDPOINT=https://your-project.openai.azure.com/
AZURE_OPENAI_MODEL=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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