Python: Support skill scripts execution (#4558)

* support skill scripts execution

* fix mixed line endings

* address comments and fix syntax issues

* use few try/except instead of one

* change samples

* validate either script path or script resource is set not both

* fix: separate LLM args from runtime kwargs in skill script execution

* address pr review comments

* address PR review comments

* Update python/packages/core/agent_framework/_skills.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update python/packages/core/agent_framework/_skills.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update python/packages/core/agent_framework/_skills.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* 1. Fixing the caching bug where parameters_schema would re-inspect on every call when the result was None
   2. Updating the arguments tool description to be more generic (not CLI-specific)

* fix failing tests

* address pr review comments

* address pr review comments

* allow resource function returning any instead of sting

* address PR review comments

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
This commit is contained in:
SergeyMenshykh
2026-03-11 18:28:30 +00:00
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commit 23ebfbc937
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# Script Approval — Human-in-the-Loop for Skill Scripts
This sample demonstrates how to require **human approval** before executing skill scripts using the `require_script_approval=True` option on `SkillsProvider`.
## How It Works
When `require_script_approval=True` is set, the agent pauses before executing any skill script and returns approval requests instead:
1. The agent tries to call `run_skill_script` — execution is paused
2. `result.user_input_requests` contains approval request(s) with function name and arguments
3. The application inspects each request and decides to approve or reject
4. `request.to_function_approval_response(approved=True|False)` creates the response
5. The response is sent back via `agent.run(approval_response, session=session)`
6. If approved, the script executes; if rejected, the agent receives an error
## Key Components
- **`require_script_approval=True`** — Gates all script execution on human approval
- **`result.user_input_requests`** — Contains pending approval requests after `agent.run()`
- **`request.to_function_approval_response()`** — Creates an approval or rejection response
## Running the Sample
### Prerequisites
- An [Azure AI Foundry](https://ai.azure.com/) project with a deployed model (e.g. `gpt-4o-mini`)
### Environment Variables
Set the required environment variables in a `.env` file (see `python/.env.example`):
- `AZURE_AI_PROJECT_ENDPOINT`: Your Azure AI Foundry project endpoint
- `AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME`: The name of your model deployment (defaults to `gpt-4o-mini`)
### Authentication
This sample uses `AzureCliCredential` for authentication. Run `az login` in your terminal before running the sample.
### Run
```bash
cd python
uv run samples/02-agents/skills/script_approval/script_approval.py
```
## Learn More
- [File-Based Skills Sample](../file_based_skill/)
- [Code-Defined Skills Sample](../code_defined_skill/)
- [Mixed Skills Sample](../mixed_skills/)
- [Agent Skills Specification](https://agentskills.io/)