Release 1.1.0

[3dgiordano]

This pull request introduces several significant improvements and new features to the project, expanded AI Scriptless modeling, and improved build and test infrastructure and focusing on enhanced telemetry and observability, The most important changes are grouped below by theme.

AI Scriptless Modeling Enhancements:

• Introduced new Pydantic models in models/ai_scriptless.py for representing Scriptless test structures, command catalogs, snapshots, and command definitions, enabling more robust and type-safe handling of Scriptless automation data.
• Expanded the config/perfecto.py module with new utility functions for constructing URLs related to Scriptless lab, draft management, command repository, and repository management APIs. [1] [2]

Testing and CI/CD:

• Added a new GitHub Actions workflow (.github/workflows/tests.yaml) to automate running tests on both Ubuntu and Windows environments, using uv for dependency management.
• Introduced a test fixture in tests/conftest.py for providing a reusable PerfectoToken in tests.

User Model and Formatting:

• Enhanced the User model and user formatting logic to include cloud_name and cloud_url fields, providing more contextual information about users related to the Perfecto cloud configuration. [1] [2]

Other minor changes include a version bump to 1.1.0 in pyproject.toml and documentation updates in the Dockerfile. [1] [2]

Telemetry and Observability:

• Added OpenTelemetry-based tracing and metrics collection with a new telemetry.py module, including automatic instrumentation for tool calls, error handling, and support for configuration via environment variables. Telemetry is initialized in main.py, and new dependencies for OpenTelemetry are added to pyproject.toml. [1] [2] [3] [4]

Build and Packaging Improvements:

• Updated build.py to include additional hidden imports and submodules for PyInstaller, ensuring all necessary modules (including OpenTelemetry and Scriptless tools) are bundled in the executable. [1] [2]