engine: update dependencies, enforce coverage, and expand tests

[Ludy87]

Summary

This PR updates the AI Engine toolchain and strengthens its automated quality checks.

Changes

• Update the AI Engine's runtime, development, and pre-commit dependencies.
• Add pytest-cov and a dedicated task engine:test:coverage task.
• Enforce a minimum of 90% coverage for every measured source file.
• Run coverage in CI, publish the report in the workflow summary, and upload HTML/XML/JSON reports as an artifact.
• Extend Ruff configuration and formatting coverage for repository Python files.
• Add and expand unit tests for:
  • orchestrator routing and dispatch,
  • PDF editing workflows,
  • API streaming helpers,
  • ledger agents and formula validation,
  • application utilities,
  • edge cases and error handling.
• Ignore generated coverage output.

Motivation

Keeping the engine dependencies current and enforcing per-file coverage improves reliability, makes regressions easier to detect, and gives contributors and reviewers accessible coverage reports.

Testing

• task engine:test:coverage
• task engine:check

Checklist

General

• I have read the Contribution Guidelines
• I have read the Stirling-PDF Developer Guide (if applicable)
• I have performed a self-review of my own code
• My changes generate no new warnings

Documentation

• I have updated relevant docs on Stirling-PDF's doc repo (if functionality has heavily changed)

Testing

• I have run the relevant checks locally
• I have tested my changes locally

[github-actions]

Generated Models Check Failed

One or more generated files are out of date with the Java OpenAPI spec and will need to be regenerated before they can be merged in.

Run task tool-models to regenerate them, then commit the updated files.