feat(eval): add Ragas-style context precision and recall metrics

[Isha-Zaka]

Description

Adds Ragas-style context precision and context recall metrics to the RAG evaluation framework, with model-layer judge support and batch evaluation for labeled examples.

Related issue

Fixes #303

Changes

• Added Ragas-style context precision with rank-sensitive relevance scoring and context recall based on reference-answer claim coverage.
• Added ChatModelJudge to support evaluation through Dynavec's existing ChatModel abstraction.
• Extended evaluate_rag() and EvalRunner to support all four RAG evaluation metrics and batch evaluation with optional reference answers, with fake-judge test coverage.

Testing

Validation: 36 passed in tests/test_eval.py; full make run-ci passed; mypy passed on 81 source files; 1 snapshot passed; git diff --check passed.

• Tests pass locally
• Ruff checks pass
• Documentation updated, if applicable

Checklist

• My changes are focused and relevant to this pull request.
• I have added or updated tests where appropriate.
• I have reviewed my changes for unrelated modifications.
• I have updated documentation where necessary.