evalproof 0.1.0

First release.

Added

• Suites in YAML: a JSONL golden set, a system under test, scorers, an optional judge,
  calibration settings and a gate.
• Systems under test: Ollama, Anthropic and OpenAI models with a prompt template; Python
  functions; HTTP endpoints. System failures are recorded per case, never fatal.
• Scorers: exact match, contains, regex with accept/reject answer keys, a JSON Schema
  subset, numeric tolerance, recall@k, MRR, nDCG, and an LLM judge with a strict JSON
  verdict, one parse retry and an explicit undecided state.
• Pairwise judging with order swap; position-inconsistent verdicts become ties.
• Judge calibration: confusion matrix, TPR, FPR, Cohen's κ, and prevalence-corrected pass
  rates by adjusted classify-and-count (bootstrap interval) and prediction-powered
  inference (normal interval).
• Paired comparison of two runs: exact McNemar for pass/fail, paired bootstrap for scores.
• A CI gate that fails only on a drop that is both beyond max_drop and significant at
  alpha, plus p95-latency and cost budgets, with distinct exit codes.
• Content-addressed response cache; runs record the Ollama version and model digests.
• Markdown reports for GitHub step summaries, JSON reports, and a composite GitHub Action.
• Two examples: an offline ticket router (CI's gate contract) and a support assistant for
  a fictional product judged by a local model, with measurements.