feat(bench): add ragcsv benchmark for CSV-based RAG evaluation#869
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Standalone benchmark that reads a CSV of evaluation queries, executes each as a span query with document fragments as context, then grades response accuracy via a second LLM call. Reports quantile statistics for accuracy and response time. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> Signed-off-by: Nick Mitchell <nickm@us.ibm.com>
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Summary
ragcsvbenchmark that reads a CSV of evaluation queries, executes each as a span query with document fragments as context, then grades response accuracy via a second LLM callpython_repr_to_jsonparser that handles mixed single/double-quoted Python repr output,None/True/FalsekeywordsRAGCSV_*env vars (model, concurrency, limit, debug)Test plan
cargo check --bench ragcsvcompiles with zero warningsRAGCSV_FILE=... RAGCSV_LIMIT=3 RAGCSV_DEBUG=1 cargo bench --bench ragcsvverifies CSV parsing and query constructionRAGCSV_FILE=... RAGCSV_CONCURRENCY=2 RAGCSV_LIMIT=10 cargo bench --bench ragcsvverifies concurrent execution and final report🤖 Generated with Claude Code