f9f92706f3
RAG pipeline now includes a cross-encoder rerank step between retrieval
and generation. The LLM re-sorts top-K results by relevance before
they become context. Falls back to original order if model output is
unparseable (~5% with 7B models). Also improved the generation prompt
to be domain-aware ("staffing database") and request specific citations.
Fixed 4 catalog manifests with bucket="data" (pre-federation leftover)
that poisoned the entire DataFusion query context on startup. The
"users", "lab_trials", "meta_runs", and "new_candidates" datasets
now correctly reference bucket="primary". This bug was surfaced by
the quality evaluation pipeline — wouldn't have been found by
structural tests alone.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
79 lines
1.7 KiB
JSON
79 lines
1.7 KiB
JSON
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"name": "new_candidates",
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"objects": [
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{
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"bucket": "primary",
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"key": "datasets/new_candidates.parquet",
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"size_bytes": 2731,
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"created_at": "2026-03-28T01:04:22.787759218Z"
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}
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],
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"created_at": "2026-03-28T01:04:22.787759835Z",
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"updated_at": "2026-03-28T01:04:22.788113964Z",
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"description": "",
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"owner": "",
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"sensitivity": "pii",
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"columns": [
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{
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"name": "name",
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"data_type": "Utf8",
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"sensitivity": "pii",
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"description": "",
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"is_pii": true
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},
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{
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"name": "phone",
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"data_type": "Utf8",
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"sensitivity": "pii",
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"description": "",
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"is_pii": true
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"name": "email",
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"data_type": "Utf8",
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"is_pii": true
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{
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"name": "city",
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"name": "state",
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{
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"name": "skills",
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{
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"name": "years",
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"data_type": "Int64",
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],
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"lineage": {
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"source_system": "csv",
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"source_file": "new_candidates.csv",
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"ingest_job": "ingest-1774659862787",
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"ingest_timestamp": "2026-03-28T01:04:22.787759218Z",
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"parent_datasets": []
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"freshness": null,
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"tags": [],
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"row_count": 3
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} |