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>
- POST /ingest/postgres/tables — list all tables in a database
- POST /ingest/postgres/import — import table → Parquet → catalog → queryable
- Auto type mapping: int2/4/8 → Int, float4/8 → Float64, bool → Boolean,
text/varchar/jsonb/timestamp → Utf8 (safe default per ADR-010)
- Auto PII detection + lineage on import
- Empty password support for trust auth
- Tested: imported lab_trials (40 rows, 10 cols) and threat_intel (20 rows, 30 cols)
from local knowledge_base Postgres database — immediately queryable
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
