Implement two-tier Docling parsing for faster ingestion#388
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ArnavAgrawal03 wants to merge 2 commits intomainfrom
Open
Implement two-tier Docling parsing for faster ingestion#388ArnavAgrawal03 wants to merge 2 commits intomainfrom
ArnavAgrawal03 wants to merge 2 commits intomainfrom
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…tion Replace always-on OCR with a fast-first approach: try text-layer extraction without OCR/table detection first (seconds), then fall back to full OCR only if no text is found (scanned/image PDFs). This restores the performance of the old unstructured parser while maintaining quality for documents that need it. Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
…_URI in entrypoint The docker-build CI was failing because: - The entrypoint script hardcoded `pg_isready -h postgres` instead of parsing the host from POSTGRES_URI - No PostgreSQL instance was available during the CI test The entrypoint now extracts host/port/user/db from POSTGRES_URI, and the CI workflow spins up a pgvector/pgvector:pg16 container on a shared Docker network before running the health check.
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Summary
Implement a two-tier document parsing strategy to resolve the significant ingestion slowdown caused by always-on OCR. The parser now tries fast text-layer extraction first (no OCR, no table detection), and only falls back to the full OCR pipeline if no text is found, which is exactly when it's needed (scanned/image PDFs).
Impact
For text-based PDFs (the majority), parsing time drops from minutes back to seconds, matching the old
unstructuredlibrary behavior. Scanned documents still get OCR'd automatically. This should reduce typical ingestion times from 2+ hours back to minutes for batch uploads.Changes
_parse_document_local()now tries fast first, returns immediately if text is found🤖 Generated with Claude Code