673b7f86ba
When a KB has chunking_strategy = 'late', ingestion takes a separate
code path that embeds the full document in a single forward pass and
mean-pools token embeddings per chunk span. Each chunk vector carries
full-document context via the encoder's bidirectional attention —
Jina's published technique, ~+6.5 nDCG@10 on long docs.
Backend
- chunking.py: new chunk_pages_with_spans() that joins all pages into a
single full_doc, runs the existing recursive splitter, and returns
per-chunk (char_start, char_end) offsets. Page-number metadata is
recovered by overlap with the original page ranges so PDF citations
still work. Existing chunk_pages() unchanged.
- embeddings.py: new late_chunk_encode(doc_text, char_spans). Tokenizes
the doc with return_offsets_mapping, runs the underlying transformer
to get per-token last_hidden_state, then mean-pools per chunk span.
When the doc exceeds the embedder's context, falls back to windowed
late chunking with a 512-token overlap so cross-window context is
partially preserved.
- ingestion.py _subprocess_worker: branches on chunking_strategy.
'late' path: chunk_pages_with_spans -> late_chunk_encode -> one big
chunks_batch message. 'standard' path unchanged. Both reuse the same
parent-side pump.
- ingestion.enqueue_ingestion: new chunking_strategy + mode kwargs;
defaults to 'standard' / 'text' for legacy callers. embedder model
resolved via resolve_embedder() from the (mode, strategy) matrix.
- routes/rag.py: KB-doc upload reads chunking_strategy + mode from the
KB row (defensive .get for pre-Phase-3 schemas) and threads them
through _start_ingestion.
Frontend
- kb-create-dialog.tsx: new "Chunking strategy" select with Standard /
Late options. Embedding-model placeholder switches to nomic when
Late is picked. createKB request now carries chunking_strategy.
- kb-list.tsx + chat-settings-sheet.tsx: small "⚡ Late" badge next to
late-chunking KB names in the settings KB list and the chat sidebar
dropdown so users see the mode at a glance.
Tests
- test_rag_late_chunking.py: pure-python tests for chunk_pages_with_spans
(chunks index back into full_doc; page numbers inherited by overlap;
pages joined with blank line). A server-marked test loads
all-MiniLM-L6-v2 to exercise late_chunk_encode end-to-end.
No multimodal yet; that's Phase 3B-multimodal (next PR).
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