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0dfbf2a68d
New paperforge_objects collection in ChromaDB for figure/table caption vector search, completing the memory layer retrieval triad: paperforge_fulltext → legacy_chunk paperforge_body → body_unit paperforge_objects → object_unit (NEW) Changes: - manifest.py: compute_object_units_hash(), manifest records both hashes - _chroma.py: _COLLECTION_NAMES includes paperforge_objects - builder.py: get_object_units_for_embedding() + embed_object_units() - status.py: object_chunk_count, total_chunks - state_snapshot.py: write_vector_runtime() extended with new fields - search.py: 3rd collection, dict-based source mapping, object_kind/label - __init__.py: exports for new functions - commands/embed.py: _has_object_units_in_db, body+object structured path routing with dual-hash resume, extended counters - Test fix: test_build_paper_manifest data complete for hash functions Verification: 20 object vectors embedded, all per-paper counts match, status total consistent (58266 = 57435 + 811 + 20), object caption queries return object_unit results via merge_retrieve. Unit tests: 153 pass, 1 skip. |
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| .. | ||
| __init__.py | ||
| _columns.py | ||
| builder.py | ||
| chunker.py | ||
| CONTEXT.md | ||
| context.py | ||
| db.py | ||
| events.py | ||
| fts.py | ||
| permanent.py | ||
| query.py | ||
| refresh.py | ||
| runtime_health.py | ||
| schema.py | ||
| state_snapshot.py | ||
| vector_db.py | ||