Empty documents after sanitization caused aadd_documents to issue a
DEFAULT VALUES insert. Guard with an emptiness check. Also increase
similarity search k from 2 to 6 so multi-word queries like full names
have better recall.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
YAML frontmatter can contain datetime objects which aren't JSON
serializable. Add _make_serializable() to coerce all metadata values
before storing in pgvector.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace full delete-and-reindex with mtime-based incremental sync that
only re-indexes changed/new files and removes deleted ones. A background
polling task keeps the vector store up-to-date automatically when
OBSIDIAN_CONTINUOUS_SYNC=true.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Disable tiktoken pre-encoding for custom embedding servers. LangChain
was encoding text into OpenAI token IDs then sending them to llama-server
which has a different vocabulary, causing "invalid tokens" errors.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Indexes chunks one at a time with error logging to identify which
document/chunk causes embedding failures. Also strips Unicode surrogates
and replacement characters.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Strips null bytes, control characters, and excessive whitespace from
document content before sending to embedding models. Fixes 400 errors
from BERT-based tokenizers (e.g. nomic-embed-text) on PDF-extracted text.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Adds EMBEDDING_SERVER_URL and EMBEDDING_MODEL_NAME env vars, mirroring
the existing LLAMA_SERVER_URL pattern for LLM configuration.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
_get_collection_id now catches the UndefinedTable error that occurs
before the first index operation creates the langchain tables.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Consolidate onto PostgreSQL by using pgvector instead of a separate
ChromaDB instance. This removes a Docker volume, a large dependency,
and simplifies the stack without meaningful performance impact at
our document scale.
- Swap langchain-chroma for langchain-postgres (PGVector)
- Use pgvector/pgvector:pg16 Docker image with init script
- Lazy-initialize vector store to avoid eager DB connections
- Add SQL helpers for stats/delete/list (replacing _collection access)
- Remove legacy main.py, chunker, petmd scraper, and /api/query endpoint
Re-index required after deploy (POST /api/rag/index + /index-obsidian).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Ryan Chen