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feat: add BM25 text indexing support for hybrid search#908
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Add a `text_indexing` parameter to `create_vectorizer` that enables BM25
full-text search indexing via the pg_textsearch extension. This enables
hybrid search (vector + BM25) on vectorized data.
Features:
- `ai.text_indexing_bm25(text_config, k1, b)` function with sane defaults
- `ai.text_indexing_none()` to explicitly disable (default)
- Auto-infers target column: chunk column if chunking enabled, source
column if chunking disabled
- Index created immediately when vectorizer is created
- Fails with descriptive error if pg_textsearch extension not installed
Example usage:
```sql
SELECT ai.create_vectorizer(
'my_documents'::regclass,
embedding => ai.embedding_openai('text-embedding-3-small', 768),
text_indexing => ai.text_indexing_bm25()
);
```
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Add a
text_indexingparameter tocreate_vectorizerthat enables BM25 full-text search indexing via the pg_textsearch extension. This enables hybrid search (vector + BM25) on vectorized data.ai.text_indexing_bm25(text_config, k1, b)- enable BM25 indexing with optional parametersai.text_indexing_none()- explicitly disable (default)