forked from Archives/langchain
d1f65d8dc1
# Create elastic_vector_search.ElasticKnnSearch class
This extends `langchain/vectorstores/elastic_vector_search.py` by adding
a new class `ElasticKnnSearch`
Features:
- Allow creating an index with the `dense_vector` mapping compataible
with kNN search
- Store embeddings in index for use with kNN search (correct mapping
creates HNSW data structure)
- Perform approximate kNN search
- Perform hybrid BM25 (`query{}`) + kNN (`knn{}`) search
- perform knn search by either providing a `query_vector` or passing a
hosted `model_id` to use query_vector_builder to automatically generate
a query_vector at search time
Connection options
- Using `cloud_id` from Elastic Cloud
- Passing elasticsearch client object
search options
- query
- k
- query_vector
- model_id
- size
- source
- knn_boost (hybrid search)
- query_boost (hybrid search)
- fields
This also adds examples to
`docs/modules/indexes/vectorstores/examples/elasticsearch.ipynb`
Fixes # [5346](https://github.com/hwchase17/langchain/issues/5346)
cc: @dev2049
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Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
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| .. | ||
| _static | ||
| additional_resources | ||
| ecosystem | ||
| getting_started | ||
| integrations | ||
| modules | ||
| reference | ||
| templates | ||
| tracing | ||
| use_cases | ||
| conf.py | ||
| dependents.md | ||
| index.rst | ||
| integrations.rst | ||
| make.bat | ||
| Makefile | ||
| reference.rst | ||
| requirements.txt | ||