forked from Archives/langchain
0118706fd6
### Description This PR adds a wrapper which adds support for the OpenSearch vector database. Using opensearch-py client we are ingesting the embeddings of given text into opensearch cluster using Bulk API. We can perform the `similarity_search` on the index using the 3 popular searching methods of OpenSearch k-NN plugin: - `Approximate k-NN Search` use approximate nearest neighbor (ANN) algorithms from the [nmslib](https://github.com/nmslib/nmslib), [faiss](https://github.com/facebookresearch/faiss), and [Lucene](https://lucene.apache.org/) libraries to power k-NN search. - `Script Scoring` extends OpenSearch’s script scoring functionality to execute a brute force, exact k-NN search. - `Painless Scripting` adds the distance functions as painless extensions that can be used in more complex combinations. Also, supports brute force, exact k-NN search like Script Scoring. ### Issues Resolved https://github.com/hwchase17/langchain/issues/1054 --------- Signed-off-by: Naveen Tatikonda <navtat@amazon.com> |
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| .. | ||
| analyze_document.ipynb | ||
| chat_vector_db.ipynb | ||
| graph_qa.ipynb | ||
| qa_with_sources.ipynb | ||
| question_answering.ipynb | ||
| summarize.ipynb | ||
| vector_db_qa_with_sources.ipynb | ||
| vector_db_qa.ipynb | ||
| vector_db_text_generation.ipynb | ||