Qdrant supports hybrid search by combining search results from sparse and dense vectors. dense vectors are the ones you have probably already been using -- ...

In this tutorial, we show you how to define a very simple version of hybrid search! Combine keyword lookup retrieval with vector retrieval using "AND" and "OR" ...

Query Index with Hybrid Search¶ ... Use hybrid search with bm25 and vector. alpha parameter determines weighting (alpha = 0 -> bm25, alpha=1 -> vector search).

Pinecone Vector Store - Hybrid Search¶ ... If you're opening this Notebook on colab, you will probably need to install LlamaIndex . ... Copied!

31 янв. 2024 г. · In this blog post, we will look into tuning Alpha within the Weaviate vector database using the Retrieval Evaluation module of LlamaIndex with and without ...

22 мар. 2024 г. · To perform hybrid search, you need to define the retrieval_strategy parameter in the ElasticsearchStore class and create the index and query ...

17 окт. 2024 г. · Hybrid search combines full-text search with vector search to identify both exact matches and semantically similar content. This approach is ...

In llama-index, we can construct a hybrid index in just a few lines of code. If you've tried hybrid in the past with splade, you will notice that this is much ...

I am trying to build an index that should support a hybrid search mechanism consisting of both BM25 and vector searches.

BGE-M3 from FlagEmbedding is used as the default sparse embedding method, so it needs to be installed along with llama-index.