Description I am new to Weaviate and would appreciate some clarification. Here’s a bit of background about my situation: I have been working with vector databases, specifically testing Pinecone for a personal project. In my project, I want to implement hybrid search, but with Pinecone, I face a cha…

it will happen when data is added/updated. So when you ingest/update data, Weaviate will vectorize your data, ingest and index into the vector index, like hnsw. That will give you the vector side of your search. It will also create all the necessary inverted index for BM25 search. Then you can do …

hi @gaurav_sharma !! Welcome to our community :hugs: Your assumptions are correct. When you create a collection in Weaviate, you can specify a vectorizer, like so: from weaviate import classes as wvc wcd_url = os.environ["WCD_DEMO_URL"] wcd_api_key = os.environ["WCD_DEMO_RO_KEY"] openai_api_key…

[image] DudaNogueira: If you do not specify the vector parameter, it will now vectorize the word “food” and use the generated vector for the vector search as well. Thank you for the clarification @DudaNogueira . My understanding is that to calculate sparse embeddings (such as TF-IDF or BM25)…

Morning I have a question related to hybrid search. We are testing weaviate locally and doing the embedding out of the database, and pass it the vector to insert and query data. But, because of this, If I fill query parameter query in the following call, it raises an error because the database can´…

this question was also asked and answered here: [image] Hybrid search with embedding outside the database Support hi @LauraZ !! The hybrid search is a fusion of the keyword search and the vector search. When you provide the vector parameter, Weaviate will not…

Hybrid Search Implementation Without Predefined Sparse Vectors in Weaviate

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DudaNogueira September 16, 2024, 8:47pm 6

this question was also asked and answered here:

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Hybrid Search Implementation Without Predefined Sparse Vectors in Weaviate

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