Bagel

Add texts along with their corresponding embeddings and optional metadata to the Bagel cluster.

Run a similarity search with Bagel.

Run a similarity search with Bagel and return documents with their corresponding similarity scores.

Create and initialize a Bagel instance from list of texts.

Delete the cluster.

Return docs most similar to embedding vector and similarity score.

Return docs most similar to embedding vector.

Create a Bagel vectorstore from a list of documents.

Update a document in the cluster.

Gets the collection.

Delete by IDs.