Base class for Milvus built-in functions.
Milvus BM25 built-in function.
Supports both single-language and multi-language analyzers.
See:
Milvus Text Embedding built-in function (Data In Data Out).
This function allows Milvus to automatically generate embeddings from text by calling external embedding service providers (OpenAI, Bedrock, Vertex AI, etc.).
Hybrid search retriever that uses Milvus Collection to retrieve documents based on multiple fields.
For more information, please refer to: https://milvus.io/docs/release_notes.md#Multi-Embedding---Hybrid-Search
Zilliz Cloud Pipeline retriever.
Milvus vector store integration.
Zilliz vector store.
You need to have pymilvus installed and a
running Zilliz database.
See the following documentation for how to run a Zilliz instance: https://docs.zilliz.com/docs/create-cluster
IF USING L2/IP metric IT IS HIGHLY SUGGESTED TO NORMALIZE YOUR DATA.
