🔍Retrivers

AI components that efficiently fetch relevant data from knowledge bases in response to queries, supporting natural language tasks like question-answering and information retrieval.

1)Cohere Rerank Retriever

Cohere Rerank indexes the documents from most to least semantically relevant to the query.

2)Embeddings Filter Retriever

A document compressor that uses embeddings to drop documents unrelated to the query.

3)HyDE Retriever

Use HyDE retriever to retrieve from a vector store.

4)LLM Filter Retriever

Iterate over the initially returned documents and extract, from each, only the content that is relevant to the query.

5)Prompt Retriever

Store prompt template with name & description to be later queried by MultiPromptChain.

6)Reciprocal Rank Fusion Retriever

Reciprocal Rank Fusion to re-rank search results by multiple query generation.

7)Similarity Score Threshold Retriever

Return results based on the minimum similarity percentage.

8)Vector Store Retriever

Store vector store as retriever to be later queried by Multi Retrieval QA Chain.

9)Voyage AI Rerank Retriever

Voyage AI Rerank indexes the documents from most to least semantically relevant to the query.