From ba2f706c1437d71540796f0104af0425cddd6efc Mon Sep 17 00:00:00 2001 From: jacoblee93 Date: Mon, 17 Jun 2024 13:50:43 -0700 Subject: [PATCH] Format, fix link --- docs/core_docs/docs/concepts.mdx | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/docs/core_docs/docs/concepts.mdx b/docs/core_docs/docs/concepts.mdx index cf5d048820ab..88d978a9aad0 100644 --- a/docs/core_docs/docs/concepts.mdx +++ b/docs/core_docs/docs/concepts.mdx @@ -1012,13 +1012,13 @@ There are some additional tricks to improve the quality of your retrieval. Embed #### Post-processing -Sixth, consider ways to filter or rank retrieved documents. This is very useful if you are [combining documents returned from multiple sources](/docs/integrations/retrievers/cohere-reranker/#doing-reranking-with-coherererank), since it can can down-rank less relevant documents and / or [compress similar documents](/docs/how_to/contextual_compression/#more-built-in-compressors-filters). +Sixth, consider ways to filter or rank retrieved documents. This is very useful if you are [combining documents returned from multiple sources](/docs/how_to/ensemble_retriever), since it can can down-rank less relevant documents and / or [compress similar documents](/docs/how_to/contextual_compression/#more-built-in-compressors-filters). -| Name | Index Type | Uses an LLM | When to Use | Description | -| -------------------------------------------------------------- | ---------- | ----------- | ----------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| [Contextual Compression](/docs/how_to/contextual_compression/) | Any | Sometimes | If you are finding that your retrieved documents contain too much irrelevant information and are distracting the LLM. | This puts a post-processing step on top of another retriever and extracts only the most relevant information from retrieved documents. This can be done with embeddings or an LLM. | -| [Ensemble](/docs/how_to/ensemble_retriever/) | Any | No | If you have multiple retrieval methods and want to try combining them. | This fetches documents from multiple retrievers and then combines them. | -| [Re-ranking](/docs/integrations/retrievers/cohere-reranker/) | Any | Yes | If you want to rank retrieved documents based upon relevance, especially if you want to combine results from multiple retrieval methods . | Given a query and a list of documents, Rerank indexes the documents from most to least semantically relevant to the query. | +| Name | Index Type | Uses an LLM | When to Use | Description | +| -------------------------------------------------------------------- | ---------- | ----------- | ---------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| [Contextual Compression](/docs/how_to/contextual_compression/) | Any | Sometimes | If you are finding that your retrieved documents contain too much irrelevant information and are distracting the LLM. | This puts a post-processing step on top of another retriever and extracts only the most relevant information from retrieved documents. This can be done with embeddings or an LLM. | +| [Ensemble](/docs/how_to/ensemble_retriever/) | Any | No | If you have multiple retrieval methods and want to try combining them. | This fetches documents from multiple retrievers and then combines them. | +| [Re-ranking](/docs/integrations/document_compressors/cohere_rerank/) | Any | Yes | If you want to rank retrieved documents based upon relevance, especially if you want to combine results from multiple retrieval methods. | Given a query and a list of documents, Rerank indexes the documents from most to least semantically relevant to the query. | :::tip