From a67bfe26edd5924ea9be80cb0a1141d6d5c8b508 Mon Sep 17 00:00:00 2001 From: Logan Markewich <logan.markewich@live.com> Date: Tue, 18 Jul 2023 19:58:34 -0600 Subject: [PATCH] fix link to node_parser --- apps/docs/docs/modules/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/apps/docs/docs/modules/index.md b/apps/docs/docs/modules/index.md index 9a4ade520..9293c7e88 100644 --- a/apps/docs/docs/modules/index.md +++ b/apps/docs/docs/modules/index.md @@ -22,7 +22,7 @@ LlamaIndex.TS offers several core modules, seperated into high-level modules for - [**Embedding**](./low_level/embedding.md): An embedding is represented as a vector of floating point numbers. OpenAI's text-embedding-ada-002 is our default embedding model and each embedding it generates consists of 1,536 floating point numbers. Another popular embedding model is BERT which uses 768 floating point numbers to represent each Node. We provide a number of utilities to work with embeddings including 3 similarity calculation options and Maximum Marginal Relevance -- [**TextSplitter/NodeParser**](./low_level/text_splitter.md): Text splitting strategies are incredibly important to the overall efficacy of the embedding search. Currently, while we do have a default, there's no one size fits all solution. Depending on the source documents, you may want to use different splitting sizes and strategies. Currently we support spliltting by fixed size, splitting by fixed size with overlapping sections, splitting by sentence, and splitting by paragraph. The text splitter is used by the NodeParser when splitting `Document`s into `Node`s. +- [**TextSplitter/NodeParser**](./low_level/node_parser.md): Text splitting strategies are incredibly important to the overall efficacy of the embedding search. Currently, while we do have a default, there's no one size fits all solution. Depending on the source documents, you may want to use different splitting sizes and strategies. Currently we support spliltting by fixed size, splitting by fixed size with overlapping sections, splitting by sentence, and splitting by paragraph. The text splitter is used by the NodeParser when splitting `Document`s into `Node`s. - [**Retriever**](./low_level/retriever.md): The Retriever is what actually chooses the Nodes to retrieve from the index. Here, you may wish to try retrieving more or fewer Nodes per query, changing your similarity function, or creating your own retriever for each individual use case in your application. For example, you may wish to have a separate retriever for code content vs. text content. -- GitLab