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ReStructuredText
34 lines
1.9 KiB
ReStructuredText
Indexes
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==========================
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Indexes refer to ways to structure documents so that LLMs can best interact with them.
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This module contains utility functions for working with documents, different types of indexes, and then examples for using those indexes in chains.
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The most common way that indexes are used in chains is in a "retrieval" step.
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This step refers to taking a user's query and returning the most relevant documents.
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We draw this distinction because (1) an index can be used for other things besides retrieval, and (2) retrieval can use other logic besides an index to find relevant documents.
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We therefor have a concept of a "Retriever" interface - this is the interface that most chains work with.
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Most of the time when we talk about indexes and retrieval we are talking about indexing and retrieving unstructured data (like text documents).
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For interacting with structured data (SQL tables, etc) or APIs, please see the corresponding use case sections for links to relevant functionality.
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The primary index and retrieval types supported by LangChain are currently centered around vector databases, and therefore
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a lot of the functionality we dive deep on those topics.
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The following sections of documentation are provided:
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- `Getting Started <./indexes/getting_started.html>`_: An overview of the base "Retriever" interface, and then all the functionality LangChain provides for working with indexes.
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- `Key Concepts <./indexes/key_concepts.html>`_: A conceptual guide going over the various concepts related to indexes and the tools needed to create them.
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- `How-To Guides <./indexes/how_to_guides.html>`_: A collection of how-to guides. These highlight how to use all the relevant tools, the different types of vector databases, different types of retrievers, and how to use retrievers and indexes in chains.
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.. toctree::
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:maxdepth: 1
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:name: LLMs
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:hidden:
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./indexes/getting_started.ipynb
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./indexes/key_concepts.md
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./indexes/how_to_guides.rst
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