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26 lines
1.2 KiB
ReStructuredText
26 lines
1.2 KiB
ReStructuredText
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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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LangChain provides common indices for working with data (most prominently support for vector databases).
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For more complicated index structures, it is worth checking out `GPTIndex <https://gpt-index.readthedocs.io/en/latest/index.html>`_.
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The following sections of documentation are provided:
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- `Getting Started <./indexes/getting_started.html>`_: An overview of 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, and how to use 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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