forked from Archives/langchain
83 lines
2.4 KiB
ReStructuredText
83 lines
2.4 KiB
ReStructuredText
Welcome to LangChain
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==========================
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Large language models (LLMs) are emerging as a transformative technology, enabling
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developers to build applications that they previously could not.
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But using these LLMs in isolation is often not enough to
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create a truly powerful app - the real power comes when you are able to
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combine them with other sources of computation or knowledge.
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This library is aimed at assisting in the development of those types of applications.
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It aims to create:
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1. a comprehensive collection of pieces you would ever want to combine
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2. a flexible interface for combining pieces into a single comprehensive "chain"
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3. a schema for easily saving and sharing those chains
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The documentation is structured into the following sections:
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.. toctree::
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:maxdepth: 1
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:caption: Getting Started
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:name: getting_started
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getting_started/installation.md
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getting_started/environment.md
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getting_started/llm.md
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getting_started/chains.md
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Goes over a simple walk through and tutorial for getting started setting up a simple chain that generates a company name based on what the company makes.
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Covers installation, environment set up, calling LLMs, and using prompts.
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Start here if you haven't used LangChain before.
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.. toctree::
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:maxdepth: 1
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:caption: How-To Examples
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:name: examples
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examples/demos.rst
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examples/integrations.rst
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examples/prompts.rst
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examples/model_laboratory.ipynb
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More elaborate examples and walk-throughs of particular
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integrations and use cases. This is the place to look if you have questions
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about how to integrate certain pieces, or if you want to find examples of
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common tasks or cool demos.
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.. toctree::
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:maxdepth: 1
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:caption: Reference
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:name: reference
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installation.md
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integrations.md
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modules/prompt
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modules/llms
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modules/embeddings
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modules/text_splitter
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modules/vectorstore
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modules/chains
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Full API documentation. This is the place to look if you want to
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see detailed information about the various classes, methods, and APIs.
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.. toctree::
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:maxdepth: 1
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:caption: Resources
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:name: resources
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core_concepts.md
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glossary.md
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Discord <https://discord.gg/6adMQxSpJS>
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Higher level, conceptual explanations of the LangChain components.
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This is the place to go if you want to increase your high level understanding
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of the problems LangChain is solving, and how we decided to go about do so.
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