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