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- put use cases in main sidebar - move modules to own sidebar, rename components - cleanup lcel section - cleanup guides - update font, cell highlighting --------- Co-authored-by: Chester Curme <chester.curme@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>
101 lines
4.8 KiB
Plaintext
101 lines
4.8 KiB
Plaintext
---
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sidebar_position: 0
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sidebar_class_name: hidden
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---
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# Introduction
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**LangChain** is a framework for developing applications powered by large language models (LLMs).
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LangChain simplifies every stage of the LLM application lifecycle:
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- **Development**: Build your applications using LangChain's open-source [building blocks](/docs/expression_language/) and [components](/docs/modules/). Hit the ground running using [third-party integrations](/docs/integrations/platforms/) and [Templates](/docs/templates).
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- **Productionization**: Use [LangSmith](/docs/langsmith/) to inspect, monitor and evaluate your chains, so that you can continuously optimize and deploy with confidence.
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- **Deployment**: Turn any chain into an API with [LangServe](/docs/langserve).
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import ThemedImage from '@theme/ThemedImage';
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<ThemedImage
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alt="Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers."
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sources={{
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light: '/svg/langchain_stack.svg',
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dark: '/svg/langchain_stack_dark.svg',
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}}
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title="LangChain Framework Overview"
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/>
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Concretely, the framework consists of the following open-source libraries:
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- **`langchain-core`**: Base abstractions and LangChain Expression Language.
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- **`langchain-community`**: Third party integrations.
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- Partner packages (e.g. **`langchain-openai`**, **`langchain-anthropic`**, etc.): Some integrations have been further split into their own lightweight packages that only depend on **`langchain-core`**.
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- **`langchain`**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
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- **[langgraph](/docs/langgraph)**: Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph.
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- **[langserve](/docs/langserve)**: Deploy LangChain chains as REST APIs.
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The broader ecosystem includes:
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- **[LangSmith](/docs/langsmith)**: A developer platform that lets you debug, test, evaluate, and monitor LLM applications and seamlessly integrates with LangChain.
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## Get started
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We recommend following our [Quickstart](/docs/get_started/quickstart) guide to familiarize yourself with the framework by building your first LangChain application.
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[See here](/docs/get_started/installation) for instructions on how to install LangChain, set up your environment, and start building.
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:::note
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These docs focus on the Python LangChain library. [Head here](https://js.langchain.com) for docs on the JavaScript LangChain library.
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:::
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## Use cases
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If you're looking to build something specific or are more of a hands-on learner, check out our [use-cases](/docs/use_cases).
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They're walkthroughs and techniques for common end-to-end tasks, such as:
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- [Question answering with RAG](/docs/use_cases/question_answering/)
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- [Extracting structured output](/docs/use_cases/extraction/)
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- [Chatbots](/docs/use_cases/chatbots/)
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- and more!
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## Expression Language
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LangChain Expression Language (LCEL) is the foundation of many of LangChain's components, and is a declarative way to compose chains. LCEL was designed from day 1 to support putting prototypes in production, with no code changes, from the simplest “prompt + LLM” chain to the most complex chains.
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- **[Get started](/docs/expression_language/)**: LCEL and its benefits
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- **[Runnable interface](/docs/expression_language/interface)**: The standard interface for LCEL objects
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- **[Primitives](/docs/expression_language/primitives)**: More on the primitives LCEL includes
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- and more!
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## Ecosystem
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### [🦜🛠️ LangSmith](/docs/langsmith)
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Trace and evaluate your language model applications and intelligent agents to help you move from prototype to production.
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### [🦜🕸️ LangGraph](/docs/langgraph)
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Build stateful, multi-actor applications with LLMs, built on top of (and intended to be used with) LangChain primitives.
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### [🦜🏓 LangServe](/docs/langserve)
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Deploy LangChain runnables and chains as REST APIs.
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## [Security](/docs/security)
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Read up on our [Security](/docs/security) best practices to make sure you're developing safely with LangChain.
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## Additional resources
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### [Components](/docs/modules/)
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LangChain provides standard, extendable interfaces and integrations for many different components, including:
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### [Integrations](/docs/integrations/providers/)
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LangChain is part of a rich ecosystem of tools that integrate with our framework and build on top of it. Check out our growing list of [integrations](/docs/integrations/providers/).
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### [Guides](/docs/guides/)
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Best practices for developing with LangChain.
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### [API reference](https://api.python.langchain.com)
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Head to the reference section for full documentation of all classes and methods in the LangChain and LangChain Experimental Python packages.
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### [Contributing](/docs/contributing)
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Check out the developer's guide for guidelines on contributing and help getting your dev environment set up.
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