*   [](/v0.2/)
*   Introduction

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Introduction
============

**LangChain** is a framework for developing applications powered by large language models (LLMs).

LangChain simplifies every stage of the LLM application lifecycle:

*   **Development**: Build your applications using LangChain's open-source [building blocks](/v0.2/docs/concepts/#langchain-expression-language-lcel) and [components](/v0.2/docs/concepts/). Hit the ground running using [third-party integrations](/v0.2/docs/integrations/platforms/) and [Templates](/v0.2/docs/templates/).
*   **Productionization**: Use [LangSmith](https://docs.smith.langchain.com/) to inspect, monitor and evaluate your chains, so that you can continuously optimize and deploy with confidence.
*   **Deployment**: Turn any chain into an API with [LangServe](/v0.2/docs/langserve/).

![Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers.](/v0.2/svg/langchain_stack.svg "LangChain Framework Overview")![Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers.](/v0.2/svg/langchain_stack_dark.svg "LangChain Framework Overview")

Concretely, the framework consists of the following open-source libraries:

*   **`langchain-core`**: Base abstractions and LangChain Expression Language.
*   **`langchain-community`**: Third party integrations.
    *   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`**.
*   **`langchain`**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
*   **[LangGraph](https://langchain-ai.github.io/langgraph)**: Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph.
*   **[LangServe](/v0.2/docs/langserve/)**: Deploy LangChain chains as REST APIs.
*   **[LangSmith](https://docs.smith.langchain.com)**: A developer platform that lets you debug, test, evaluate, and monitor LLM applications.

note

These docs focus on the Python LangChain library. [Head here](https://js.langchain.com) for docs on the JavaScript LangChain library.

[Tutorials](/v0.2/docs/tutorials/)[​](#tutorials "Direct link to tutorials")
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If you're looking to build something specific or are more of a hands-on learner, check out our [tutorials](/v0.2/docs/tutorials/). This is the best place to get started.

These are the best ones to get started with:

*   [Build a Simple LLM Application](/v0.2/docs/tutorials/llm_chain/)
*   [Build a Chatbot](/v0.2/docs/tutorials/chatbot/)
*   [Build an Agent](/v0.2/docs/tutorials/agents/)

Explore the full list of tutorials [here](/v0.2/docs/tutorials/).

[How-to guides](/v0.2/docs/how_to/)[​](#how-to-guides "Direct link to how-to-guides")
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[Here](/v0.2/docs/how_to/) you’ll find short answers to “How do I….?” types of questions. These how-to guides don’t cover topics in depth – you’ll find that material in the [Tutorials](/v0.2/docs/tutorials/) and the [API Reference](https://api.python.langchain.com/en/latest/). However, these guides will help you quickly accomplish common tasks.

[Conceptual guide](/v0.2/docs/concepts/)[​](#conceptual-guide "Direct link to conceptual-guide")
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Introductions to all the key parts of LangChain you’ll need to know! [Here](/v0.2/docs/concepts/) you'll find high level explanations of all LangChain concepts.

[API reference](https://api.python.langchain.com)[​](#api-reference "Direct link to api-reference")
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Head to the reference section for full documentation of all classes and methods in the LangChain Python packages.

Ecosystem[​](#ecosystem "Direct link to Ecosystem")
---------------------------------------------------

### [🦜🛠️ LangSmith](https://docs.smith.langchain.com)[​](#️-langsmith "Direct link to ️-langsmith")

Trace and evaluate your language model applications and intelligent agents to help you move from prototype to production.

### [🦜🕸️ LangGraph](https://langchain-ai.github.io/langgraph)[​](#️-langgraph "Direct link to ️-langgraph")

Build stateful, multi-actor applications with LLMs, built on top of (and intended to be used with) LangChain primitives.

### [🦜🏓 LangServe](/v0.2/docs/langserve/)[​](#-langserve "Direct link to -langserve")

Deploy LangChain runnables and chains as REST APIs.

Additional resources[​](#additional-resources "Direct link to Additional resources")
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### [Security](/v0.2/docs/security/)[​](#security "Direct link to security")

Read up on our [Security](/v0.2/docs/security/) best practices to make sure you're developing safely with LangChain.

### [Integrations](/v0.2/docs/integrations/providers/)[​](#integrations "Direct link to integrations")

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](/v0.2/docs/integrations/providers/).

### [Contributing](/v0.2/docs/contributing/)[​](#contributing "Direct link to contributing")

Check out the developer's guide for guidelines on contributing and help getting your dev environment set up.

[Edit this page](https://github.com/langchain-ai/langchain/edit/master/docs/docs/introduction.mdx)

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Tutorials

](/v0.2/docs/tutorials/)

*   [Tutorials](#tutorials)
*   [How-to guides](#how-to-guides)
*   [Conceptual guide](#conceptual-guide)
*   [API reference](#api-reference)
*   [Ecosystem](#ecosystem)
    *   [🦜🛠️ LangSmith](#️-langsmith)
    *   [🦜🕸️ LangGraph](#️-langgraph)
    *   [🦜🏓 LangServe](#-langserve)
*   [Additional resources](#additional-resources)
    *   [Security](#security)
    *   [Integrations](#integrations)
    *   [Contributing](#contributing)