---
sidebar_position: 0
sidebar_class_name: hidden
---

# 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](/docs/concepts#langchain-expression-language-lcel), [components](/docs/concepts), and [third-party integrations](/docs/integrations/platforms/).
Use [LangGraph](/docs/concepts/#langgraph) to build stateful agents with first-class streaming and human-in-the-loop support.
- **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 your LangGraph applications into production-ready APIs and Assistants with [LangGraph Cloud](https://langchain-ai.github.io/langgraph/cloud/).

import ThemedImage from '@theme/ThemedImage';
import useBaseUrl from '@docusaurus/useBaseUrl';

<ThemedImage
  alt="Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers."
  sources={{
    light: useBaseUrl('/svg/langchain_stack_062024.svg'),
    dark: useBaseUrl('/svg/langchain_stack_062024_dark.svg'),
  }}
  style={{ width: "100%" }}
  title="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. Integrates smoothly with LangChain, but can be used without it.
- **[LangServe](/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](/docs/tutorials)

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

These are the best ones to get started with:

- [Build a Simple LLM Application](/docs/tutorials/llm_chain)
- [Build a Chatbot](/docs/tutorials/chatbot)
- [Build an Agent](/docs/tutorials/agents)
- [Introduction to LangGraph](https://langchain-ai.github.io/langgraph/tutorials/introduction/)

Explore the full list of LangChain tutorials [here](/docs/tutorials), and check out other [LangGraph tutorials here](https://langchain-ai.github.io/langgraph/tutorials/).


## [How-to guides](/docs/how_to)

[Here](/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](/docs/tutorials) and the [API Reference](https://python.langchain.com/v0.2/api_reference/).
However, these guides will help you quickly accomplish common tasks.

Check out [LangGraph-specific how-tos here](https://langchain-ai.github.io/langgraph/how-tos/).

## [Conceptual guide](/docs/concepts)

Introductions to all the key parts of LangChain you’ll need to know! [Here](/docs/concepts) you'll find high level explanations of all LangChain concepts.

For a deeper dive into LangGraph concepts, check out [this page](https://langchain-ai.github.io/langgraph/concepts/).

## [API reference](https://python.langchain.com/v0.2/api_reference/)
Head to the reference section for full documentation of all classes and methods in the LangChain Python packages.

## Ecosystem

### [🦜🛠️ LangSmith](https://docs.smith.langchain.com)
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)
Build stateful, multi-actor applications with LLMs. Integrates smoothly with LangChain, but can be used without it.

## Additional resources

### [Versions](/docs/versions/overview/)
See what changed in v0.2, learn how to migrate legacy code, and read up on our release/versioning policies, and more.

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

### [Integrations](/docs/integrations/providers/)
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/).

### [Contributing](/docs/contributing)
Check out the developer's guide for guidelines on contributing and help getting your dev environment set up.
