--- 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/expression_language/) and [components](/docs/modules/). Hit the ground running using [third-party integrations](/docs/integrations/platforms/) and [Templates](/docs/templates). - **Productionization**: Use [LangSmith](/docs/langsmith/) 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](/docs/langserve). import ThemedImage from '@theme/ThemedImage'; 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](/docs/langgraph)**: Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. - **[langserve](/docs/langserve)**: Deploy LangChain chains as REST APIs. - **[LangSmith](/docs/langsmith)**: 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](/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) Explore the full list of tutorials [here](/docs/tutorials). ## [How-To Guides](/docs/how_to_guides) [Here](/docs/how_to_guides) 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://api.python.langchain.com/en/latest/). However, these guides will help you quickly accomplish common tasks. ## [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. ## [API reference](https://api.python.langchain.com) Head to the reference section for full documentation of all classes and methods in the LangChain Python packages. ## Ecosystem ### [🦜🛠️ LangSmith](/docs/langsmith) Trace and evaluate your language model applications and intelligent agents to help you move from prototype to production. ### [🦜🕸️ LangGraph](/docs/langgraph) Build stateful, multi-actor applications with LLMs, built on top of (and intended to be used with) LangChain primitives. ### [🦜🏓 LangServe](/docs/langserve) Deploy LangChain runnables and chains as REST APIs. ## Additional resources ## [Security](/docs/security) Read up on our [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.