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96 lines
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96 lines
5.0 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/concepts#langchain-expression-language-lcel), [components](/docs/concepts), and [third-party integrations](/docs/integrations/platforms/).
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Use [LangGraph](/docs/concepts/#langgraph) to build stateful agents with first-class streaming and human-in-the-loop support.
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- **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.
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- **Deployment**: Turn your LangGraph applications into production-ready APIs and Assistants with [LangGraph Cloud](https://langchain-ai.github.io/langgraph/cloud/).
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import ThemedImage from '@theme/ThemedImage';
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import useBaseUrl from '@docusaurus/useBaseUrl';
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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: useBaseUrl('/svg/langchain_stack_062024.svg'),
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dark: useBaseUrl('/svg/langchain_stack_062024_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](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.
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- **[LangServe](/docs/langserve)**: Deploy LangChain chains as REST APIs.
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- **[LangSmith](https://docs.smith.langchain.com)**: A developer platform that lets you debug, test, evaluate, and monitor LLM applications.
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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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## [Tutorials](/docs/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 section](/docs/tutorials).
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This is the best place to get started.
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These are the best ones to get started with:
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- [Build a Simple LLM Application](/docs/tutorials/llm_chain)
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- [Build a Chatbot](/docs/tutorials/chatbot)
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- [Build an Agent](/docs/tutorials/agents)
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- [Introduction to LangGraph](https://langchain-ai.github.io/langgraph/tutorials/introduction/)
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Explore the full list of LangChain tutorials [here](/docs/tutorials), and check out other [LangGraph tutorials here](https://langchain-ai.github.io/langgraph/tutorials/).
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## [How-to guides](/docs/how_to)
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[Here](/docs/how_to) you’ll find short answers to “How do I….?” types of questions.
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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/).
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However, these guides will help you quickly accomplish common tasks.
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Check out [LangGraph-specific how-tos here](https://langchain-ai.github.io/langgraph/how-tos/).
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## [Conceptual guide](/docs/concepts)
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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.
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For a deeper dive into LangGraph concepts, check out [this page](https://langchain-ai.github.io/langgraph/concepts/).
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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 Python packages.
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## Ecosystem
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### [🦜🛠️ LangSmith](https://docs.smith.langchain.com)
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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](https://langchain-ai.github.io/langgraph)
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Build stateful, multi-actor applications with LLMs. Integrates smoothly with LangChain, but can be used without it.
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## Additional resources
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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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### [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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### [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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