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docs: update README/intro (langchain-ai#29492)
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README.md

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- **Integration packages** (e.g. **`langchain-openai`**, **`langchain-anthropic`**, etc.): Important integrations have been split into lightweight packages that are co-maintained by the LangChain team and the integration developers.
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- **`langchain`**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
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- **`langchain-community`**: Third-party integrations that are community maintained.
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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. To learn more about LangGraph, check out our first LangChain Academy course, *Introduction to LangGraph*, available [here](https://academy.langchain.com/courses/intro-to-langgraph).
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- **[LangGraph](https://langchain-ai.github.io/langgraph)**: LangGraph powers production-grade agents, trusted by Linkedin, Uber, Klarna, GitLab, and many more. 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. To learn more about LangGraph, check out our first LangChain Academy course, *Introduction to LangGraph*, available [here](https://academy.langchain.com/courses/intro-to-langgraph).
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### Productionization:
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docs/docs/introduction.mdx

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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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Build stateful, multi-actor applications with LLMs. Integrates smoothly with LangChain, but can be used without it. LangGraph powers production-grade agents, trusted by Linkedin, Uber, Klarna, GitLab, and many more.
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## Additional resources
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