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docs: link to langgraph platform (#28150)

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Link to langgraph platform
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Eugene Yurtsev 2024-11-16 22:37:58 -05:00 committed by GitHub
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README.md
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@ -129,7 +129,7 @@ Please see [here](https://python.langchain.com) for full documentation, which in
- [🦜🛠️ 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/): Create stateful, multi-actor applications with LLMs. Integrates smoothly with LangChain, but can be used without it.
- [🦜🏓 LangServe](https://python.langchain.com/docs/langserve): Deploy LangChain runnables and chains as REST APIs.
- [🦜🕸️ LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/#langgraph-platform): Deploy LLM applications built with LangGraph into production.
## 💁 Contributing

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docs/docs/introduction.mdx
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@ -33,7 +33,7 @@ Concretely, the framework consists of the following open-source libraries:
- **`langchain`**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
- **`langchain-community`**: Third-party integrations that are community maintained.
- **[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.
- **[LangGraphPlatform](https://langchain-ai.github.io/langgraph/concepts/#langgraph-platform)**: Deploy LLM applications built with LangGraph to production.
- **[LangSmith](https://docs.smith.langchain.com)**: A developer platform that lets you debug, test, evaluate, and monitor LLM applications.