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docs/docs_skeleton/docs/guides/langsmith/index.md
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import DocCardList from "@theme/DocCardList";
LangSmith helps you trace and evaluate your language model applications and intelligent agents to help you
[LangSmith](https://smith.langchain.com) helps you trace and evaluate your language model applications and intelligent agents to help you
move from prototype to production.
Check out the [interactive walkthrough](/docs/guides/langsmith/walkthrough) below to get started.
For more information, please refer to the [LangSmith documentation](https://docs.smith.langchain.com/)
For more information, please refer to the [LangSmith documentation](https://docs.smith.langchain.com/).
For tutorials and other end-to-end examples demonstrating ways to integrate LangSmith in your workflow,
check out the [LangSmith Cookbook](https://github.com/langchain-ai/langsmith-cookbook). Some of the guides therein include:
- Leveraging user feedback in your JS application ([link](https://github.com/langchain-ai/langsmith-cookbook/blob/main/feedback-examples/nextjs/README.md)).
- Building an automated feedback pipeline ([link](https://github.com/langchain-ai/langsmith-cookbook/blob/main/feedback-examples/algorithmic-feedback/algorithmic_feedback.ipynb)).
- How to evaluate and audit your RAG workflows ([link](https://github.com/langchain-ai/langsmith-cookbook/tree/main/testing-examples/qa-correctness)).
- How to fine-tune a LLM on real usage data ([link](https://github.com/langchain-ai/langsmith-cookbook/blob/main/fine-tuning-examples/export-to-openai/fine-tuning-on-chat-runs.ipynb)).
- How to use the [LangChain Hub](https://smith.langchain.com/hub) to version your prompts ([link](https://github.com/langchain-ai/langsmith-cookbook/blob/main/hub-examples/retrieval-qa-chain/retrieval-qa.ipynb))
<DocCardList />