Update agent eval tutorial #582
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baskaryan
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Dec 11, 2024
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| _set_env("LANGCHAIN_API_KEY") | ||
| _set_env("OPENAI_API_KEY") | ||
| #endregion | ||
| ``` | ||
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Suggested change
| While we're using OpenAI for this example, you can use any [LangChain supported chat model](https://python.langchain.com/docs/integrations/chat/#all-chat-models). |
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nothing looks openai dependent from a quick skim but need to confirm if true
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i dont know if we should even say that you need to use langchain. yes this code is langchain-based but you could apply all the same techniques without it, from langsmith perspective it doesn't matter if you use langchain
Co-authored-by: Tanushree <[email protected]>
Co-authored-by: Tanushree <[email protected]>
isahers1
reviewed
Dec 18, 2024
isahers1
reviewed
Dec 18, 2024
isahers1
reviewed
Dec 18, 2024
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| # Grade prompt | ||
| grade_prompt_answer_accuracy = prompt = hub.pull("langchain-ai/rag-answer-vs-reference") | ||
| You can see what these results look like here: [LangSmith link](https://smith.langchain.com/public/708d08f4-300e-4c75-9677-c6b71b0d28c9/d). |
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I think embedding the link on the word "here" makes more sense to me
…/langsmith-docs into bagatur/eval_agent_tutorial
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