From 2b2c230aa1b2158c57ccc39f61adf134b408330b Mon Sep 17 00:00:00 2001 From: guangzhengli Date: Mon, 7 Aug 2023 22:08:57 +0800 Subject: [PATCH] Fix the expired LangChain link. --- pages/techniques/rag.en.mdx | 2 +- pages/techniques/rag.it.mdx | 2 +- pages/techniques/rag.zh.mdx | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/pages/techniques/rag.en.mdx b/pages/techniques/rag.en.mdx index 4694ca5..4ca7f88 100644 --- a/pages/techniques/rag.en.mdx +++ b/pages/techniques/rag.en.mdx @@ -22,4 +22,4 @@ This shows the potential of RAG as a viable option for enhancing outputs of lang More recently, these retriever-based approaches have become more popular and are combined with popular LLMs like ChatGPT to improve capabilities and factual consistency. -You can find a [simple example of how to use retrievers and LLMs for question answering with sources](https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_qa_with_sources.html) from the LangChain documentation. \ No newline at end of file +You can find a [simple example of how to use retrievers and LLMs for question answering with sources](https://python.langchain.com/docs/use_cases/question_answering/how_to/vector_db_qa) from the LangChain documentation. \ No newline at end of file diff --git a/pages/techniques/rag.it.mdx b/pages/techniques/rag.it.mdx index eceeb92..ff5d7bb 100644 --- a/pages/techniques/rag.it.mdx +++ b/pages/techniques/rag.it.mdx @@ -22,4 +22,4 @@ Questo mostra il potenziale di RAG come opzione valida per migliorare gli output Più recentemente, questi approcci basati su recupero sono diventati più popolari e sono combinati con LLM popolari come ChatGPT per migliorare le capacità e la coerenza fattuale. -Puoi trovare un [esempio semplice di come usare i recuperatori e i LLM per rispondere alle domande con le fonti](https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_qa_with_sources.html) dalla documentazione di LangChain. +Puoi trovare un [esempio semplice di come usare i recuperatori e i LLM per rispondere alle domande con le fonti](https://python.langchain.com/docs/use_cases/question_answering/how_to/vector_db_qa) dalla documentazione di LangChain. diff --git a/pages/techniques/rag.zh.mdx b/pages/techniques/rag.zh.mdx index f7a5fb2..82c11b0 100644 --- a/pages/techniques/rag.zh.mdx +++ b/pages/techniques/rag.zh.mdx @@ -22,4 +22,4 @@ RAG 在 [Natural Questions](https://ai.google.com/research/NaturalQuestions)、[ 最近,基于检索器的方法越来越流行,经常与 ChatGPT 等流行 LLM 结合使用来提高其能力和事实一致性。 -LangChain 文档中可以找到[一个使用检索器和 LLM 回答问题并给出知识来源的简单例子](https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_qa_with_sources.html)。 +LangChain 文档中可以找到[一个使用检索器和 LLM 回答问题并给出知识来源的简单例子](https://python.langchain.com/docs/use_cases/question_answering/how_to/vector_db_qa)。