Signed-off-by: Jin Hai <haijin.chn@gmail.com>
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Jin Hai 2024-05-20 20:58:00 +08:00
parent 70574c2139
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@ -48,8 +48,8 @@ English/[简体中文](https://github.com/deepseek-ai/awesome-deepseek-integrati
### RAG framework
<table>
<tr>
<td> <img src="https://github.com/deepseek-ai/awesome-deepseek-integration/assets/33142505/77093e84-9f7c-4716-9168-bac962fa1372" alt="Icon" width="160" height="auto" /> </td>
<td> <a href="https://github.com/infiniflow/ragflow">RAGFlow</a> </td>
<td> <img src="https://github.com/deepseek-ai/awesome-deepseek-integration/assets/33142505/77093e84-9f7c-4716-9168-bac962fa1372" alt="Icon" width="64" height="auto" /> </td>
<td> <a href="https://github.com/deepseek-ai/awesome-deepseek-integration/blob/main/docs/ragflow/README.md"> RAGFlow </a> </td>
<td> An open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data. </td>
</tr>
</table>

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### RAG 框架
<table>
<tr>
<td> <img src="https://github.com/deepseek-ai/awesome-deepseek-integration/assets/33142505/77093e84-9f7c-4716-9168-bac962fa1372" alt="Icon" width="160" height="auto" /> </td>
<td> <a href="https://github.com/infiniflow/ragflow">RAGFlow</a> </td>
<td> <img src="https://github.com/deepseek-ai/awesome-deepseek-integration/assets/33142505/77093e84-9f7c-4716-9168-bac962fa1372" alt="Icon" width="64" height="auto" /> </td>
<td> <a href="https://github.com/deepseek-ai/awesome-deepseek-integration/blob/main/docs/ragflow/README_cn.md"> RAGFlow </a> </td>
<td> 一款基于深度文档理解构建的开源 RAGRetrieval-Augmented Generation引擎。RAGFlow 可以为各种规模的企业及个人提供一套精简的 RAG 工作流程结合大语言模型LLM针对用户各类不同的复杂格式数据提供可靠的问答以及有理有据的引用。 </td>
</tr>
</table>

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<img src="https://github.com/deepseek-ai/awesome-deepseek-integration/assets/33142505/77093e84-9f7c-4716-9168-bac962fa1372" alt="Icon" width="64" height="auto" />
# [RAGFlow](https://github.com/infiniflow/ragflow)
An open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data.
## UI
![image](https://github.com/deepseek-ai/awesome-deepseek-integration/assets/33142505/a69ce143-931c-4a75-b129-f6a1ddd114a2)
## Integrate with Deepseek API
![image](https://github.com/deepseek-ai/awesome-deepseek-integration/assets/33142505/49dc1916-c3c2-470a-a3ea-b5877de52958)

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<img src="https://github.com/deepseek-ai/awesome-deepseek-integration/assets/33142505/77093e84-9f7c-4716-9168-bac962fa1372" alt="Icon" width="64" height="auto" />
# [RAGFlow](https://github.com/infiniflow/ragflow)
一款基于深度文档理解构建的开源 RAGRetrieval-Augmented Generation引擎。RAGFlow 可以为各种规模的企业及个人提供一套精简的 RAG 工作流程结合大语言模型LLM针对用户各类不同的复杂格式数据提供可靠的问答以及有理有据的引用。
## UI
![image](https://github.com/deepseek-ai/awesome-deepseek-integration/assets/33142505/a69ce143-931c-4a75-b129-f6a1ddd114a2)
## 配置 Deepseek API
![image](https://github.com/deepseek-ai/awesome-deepseek-integration/assets/33142505/514b87e3-2eef-4dd2-b21d-88bb3f381573)