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feat: add autoflow in rag section (#261)
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@ -264,13 +264,16 @@ English/[简体中文](https://github.com/deepseek-ai/awesome-deepseek-integrati
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<td> <a href="https://github.com/deepseek-ai/awesome-deepseek-integration/blob/main/docs/ragflow/README.md"> RAGFlow </a> </td>
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<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>
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</tr>
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<tr>
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<td> <img src="https://raw.githubusercontent.com/pingcap/tidb.ai/main/frontend/app/public/nextra/icon-dark.svg" alt="Icon" width="64" height="auto" /> </td>
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<td> <a href="https://github.com/deepseek-ai/awesome-deepseek-integration/blob/main/docs/autoflow/README.md"> Autoflow </a> </td>
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<td> <a href="https://github.com/pingcap/autoflow">AutoFlow</a> is an open-source knowledge base tool based on GraphRAG (Graph-based Retrieval-Augmented Generation), built on <a href="https://www.pingcap.com/ai?utm_source=tidb.ai&utm_medium=community">TiDB</a> Vector, LlamaIndex, and DSPy. It provides a Perplexity-like search interface and allows easy integration of AutoFlow's conversational search window into your website by embedding a simple JavaScript snippet. </td>
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</tr>
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<tr>
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<td> <img src="https://assets.zilliz.com/Zilliz_Logo_Mark_White_20230223_041013_86057436cc.png" alt="Icon" width="64" height="auto" /> </td>
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<td> <a href="https://github.com/zilliztech/deep-searcher"> DeepSearcher </a> </td>
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<td> DeepSearcher combines powerful LLMs (DeepSeek, OpenAI, etc.) and Vector Databases (Milvus, etc.) to perform search, evaluation, and reasoning based on private data, providing highly accurate answer and comprehensive report. </td>
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</tr>
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</table>
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### Solana frameworks
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@ -186,6 +186,11 @@
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<td> <a href="https://github.com/deepseek-ai/awesome-deepseek-integration/blob/main/docs/ragflow/README_cn.md"> RAGFlow </a> </td>
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<td> 一款基于深度文档理解构建的开源 RAG（Retrieval-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>
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</tr>
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<tr>
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<td> <img src="https://raw.githubusercontent.com/pingcap/tidb.ai/main/frontend/app/public/nextra/icon-dark.svg" alt="Icon" width="64" height="auto" /> </td>
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<td> <a href="https://github.com/deepseek-ai/awesome-deepseek-integration/blob/main/docs/autoflow/README_cn.md"> Autoflow </a> </td>
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<td> <a href="https://github.com/pingcap/autoflow">AutoFlow</a> 是一个开源的基于 GraphRAG 的知识库工具，构建于 <a href="https://www.pingcap.com/ai?utm_source=tidb.ai&utm_medium=community">TiDB</a> Vector、LlamaIndex 和 DSPy 之上。提供类 Perplexity 的搜索页面，并可以嵌入简单的 JavaScript 代码片段，轻松将 Autoflow 的对话式搜索窗口集成到您的网站。 </td>
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</tr>
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<tr>
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<td> <img src="https://assets.zilliz.com/Zilliz_Logo_Mark_White_20230223_041013_86057436cc.png" alt="Icon" width="64" height="auto" /> </td>
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<td> <a href="https://github.com/zilliztech/deep-searcher"> DeepSearcher </a> </td>
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@ -173,6 +173,11 @@ DeepSeek API を人気のソフトウェアに統合します。API キーを取
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<td> <a href="https://github.com/deepseek-ai/awesome-deepseek-integration/blob/main/docs/ragflow/README.md"> RAGFlow </a> </td>
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<td> 深い文書理解に基づいたオープンソースのRAG（Retrieval-Augmented Generation）エンジン。RAGFlowは、あらゆる規模の企業や個人に対して、ユーザーのさまざまな複雑な形式のデータに対して信頼性のある質問応答と根拠のある引用を提供するための簡素化されたRAGワークフローを提供します。 </td>
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</tr>
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<tr>
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<td> <img src="https://raw.githubusercontent.com/pingcap/tidb.ai/main/frontend/app/public/nextra/icon-dark.svg" alt="Icon" width="64" height="auto" /> </td>
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<td> <a href="https://github.com/deepseek-ai/awesome-deepseek-integration/blob/main/docs/autoflow/README.md"> Autoflow </a> </td>
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<td> <a href="https://github.com/pingcap/autoflow">AutoFlow</a> は、GraphRAGに基づくオープンソースのナレッジベースツールであり、<a href="https://www.pingcap.com/ai?utm_source=tidb.ai&utm_medium=community">TiDB</a> Vector、LlamaIndex、DSPy の上に構築されています。Perplexity のような検索インターフェースを提供し、シンプルな JavaScript スニペットを埋め込むことで、AutoFlow の対話型検索ウィンドウを簡単にウェブサイトに統合できます。 </td>
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</tr>
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<tr>
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<td> <img src="https://assets.zilliz.com/Zilliz_Logo_Mark_White_20230223_041013_86057436cc.png" alt="Icon" width="64" height="auto" /> </td>
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<td> <a href="https://github.com/zilliztech/deep-searcher"> DeepSearcher </a> </td>
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23
docs/autoflow/README.md
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docs/autoflow/README.md
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# Autoflow
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<a href="https://trendshift.io/repositories/12294" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12294" alt="pingcap%2Fautoflow | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
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[AutoFlow](https://github.com/pingcap/autoflow) is an open-source knowledge base tool based on GraphRAG (Graph-based Retrieval-Augmented Generation), built on [TiDB](https://www.pingcap.com/ai?utm_source=tidb.ai&utm_medium=community) Vector, LlamaIndex, and DSPy. It provides a Perplexity-like search interface and allows easy integration of AutoFlow's conversational search window into your website by embedding a simple JavaScript snippet.
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## UI
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1. **Perplexity-style Conversational Search page**: Our platform features an advanced built-in website crawler, designed to elevate your browsing experience. This crawler effortlessly navigates official and documentation sites, ensuring comprehensive coverage and streamlined search processes through sitemap URL scraping.
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2. **Embeddable JavaScript Snippet**: Integrate our conversational search window effortlessly into your website by copying and embedding a simple JavaScript code snippet. This widget, typically placed at the bottom right corner of your site, facilitates instant responses to product-related queries.
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## Integrate with Deepseek API
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- Click the tab `Models` then `LLMs` to enter the LLM model management page.
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- Click the `Create` button to create a new LLM model.
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- Input data like below, then click the `Create LLM` button.
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23
docs/autoflow/README_cn.md
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docs/autoflow/README_cn.md
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# Autoflow
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<a href="https://trendshift.io/repositories/12294" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12294" alt="pingcap%2Fautoflow | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
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[AutoFlow](https://github.com/pingcap/autoflow) 是一个基于 GraphRAG（基于图的检索增强生成）的开源知识库工具，构建于 [TiDB](https://www.pingcap.com/ai?utm_source=tidb.ai&utm_medium=community) Vector、LlamaIndex 和 DSPy 之上。它提供类似 Perplexity 的搜索界面，并允许通过嵌入简单的 JavaScript 代码片段，将 AutoFlow 的对话式搜索窗口轻松集成到您的网站中。
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## UI 界面
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1. **Perplexity 风格的对话式搜索页面**：我们的平台配备了高级内置网站爬虫，旨在提升您的浏览体验。该爬虫能够轻松抓取官方网站和文档站点，通过 sitemap 抓取，实现全面覆盖和高效搜索。
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2. **可嵌入的 JavaScript 代码片段**：通过复制并嵌入一段简单的 JavaScript 代码，即可轻松将我们的对话式搜索窗口集成到您的网站中。此小部件通常放置在网站右下角，可即时回答与产品相关的查询。
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## 集成 Deepseek API
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- 点击 `Models` 选项卡，然后进入 `LLMs` 以进入 LLM 模型管理页面。
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- 点击 `Create` 按钮创建一个新的 LLM 模型。
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- 按照下方示例输入数据，然后点击 `Create LLM` 按钮。
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