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    <title>DEV Community: Abdelrahman Abdallah</title>
    <description>The latest articles on DEV Community by Abdelrahman Abdallah (@abdelrahman_abdallah_7593).</description>
    <link>https://dev.to/abdelrahman_abdallah_7593</link>
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      <title>DEV Community: Abdelrahman Abdallah</title>
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      <title>Rankify: The All-in-One Toolkit for Retrieval, Re-Ranking, and RAG</title>
      <dc:creator>Abdelrahman Abdallah</dc:creator>
      <pubDate>Fri, 28 Feb 2025 11:31:45 +0000</pubDate>
      <link>https://dev.to/abdelrahman_abdallah_7593/rankify-the-all-in-one-toolkit-for-retrieval-re-ranking-and-rag-1724</link>
      <guid>https://dev.to/abdelrahman_abdallah_7593/rankify-the-all-in-one-toolkit-for-retrieval-re-ranking-and-rag-1724</guid>
      <description>&lt;p&gt;We’re thrilled to introduce Rankify 🎉—a comprehensive, modular, and open-source Python framework that unifies retrieval, re-ranking, and retrieval-augmented generation (RAG) into a single powerful ecosystem.&lt;/p&gt;

&lt;p&gt;Rankify is designed for researchers, engineers, and AI practitioners working on search engines, question-answering, and knowledge-based text generation. Our goal is to provide a unified and scalable toolkit that simplifies benchmarking, experimentation, and deployment across state-of-the-art retrieval and ranking models.&lt;/p&gt;

&lt;p&gt;🔗 Paper: Read on &lt;a href="https://arxiv.org/abs/2502.02464" rel="noopener noreferrer"&gt;arXiv &lt;/a&gt;&lt;br&gt;
🔗 GitHub: View the &lt;a href="https://github.com/DataScienceUIBK/Rankify/tree/main" rel="noopener noreferrer"&gt;Repository&lt;/a&gt;&lt;br&gt;
🔗 Docs: Comprehensive &lt;a href="https://rankify.readthedocs.io/en/latest/" rel="noopener noreferrer"&gt;Documentation&lt;/a&gt;&lt;/p&gt;

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      <title>Rankify: The All-in-One Toolkit for Retrieval, Re-Ranking, and RAG</title>
      <dc:creator>Abdelrahman Abdallah</dc:creator>
      <pubDate>Fri, 28 Feb 2025 02:05:58 +0000</pubDate>
      <link>https://dev.to/abdelrahman_abdallah_7593/rankify-the-all-in-one-toolkit-for-retrieval-re-ranking-and-rag-1472</link>
      <guid>https://dev.to/abdelrahman_abdallah_7593/rankify-the-all-in-one-toolkit-for-retrieval-re-ranking-and-rag-1472</guid>
      <description>&lt;p&gt;We’re thrilled to introduce Rankify 🎉—a comprehensive, modular, and open-source Python framework that unifies retrieval, re-ranking, and retrieval-augmented generation (RAG) into a single powerful ecosystem.&lt;/p&gt;

&lt;p&gt;Rankify is designed for researchers, engineers, and AI practitioners working on search engines, question-answering, and knowledge-based text generation. Our goal is to provide a unified and scalable toolkit that simplifies benchmarking, experimentation, and deployment across state-of-the-art retrieval and ranking models.&lt;/p&gt;

&lt;p&gt;🔗 Paper: Read on &lt;a href="https://arxiv.org/abs/2502.02464" rel="noopener noreferrer"&gt;arXiv &lt;/a&gt;&lt;br&gt;
🔗 GitHub: View the &lt;a href="https://github.com/DataScienceUIBK/Rankify/tree/main" rel="noopener noreferrer"&gt;Repository&lt;/a&gt;&lt;br&gt;
🔗 Docs: Comprehensive &lt;a href="https://rankify.readthedocs.io/en/latest/" rel="noopener noreferrer"&gt;Documentation&lt;/a&gt;&lt;/p&gt;

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    <item>
      <title>🚀 Announcing Rankify: The All-in-One Toolkit for Retrieval, Re-Ranking, and RAG</title>
      <dc:creator>Abdelrahman Abdallah</dc:creator>
      <pubDate>Thu, 27 Feb 2025 20:54:11 +0000</pubDate>
      <link>https://dev.to/abdelrahman_abdallah_7593/announcing-rankify-the-all-in-one-toolkit-for-retrieval-re-ranking-and-rag-1jma</link>
      <guid>https://dev.to/abdelrahman_abdallah_7593/announcing-rankify-the-all-in-one-toolkit-for-retrieval-re-ranking-and-rag-1jma</guid>
      <description>&lt;p&gt;We’re thrilled to introduce Rankify 🎉—a comprehensive, modular, and open-source Python framework that unifies retrieval, re-ranking, and retrieval-augmented generation (RAG) into a single powerful ecosystem.&lt;/p&gt;

&lt;p&gt;Rankify is designed for researchers, engineers, and AI practitioners working on search engines, question-answering, and knowledge-based text generation. Our goal is to provide a unified and scalable toolkit that simplifies benchmarking, experimentation, and deployment across state-of-the-art retrieval and ranking models.&lt;/p&gt;

&lt;p&gt;🔗 Paper: Read on &lt;a href="https://arxiv.org/abs/2502.02464" rel="noopener noreferrer"&gt;arXiv &lt;/a&gt;&lt;br&gt;
🔗 GitHub: View the &lt;a href="https://github.com/DataScienceUIBK/Rankify/tree/main" rel="noopener noreferrer"&gt;Repository&lt;/a&gt;&lt;br&gt;
🔗 Docs: Comprehensive &lt;a href="https://rankify.readthedocs.io/en/latest/" rel="noopener noreferrer"&gt;Documentation&lt;/a&gt;&lt;/p&gt;

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      <category>python</category>
      <category>ai</category>
      <category>openai</category>
      <category>rag</category>
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