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  1. Red Hat Enterprise Linux AI
  2. RHELAI-3483

(draft) [rag] Agentic RAG with Llama Stack

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      Feature Overview
      Implement Agentic RAG with Llama Stack, with capabilities for:

      • multilanguage RAG
      • vision retrieval
      • interaction with granite 3.x vision model

       

      Goals

      • Basic Agentic RAG flow
      • Multi-turn interaction before and after retrieval
      • English, non-English/multilingual
      • Using vectordb over Llama Stack
        • Vectordb should support multimodal RAG
      • Interaction with granite 3.x vision model

       

      Stretched goal:

      • Hybrid Search/Hybrid Retrieval

       

      Requirements

      • Implementation of Agentic RAG using Llama Stack API
        • Llama Stack Client SDK
        • Llama Stack Tool RAG Provider

      Done

       

      Use Cases
      <your text here>

       

      Out of Scope
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      Documentation Considerations
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      Questions to Answer
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              wcabanba@redhat.com William Caban
              wcabanba@redhat.com William Caban
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                Created:
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