Llama Stack: Building RAG Agents from Meta

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  • Опубліковано 9 січ 2025

КОМЕНТАРІ • 5

  • @AIFunFactsForAll
    @AIFunFactsForAll  4 дні тому

    Get the notebook for free:
    upaspro.com/llama-stack-building-rag-agents-from-meta/

  • @omidmohaseb8561
    @omidmohaseb8561 День тому

    So perfect

  • @Moonirrastegar
    @Moonirrastegar 4 дні тому

    Is there an actual difference between this and others like LangChain. I wonder if there is a benchmark for comparing performance of RAGs

    • @AIFunFactsForAll
      @AIFunFactsForAll  4 дні тому

      As I mentioned, it is best-spoke for Llama models. Also, they are handling compatibility of funciton calling in a systematic way. There are different RAG benchmark. I saw CRAG (arxiv.org/pdf/2406.04744) in Neurips, there are some other ones like RAGBench (arxiv.org/pdf/2407.11005)

  • @sanazagand7606
    @sanazagand7606 3 дні тому

    They are advocating for function calling but in their website they haven’t fully covered lots of applicable functions …