RouteLLM: How I Route to The Best Model to Cut API Costs

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  • เผยแพร่เมื่อ 22 ม.ค. 2025

ความคิดเห็น • 14

  • @pillowbug999
    @pillowbug999 6 หลายเดือนก่อน +1

    Great Video Nice

    • @GaoDalie_AI
      @GaoDalie_AI  6 หลายเดือนก่อน

      Thank you for watching

  • @GaoDalie_AI
    @GaoDalie_AI  5 หลายเดือนก่อน

    🙏❣join to my Patreon: www.patreon.com/GaoDalie_AI
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  • @StnImg
    @StnImg 6 หลายเดือนก่อน +2

    Dspy, ARAG & latest fusion was ultimate. I built it together based on your guidance & it works amazing. I have a small doubt. Isn't graph rag to be done specifically with Neo4j types Graph DBs or how is it, Can u make a video with Neo4j for better understanding

    • @GaoDalie_AI
      @GaoDalie_AI  6 หลายเดือนก่อน

      hey, thank you for reaching out, please I have made a video about Graph Rag you can check my videos in my profile.

    • @StnImg
      @StnImg 6 หลายเดือนก่อน +3

      ​@@GaoDalie_AISaw Graph RAG too again. I thought Graph can only be stored in Graph DBs like Neo4j. But Rag FUSION+CRAG data is stored in chromadb which is not a Graph DB. This confused me now. I loved the implementation & ur efforts in both the methods. But confusion strikes. How chromadb handles Graph

    • @GaoDalie_AI
      @GaoDalie_AI  6 หลายเดือนก่อน +1

      @@StnImg Yes, that is true. In Fusion + CRAG, I use ChromaDB; I didn't use Graph DB. I just understood your question, and I apologize for the misunderstanding. Yes, you can only use Neo4j because their data is stored on their cloud. We just hit the API to extract data. I hope I could answer your question

    • @StnImg
      @StnImg 5 หลายเดือนก่อน +2

      Boss, i finally understood your implementation after understanding indepth on GraphDB. Your implementation is more of a procedure oriented & if I have to persist the nodes, relationship & proprties, I need to employ Neo4j DB. I added Neo4j, modified chroma to Qdrant to see my embedding & employed crew ai agents. Also added Redis caching & celery Message broker & added enhancements to make it an adaptive RAG with my trained NLP model as one more layer to refine. I'm getting the best of the best results.🎉🎉🎉

    • @GaoDalie_AI
      @GaoDalie_AI  5 หลายเดือนก่อน +2

      @@StnImg bro you are a rock star , i appreciate your hardworking , would you like to share the code with me to take a look how you did it thanks

  • @CaptTerrific
    @CaptTerrific 6 หลายเดือนก่อน +1

    I'm trying to understand the use case for this - in most situations where you are orchestrating across LLMs, you will have enough consistency in query structure that you probably would have more success leveraging traditional NLP and business rules for routing. While the benefits of the LLM learning to improve its routing from user patterns seems useful at first glance, that's still a lot of inconsistency we desperately want to avoid when making these decisions, lest we send "code me a website showing our menu" to the 4B "food/menu expert" instead of the "web dev" expert even 1% of the time.
    Maybe I lack the imagination for where an LLM is better here? Because the only situation I can imagine is for facing a generalized userbase with generalized queries, which none of us are likely ever going to compete with :D

  • @Username56291
    @Username56291 6 หลายเดือนก่อน +1

    hello quick question will you guide me with resources if i patreon for your discord? i couldnt run the model i bought(my fault)

    • @GaoDalie_AI
      @GaoDalie_AI  6 หลายเดือนก่อน

      Hey, thank you for reaching out. Yes, I can assist you if you subscribe to Rainbow Superstar or Diamond Superstar. I also have a Discord for free users where I share information, but I do not provide assistance or help there.

  • @brianrowe1152
    @brianrowe1152 5 หลายเดือนก่อน +1

    This video basically creates mis-information. Not for practitioners. RouteLLM doesn't really do what they suggest. You can only choose between 2 llms.

    • @GaoDalie_AI
      @GaoDalie_AI  5 หลายเดือนก่อน

      Thank you for watching. I don't know where I created misinformation, but if you look carefully, you will see I highlighted two models: a weak model and a strong model, which are two LLMs you can choose from. Thanks again, and welcome to join us