Let’s Build an AI Chatbot for Expo Docs: RAG Tutorial

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  • Опубліковано 21 вер 2024
  • In this video, learn how to build an AI chatbot using Retrieval-Augmented Generation (RAG) systems. We'll guide you through obtaining data from Expo Docs, generating vector embeddings, storing them in a vector database, and performing similarity searches. Finally, we'll integrate everything into a sleek chat UI for both mobile and web using Expo and Expo Router. Ready to get started and build your own AI Chat Bot? 🤖
    ✅ Project Page: www.notjust.de...
    💻 Source Code: github.com/not...
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    📚 This video includes a lot of tools and technologies, providing an excellent opportunity to learn about:
    - RAG systems
    - Gathering data from Expo Docs
    - Generating vector embeddings
    - Storing embeddings in a vector database
    - Performing similarity searches
    - Building a chat User Interface with Expo and Expo Router
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    Disclaimer: This build is for educational purposes only. All views, opinions, and technology choices expressed in this video are my own and do not represent the views, opinions, or technology choices of any entity I have been, am now, or will be affiliated with.
    #notjustdev #aichatbot #reactnative

КОМЕНТАРІ • 14

  • @tref6593
    @tref6593 2 місяці тому

    Awesome project! Thanks Vadim for clarifying RAG

  • @SAMAmUrl
    @SAMAmUrl 3 місяці тому

    Pure pleasure , I have to sleep early for next day Dragon Boat Competition , then Found myself surfing on the presentation Wave. It worth it. Thank you Vadim for making things simpler fro the mere mortal developper,

  • @UnchartedWorlds
    @UnchartedWorlds 3 місяці тому +1

    I'm just going through this one! Perfect tutorial!

  • @ravilamontagne9836
    @ravilamontagne9836 3 місяці тому +1

    Why was it necessary to use the raw text from Github and not just scrap the text from the website? What if you have text stored in a database, how to pass that data to the vector database?

  • @tref6593
    @tref6593 2 місяці тому

    for getting embedding (to get vector from a text)
    BadRequestError: 400 This model's maximum context length is 8192 tokens, however you requested 9193 tokens (9193 in your prompt; 0 for the completion). Please reduce your prompt; or completion length.
    For example for the slug 'modules/module-api' or 'guides/authentication'

  • @user-iy1ch3lv3h
    @user-iy1ch3lv3h 3 місяці тому +2

    When is your ultimate react native course?

  • @birolaydin4731
    @birolaydin4731 3 місяці тому

    Great content. How can we print the answers letter by letter?

  • @felipe86ata
    @felipe86ata 3 місяці тому

    Vadim try to use crewai in a app

  • @reginaldoassuncao
    @reginaldoassuncao 3 місяці тому

    Legends please

  • @YazyPato
    @YazyPato 2 місяці тому

    крутону себе джоинт - крутону связку

  • @xpersion
    @xpersion Місяць тому

    Dusunsene onca meslek gurubu son model araba altlarinda vergiye verdikleri asgari ucretli gibi odeme.. Vah ki vah Halimize... Sonra sozculeri konusur inanirsan