Chat with Your Own Data using Langchain and Streamlit

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  • Опубликовано: 12 янв 2025

Комментарии • 16

  • @paullopez_ai
    @paullopez_ai Год назад +3

    Dona - this is one of the most comprehensive videos i’ve seen in quite a while! I like the way you have organized the code in the files, you can tell that you know how to build enterprise apps.

    • @DonaAI
      @DonaAI  Год назад

      Thanks! I am glad you liked it!

  • @nvn1234562009
    @nvn1234562009 Год назад +2

    Thanks for the detailed explanation! Love this series :)

    • @DonaAI
      @DonaAI  Год назад

      Glad you like this series! Comments like yours mean a lot!

  • @EvelynShi-l1b
    @EvelynShi-l1b Год назад +2

    Good learning materials. Very detailed. Thx!

  • @karldergrosse-333
    @karldergrosse-333 Год назад

    Thank you for your guidance, Dona - great tutorial!

  • @purple_bread24
    @purple_bread24 Год назад +2

    Thanks for sharing this! I am learning about chatbots and this is a great tutorial!

    • @DonaAI
      @DonaAI  Год назад

      Glad you enjoyed it!

  • @squarebaga116
    @squarebaga116 Год назад +1

    Great tutorial, thanks. Dona.

  • @gplayerone9591
    @gplayerone9591 Год назад

    Hi! Nice video! thanks for sharing. I just have a question: I'm looking to create an AI agent (chatbot) where I can upload documents (totaling more than 500MB of text storage) and share it as a web application or embed it on a webpage. It should have the following functionalities:
    1) The chatbot should allow users to log in using Google Auth, enabling each person to have their own account to use the chat.
    2) Monetization capabilities to limit the number of queries to the chat to a maximum of 10 in the free plan. Registered users should be able to subscribe to a paid plan for unlimited access to questions (thus requiring an integrated payment gateway).
    3) As the administrator and creator of the chat, I should have access to metrics such as the number of registered users, usage times, most frequent questions or queries, etc.
    And think that, also, it should support usage by many people (more than 1000).
    How would you recommend carrying out this project? Any specific software, application, or method you would suggest?

  • @EvelynSHI-q4u
    @EvelynSHI-q4u Год назад

    Love this. Maybe you should give classes or run some workshops 🙃

  • @sureshm3435
    @sureshm3435 Год назад +1

    i gave a thumb and subscribed 🙂

  • @dbarash1
    @dbarash1 5 месяцев назад

    Thanks a lot for this lesson! I have an issue with ingesting, create_chunks() returns 0 even though pdf documents have been uploaded and saved successfully. Any ideas why this exception: langchain\vectorstores\faiss.py", line 562, in __from
    index = faiss.IndexFlatL2(len(embeddings[0]))
    ~~~~~~~~~~^^^
    IndexError: list index out of range

    • @DonaAI
      @DonaAI  5 месяцев назад

      Check that you are importing `unstructured[all-docs]` and not `unstructured`

  • @zas0987654321
    @zas0987654321 Год назад +1

    Is there an alternative to using Poetry?

    • @DonaAI
      @DonaAI  Год назад +1

      That's a good question. You can also use "pip install". I just find poetry easier to use.