วีดีโอ

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Unfortunately, I only do Python on this channel. It shouldn't be too hard to convert the code to JS though using even ChatGPT.

Love you too!

Thank you! Cheers!

Thank you for the kind words. Yes, if you use Ollama models like we did on the video, then your content will stay private and not be sent to any online service. To be sure, I'd recommend turning off your WiFi or any connection once you've loaded all the dependencies and imports. You can then run the cells to lead your PDF to a vector db and chat with it. After you're done, you can delete the collection where you saved the vectors of your PDF before turning your connection back on. This is an extra measure to give you peace of mind.

So it seems to be an issue with Ollama installation on Windows. I haven't tried installing Ollama on Windows but might be a good time to add a tutorial on that, maybe. Have you tried watching other tutorials or docs on how to set up Ollama on Windows?

@@tonykipkemboi okay that’s kind of you. The problem is not with installation I guess, im successfuly running on powershell and command prompt. The message is appearing on colab notebook.

@@Justme-dk7vm ah I see. So you're using it in colab instead of "Jupyter Lab" locally? I would suggest starting with using it on Jupyter Lab. You just need to install it using "pip install jupyterlab". I haven't ran it on colab but am sure it's possible.

@@tonykipkemboi Okay thankyou so much. I was just scrolling through your videos, it amazed me, you are damn Sir ❤️I would love to get connected with you on linkedin, could you please provide the link.

@@tonykipkemboi hey I tried on Jupyter lab today as you said, I'm not getting that error like previous. But when I entered a query, its taking so much time to load. How to resolve this?

You can definitely replace chroma with any other db like Weaviate or Qdrant or Milvus and so on.

Thanx man ! It worked 👌

@@nitinkhanna9754 awesome!

Ah yes, good idea. I think for this, you'll have to add citations. I'm early into playing with this as I am working on the Streamlit UI for RAG. Always good to have cited sources.

Thank you 😊

Thank you. Have you tried using chatgpt to troubleshoot?

Glad you found it helpful. For different file types, you would consider the loading/parsing and chunking strategies that fit those data types. I'm working on the next video which I will go over CSV & Excel RAG.

yes and yes

That is correct. I did not change the code after testing it previously with loading individual pages. You can load by page and add metadata that way.

@@tonykipkemboi but cool tutorial for summarisation using a multi query retriever. I didn't know this was a thing in langchain

@@madhudson1 thank you. Yes, it's a neat function

Yes you can use llama3.

Thanks ✌️

Awesome 🤩 Love to hear that! Did you experiment without using the MultiQueryRetriever in the tutorial to see the difference?

@@tonykipkemboi That's an interesting question. I tried and found that MultiQueryRetriever works well in general, when LLM needs to connect indirect information from document, but fails to provide relevant information for direct information present in the document. But, this observation could differ case to case.

Did you mean to say it takes time to upload the documents to vector store and query over them? If yes, I do agree with you that latency is an issue especially since we're adding another layer of retrieval using the MultiQueryRetriever. It would also depend on your system as well if you're using Ollama.

❤️🫡

Thank you. Yes that would be cool. I can see the challenge coming from finding an open source model that is good at multiple languages. The ones I used are not great at all. For voice, it'd probably be easy to use an open source TTS or even be more granular and use 11labs for a better quality in spite of it not being local.

Thank you! 😊 I noticed that I didn't adjust my gain after I had posted. Thanks for your feedback.

Yes, all the stuff in the video is running locally

We do use Chroma in the tutorial.

😎 thank you brother! Yes, got a lot of ideas floating around that I need to start working on. Once most of my summer work travel is done I'll be back to the video grind.

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Python 3.9

Kabisa bro 😎

@@tonykipkemboi am, vouching for u bro, kitu yoyote mpya about Ai, LLMs, etc ikitokea, we weka hapa asap, we're fully behind you

I'm going to probably work on it next month. I've been traveling a lot for work the last few weeks and have time had time to shoot.

@@tonykipkemboi Much awaited! Its a special request please try to release it as early as you can.

@@tonykipkemboi yes bro, waiting for that

You can try installing them directly on your system using the terminal or close the notebook and restart.

Thank you so much

Can I ask one more question I get all good. But in the last chain.invoke when I ask the questions it is taking a very long time to run and there pops up an error. __init__() takes 1 positional argument but 2 were given. Can you help me with that as well?

@@hibakabeer1685 so the latency is potentially introduced because we used the MultiQueryRetriever function which generates 5 more queries similar to your original question then sends them to the vector db to get context on them too. For the error, can you show me the code portion that is failing and also add the full error message?

Sure

The error message indicates a conflict between the versions of `imageio` and `Pillow` packages. Here's how you can resolve this issue: 1. **Uninstall the current version of Pillow:** ```bash !pip uninstall pillow -y ``` 2. **Install the compatible version of Pillow required by imageio:** ```bash !pip install pillow==10.0.0 ``` 3. **Reinstall imageio to ensure all dependencies are correctly aligned:** ```bash !pip install imageio --upgrade ``` Here’s how you can run these commands in a Colab cell: ```python !pip uninstall pillow -y !pip install pillow==10.0.0 !pip install imageio --upgrade ``` This sequence will uninstall the conflicting version of `Pillow`, install a compatible version, and ensure `imageio` is up to date. This should resolve the dependency conflict you are encountering. Let me know if it works.

@@tonykipkemboi tks a lot

I haven't tested it with many documents but will do.

Will appreciate a lot. Much love from Kenya btw😃

@@AfrivisionMediake 🫡

🙏

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Do you have one agent create a response and you're trying to pass that to the next agent? If yes, then you can add the response file to the tasks.yaml file with explicit instructions for it to pass that output to the next agent.

Glad you share the same humour 🤣

Sorry to hear the troubles but this is very common. Have you tried setting the temperature of the model to 0? That way there's no room for it to be creative.

@@tonykipkemboi Interesting, I'll look into that thanks!

@@user-eh2zd2ih8v let me know what comes of it.