Yes. It runs on our local computer and does not need internet for it, Now for sharing it on streamlit cloud is not possible with ollama because streamlit does not let u run ollama there and yes it does not have high resource or GPU. You can deploy Ollama on some cloud instance (Gcloud or AWS) and then access it through API. You can then replace code to access ollama through that cloud instance based URL (base_url parameter). That's one solution. Another solution would be to use OpenAI rest API but it is not free. Recently, I have started using Groq REST API which is free. They provide latest Open source models like Llama-3.1, though there is request limit (30 requests per minute). Also, there models are full and not quantized one like Ollama hence more accurate.

@@CoderzColumn aahh i see, so we can build and host our model in server that have high resource, then we use it as rest API for streamlit web app that we share, thx for explain.

Yea. You can use it other platforms than Streamlit because just like openai API, your models are available through API. You can even create models for custom uses. But i feel the cloud instance are bit pricey. You'll need good instance with 16/32/64 GB RAM and one with high GPU RAM. The cost increases fastly with specs. You know if you have some spare system with GPU lying around then you can use it as well.You'll have to keep it on all the time and initially, you'll have to do few firewall settings to make it accessible to outside world on internet. This one can be cheaper hopefully but you'll still have to pay for electricity for keeping this system on (which has GPU hence more electricity usage).

@@CoderzColumn yep you right, even if we make own server to host Rest API, we can use it for any use case. thx for response

Thanks for your feedback. Really Appreciate it.

Thanks for your feedback. Really Appreciate it.

Yes, definitely you can use it with Plotly. It'll work fine. Also, I think that with plotly, if you use FigureWidget by wrapping figure object inside it then it'll be better. Check out this article. plotly.com/python/getting-started/#jupyter-notebook-support

@@CoderzColumn You are nice! Thanks you for your help. greetings from Perú

No probs. Hope my answer help you solve the problem.

Glad you enjoyed it!

If you have set max_instance in config file to 1 then it won't cost you anything. But if you increase count of instances then it'll charge based on usage of instance. I have included info about instance charge pages in video. Please feel free to check them to know more about charges. But with just one instance running, it comes under free tier hence no charges.

Thanks for comment.

Thanks for the feedback. Appreciate it.

I think that when you load transcripts, you can load it in chunks and then create vector store using it. That way you can retrieve timestamps from retrieved relevant documents. Start time of chunk is available as metadata. It'll require bit of coding changes. It won't be accurate but near to answer.

Thanks for taking time to comment !! Really appreciate it !!!

Thanks for taking time to comment !! Really appreciate it !!!

Thanks for taking time to comment !! Really appreciate it !!!

Thank you 🙂

Thanks for feedback. Appreciate it. In this tutorial, I have used Groq API for accessing LlaMa-3 hence you should be able to run it even with 2 GB RAM. Because it'll hit Groq API for LLM. You'll need to create api-key on groq though. But if you want to use Local LLMs like the one available from Ollama then you'll need around 8 GB of RAM. It'll be better with more than 8GB but 7-8 B parameters model works with 8 GB as well. Good to have i3 or or above processor. But want to inform you that results were not that good with Llama-3 accessed through Ollama. I have tried it. Maybe because it's quantized version. I would suggest you using Groq API.

@@CoderzColumn Thank you .RAG vs fine tuning can you explain the difference please in which situations we use them.

We can use LangGraph as well. In future, I'll try langgraph as well.

Thanks for watching!

Thanks for your feedback. Appreciate it.

Can you share which line of code is failing? Is it something failing from Notebook of tutorial or you are trying something new which is failing? I am not able to understand error from this trace only.

Thanks for the feedback.

Thanks for your comment. Really appreciate it.

Thanks for feedback. I really needed to know this. I'll try to include less bells in intro. I feel i included many this time when things pop up on screen.

Groq provides access to 4 open source LLM (Llama-3 8B & 70B, Gemma 7B & Mistral 8x7B)for free. Groq specializes in hardware creation that speed up token generation for LLMs. These LLMs that they are providing through their API are not theirs but they are open source LLMs which they have deployed on their high performing hardware and provided everyone limited access through API (30 requests per minute). You can login to console.groq.com/settings/limits and check limit for free account. I just now noticed that they added two new models (gemma2 8B and Whisper Large v3). Yes, It's not locally hosted.

@@CoderzColumn Yes, free isn't opensource. I am trying to achieve something locally as I don't want to share my functions with any third party.

Thanks for feedback. Appreciate it.

Thanks for feedback. I have code present in one my blog. Here's link * coderzcolumn.com/tutorials/data-science/timeline-using-matplotlib I included it in description as well. This is one of my earlier videos where I forgot to include code. Hope this helps.

Glad it was helpful!

Thanks for the comment. Ideally, if you want to include chart in your Django website, I would recommend to use some Javascript library like Amcharts, d3.js, etc. I have found that it works better with django. But it'll require you to learn javascript though charts are pretty looking. Bokeh is good solution if you want to code in Python for charts and want to include them in django website. At the end of the day, it is javascript based as well. Happy to hear that my tutorial helped you.

@@CoderzColumn Thank you for your advice. I have been considering learning D3, but using D3Blocks, it appears only to render a full HTML page. I have done a fair bit of searching and can't find a way for it to just render the SVG + js without parsing the file myself. Are you aware of a way to just embed the D3 chart and not have a full html page returned? Once again - many thanks and cheers - David

I have worked with one client as freelancer sometime back. I created few sites for him using Django + Amcharts. Amcharts is bit simple. You need to pass data in proper JSON format to create charts. Here is one website (Django + Amcharts): www.cyclicalstrength.com/

Thanks for sparing time to comment! Appreciate it.

Thanks for the feedback. Really appreciate it.

Thank you too!

Welcome. Hope my content helped you.

Glad you think so! Really appreciate that you took time to comment !!! I am planning to upload regularly to get more views. Hope my content helps people around globe.

GPT-3.5, GPT-4, LlaMa-3, Phi-3, Mistral 0.3, Gemma, and few others. Most latest releases are now adding support for function calling by including it in fine-tuning step.

Thanks for feedback. No, I haven't made video on authentication for chatbots yet. Its on my radar and planning to make some videos on adding authentication to Chatbots. But as of now, there are none.

Fixed it with ax.invert_yaxis()

The reason behind that is the actual entries starts from around 6th month of 2007. Entries ends at 22-9 and thats why we have dangling 2023 as well. One way to solve this is to add 2007 date and 2023 date in list when plotting. Use below code where I have added 2007 at beginning of dates and 2023 at the end before plotting line chart. This way line will start from 2007 and end at 2023. ``` from datetime import date, datetime import numpy as np dates = np.hstack((pd.date_range("2007-1-1", "2007-1-1", freq="ys"), iphone_df.Date, pd.date_range("2023-1-1", "2023-1-1", freq="ys"))) ax.plot(dates, [0,]* (len(iphone_df)+2), "-o", color="black", markerfacecolor="white"); ```

@@CoderzColumn that worked, thanks!

*I HAVE OLLAMA INSTALLED AND RUNING*

It's highlighting "Ollama" Python library that we are using in code. Apart from software "Ollama", you'll need to install Ollama Python library as well. * pip install ollama