Make an Offline GPT Voice Assistant in Python
ฝัง
- เผยแพร่เมื่อ 5 ก.ค. 2024
- We make our own offline (local) virtual voice assistant using Python that lets you control your computer and ask it anything!
This is yet another great example of how open source software can be incredible for anyone. Without having to rely on any API or sending our data to any servers we can make a pretty solid offline virtual voice assistant for free!
Windows File Path: C:\Users\{username}\.cache\whisper
Mac File Path: /Users/{username}/.cache/whisper
Commands:
curl -o encoder.json openaipublic.blob.core.window...
curl -o vocab.pbe openaipublic.blob.core.window...
GPT4All: gpt4all.io/index.html
Code: github.com/Jalsemgeest/Python...
Join my Discord at / discord
Thanks for watching! ❤️
Timestamps:
0:00 Intro
0:39 Speech Recognition
3:30 Offline Open AI Whisper
12:00 Text to Speech
14:20 Local LLM
23:04 Outtro
if u had a problem with the vocab file download so basically its vocab.bpe not vocab.pbe u just need to change this in the curl command and it should work just fine
Thanks for the comment!
Awesome video! Quick question, when you already used the speech_recognition library, why didn't you use the recognize_whisper method from it and used the whisper library instead?
Heyo! Awesome Video! Thanks so much for doing this man. So insightful
Appreciate it! Really happy you enjoyed it :)
Awesome Video! I am mainly GNU/Linux user and recently I am using also MS Windows, so may be this is a silly question: Are you running that in WSL2? If so, it is easy to use microphone and speakers with Python in WSL2?
Thank you!
I'm running this on Windows. You might need to tinker around on GNU/Linux a bit more to get it working for the microphone input, but it shouldn't be too bad. I've seen a number of cases where linux users were using the microphone input.
Happy coding :)
Thank you for the great content
Thank you! ❤️/ Jake
Thanks for the awesome video! just curious, if I want to make the python text-to-speech offline more realistic with model (like in hugging face) is it possible?
Yeah it should be possible! There are some great OLlama models available now too :)
Just out of interest. Do you have a GPU in your machine (laptop/desktop)? That would give some context to the performance you are getting.
Great question! I have an AMD Radeon RX 6800. So certainly not top of the line. Also, in my experience a lot of GPU accelerated things have only worked with NVidia with AMD being a 'TODO' on the developers side :)
As part of my engineering project , I want to make a similar voice assistant specifically for agriculture which clears farmer's queries and also gives crop suggestions based on the local conditions.Can you please guide me through the project?
Wow! That sounds like a great project! I'm not sure I could guide you through the project, but you may want to try to find a machine learning model that is more specialized on plants and agriculture. You could even look into making one yourself if you have enough training data! :)
@@jakeeh I am so curious to know how to train a domain-knowledge only model, that would be brilliant. There must be a way of doing it, I am also learning AI for fun out side of my day job.
Hi Jake. Where do you import pyautogui from?
Hey, you need to install it using pip.
Run “python -m pip install pyautogui” then you can just import pyautogui in your file.
Make sure you use the same python when running your file as you do when you install with pip
I think gemma could be a better option than this cus i dont think that it would have the token restrictions that gpt4all had, and its pretty easy to install using ollama. even with an integrated gpu from 5 years ago, i was able to get a comfortable experience with the llm model.
Yeah at the time llama wasn’t easily available for windows. There are definitely some better things available now
4:36 I think its Video RAM - Basically the RAM available on whichever GPU you're using for inference
Yeah I think you're right. Thanks! :)
Please do more advanced versions of this, I am a web dev and would love to start integration my own voice assitance, I'm just a bit newbe to AI
Thanks for the comment! Yeah, I’d be happy to do some more stuff on this. I think the new version would use OLlama. Although I’d like to go over how to train your own model too.
Thx
Thanks for your comment!
is this possible on linux and if so can you make a tutorial or link a text guide to something similar
Yes absolutely you should be able to do this on Linux as well. You could take a look at medium.com/@vndee.huynh/build-your-own-voice-assistant-and-run-it-locally-whisper-ollama-bark-c80e6f815cba which uses OLlama as well which is probably a great option nowadays too :)
@@jakeeh thank you
can you combine it with frontend
You could absolutely make a front end for this so you could interact with it through a GUI and/or voice.
i'm using linux can you tell me how how to do it in linux
Which part are you having trouble with in Linux? :)
It is (very) clear you do not have a technical AI background, but you inspired me to try and make my own local assistant. Thanks!
Oh absolutely! I certainly have a technical background, but I am far away from having too much experience outside of scraping the surface of AI. Happy you felt inspired to give things a shot! You've got to start somewhere! :)
I used LM Studio mostly as it loads multi models, with 3x 24gb GPU's 70GB VRAM you can run like 10 models at same time, more polished then GPT4ALL but both work and free.
Oh that sounds great! I certainly don't have those specs, but that does sound great nonetheless.
Thanks for your comment! :)
@@jakeeh i wonder if it is worth to compare those like Ollama, LM Studio or just the way you've shown in the video, thought i don't quite get how Ollama or LM Studio works (I thought gguf is the only way to work witht local offline method, didn't know what is inside Ollama). Do they really help to speed up things?
I think it really depends on the hardware of your machine. If they can utilize your GPU then they can likely greatly improve the performance. Although I'm not an expert on them :)