buzz VS private-gpt

Easiest 1-click way to install and use Stable Diffusion on your computer."

https://github.com/easydiffusion/easydiffusion

And while Whisper is OpenAI, it is trivial to use locally and extremely usefull

https://github.com/chidiwilliams/buzz

Install this for Resolve

Just use this one: https://github.com/chidiwilliams/buzz

What utilities related to Whisper do you wish existed? What have you had to build yourself?

On the end user application side, I wish there was something that let me pick a podcast of my choosing, get it fully transcribed, and get an embeddings search plus answer q&a on top of that podcast or set of chosen podcasts. I've seen ones for specific podcasts, but I'd like one where I can choose the podcast. (Probably won't build it)

Also on the end user side, I wish there was an Otter alternative (still paid $30/mo, but unlimited minutes per month) that had longer transcription limits. (Started building this, not much interest from users though)

Things I've seen on the dev tool side:

Gladia (API call version of Whisper)

Whisper.cpp

Whisper webservice (https://github.com/ahmetoner/whisper-asr-webservice) - via this thread

Live microphone demo (not real time, it still does it in chunks) https://github.com/mallorbc/whisper_mic

Streamlit UI https://github.com/hayabhay/whisper-ui

Whisper playground https://github.com/saharmor/whisper-playground

Real time whisper https://github.com/shirayu/whispering

Whisper as a service https://github.com/schibsted/WAAS

Improved timestamps and speaker identification https://github.com/m-bain/whisperX

MacWhisper https://goodsnooze.gumroad.com/l/macwhisper

Crossplatform desktop Whisper that supports semi-realtime https://github.com/chidiwilliams/buzz

PrivateGPT is a nice tool for this. It's not exactly what you're asking for, but it gets part of the way there.

https://github.com/zylon-ai/private-gpt

Further details available at: https://docs.privategpt.dev/api-reference/api-reference/ingestion

Run https://github.com/imartinez/privateGPT

Then

make ingest /path/to/folder/with/files

Then chat to the LLM.

Done.

Docs: https://docs.privategpt.dev/overview/welcome/quickstart

PrivateGPT repository in case anyone's interested: https://github.com/imartinez/privateGPT . It doesn't seem to be linked from their official website.

I’m preparing a small internal tool for my work to search documents and provide answers (with references), I’m thinking of using GPT4All [0], Danswer [1] and/or privateGPT [2].

The RAG technique is very close to what I have in mind, but I don’t want the LLM to “hallucinate” and generate answers on its own by synthesizing the source documents. As stated by many others, we’re living in interesting times.

[0] https://gpt4all.io/index.html

[1] https://www.danswer.ai/

[2] https://github.com/imartinez/privateGPT

https://www.reddit.com/r/LocalLLaMA/comments/14niv66/using_a...

https://github.com/imartinez/privateGPT

I've been playing around with https://github.com/imartinez/privateGPT and https://github.com/simonw/llm and wanted to create a simple Python package that made it easier to run ChatGPT-like LLMs on your own machine, use them with non-public data, and integrate them into practical applications.

This resulted in Python package I call OnPrem.LLM.

In the documentation, there are examples for how to use it for information extraction, text generation, retrieval-augmented generation (i.e., chatting with documents on your computer), and text-to-code generation: https://amaiya.github.io/onprem/

Enjoy!