buzz VS paperai

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

Nice project!

I've spent quite a lot of time in the medical/scientific literature space. With regards to LLMs, specifically RAG, how the data is chunked is quite important. With that, I have a couple projects that might be beneficial additions.

paperetl (https://github.com/neuml/paperetl) - supports parsing arXiv, PubMed and integrates with GROBID to handle parsing metadata and text from arbitrary papers.

paperai (https://github.com/neuml/paperai) - builds embeddings databases of medical/scientific papers. Supports LLM prompting, semantic workflows and vector search. Built with txtai (https://github.com/neuml/txtai).

While arbitrary chunking/splitting can work, I've found that integrating parsing that has knowledge of medical/scientific paper structure increases the overall accuracy and experience of downstream applications.

https://github.com/neuml/paperai

Disclaimer: I am the author of both

paperai | paperetl

action: translate input: txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications. output: txtai exécute des workflows d'apprentissage automatique pour transformer les données et construire des applications de recherche sémantique alimentées par l'IA. action: translate input: Traditional search systems use keywords to find data output: Les systèmes de recherche traditionnels utilisent des mots-clés pour trouver des données action: summary input: https://github.com/neuml/txtai output: txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications. Semantic search applications have an understanding of natural language and identify results that have the same meaning, not necessarily the same keywords. API bindings for JavaScript, Java, Rust and Go. Cloud-native architecture scales out with container orchestration systems (e. g. Kubernetes) action: summary input: https://github.com/neuml/paperai output: paperai is an AI-powered literature discovery and review engine for medical/scientific papers. Paperai was used to analyze the COVID-19 Open Research Dataset (CORD-19) paperai and NeuML have been recognized in the following articles: Cord-19 Kaggle Challenge Awards Machine-Learning Experts Delve Into 47,000 Papers on Coronavirus Family. real 0m22.478s user 0m13.776s sys 0m3.218s