kobold_assistant VS whisper.cpp

My project, https://github.com/lee-b/kobold_assistant, is similar to this: currently works locally, listens and responds in a loop, but doesn't function (well) remotely through a server or anything. There is a mumble branch that works over a mumble voice chat, but it has echo/feedback/noise reduction problems right now.

KoboldAI has text completion and text chat interface built in, and I built (or am building) https://github.com/lee-b/kobold_assistant to provide a voice chat interface to that, and I have an 'ai' command that I can run from a linux shell, for any time I want the same AI to assist with anything in a command pipeline, and some steam games already use it. LocalAI will provide a local adapter to make OpenAI-based stuff use a local model instead -- I don't think this talks to KoboldAI, but I plan to modify it to do so, if it doesn't already. Finally, I plan to run (or build) something similar to SillyTavern, but instead of "joke"/fun anime characters, make it like an advisory council, where there's a philosophy advisor, a scientific advisor, an economics advisor, and so on all in a chat room, and I can just post ideas or articles I'm interested in, to get feedback from multiple perspectives, all driven by one AI -- or maybe a small number of AIs, like a specialised medical model or science or law model, and then a general model for everything else.

kobold-assistant uses whisper. https://github.com/lee-b/kobold_assistant

whisper.cpp [1] has a karaoke example that uses ffmpeg's drawtext filter to display rudimentary karaoke-like captions. It also supports diarisation. Perhaps it could be a starting point to create a better script that does what you need.

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1: https://github.com/ggerganov/whisper.cpp/blob/master/README....

The ggml library is one of the first library for local LLM interference. It’s a pure C library that converts models to run on several devices, including desktops, laptops, and even mobile device - and therefore, it can also be considered as a tinkering tool, trying new optimizations, that will then be incorporated into other downstream projects. This tool is at the heart of several other projects, powering LLM interference on desktop or even mobile phones. Subprojects for running specific LLMs or LLM families exists, such as whisper.cpp.

I'm not sure if it is _fully_ openai compatible, but whispercpp has a server bundled that says it is "OAI-like": https://github.com/ggerganov/whisper.cpp/tree/master/example...

I don't have any direct experience with it... I've only played around with whisper locally, using scripts.

unless i'm misunderstanding `whisper.cpp` seems to support streaming & the repository includes a native example[0] and a WASM example[1] with a demo site[2].

[0]: https://github.com/ggerganov/whisper.cpp/tree/master/example...

Usage 1: Good to transcribe audio. An example use case could be to summarize YouTube videos or long courses. Usage 2: You talk with voice to your AI that responds with text (later with audio too). - https://github.com/ggerganov/whisper.cpp

🗣️🎙️ whisper.cpp (offline speech-to-text transcription, models trained by OpenAI, CLI based, browser based)

Has anyone played around with Whisper C++ for swift? I'm hitting a snag even on the demo. I've downloaded the github repo and everything matches up with this video [ https://youtu.be/b10OHCDHDQ4 ] but when he hits the transcribe button, it actually prints out the captioning. When I do it, it skips that part and just says "Done...". But it, does everything else - plays the audio, says it's transcribing.. just doesn't show me the transcription: and it's not in the debug window either. But the demo isn't throwing any errors, and I haven't messed with the code really so this is their example. https://github.com/ggerganov/whisper.cpp