docker-registry-ui VS vosk-api

If it's only the UX you care about then you can use the docker registry image which supports arm64 and then use a ux like docker-registry-ui and have a nice ui.

I didn't know Fleet. For my own images repos (not Dockerhub hosted) I use Docker Registry UI (on top of registry:2). It's tiny and works perfectly fine.

# required to avoid HTTP 411: see Issue #1486 (https://github.com/moby/moby/issues/1486) chunked_transfer_encoding on; # required for strict SNI checking: see Issue #70 (https://github.com/Joxit/docker-registry-ui/issues/70) proxy_ssl_server_name on; proxy_buffering off; proxy_ignore_headers "X-Accel-Buffering";

I use the default Docker registry container, but with Docker Registry UI.

I’m not familiar with jfrog/artifactory but I self-host a registry on my network. I use joxit/docker-registry-ui for visualization. This is just a frontend on the API provided by the docker registry. AFAIK catalog is the best way to list the images

So I don't know if my issue comes from my lack of knowledge of discord.js/voice or VOSK. so I guess the most important thing I need to see is if I am creating a proper stream for the Vosk API to capture the audio. if I can figure out how to capture an audio stream I can probably import that in to vosk and figure out how to use vosk myself. but right now I can't even get close! Thank you in advance...Sorry if this isn't the right place for this

I remember a while ago checking out the issues with Vosk speech recognition (written in C). A handful of it's issues are related to segfaults and null pointers.

first, good initiative! thanks for sharing. i think you gotta be more diligent and careful with the problem statement.

checking the weather in Sofia, Bulgaria requires cloud, current information. it's not "random speech". ESP SR capability issues don't mean that you cannot process it locally.

the comment was on "voice processing" i.e. sending speech to the cloud, not sending a call request to get the weather information.

besides, local intent detection, beyond 400 commands, there are great local STT options, working better than most cloud STTs for "random speech"

https://github.com/alphacep/vosk-api

I did a one-off text to speech tool for someone last year and had pretty good results with VOSK. One upside is that it works offline, although I imagine if you use TTS a lot you'll notice issues I didn't.

You can use vosk-api (https://github.com/alphacep/vosk-api) to listen to your audio, transform it to text, and then post the text to GPT-3, then using the vector sdk, have your responses said by vector.

The set up script wants to download https://github.com/alphacep/vosk-api/releases/download/v0.3.45/vosk-model-en-v0.3.45.zip, but this resource is not found. AFAICT all releases never contained a model file. Remedy: hardcode one model from https://alphacephei.com/vosk/models. I guessed and picked the one with the closest name, vosk-model-en-us-0.22.zip, just so I could continue.