And to answer your question, you're seeing that kind of styling so frequently because it's likely part of Framer Motion, an extremely popular animation library

https://www.npmjs.com/package/framer-motion https://www.npmjs.com/package/motion

If CORS weren't an issue, it could've been done in 1/10th of that time. But if that were the case, there would've already been tons of web-based RSS readers available.

Anyway, the goal of this project is to help foster interest in indie blogs and help a bit with discovery. Feel free to submit your blog if you'd like!

If anyone has any questions, I'd be happy to answer them.

Just wanted to comment to see if I can help answer any questions as well as mentioning that we improved the instructions in the README based on some of the points Rob made a few weeks back.

There really are a large number of us out there that know Tahoe would be a downgrade to their current setup

If you have any ideas on how to improve the resilience of the workarounds, please connect on the GitHub, or just starring the repo would help, as the project would get more attention and hopefully more solutions offered as a result.

It's frustrating to feel like your computer isn't.. yours anymore when you're pushed so insistently like with this "upgrade". Hopefully we can figure out some sustainable ways to get some autonomy back.

With the potential to set off the installation flow with the wrong click (when its being shown over-and-over again), it makes me anxious and feel like I'm not even in control of my own computer anymore.

For the time being, I've installed a management profile to defer updates, disabled the Settings options for automatic updates, and used "Quiet You!" to try and keep the notifications at bay.

But the maximum deferral time for profiles is 90 days, so if anyone knows of a better solution or work-around, please let me know

What did your `it/s` end up looking like with that setup? MLX is fascinating to me. Apple made a really smart decision with the induction of its M-series.

With regard to the artifacts — this is definitely a known issue with Chatterbox. I'm unsure of where the current investigation on fixing it is at (or what the "tricks" are to avoid this), but it's definitely something that is eery among other things.

I appreciate your feedback through all of this!

Would love to have you on the Discord to keep in touch https://chatterboxtts.com/discord

For now, there's just a textarea for input (so you'll have to copy the `.txt` contents) — but it's a lot easier than trying to finagle into a `curl` request

Let me know if you have any issues!

I'm new to actually commenting on HN as opposed to just lurking, so I hope this formatting works..

  cat your_file.txt | python3 -c 'import sys, json; print(json.dumps({"input": sys.stdin.read()}))' | curl -X POST http://localhost:5123/v1/audio/speech \
    -H "Content-Type: application/json" \
    -d @- \
    --output speech.wav

This'll hopefully handle any potential issues you'd have with quotes or other symbols breaking the JSON input.

Let me know how it goes!

Oh and you might want to change `python3` to `python` depending on your setup.

A lot of these frontends have an option for using OpenAI's TTS API, and some of them allow you to specify the URL for that endpoint, allowing for "drop-in replacements" like this project.

So the speech generation endpoint in the API is designed to fill that niche. However, its usage is pretty basic and there are curl statements in the README for testing your setup.

Anyway, to get to your actual question, let me see if I can whip something up. I'll edit this comment with the command if I can swing it.

In the meantime, can I assume your local text files are actual `.txt` files?

If you want to run it without size limits, here's an open-source API wrapper that fixes some of the main headaches with the main repo https://github.com/travisvn/chatterbox-tts-api/

To be honest, it uses a decently large amount of resources. If you had a GPU, you could expect about 4-5 gb memory usage. And given the optimizations for tensors on GPUs, I'm not sure how well things would work "CPU only".

If you try it, let me know. There are some "CPU" Docker builds in the repo you could look at for guidance.

If you want free TTS without using local resources, you could try edge-tts https://github.com/travisvn/openai-edge-tts

I created an API wrapper that also makes installation easier (Dockerized as well) https://github.com/travisvn/chatterbox-tts-api/

Best voice cloning option available locally by far, in my experience.