Links and Commands:
1) GitHub Repository for Local Text-to-Speech Server:
https://github.com/matatonic/openedai-speech
2) Clone the Repository:
git clone https://github.com/matatonic/openedai-speech
3) Rename the sample.env File:
Rename sample.env to speech.env in the project folder.
4) Start the Docker Container:
docker compose up
5)Verify the Setup:
Open http://localhost:8000/docs in your browser.
6)API to Add in OpenWebUI:
http://host.docker.internal:8000/v1
7) API Key:
sk-111111111
8) Piper TTS for Adding More Voices:
https://github.com/rhasspy/piper
Video Description:
In this video, we dive into setting up a completely local Text-to-Speech (TTS) inference server using open-source tools. If you're looking to keep your data secure and run TTS models directly on your own machine, this tutorial is for you! Here's what we'll cover:
Introduction: Why choose a local inference server over cloud-based solutions like 11 Labs?
Setting Up the Server: Step-by-step instructions for cloning the repository, renaming configuration files, and launching the Docker container.
Testing the Server: Verifying the setup by accessing the local API endpoint and testing different TTS models and voices.
Customizing Voices:
Adding new voices using the Piper TTS framework.
Downloading ONNX model files and JSON configuration files for custom voices.
Updating the repository to support a variety of unique voices, including examples like "Alba."
OpenWebUI Integration: Configuring the API in OpenWebUI to seamlessly use the local TTS server for your projects.
Demo: Testing the setup with multiple voice models and showcasing real-time voice output directly from the local server.
What You'll Learn:
How to clone and configure a GitHub repository for local TTS.
Using Docker Compose to set up a robust containerized TTS environment.
Tips for integrating TTS models into existing frameworks like OpenWebUI.
Adding and customizing voices using Piper TTS.
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