whisper-api-server/README.md

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# Whisper API Server (Go)
## ⚠️ This project is a work in progress (WIP).
This API server enables audio transcription using the OpenAI Whisper models.
# Setup
- Download `.exe` from [Releases](https://github.com/xzeldon/whisper-api-server/releases/latest)
- Just run it!
# Build from source
Download the sources and use `go build`.
For example, you can build using the following command:
```bash
go build -ldflags "-s -w" -o server.exe main.go
```
# Usage example
Make a request to the server using the following command:
```sh
curl http://localhost:3000/v1/audio/transcriptions \
-H "Content-Type: multipart/form-data" \
-F file="@/path/to/file/audio.mp3" \
```
Receive a response in JSON format:
```json
{
"text": "Imagine the wildest idea that you've ever had, and you're curious about how it might scale to something that's a 100, a 1,000 times bigger. This is a place where you can get to do that."
}
```
# Usage with [Obsidian](https://obsidian.md/)
To integrate this with the [Obsidian voice recognotion plugin](https://github.com/nikdanilov/whisper-obsidian-plugin), follow these steps:
1. Open the plugin's settings.
2. Set the following values:
- API KEY: `sk-1`
- API URL: `http://localhost:3000/v1/audio/transcriptions`
- Model: `whisper-1`
# Roadmap
- [x] Implement automatic model downloading from [huggingface](https://huggingface.co/ggerganov/whisper.cpp/tree/main)
- [x] Implement automatic `Whisper.dll` downloading from [Guthub releases](https://github.com/Const-me/Whisper/releases)
- [x] Provide prebuilt binaries for Windows
- [ ] Include instructions for running on Linux with Wine (likely possible).
- [ ] Use flags to override the model path
- [ ] Use flags to override the model type (when downloading the model)
- [ ] Use flags to override the port
# Credits
- [Const-me/Whisper](https://github.com/Const-me/Whisper) project
- [goConstmeWhisper](https://github.com/jaybinks/goConstmeWhisper) for the remarkable Go bindings for [Const-me/Whisper](https://github.com/Const-me/Whisper)
- [Georgi Gerganov](https://github.com/ggerganov) for GGML models