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Serge Zaigraeff
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## Overview ## Overview
This project is a local API server compatible with OpenAI's API for transcribing audio to text using the Whisper model. It's designed to run as a system service, loading the Whisper model into memory at startup and handling transcription requests via REST API. This project is a lightweight, OpenAI-compatible API server for transcribing audio to text using the Whisper model. It's designed to run locally, making it easy to set up and use for speech-to-text tasks.
## Features ## Features
- **Audio Transcription**: Supports various input methods: - **OpenAI API Compatibility**: Fully compatible with OpenAI's `/v1/audio/transcriptions` and `/v1/models` endpoints.
- Local server files - **Local File Support**: Transcribe audio files stored locally on your machine.
- **Multiple Input Methods**: Supports:
- Local file paths
- Files accessible via URL - Files accessible via URL
- Base64-encoded files - Base64-encoded audio
- Multipart form data - Multipart form uploads
- **OpenAI API Compatibility**: Works with `/v1/audio/transcriptions` and `/v1/models` endpoints. - **Easy Setup**: Designed to run as a local service with minimal configuration.
- **Audio Preprocessing**: Converts audio to WAV, normalizes, and adds silence. - **Hardware Optimization**: Utilizes GPU (CUDA, MPS) or CPU for efficient processing.
- **Hardware Support**: Utilizes GPU (CUDA, MPS) or CPU. - **Health Check**: Includes a `/health` endpoint for service monitoring.
- **Logging**: Tracks all operations.
- **Health Check**: Includes a health check endpoint. ## Recommended Model
For Russian language transcription, we recommend using the [**whisper-large-v3-russian**](https://huggingface.co/antony66/whisper-large-v3-russian) model from Hugging Face. This model is fine-tuned specifically for Russian speech recognition and delivers high accuracy.
Perfect for local development or offline use cases where OpenAI's API isn't accessible.
## Quick Start ## Quick Start