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## Overview
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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.
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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.
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## Features
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- **Audio Transcription**: Supports various input methods:
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- Local server files
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- **OpenAI API Compatibility**: Fully compatible with OpenAI's `/v1/audio/transcriptions` and `/v1/models` endpoints.
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- **Local File Support**: Transcribe audio files stored locally on your machine.
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- **Multiple Input Methods**: Supports:
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- Local file paths
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- Files accessible via URL
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- Base64-encoded files
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- Multipart form data
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- **OpenAI API Compatibility**: Works with `/v1/audio/transcriptions` and `/v1/models` endpoints.
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- **Audio Preprocessing**: Converts audio to WAV, normalizes, and adds silence.
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- **Hardware Support**: Utilizes GPU (CUDA, MPS) or CPU.
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- **Logging**: Tracks all operations.
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- **Health Check**: Includes a health check endpoint.
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- Base64-encoded audio
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- Multipart form uploads
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- **Easy Setup**: Designed to run as a local service with minimal configuration.
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- **Hardware Optimization**: Utilizes GPU (CUDA, MPS) or CPU for efficient processing.
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- **Health Check**: Includes a `/health` endpoint for service monitoring.
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## Recommended Model
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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.
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Perfect for local development or offline use cases where OpenAI's API isn't accessible.
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## Quick Start
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