馃 distributed transcription service
thistle.dunkirk.sh
dunkirk.sh
1# Whisper Transcription Server
2
3This is a FastAPI server that provides real-time audio transcription using the faster-whisper library.
4
5## Features
6
7- Real-time transcription with streaming progress updates
8- Supports multiple audio formats (MP3, WAV, M4A, etc.)
9- Language detection
10- Segment-based transcription with timestamps
11- RESTful API endpoint
12
13## Setup
14
15### 1. Install Dependencies
16
17```bash
18pip install -r requirements.txt
19```
20
21### 2. Run the Server
22
23**Option 1: Manual setup**
24```bash
25pip install -r requirements.txt
26python main.py
27```
28
29**Option 2: Quick start script**
30```bash
31./run.sh
32```
33
34The server will start on `http://localhost:8000` and load the Whisper model (this may take a few minutes on first run).
35
36## API Usage
37
38### POST `/transcribe-with-progress`
39
40Upload an audio file to get real-time transcription progress.
41
42**Example with curl:**
43```bash
44curl -X POST "http://localhost:8000/transcribe-with-progress" \
45 -F "file=@/path/to/your/audio.mp3"
46```
47
48**Streaming Response:**
49The endpoint returns a stream of JSON objects:
50
51```json
52{"status": "starting", "total_duration": 15.36, "language": "en", "language_probability": 0.99}
53{"status": "progress", "percentage": 25.59, "start": 0.0, "end": 3.93, "text": "This is a test of the transcription server."}
54{"status": "progress", "percentage": 57.68, "start": 3.93, "end": 8.86, "text": "It should be streaming the results back in real time."}
55{"status": "complete"}
56```
57
58### Response Format
59
60- `starting`: Initial metadata about the audio file
61- `progress`: Transcription segments with progress percentage
62- `complete`: Transcription finished successfully
63- `error`: An error occurred during transcription
64
65## Configuration
66
67You can modify the model settings in `main.py`:
68
69```python
70model_size = "base" # Options: tiny, base, small, medium, large-v1, large-v2, large-v3
71model = WhisperModel(model_size, device="cpu", compute_type="int8")
72```
73
74For GPU acceleration, change to:
75```python
76model = WhisperModel(model_size, device="cuda", compute_type="float16")
77```
78
79## Integration with Thistle
80
81This server is designed to work with the Thistle web application. Set the `WHISPER_SERVICE_URL` environment variable in Thistle to point to this server.
82
83```bash
84# In Thistle's .env file
85WHISPER_SERVICE_URL=http://localhost:8000
86```