title | emoji | colorFrom | colorTo | sdk | app_file | app_port |
---|---|---|---|---|---|---|
whisper.api |
😶🌫️ |
purple |
gray |
docker |
Dockerfile |
7860 |
This open source project provides a self-hostable API for speech to text transcription using a finetuned Whisper ASR model. The API allows you to easily convert audio files to text through HTTP requests. Ideal for adding speech recognition capabilities to your applications.
Key features:
- Uses a finetuned Whisper model for accurate speech recognition
- Simple HTTP API for audio file transcription
- User level access with API keys for managing usage
- Self-hostable code for your own speech transcription service
- Quantized model optimization for fast and efficient inference
- Open source implementation for customization and transparency
This repository contains code to deploy the API server along with finetuning and quantizing models. Check out the documentation for getting started!
To install the necessary dependencies, run the following command:
# Install ffmpeg for Audio Processing
sudo apt install ffmpeg
# Install Python Package
pip install -r requirements.txt
To run the project, use the following command:
uvicorn app.main:app --reload
To get your token, use the following command:
curl -X 'POST' \
'http://localhost:8000/api/v1/users/get_token' \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
"email": "example@domain.com",
"password": "password"
}'
To upload a file and transcribe it, use the following command: Note: The token is a dummy token and will not work. Please use the token provided by the admin.
Here are the available models:
- tiny.en
- tiny.en.q5
- base.en.q5
# Modify the token and audioFilePath
curl -X 'POST' \
'http://localhost:8000/api/v1/transcribe/?model=tiny.en.q5' \
-H 'accept: application/json' \
-H 'Authentication: e9b7658aa93342c492fa64153849c68b8md9uBmaqCwKq4VcgkuBD0G54FmsE8JT' \
-H 'Content-Type: multipart/form-data' \
-F 'file=@audioFilePath.wav;type=audio/wav'
- https://github.com/openai/whisper
- https://openai.com/blog/whisper/
- https://github.com/ggerganov/whisper.cpp
Just try to be a developer!
For support, email vedgupta@protonmail.com