Whisper.api Save

title: whisper.api emoji: 😶‍🌫️ colorFrom: purple colorTo: gray sdk: docker app_file: Dockerfile app_port: 7860

Whisper API - Speech to Text Transcription

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!

Installation

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

Running the Project

To run the project, use the following command:

uvicorn app.main:app --reload

Get Your token

To get your token, use the following command:

curl -X 'POST' \
  'https://innovatorved-whisper-api.hf.space/api/v1/users/get_token' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
  "email": "[email protected]",
  "password": "password"
}'

Example to Transcribe a File

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 '[email protected];type=audio/wav'

License

MIT

Reference & Credits

• https://github.com/openai/whisper
• https://openai.com/blog/whisper/
• https://github.com/ggerganov/whisper.cpp

Authors

• Ved Gupta

🚀 About Me

Just try to be a developer!

Support

For support, email [email protected]