Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/concaption/containerized-transcription-api

Containerized Transcription API using Whisper Model and FastAPI
https://github.com/concaption/containerized-transcription-api

docker fastapi openai transcription whisper

Last synced: 8 days ago
JSON representation

Containerized Transcription API using Whisper Model and FastAPI

Host: GitHub
URL: https://github.com/concaption/containerized-transcription-api
Owner: concaption
Created: 2023-10-09T03:35:43.000Z (about 1 year ago)
Default Branch: main
Last Pushed: 2023-10-10T08:19:48.000Z (about 1 year ago)
Last Synced: 2023-10-11T08:51:03.326Z (about 1 year ago)
Topics: docker, fastapi, openai, transcription, whisper
Language: Jupyter Notebook
Homepage:
Size: 5.59 MB
Stars: 0
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md

Awesome Lists containing this project

README

        


# Containerized Transcription API using Whisper Model and FastAPI

[![Docker](https://github.com/buildberg/containerized-transcription-api/actions/workflows/docker-publish.yml/badge.svg)](https://github.com/buildberg/containerized-transcription-api/actions/workflows/docker-publish.yml)

[![Open Source Love svg1](https://badges.frapsoft.com/os/v1/open-source.svg?v=103)](#)

[![GitHub Forks](https://img.shields.io/github/forks/buildberg/containerized-transcription-api.svg?style=social&label=Fork&maxAge=2592000)](https://github.com/buildberg/containerized-transcription-api/fork)

[![GitHub Issues](https://img.shields.io/github/issues/buildberg/containerized-transcription-api.svg?style=flat&label=Issues&maxAge=2592000)](https://github.com/buildberg/containerized-transcription-api/issues)

[![contributions welcome](https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat&label=Contributions&colorA=red&colorB=black	)](#)

[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/concaption/containerized-transcription-api)



![](screenshot.png)

### Overview

This project sets up a robust web application using FastAPI. It integrates the open-source Whisper AI model for Speech-to-Text (STT) transcription, enabling accurate and efficient audio-to-text conversion. The application is containerized using Docker, ensuring consistent and efficient runtime in any environment.

### Features

* **FastAPI Backend:** A high-performance, easy-to-learn backend.

* **Whisper AI Integration:** Cutting-edge STT transcription.

* **Dockerized:** Simplified deployment, scalability, and management.

### Why this project?

Whether you want to automate your transcription tasks, enhance accessibility for your content, or explore the world of AI-powered applications, this project has you covered.

### Installation

1. Clone the repository

```

git clone https://github.com/buildberg/containerized-transcription-api

```

2. Navigate into the project folder

```

cd containerized-transcription-api

```

3. Build and run Docker container

```

make docker

```

### Usage

Convert Audio to Text

```bash

POST /whisper

```

```mermaid

graph LR

  setup[make setup]

  setup -->|1. Make script executable| setup.sh[setup.sh]

  setup -->|2. Run script| setup.sh

  install[make install]

  install -->|1. Upgrade pip| pip[pip]

  install -->|2. Install requirements| requirements[requirements.txt]

  format[make format]

  format -->|Format all code| black[Black]

  lint[make lint]

  lint -->|Find and lint .py files| pylint[Pylint]

  precommit[make precommit]

  precommit -->|1. Install pre-commit hooks| pre-commit-install[pre-commit install]

  precommit -->|2. Run hooks on all files| pre-commit-run[pre-commit run]

  refactor[make refactor]

  refactor --> format

  refactor --> precommit

  refactor --> lint

  push[make push]

  push -->|1. Add changes| git-add[git add]

  push -->|2. Commit changes| git-commit[git commit]

  push -->|3. Push to repository| git-push[git push]

  docker[make docker]

  docker -->|1. Docker-compose build and up| docker-compose[docker-compose up -d --build]

  run[make run]

  run -->|1. Execute main script| main-script[python src/main.py]

```