SumUp4Me

A powerful REST API service that provides intelligent audio transcription and text summarization capabilities powered by OpenAI and Google's AI models.

🚀 Features

• Audio Transcription: Convert audio files to text using OpenAI's Whisper model
• Text Summarization: Generate organized summaries and topic breakdowns using Google's Gemini AI
• Combined Workflow: Transcribe audio files and automatically summarize the content
• Multi-format Support: Supports MP3, WAV, and M4A audio formats
• RESTful API: Clean, well-documented REST endpoints
• Configurable: Flexible configuration through environment variables
• Production Ready: Comprehensive logging and error handling

📋 Prerequisites

• Go 1.24.1 or higher
• OpenAI API key (for audio transcription)
• Google Gemini API key (for text summarization)

🛠️ Installation

1. Clone the repository:

git clone https://github.com/8bury/sumup4me.git
cd sumup4me

2. Install dependencies:

go mod tidy

3. Build the application:

go build -o sumup4me ./cmd/api

⚙️ Configuration

Create a .env file in the root directory with the following variables:

# OpenAI Configuration
OPENAI_API_KEY=your_openai_api_key_here
OPENAI_BASE_URL=https://api.openai.com/v1  # Optional, defaults to OpenAI's API

# Google Gemini Configuration
GEMINI_API_KEY=your_gemini_api_key_here

Environment Variables

Variable	Description	Required	Default
OPENAI_API_KEY	Your OpenAI API key for Whisper transcription	Yes	-
OPENAI_BASE_URL	OpenAI API base URL	No	https://api.openai.com/v1
GEMINI_API_KEY	Your Google Gemini API key for text summarization	Yes	-

🚀 Usage

1. Start the server:

./sumup4me

The server will start on port 8080 by default.

2. The API will be available at http://localhost:8080

📚 API Documentation

Base URL

http://localhost:8080/v1

Endpoints

1. Transcribe Audio

Convert audio files to text.

Endpoint: POST /v1/transcribe

Request:

• Method: POST
• Content-Type: multipart/form-data
• Body: Audio file (key: "audio")

Supported Formats: MP3, WAV, M4A

Response:

{
  "transcription": "Transcribed text content here..."
}

Example using curl:

curl -X POST http://localhost:8080/v1/transcribe \
  -F "audio=@your-audio-file.mp3"

2. Summarize Text

Generate an organized summary of text content.

Endpoint: POST /v1/sumup/text

Request:

• Method: POST
• Query Parameter: text (the text to summarize)

Response:

"• Topic 1: Summary point about first topic\n• Topic 2: Summary point about second topic\n..."

Example using curl:

curl -X POST "http://localhost:8080/v1/sumup/text?text=Your long text content here..."

3. Transcribe and Summarize Audio

Transcribe audio and automatically generate a summary.

Endpoint: POST /v1/sumup/audio

Request:

• Method: POST
• Content-Type: multipart/form-data
• Body: Audio file (key: "audio")

Response:

"• Topic 1: Summary of transcribed content\n• Topic 2: Another key point\n..."

Example using curl:

curl -X POST http://localhost:8080/v1/sumup/audio \
  -F "audio=@your-audio-file.mp3"

Error Responses

All endpoints return appropriate HTTP status codes and error messages:

400 Bad Request:

{
  "error": "Error description"
}

500 Internal Server Error:

{
  "error": "Internal server error description"
}

🏗️ Project Structure

sumup4me/
├── cmd/
│   └── api/
│       └── main.go              # Application entry point
├── internal/
│   ├── audio/
│   │   └── audio.go             # Audio file validation utilities
│   ├── config/
│   │   └── config.go            # Application configuration and DI setup
│   ├── controller/
│   │   ├── sumup.controller.go      # Summary and combined workflow endpoints
│   │   └── transcribing.controller.go # Transcription endpoints
│   ├── dao/
│   │   ├── sumup.dao.go         # Gemini AI integration
│   │   └── transcribing.dao.go  # OpenAI Whisper integration
│   ├── model/
│   │   ├── transcription.model.go # Data models
│   │   └── errors.go            # Error models
│   └── service/
│       ├── sumup.service.go     # Business logic for summarization
│       └── transcribing.service.go # Business logic for transcription
├── go.mod                       # Go module definition
├── go.sum                       # Go module checksums
└── README.md                    # This file

🔧 Development

Running in Development Mode

go run ./cmd/api

Building for Production

go build -ldflags="-s -w" -o sumup4me ./cmd/api

Testing the API

You can test the API using the provided curl examples or any HTTP client like Postman, Insomnia, or HTTPie.

🤝 Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📝 Notes

• The transcription service is configured for Portuguese language by default
• Audio files are processed in memory - ensure adequate server resources for large files
• All API responses include comprehensive logging for debugging and monitoring
• The summarization uses Gemini 2.0 Flash model for optimal performance and quality

🔒 Security

• Store API keys securely and never commit them to version control
• Use environment variables or secure secret management systems in production
• Consider implementing rate limiting and authentication for production deployments

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Built with ❤️ using Go, OpenAI Whisper, and Google Gemini