amha-kindu/terguami-api

Terguami is a FastAPI application powered by a custom transformer model built with PyTorch. It provides fast and accurate English-to-Amharic translations, with features like Docker support and interactive OpenAPI documentation, making it a scalable and easy-to-deploy solution for machine translation. # Terguami: English-to-Amharic Translation API This repository provides an English-to-Amharic translation API built with **FastAPI**. The core of the application is a custom transformer-based model trained from scratch using **PyTorch** on a carefully curated dataset. It offers a robust, scalable solution for translating English text into Amharic, with performance and extensibility in mind. --- ## ✨ Features - 🚀 **High-Performance API**: Powered by FastAPI for asynchronous, fast, and efficient HTTP requests. - 🧠 **Custom Transformer Model**: A transformer-based machine learning model developed from scratch with PyTorch. - 📈 **Custom Dataset**: The model is trained on a carefully curated dataset to ensure accurate English-to-Amharic translations. - 📜 **Extensible API**: Modular structure for easy integration with other systems or expansion with new features. - 🔄 **OpenAPI Documentation**: Automatically generated and customizable API docs for developers. --- ## 🖼️ Demo Images ### API in Action --- ## Table of Contents 1. Installation 2. Usage 3. Running with Docker 4. Endpoints 5. Model Details 6. Future Improvements 7. License --- ## ⚙️ Installation ### Prerequisites - **Python 3.10+** - **pip** package manager ### Clone the Repository ```bash git clone github.com cd terguami ``` ### Install Dependencies ```bash pip install -r requirements.txt ``` **`requirements.txt`** ``` fastapi==0.115.5 uvicorn==0.32.2 pydantic==2.9.2 pydantic-settings==2.6.1 numpy==1.26.3 tokenizers==0.15.0 torch==2.1.2 ``` --- ## 🚀 Usage ### Running the Server To start the server locally, run: ```bash uvicorn main:app --host 0.0.0.0 --port 7000 --reload ``` Once running, the API will be accessible at `localhost`. --- ## 🐳 Running with Docker ### Prerequisites - **Docker** installed on your machine. ### Build the Docker Image ```bash docker build -t terguami:v1 . ``` ### Run the Docker Container ```bash docker run -d -p …