Foodle

🍜 Foodle — AI-Powered Menu Translator & Dish Explainer

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle

What I Built

Foodle is an AI-powered menu translator designed to help travelers, international students, and food lovers understand restaurant menus in languages they may not speak.

Imagine visiting a restaurant in another country, looking at a menu full of unfamiliar dish names, and having no idea what to order. Foodle aims to solve that problem by helping users translate menus and understand what dishes might contain.

🍽️ What Foodle aims to offer

• Menu translation: Translate menu text into a language you understand.
• Dish explanations: Get understandable descriptions of unfamiliar dishes, including their ingredients, preparation, flavor, and spice level when the information is available.
• Menu image processing: Extract text from a photo of a restaurant menu using OCR.
• Restaurant Menu Studio: Help small restaurants prepare translated versions of their menus.
• Export options: Save translated menu content in convenient formats.

Foodle is designed for two audiences: travelers who want to order with confidence and small restaurants that want to make their menus accessible to international customers.

💡 The Side Hustle Opportunity

The core idea is to make menu translation useful and accessible for everyday users, while exploring a potential paid offering for restaurants that need multilingual menus.

A possible business model is a free tier for individual travelers and a paid tier for restaurants that need more menu translations, editable menu drafts, and export options.

The goal is simple: make food easier to understand, wherever you are.

Demo

🚀 Live Demo: https://foodle.streamlit.app/

Code

💻GitHub Repository: https://github.com/neomon-dev/Foodle/tree/main

Foodle is being developed as a Python application with a focus on a simple user experience and a modular architecture.

If you try it out, feedback and contributions are welcome!

How I Built It

Foodle is being built with a Python-based application architecture.

The planned technology stack includes:

• Python for the core application.
• Streamlit for the interactive web interface.
• Ollama with an open-weight language model for local AI inference.
• OCR tooling to extract text from menu photos.
• SQLite for locally stored translation sessions.
• pytest for automated testing.

The application separates OCR, translation, dish explanation, data storage, and menu export into distinct modules. This makes the code easier to maintain and allows individual components to be improved independently.

The AI layer is intended to explain unfamiliar dishes in simple language rather than merely translating their names. It must also communicate uncertainty instead of inventing ingredients or making unsupported allergy-safety claims.

The exact model and supported capabilities depend on the model installed and the features successfully implemented in the final version.

Why Does Open Innovation Matter?

Open innovation makes projects like Foodle possible for developers who want to experiment with AI without depending entirely on proprietary APIs.

Using open-weight models with local inference can offer several advantages:

• More control: Developers can choose and configure the model that fits their needs.
• Privacy potential: Menu text can be processed locally when the complete application and model are configured for local inference.
• Lower dependency on external services: Local inference can reduce reliance on third-party AI APIs and their usage limits.
• Experimentation: Developers can test different models and improve prompts and workflows.
• Accessibility: Open-source tools make it easier for students and independent developers to build useful AI applications.

Open innovation is not just about making the code available. It is about giving more people the opportunity to understand, modify, and build on AI technology.

For Foodle, that means exploring how open AI can make everyday experiences—like ordering food in an unfamiliar place—a little easier.

Prize Categories

Render
TabPFN
Tinker
Arduino

Backboard

Building Foodle has been an opportunity to explore how open AI can solve a practical problem while leaving room for a sustainable product.

If you have ever struggled to understand a menu while traveling, I'd love to hear what features would make a tool like this genuinely useful to you!

Hacktoberfest #OpenSourceAI #Python #Streamlit #Ollama #AI #BuildInPublic