This project is a recipe recommendation system that helps users find recipes based on available ingredients. It includes an offline mode that ensures users can still find recipes even when the AI service is unavailable.
Our project leverages Smalltalk for data preprocessing and recipe generation, ensuring structured and accessible recipe data across different application states. Using Pharo Smalltalk, we converted raw recipe data into a well-structured JSON format, allowing for efficient storage and retrieval. Additionally, we generated prebuilt offline recipes to maintain functionality when AI-powered services are unavailable, providing users with a fallback solution for recipe recommendations. To enhance usability, we parsed and formatted the JSON data for seamless integration into the React frontend, enabling dynamic recipe searches and efficient filtering based on user-provided ingredients.
backend/parse_data.st→ Smalltalk script that generatesrecipe.jsonpublic/recipe.json→ JSON output from Smalltalk, used in the offline modeOfflinePage.tsx(src/pages/) → React component that loadsrecipe.jsonin offline mode
- Open Pharo Smalltalk
- Load and run
parse_data.st - The script generates
recipe.jsonin thepublic/directory - Run the React app to test offline mode with the generated JSON
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In the project directory, you can run:
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See the section about running tests for more information.
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