Food Seer takes the stress out of choosing what to eat by turning meal selection into a smart and personalized experience. Whether you're in the mood for a quick quiz or a natural conversation, Food Seer helps you find the perfect meal based on your preferences, mood, and budget. Start a short quiz or chat with our AI assistant — and receive a tailored meal suggestion in seconds.
VIDEO
- 💡 Why This Project?
- 📈 Use Case
- 🚀 Key Features
- Technology Stack
- 🔧 Installation
- 🎥 Demo Video
- 📊 Project Poster
- 📚 Case Studies
- 🎓 Academic Paper Guidance
- 🤝 Contribution Guidelines
- 📈 Code Coverage
- 🌐 Future Scope
- 🙌 Contributors
- 🙏 Acknowledgements
- 💡 Feedback
- 🏛️ Governance Model
- 🔔 Notifications
- 📅 Roadmap & Funding Information
- 🌟 Success Stories
- 📎 Recommended Citation
⚠️ Disclaimer
Menu overload is real — and decision fatigue hits hard when you're hungry. Food Seer eliminates the guesswork by guiding users toward a meal that fits their lifestyle and cravings without the hassle of scrolling through endless options.
We built Food Seer to:
- ✅ Reduce menu fatigue and decision stress
- 🤖 Provide personalized suggestions via AI chat
- ❓ Offer a quiz-based food recommendation system
- 🛒 Streamline ordering into a simple “choose and order” flow
- 🧾 Empower staff with inventory, user, and order management tools
Food Seer bridges AI-driven personalization with restaurant efficiency — improving both customer experience and backend operations.
Scenario: Sarah is tired after work and doesn't want to decide what to eat.
- Sarah opens Food Seer
- She chooses between:
- a quick interactive quiz, or
- chatting with our Ollama-powered chatbot
- She instantly receives a personalized meal recommendation
- With one click, she can place an order — no browsing required
Food Seer transforms meal choices from a chore into a simple, enjoyable interaction.
- Interactive Quiz System to generate meal recommendations
- Ollama-powered AI chatbot for conversational food suggestions
- Clean, tab-based UI for seamless navigation between ordering, recommendations, and account features
- Back-end systems for inventory, ordering, session management, and user accounts
- Automated tests with 85%+ coverage across frontend & backend
To set up the project locally, follow these steps.
Clone the Repository:
git clone https://github.com/NovaCorz/CSC510.git
cd CSC510Choose Your Installation Method. Detailed instructions are available in INSTALL.md.
Check out our demo video to see the application in action! Click the link below to watch:
Curious about our project? View our project poster showcasing key aspects of the system here.
Food Seer was used and evaluated in a controlled environment by our development team and peers.
Through hands-on testing sessions, we observed that Food Seer improves food decision-making by:
- Reducing decision fatigue around choosing meals
- Helping users quickly narrow down food options
- Providing fast, personalized suggestions through quizzes and AI chat
- Making the meal-selection process feel more guided and enjoyable
Our internal testers consistently reported that Food Seer made deciding what to eat faster, simpler, and less overwhelming, especially when unsure where to start.
Additional user studies and data-driven evaluations are planned as the system matures.
The guidance for Food Seer's chat bot was based on the influence on the following academic papers. These papers prompted ethical use and implementation of the chat bot for the best experience for users.
- The influence of chatbot humour on consumer evaluations of services. - Hyunju Shin, Isabella Bunosso, Lindsay R. Levine
- “I Am Here to Assist You Today”: The Role of Entity, Interactivity and Experiential Perceptions in Chatbot Persuasion. - Carolin Ischen, Theo Araujo, Guda van Noort, Hilde Voorveld, Edith Smit
- Understanding the impact of control levels over emotion-aware chatbots. - Ivo Benke, Ulrich Gnewuch, Alexander Maedche
The rules listed below are to be followed by the ones who will be contributing to the code in the repository:
- Atleast one review/approval is required from any other contributors of the project to merge a commit to the main branch.
- It is recommended to delete the branch as soon as it is merged to the main branch to avoid stale branches in the repository.
- It is encouraged to add name tags such as "feature/" or "patch/" in the branches if it is used to add code-patches or features in the project.
For more details on contributing to Food Seer, please read our full guide here: CONTRIBUTING.md
We're excited about the enhancements coming to Food Seer! Here's what's next:
-
Chat-Bot Memory & History
Allow the AI to retain past conversations, preferences, and recommendations — creating a truly personalized dining assistant that learns over time. -
Recommendation Feedback & Improvement Loop
Enable rating and review features for each recommendation, helping the system continuously refine and improve food suggestions. -
Analytics & Insights Dashboard
Introduce a business-facing analytics suite that visualizes customer preferences, order trends, and engagement insights to support smarter restaurant decisions. -
Voice-Enabled Chat Experience
Add speech-to-text and text-to-speech so users can talk to the chatbot like a real waiter and receive spoken, natural meal recommendations — making the experience hands-free and more conversational.
A heartfelt thank you to our contributors who made this project possible:
Group #13
- Justin Kuethe - jrkuethe
- Chase Goins - jcgoins2
- Andrew Parr - aaparr
- Mukul Sauhta - msauhta2
We extend our heartfelt thanks to Professor Dr. Timothy Menzies for his invaluable guidance in shaping our understanding of effective Software Engineering practices. We’re also deeply grateful to the teaching assistants for their consistent support and encouragement throughout the project.
Your input matters to us! If you have ideas for enhancements or new features, feel free to open an issue or submit a pull request. Thoughtful feedback from contributors like you helps us improve and evolve.
Food Seer is maintained as an open-source project by its core development team.
Project decisions — including new features, bug fixes, and roadmap updates — are made collaboratively through discussion and consensus among contributors.
While we do not currently have a formal governance structure, our guiding principles are:
- Transparency: All changes are proposed and reviewed publicly through GitHub pull requests.
- Collaboration: Contributions are encouraged from all team members and external participants.
- Consensus-based Decision-Making: Updates and feature changes are approved when all active contributors agree on the direction.
- Future Growth: As the project expands and attracts more contributors, we plan to introduce a clearer governance model outlining maintainer roles, voting processes, and long-term project stewardship.
This approach ensures Food Seer remains both open and adaptable while maintaining high standards for code quality and collaboration.
Users can subscribe to notifications to track changes to the Food Seer repository.
To follow updates, visit the repo and click:
Watch → All Activity
This sends alerts for code updates, pull requests, issues, releases, and discussions.
Our current development focus covers the next 3 months, which includes:
- Enhancing AI memory & personalization
- Adding user feedback to refine recommendations
- Introducing analytics dashboards for insights
- Expanding to a voice-enabled chatbot experience
This project is self-developed and unfunded, created as part of academic coursework.
- No external financial sponsors
- Maintained by the student development team
- Future support may include community contributions or academic extensions
Food Seer has been tested among a small group of users, including friends and classmates, to evaluate its effectiveness in real-world decision-making.
During these early trials, users reported that Food Seer:
- Made choosing a meal faster and less stressful
- Offered accurate and relevant suggestions through both quiz and chat modes
- Provided a clean, easy-to-navigate interface for exploring recommendations
“It actually picked something I wanted without me scrolling for 10 minutes.” — Early User
If you use Food Seer in academic work, research, or presentations, please cite our project as follows:
APA Format
Kuethe, J., Goins, C., Parr, A., & Sauhta, M. (2025). Food Seer: Smart Meal Recommendation System. GitHub Repository. https://github.com/NovaCorz/CSC510
BibTeX
@software{foodseer2025,
author = {Kuethe, Justin and Goins, Chase and Parr, Andrew and Sauhta, Mukul},
title = {Food Seer: Smart Meal Recommendation System},
year = {2025},
publisher = {GitHub},
url = {https://github.com/NovaCorz/CSC510},
}See the full evaluation criteria in the RUBRIC.md.
Food Seer is designed as a smart recommendation system for restaurant delivery services. All meal recommendations are suggestions based on user input and preferences. Individual dietary needs, allergies, and health conditions should always be considered when making food choices. We are not responsible for any adverse reactions or health issues that may arise from following our recommendations.