Project Info

HungryFlow

Inspiration

As someone who often stares at their fridge. Deciding what they're going to eat takes 1 to 10 minutes.

What it does

You upload an image of your fridge and add the description of what taste you're currently feeling. Once complete, the AI agent's process will commence. The AI summarizes your description and ingredients, transfers that info to another AI to give a recipe, then it will talk to an AI that is programmed to judge the food if it is the right quality the user is asking, if not, Cooking AI and Food Adviser AI will go back and forward until a recipe is found.

How we built it

We used Fetch AI(uAgent), Groq, Genimini 2.5 flash, Postman, FastAPI, React with Tailwind, and Vite to build this project. Genimini 2.5 flash we use to scan the photo for ingredients. React with Tailwind and Vite as the frontend framework. Fetch AI and Groq to create an AI Agent to complete our goal.

Challenges we ran into

The challenge we ran into was that initially, we had an idea with YOLO for this project; however, we tried to implement YOLO, but it wouldn't work. The next challenge we came across was connecting our backend with our AI agents server, to was a difficult task. The big challenge was getting a good internet connection while we were working on our project.

Accomplishments we're proud of

We finally got our AI agents all talking together, and we have two that are talking until a condition is met.

What we learned

We learned

What's next

HungryFlow's next step will be adding voice recognition to allow user to input their text by speech, add a database for food, and

Hungry Flow - CalHack12.0

Hungry Flow is your AI-powered multi-agent assistant for generating recipes from images and text. Upload a food photo and describe your cravings in plain English—Hungry Flow will detect ingredients, summarize your request, cook up a recipe, and advise on its quality, all with visible step-by-step progress.

Features

Image-to-Recipe AI: Upload a food image and get a custom recipe generated using advanced AI agents.
Multi-Agent System: Detect, summarize, cook, and advise—each step handled by a dedicated agent for transparency and modularity.
Step-by-Step Progress: See each stage of the recipe creation process in real time, with retry logic for quality improvement.
Sponsor Image Integration: Easily fetch and display sponsor images using Google API, Bright Data, or Gemini-generated images.
Frontend/Backend Separation: Modern React frontend and FastAPI/uAgents backend for scalability and clarity.

Diagram

[User Uploads Image/Text]
        |
   [Detect Ingredients]
        |
   [Summarize Request]
        |
   [Cook Recipe]
        |
   [Advisor Quality Check]
        |
   [Retry (if needed)]
        |
   [Final Result]

Instructions

Frontend

Install Node.js and npm.
Change directory to frontend and run:
```
npm install
npm run dev
```
Access the app at http://localhost:5173 (or as shown in your terminal).

Backend

Install Python (minimum version 3.10).

Change directory to backend and set up your environment:

python -m venv venv
.\venv\Scripts\activate
pip install -r requirements.txt

Add your API keys to a .env file (see below).
Open two terminals:
- Terminal 1: Run the agent system:
```
python agents.py
```
- Terminal 2: Start the FastAPI server:
```
python server.py
```

Environment Variables

Create a .env file in backend/ with your API keys:

GROQ_API_KEY=your_groq_api_key
GOOGLE_API_KEY=your_google_api_key

Use Cases

Generate recipes from food images and text descriptions
Visualize each step of the agent workflow in real time
Fetch and display sponsor images for demo or branding
Retry recipe generation for improved quality

Audience

Anyone who wants to turn food photos and cravings into actionable recipes—home cooks, food bloggers, hackathon teams, and more. No technical expertise required!

Demo

Watch a demo: https://www.youtube.com/watch?v=O6Mta3VZrSQ

Quick Troubleshooting

If you see connection errors, make sure both backend terminals are running and ports are not blocked.
If sponsor images do not appear, check your API keys and backend logs.
For step-by-step progress, ensure the frontend is polling the backend and delays are set for visibility.

For more details, see the code and comments in frontend/ and backend/. Contributions and feedback welcome!

Analysis

Compare with all teams

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Metric

Quoc Anh Khoa Nguyen
13
hung98po
12

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only

CSSIn code
FastAPIIn code
HTMLIn code
JavaScriptIn code
PythonIn code
ReactIn code
Tailwind CSSIn code
TypeScriptIn code

8 of 8 appear in the indexed code.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

65 KB

Source files

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.