PantryPal – AI Recipe Generator 🥕

Meet PantryPal: Your Personal AI-Powered Sous-Chef 🎉🍽️

Say goodbye to pantry panic! PantryPal instantly transforms whatever you’ve got on hand—plus any dietary preferences—into mouth-watering, chef-level recipes in just seconds. No more copy-pasting lists into ChatGPT or scrolling through endless recipe sites.

Built from the frustration of “what’s for dinner?”, PantryPal combines the power of Google Gemini AI with a sleek, intuitive Streamlit interface. Simply list your ingredients, set your dietary restrictions and servings, and watch as AI crafts a custom recipe complete with step-by-step instructions, nutrition breakdown, shopping list, and stunning hero images. Cooking has never been this effortless—or this inspiring!

Table of Contents

• 🌐 Live App
• 📝 Features
• 🛠️ Prerequisites
• 🚀 Installation
• 🔑 Configuration
• 📂 Directory Structure
• ▶️ Running the App
• 🧰 Linting & Formatting
• 🧑‍🍳 How to Use
• ⚙️ Customization
• 🐳 Docker Support
• 📊 Analysis Scripts
• 🤝 Contributing
• 📄 License
• 📧 Contact
• 🙏 Acknowledgments

🌐 Live App

Try it now in your browser: https://pantrypal-app.streamlit.app. Feel free to explore and generate recipes with your pantry items!

Home Page

Recipe Page

📝 Features

Although Streamlit is not a full-fledged web framework, it provides a simple and effective way to create interactive data-based web applications. Here are some of the key features of PantryPal:

• Pantry-based recipe generation: Enter your pantry items and get a recipe tailored to what you have.
• Surprise Me!: Let the AI create a random recipe from scratch.
• Dietary restrictions: Choose from options like Vegetarian, Vegan, Gluten-Free, and more.
• Servings slider: Adjust the number of servings from 1 to 12.
• Hero image selection: Pick a beautiful image for your recipe from Unsplash.
• Interactive ingredients checklist: Check off ingredients as you gather them.
• Shopping list download: Download a TXT file of your shopping list.
• Nutrition bar & donut charts: Visualize the nutritional breakdown per serving.
• Estimated difficulty: Get an idea of how challenging the recipe is.
• Download recipe: Save your recipe as JSON, Markdown, or plain TXT.
• Docker support: Run the app in a containerized environment for easy deployment.
• Linting & formatting: Code is formatted with Black and imports are sorted with isort.
• Environment variable management: Use .env or .streamlit/secrets.toml for sensitive information.
• Interactive charts: Nutrition information is displayed using Altair for better visualization.
• Persistent storage: Recipe history is saved and persists across sessions for easy access.
• User-friendly UI: Built with Streamlit for a clean and intuitive interface.

🛠️ Prerequisites

• Python 3.9 or later
• A Google Cloud API key with access to the Generative AI (Gemini) API
• An Unsplash developer access key for fetching food images

🚀 Installation

1. Clone the repository

   git clone https://github.com/hoangsonww/PantryPal-Streamlit-App.git
   cd PantryPal-Streamlit-App

2. Create & activate a virtual environment

   python3 -m venv .venv
   source .venv/bin/activate      # for macOS/Linux
   .venv\Scripts\activate         # for Windows PowerShell

3. Install dependencies

   pip install --upgrade pip
   pip install -r requirements.txt

🔑 Configuration

Create a file named .env in the project root with the following variables:

# .env
GOOGLE_AI_API_KEY=<YOUR_GOOGLE_GEMINI_API_KEY>
UNSPLASH_ACCESS_KEY=<YOUR_UNSPLASH_ACCESS_KEY>

• GOOGLE_AI_API_KEY: Your Google Cloud API key for the Generative AI (Gemini) API.
• UNSPLASH_ACCESS_KEY: Your Unsplash Access Key (register at https://unsplash.com/developers).

Alternatively, create a .streamlit/secrets.toml file with the same variables:

# .streamlit/secrets.toml
GOOGLE_AI_API_KEY = "<YOUR_GOOGLE_GEMINI_API_KEY>"
UNSPLASH_ACCESS_KEY = "<YOUR_UNSPLASH_ACCESS_KEY>"

📂 Directory Structure

pantrypal/
├── app.py
├── .env                 # Environment variables
├── .streamlit/
│   ├── config.toml      # Streamlit configuration
│   └── secrets.toml     # Alternative for .env
├── Dockerfile           # Dockerfile for containerization
├── docker-compose.yml   # Docker Compose file
├── analysis/
│   ├── ingredient_frequency.py
│   ├── nutrition_summary.py
│   └── trends_over_time.py
├── components/
│   ├── inputs.py        # Sidebar input UI
│   └── display.py       # Recipe & history rendering
├── utils/
│   ├── genai_client.py  # Gemini AI wrapper
│   ├── image_fetcher.py # Unsplash image fetcher
│   └── storage.py       # JSON‐file storage for history
├── requirements.txt     # Python dependencies
└── README.md            # This file

▶️ Running the App

With your virtual environment active and .env configured, simply run:

streamlit run app.py

Then open the URL shown in your terminal (e.g. http://localhost:8501) in your browser.

🧰 Linting & Formatting

We use Black for code formatting and isort for import sorting. To check and format your code, run:

# Check code style
black --check .
isort --check .

# Format code
black .
isort .

🧑‍🍳 How to Use

1. Enter Ingredients
   • Paste a comma-separated list of pantry items (e.g. chicken, rice, tomato).
2. Select Dietary Restrictions (optional)
   • Choose from Vegetarian, Vegan, Gluten-Free, Dairy-Free, etc.
3. Adjust Servings
   • Slide to set portions (1–12).
4. Generate
   • Click Generate Recipe to fetch from Gemini AI.
5. Pick a Hero Image
   • If images are available, select your favorite and click Confirm Image once.
6. View Recipe
   • See the title, image, ingredients checklist, shopping list, nutrition charts, difficulty, instructions, and substitutions.
7. Download
   • Grab the recipe as JSON, Markdown, or plain TXT; download your shopping list (TXT).
8. History
   • Scroll down to revisit past recipes; use Delete to remove any entry.
9. Surprise Me!
   • Click to have Gemini invent a random recipe from scratch (no pantry required).
10. Clear History
    • Wipe all saved recipes with one click.
11. Enjoy Cooking!
    • Get cooking with your generated recipe! 🧑‍🍳
    • Share your creations on social media with #PantryPal!

⚙️ Customization

• Max output tokens & temperature for AI calls can be adjusted in utils/genai_client.py.
• Caching for images is handled in utils/image_fetcher.py (TTL = 1 hour).
• Recipe History uses Local Storage to persist recipe history across sessions.
  • This allows you to revisit past recipes without needing to regenerate them.

🐳 Docker Support

To run the app in a Docker container, use the provided Dockerfile and docker-compose.yml. Build and run the container with:

docker-compose up --build

This will create a Docker image and start the app in a container. Access it at http://localhost:8501.

📊 Analysis Scripts

Once you have generated some recipes, you can analyze the data using the scripts in the analysis/ directory. These scripts provide insights into ingredient frequency, nutrition summaries, and trends over time.

Run the following commands from the project root to execute the analysis scripts:

python analysis/ingredient_frequency.py
python analysis/nutrition_summary.py
python analysis/trends_over_time.py

🤝 Contributing

1. Fork the repo
2. Create a new branch (git checkout -b feature/foo)
3. Commit your changes (git commit -m "Add foo")
4. Push to the branch (git push origin feature/foo)
5. Open a Pull Request

📄 License

This project is licensed under the MIT License. See LICENSE for details.

📧 Contact

This project is created and maintained by Son Nguyen. Below are my contact details:

• LinkedIn: hoangsonw
• GitHub: @hoangsonww

🙏 Acknowledgments

• Streamlit for the web framework
• Google Gemini AI for recipe generation
• Unsplash for beautiful images
• Altair for interactive charts
• Python-dotenv for environment variable management
• pandas for data manipulation
• Snowflake for cloud deployment

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Thank you for checking out PantryPal! 👨‍🍳 We hope it makes your cooking adventures easier and more fun. If you have any questions or suggestions, feel free to reach out! 🚀

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