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Multi-Agent AI That Cooks Up Recipes Just for You ~ From fridge to feast, MASALA plans it all.

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🧠 MASala AI — Your Multi-Agent Recipe Assistant!

🍛 MASala: Multi-Agent AI That Cooks Up Recipes Just for You
~ From fridge to feast, MASALA plans it all.


👥 Team Members

  • 👨‍💻 Dhyey Joshi
  • 👨‍💻 Ashutosh Gupta
  • 👩‍💻 Vedika Shinde
  • 👨‍💻 Naman Shah

🧠 Use Case: Smart Culinary Companion for Personalized Cooking

Our Multi-Agent System intelligently assists users in discovering healthy, personalized recipes using real-time inputs such as available ingredients, dietary restrictions, and allergies. With agents collaborating as an Analyzer, Nutritionist, Chef, and Presenter, the system ensures safe, delicious, and nutrition-aware meals — all generated automatically using modern AI.


🌍 Category Impact: Health & Lifestyle | AI for Personalized Wellness

By leveraging AI agents to simplify healthy cooking at home, our system:

  • Reduces cognitive load on users,
  • Promotes food safety through allergy and dietary filtering,
  • Encourages smarter, personalized eating habits.

It’s a modern take on accessible wellness — powered by collaborative intelligence.


📌 About the Project

MASala AI is a creative, multi-agent system that generates personalized recipes for users by coordinating a set of intelligent agents. It adapts to user preferences, dietary needs, and allergies, delivering healthy and delicious options.

🎥 Project Demo

Watch MASala AI in action!
👉 Click here to view the demo on YouTube

MASala AI Demo


👨‍🍳 The Agents Behind the Magic

Agent Role
🧪 Web Analyzer Scrapes and analyzes trending recipes across the web.
🥦 Nutritionist Filters ingredients based on dietary restrictions and allergies.
🍳 Chef Crafts creative, personalized recipes based on filtered inputs.
🗣 Presenter Generates readable recipe JSON and visual prompts for sharing.

All agents communicate through shared data, orchestrated via CrewAI, ensuring a seamless flow and conflict-free coordination.


🧰 Tech Stack

  • ⚙️ CrewAI – Orchestrates agent behavior and logic.
  • 🧠 Gemini (Google AI) – Powers intelligent agent reasoning.
  • 🔗 LangChain + LangSmith – Memory, observability, and traceable runs.
  • 🎨 Pollinations API – Generates AI-based food imagery.
  • 🚀 FastAPI – Powers the backend REST API.
  • 💡 React.js – Interactive frontend dashboard.

🧱 Application Architecture


🚀 Getting Started

1. Clone the Repo

git clone https://github.com/Naman009/MASala.git
cd MASala

2. Environment Setup

Create a .env file with the following:

LANGSMITH_TRACING=true
LANGSMITH_ENDPOINT="https://api.smith.langchain.com"
LANGSMITH_API_KEY="your_langsmith_key"
LANGSMITH_PROJECT="your_project_id"
GOOGLE_API_KEY="your_google_api_key"
SERPER_API_KEY="your_serper_key"

3. Install Dependencies

python -m venv masala_env
source masala_env/bin/activate  # Windows: masala_env\Scripts\activate
pip install -r backend/requirements.txt

4. Run the Backend

cd backend
uvicorn main:app --reload

5. Start the Frontend

cd frontend
npm install
npm run dev

🧪 API Endpoints

Endpoint Description
POST /generate Send user input → Get back recipe JSON
GET /logs View LangSmith logs of recent agent runs
GET /trace Fetch public trace link for debugging

📊 Dashboard Features

  • ✅ View active agents and their current tasks.
  • 📡 Real-time communication and trace logs.
  • 🍽️ Final JSON response and shareable recipe visual from Pollinations AI.
  • 📊 Agent status: Working, Pending, Completed


📄 License

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


❤️ Acknowledgements

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