Author: Basith

This Flask application provides an API for uploading and analyzing food images using Firebase Firestore and LogMeal API. It also allows logging food items to a diet log collection.

• Image Upload and Analysis

  • Upload images of food items for nutritional analysis.
  • Preprocess images and send them to LogMeal API to retrieve nutritional data.

• Diet Logging

  • Add meals with nutritional data to a diet log collection.
  • Retrieve and display the history of scanned food items and diet logs.

• Chatbot Integration

  • Implement a chatbot using GenerativeAI to respond to user messages.

• Flask
• firebase-admin
• Pillow (PIL)
• requests
• google.generativeai (Google LLM Library)

Ensure the following environment variables are set:

• API_TOKEN: LogMeal API token
• GEMINI_API_KEY: Gemini API key for GenerativeAI

1. Clone the repository:

   git clone https://github.com/MuhammedBasith/food-lens-backend.git
   cd food-lens-backend

2. Install dependencies:

   pip install -r requirements.txt

3. Set up environment variables:

   • Create a .env file and define API_TOKEN and GEMINI_API_KEY.

4. Start the Flask server:

   python server.py

• Upload Image

  • POST /api/upload-image: Upload and analyze an image of a food item.

• Add to Diet Log

  • POST /api/add-to-diet: Log a meal with nutritional data to the diet log.

• Get Scanned Items History

  • GET /api/get-scanned-items: Retrieve the history of scanned food items.

• Get Diet Logs for Calendar

  • GET /api/calendar/diet-logs: Retrieve diet logs for display on a user calendar.

• Chatbot Interaction

  • POST /api/chatbot: Interact with a chatbot to generate responses using GenerativeAI.

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