app.py

from flask import Flask, render_template, request, jsonify
import os
import json
import datetime
import google.generativeai as genai
from dotenv import load_dotenv
import os


load_dotenv()

app = Flask(__name__)


@app.route('/')
def index():
    return render_template('index.html')


@app.route('/analyze', methods=['POST'])
def analyze():
    try:
        # Gather crop data into a list of dictionaries
        crops_data = []
        crop_count = int(request.form.get('crop_count', 0))
        for i in range(1, crop_count + 1):
            crop_name = request.form.get(f'crop_name_{i}')
            if crop_name:
                crop = {
                    'name': crop_name,
                    'quantity': request.form.get(f'crop_quantity_{i}'),
                    'unit': request.form.get(f'crop_unit_{i}'),
                    'harvest_date': request.form.get(f'harvest_date_{i}')
                }
                crops_data.append(crop)

        warehouse_size = request.form.get('warehouse_size')
        warehouse_unit = request.form.get('warehouse_unit')
        language = request.form.get('language', 'English')

        # Calculate today's date for the day-wise planner (next 7 days)
        current_date = datetime.datetime.now()
        future_dates = [current_date + datetime.timedelta(days=x) for x in range(7)]
        date_strings = [date.strftime("%d %b %Y") for date in future_dates]

        # Enhanced prompt with a complete day-wise planner and detailed spoilage symptoms & important points
        prompt = f"""
        Analyze these crops for post-harvest storage in {language}:
        json
        {json.dumps(crops_data, indent=2)}

        Warehouse size: {warehouse_size} {warehouse_unit}

        Create a practical, visual storage plan that includes:

        1. *STORAGE SUMMARY:* Start with 3-4 bullet points summarizing key actions.

        2. *CROP CARDS:* For each crop, create a visually distinct "card" section with:
           - Crop name as heading
           - Quantity and harvest date
           - Optimal temperature and humidity (exact numbers)
           - Expected shelf life in days and calculated expiry date
           - 3-4 specific spoilage symptoms and important points detailing how spoilage affects the crop
           - Recommendations for crop placement (e.g., shelf area or storage zone)
           - Necessary precautions and measures to prevent spoilage
           - Estimated space requirements

        3. *STORAGE PRIORITY:* List crops in order of storage priority based on perishability.

        4. *VISUAL STORAGE LAYOUT:* Create a markdown table that shows crop placement in the warehouse with shelf/area names.

        5. *MONITORING PLANNER:* Provide a complete day-wise planner for the next 7 days. Specify daily tasks and monitoring details for these dates: {', '.join(date_strings)}

        *IMPORTANT FORMATTING REQUIREMENTS:*
        - Use short, simple sentences (max 10-15 words each)
        - Use markdown headers (##, ###) for clear section breaks
        - Present each crop as a visually distinct "card" section
        - Use emoji icons where appropriate (🌽 🌾 🥔 etc.)
        - Bold important numbers and dates
        - Provide only practical advice that farmers can immediately apply

        Format your response as clean markdown optimized for card-based visual presentation.
        """

        # Configure Gemini API
        api_key = os.getenv("GEMINI_API")
        genai.configure(api_key=api_key)
        model = genai.GenerativeModel(model_name='gemini-1.5-flash')
        response = model.generate_content(prompt)

        return jsonify({'success': True, 'analysis': response.text})

    except Exception as e:
        return jsonify({'success': False, 'error': str(e)})


if __name__ == '__main__':
    app.run(debug=True)