Update app.py

app.py

@@ -1,250 +1,251 @@
-from flask import Flask, render_template, request, jsonify
-import joblib
-import pandas as pd
-import requests
-import json
-import plotly.graph_objects as go
-from twilio.rest import Client
-from twilio.twiml.messaging_response import MessagingResponse
-import threading
-import os
-
-app = Flask(__name__)
-
-# --- Global variable to store the latest irrigation parameters ---
-# This acts as a temporary session to hold data between the prediction and the WhatsApp confirmation.
-last_irrigation_params = {}
-
-# --- Load the pre-trained SVM model ---
-try:
-    svm_poly_model = joblib.load('svm_poly_model.pkl')
-except FileNotFoundError:
-    print("Error: svm_poly_model.pkl not found. Make sure the model file is in the correct directory.")
-    svm_poly_model = None
-
-# --- Data Mappings for the Model ---
-# These mappings convert categorical form inputs into numerical values for the SVM model.
-crop_type_mapping = {
-    'BANANA': 0, 'BEAN': 1, 'CABBAGE': 2, 'CITRUS': 3, 'COTTON': 4, 'MAIZE': 5, 
-    'MELON': 6, 'MUSTARD': 7, 'ONION': 8, 'OTHER': 9, 'POTATO': 10, 'RICE': 11, 
-    'SOYABEAN': 12, 'SUGARCANE': 13, 'TOMATO': 14, 'WHEAT': 15
-}
-soil_type_mapping = {'DRY': 0, 'HUMID': 1, 'WET': 2}
-weather_condition_mapping = {'NORMAL': 0, 'RAINY': 1, 'SUNNY': 2, 'WINDY': 3}
-
-# --- API Keys and Credentials ---
-# It's highly recommended to use environment variables for security.
-WEATHER_API_KEY = os.getenv('WEATHER_API', 'YOUR_DEFAULT_WEATHER_API_KEY')
-TWILIO_ACCOUNT_SID = os.getenv('TWILIO_ACCOUNT_SID', 'AC490e071f8d01bf0df2f03d086c788d87')
-TWILIO_AUTH_TOKEN = os.getenv('TWILIO_AUTH_TOKEN', '224b23b950ad5a4052aba15893fdf083')
-TWILIO_PHONE_NUMBER = 'whatsapp:+14155238886'
-USER_PHONE_NUMBER = 'whatsapp:+917559355282' # The farmer's WhatsApp number
-
-# Initialize Twilio Client
-twilio_client = Client(TWILIO_ACCOUNT_SID, TWILIO_AUTH_TOKEN)
-
-def get_weather(city: str):
-    """Fetches weather data from OpenWeatherMap API."""
-    url = f"https://api.openweathermap.org/data/2.5/weather?q={city}&appid={WEATHER_API_KEY}&units=metric"
-    try:
-        response = requests.get(url)
-        response.raise_for_status()  # Raises an HTTPError for bad responses (4xx or 5xx)
-        data = response.json()
-        
-        if data['cod'] == 200:
-            weather_description = data['weather'][0]['description']
-            temperature = data['main']['temp']
-            humidity = data['main']['humidity']
-            pressure = data['main']['pressure']
-            return temperature, humidity, weather_description, pressure
-    except requests.exceptions.RequestException as e:
-        print(f"Error fetching weather data: {e}")
-    except (KeyError, json.JSONDecodeError):
-        print("Error parsing weather data.")
-        
-    return None, None, None, None
-
-def send_whatsapp_message(to_number, body_text):
-    """General function to send WhatsApp messages via Twilio."""
-    try:
-        message = twilio_client.messages.create(
-            from_=TWILIO_PHONE_NUMBER,
-            body=body_text,
-            to=to_number
-        )
-        print(f"Twilio Message SID: {message.sid}")
-        return message.sid
-    except Exception as e:
-        print(f"Error sending WhatsApp message: {e}")
-        return None
-
-def trigger_irrigation_complete():
-    """Function called by the timer when irrigation is finished."""
-    global last_irrigation_params
-    if not last_irrigation_params:
-        print("No irrigation parameters found for completion message.")
-        return
-
-    crop_type = last_irrigation_params.get('crop_type', 'N/A')
-    city = last_irrigation_params.get('city', 'N/A')
-    estimated_time = last_irrigation_params.get('estimated_time_duration', 0)
-    time_unit = last_irrigation_params.get('time_unit', 'seconds')
-
-    message_text = (
-        f"✅ Irrigation Complete!\n\n"
-        f"Crop: {crop_type}\n"
-        f"Location: {city}\n"
-        f"Duration: {estimated_time:.2f} {time_unit}\n\n"
-        "The motor has been turned off automatically."
-    )
-    send_whatsapp_message(USER_PHONE_NUMBER, message_text)
-    print(f"Irrigation complete message sent after {estimated_time:.2f} {time_unit}.")
-
-# --- Flask Routes ---
-
-@app.route('/')
-def index():
-    """Renders the main input page."""
-    return render_template('index.html')
-
-@app.route('/fetch_weather', methods=['GET'])
-def fetch_weather():
-    """API endpoint to fetch weather data for the front-end."""
-    city = request.args.get('city')
-    if city:
-        temperature, humidity, description, pressure = get_weather(city)
-        if temperature is not None:
-            return jsonify({
-                'description': description.capitalize(),
-                'temperature': temperature,
-                'humidity': humidity,
-                'pressure': pressure
-            })
-    return jsonify(None), 404
-
-@app.route('/predict', methods=['POST'])
-def predict():
-    """Handles form submission, runs prediction, and shows results."""
-    if svm_poly_model is None:
-        return "Model not loaded, cannot perform prediction.", 500
-        
-    global last_irrigation_params
-
-    # --- 1. Get Form Data ---
-    crop_type = request.form['crop_type']
-    soil_type = request.form['soil_type']
-    city = request.form['city']
-    motor_capacity = float(request.form['motor_capacity'])
-
-    # --- 2. Get Weather Data ---
-    temperature, humidity, description, pressure = get_weather(city)
-    if temperature is None: # Fallback if API fails
-        temperature, humidity, description, pressure = 32.0, 60, "Not Available", 1012
-        weather_condition = 'NORMAL'
-    else:
-        desc_lower = description.lower()
-        weather_condition = ('SUNNY' if 'clear' in desc_lower else
-                             'RAINY' if 'rain' in desc_lower else
-                             'WINDY' if 'wind' in desc_lower else
-                             'NORMAL')
-
-    # --- 3. Prepare Data for Model ---
-    user_data = pd.DataFrame({
-        'CROP TYPE': [crop_type_mapping.get(crop_type)],
-        'SOIL TYPE': [soil_type_mapping.get(soil_type)],
-        'TEMPERATURE': [temperature],
-        'WEATHER CONDITION': [weather_condition_mapping.get(weather_condition)]
-    })
-
-    # --- 4. Predict Water Requirement ---
-    water_requirement = svm_poly_model.predict(user_data)[0]
-
-    # --- 5. Calculate Motor On-Time ---
-    estimated_time_seconds = (water_requirement / motor_capacity) if motor_capacity > 0 else 0
-    if estimated_time_seconds < 120:
-        time_unit = "seconds"
-        display_time = estimated_time_seconds
-    else:
-        time_unit = "minutes"
-        display_time = estimated_time_seconds / 60
-
-    # --- 6. Store Parameters and Send WhatsApp ---
-    last_irrigation_params = {
-        "estimated_time_seconds": estimated_time_seconds,
-        "estimated_time_duration": display_time,
-        "time_unit": time_unit,
-        "crop_type": crop_type,
-        "city": city,
-    }
-
-    message_to_farmer = (
-        f"💧 Irrigation Prediction Ready 💧\n\n"
-        f"Crop: *{crop_type}*\n"
-        f"Location: *{city}*\n"
-        f"Weather: {description.capitalize()}, {temperature}°C\n"
-        f"Water Needed: *{water_requirement:.2f} m³/sq.m*\n"
-        f"Est. Motor Time: *{display_time:.2f} {time_unit}*\n\n"
-        "Reply *1* to START the motor.\n"
-        "Reply *0* to CANCEL."
-    )
-    send_whatsapp_message(USER_PHONE_NUMBER, message_to_farmer)
-
-    # --- 7. Create Gauge Charts for UI ---
-    water_gauge = go.Figure(go.Indicator(
-        mode="gauge+number", value=water_requirement, title={"text": "Water Req (m³/sq.m)"},
-        gauge={"axis": {"range": [None, 100]}, "bar": {"color": "royalblue"}}
-    ))
-    time_gauge = go.Figure(go.Indicator(
-        mode="gauge+number", value=round(display_time, 2), title={"text": f"Time ({time_unit})"},
-        gauge={"axis": {"range": [None, 60 if time_unit == 'seconds' else 120]}, "bar": {"color": "green"}}
-    ))
-
-    # --- 8. Render Results Page ---
-    return render_template('predict.html',
-                           water_requirement=round(water_requirement, 2),
-                           estimated_time_duration=round(display_time, 2),
-                           time_unit=time_unit,
-                           water_gauge=water_gauge.to_html(full_html=False),
-                           time_gauge=time_gauge.to_html(full_html=False),
-                           crop_type=crop_type, city=city)
-
-@app.route('/twilio_reply', methods=['POST'])
-def twilio_reply():
-    """Handles incoming WhatsApp replies to start or cancel the motor."""
-    global last_irrigation_params
-    message_body = request.values.get('Body', '').strip()
-    resp = MessagingResponse()
-
-    if message_body == "1":
-        if last_irrigation_params and 'estimated_time_seconds' in last_irrigation_params:
-            duration_sec = last_irrigation_params['estimated_time_seconds']
-            
-            # Start a background timer thread
-            timer = threading.Timer(duration_sec, trigger_irrigation_complete)
-            timer.daemon = True
-            timer.start()
-            
-            resp.message(f"✅ Motor started! Irrigation will run for {last_irrigation_params['estimated_time_duration']:.2f} {last_irrigation_params['time_unit']} and will stop automatically.")
-        else:
-            resp.message("❌ Error: No pending irrigation task found. Please submit a new prediction first.")
-    elif message_body == "0":
-        resp.message("👍 Motor start has been canceled.")
-        last_irrigation_params = {} # Clear params
-    else:
-        resp.message("Invalid reply. Please reply '1' to start the motor or '0' to cancel.")
-
-    return str(resp)
-
-# Dummy endpoints called from front-end JS, actual logic is handled via WhatsApp reply
-@app.route('/start_motor', methods=['POST'])
-def start_motor():
-    return jsonify({"status": "motor_start_request_logged"})
-
-@app.route('/irrigation_complete', methods=['POST'])
-def irrigation_complete():
-    return jsonify({"status": "irrigation_complete_request_logged"})
-
-
-if __name__ == "__main__":
-    # For development, use debug=True. For production, use a proper WSGI server like Gunicorn.
+from flask import Flask, render_template, request, jsonify
+import joblib
+import pandas as pd
+import requests
+import json
+import plotly.graph_objects as go
+from twilio.rest import Client
+from twilio.twiml.messaging_response import MessagingResponse
+import threading
+import os
+
+
+app = Flask(__name__)
+
+# --- Global variable to store the latest irrigation parameters ---
+# This acts as a temporary session to hold data between the prediction and the WhatsApp confirmation.
+last_irrigation_params = {}
+
+# --- Load the pre-trained SVM model ---
+try:
+    svm_poly_model = joblib.load('svm_poly_model.pkl')
+except FileNotFoundError:
+    print("Error: svm_poly_model.pkl not found. Make sure the model file is in the correct directory.")
+    svm_poly_model = None
+
+# --- Data Mappings for the Model ---
+# These mappings convert categorical form inputs into numerical values for the SVM model.
+crop_type_mapping = {
+    'BANANA': 0, 'BEAN': 1, 'CABBAGE': 2, 'CITRUS': 3, 'COTTON': 4, 'MAIZE': 5, 
+    'MELON': 6, 'MUSTARD': 7, 'ONION': 8, 'OTHER': 9, 'POTATO': 10, 'RICE': 11, 
+    'SOYABEAN': 12, 'SUGARCANE': 13, 'TOMATO': 14, 'WHEAT': 15
+}
+soil_type_mapping = {'DRY': 0, 'HUMID': 1, 'WET': 2}
+weather_condition_mapping = {'NORMAL': 0, 'RAINY': 1, 'SUNNY': 2, 'WINDY': 3}
+
+# --- API Keys and Credentials ---
+# It's highly recommended to use environment variables for security.
+WEATHER_API_KEY = os.getenv('WEATHER_API', 'YOUR_DEFAULT_WEATHER_API_KEY')
+TWILIO_ACCOUNT_SID = os.getenv('TWILIO_ACCOUNT_SID', 'AC490e071f8d01bf0df2f03d086c788d87')
+TWILIO_AUTH_TOKEN = os.getenv('TWILIO_AUTH_TOKEN', '224b23b950ad5a4052aba15893fdf083')
+TWILIO_PHONE_NUMBER = 'whatsapp:+14155238886'
+USER_PHONE_NUMBER = 'whatsapp:+917559355282' # The farmer's WhatsApp number
+
+# Initialize Twilio Client
+twilio_client = Client(TWILIO_ACCOUNT_SID, TWILIO_AUTH_TOKEN)
+
+def get_weather(city: str):
+    """Fetches weather data from OpenWeatherMap API."""
+    url = f"https://api.openweathermap.org/data/2.5/weather?q={city}&appid={WEATHER_API_KEY}&units=metric"
+    try:
+        response = requests.get(url)
+        response.raise_for_status()  # Raises an HTTPError for bad responses (4xx or 5xx)
+        data = response.json()
+        
+        if data['cod'] == 200:
+            weather_description = data['weather'][0]['description']
+            temperature = data['main']['temp']
+            humidity = data['main']['humidity']
+            pressure = data['main']['pressure']
+            return temperature, humidity, weather_description, pressure
+    except requests.exceptions.RequestException as e:
+        print(f"Error fetching weather data: {e}")
+    except (KeyError, json.JSONDecodeError):
+        print("Error parsing weather data.")
+        
+    return None, None, None, None
+
+def send_whatsapp_message(to_number, body_text):
+    """General function to send WhatsApp messages via Twilio."""
+    try:
+        message = twilio_client.messages.create(
+            from_=TWILIO_PHONE_NUMBER,
+            body=body_text,
+            to=to_number
+        )
+        print(f"Twilio Message SID: {message.sid}")
+        return message.sid
+    except Exception as e:
+        print(f"Error sending WhatsApp message: {e}")
+        return None
+
+def trigger_irrigation_complete():
+    """Function called by the timer when irrigation is finished."""
+    global last_irrigation_params
+    if not last_irrigation_params:
+        print("No irrigation parameters found for completion message.")
+        return
+
+    crop_type = last_irrigation_params.get('crop_type', 'N/A')
+    city = last_irrigation_params.get('city', 'N/A')
+    estimated_time = last_irrigation_params.get('estimated_time_duration', 0)
+    time_unit = last_irrigation_params.get('time_unit', 'seconds')
+
+    message_text = (
+        f"✅ Irrigation Complete!\n\n"
+        f"Crop: {crop_type}\n"
+        f"Location: {city}\n"
+        f"Duration: {estimated_time:.2f} {time_unit}\n\n"
+        "The motor has been turned off automatically."
+    )
+    send_whatsapp_message(USER_PHONE_NUMBER, message_text)
+    print(f"Irrigation complete message sent after {estimated_time:.2f} {time_unit}.")
+
+# --- Flask Routes ---
+
+@app.route('/')
+def index():
+    """Renders the main input page."""
+    return render_template('index.html')
+
+@app.route('/fetch_weather', methods=['GET'])
+def fetch_weather():
+    """API endpoint to fetch weather data for the front-end."""
+    city = request.args.get('city')
+    if city:
+        temperature, humidity, description, pressure = get_weather(city)
+        if temperature is not None:
+            return jsonify({
+                'description': description.capitalize(),
+                'temperature': temperature,
+                'humidity': humidity,
+                'pressure': pressure
+            })
+    return jsonify(None), 404
+
+@app.route('/predict', methods=['POST'])
+def predict():
+    """Handles form submission, runs prediction, and shows results."""
+    if svm_poly_model is None:
+        return "Model not loaded, cannot perform prediction.", 500
+        
+    global last_irrigation_params
+
+    # --- 1. Get Form Data ---
+    crop_type = request.form['crop_type']
+    soil_type = request.form['soil_type']
+    city = request.form['city']
+    motor_capacity = float(request.form['motor_capacity'])
+
+    # --- 2. Get Weather Data ---
+    temperature, humidity, description, pressure = get_weather(city)
+    if temperature is None: # Fallback if API fails
+        temperature, humidity, description, pressure = 32.0, 60, "Not Available", 1012
+        weather_condition = 'NORMAL'
+    else:
+        desc_lower = description.lower()
+        weather_condition = ('SUNNY' if 'clear' in desc_lower else
+                             'RAINY' if 'rain' in desc_lower else
+                             'WINDY' if 'wind' in desc_lower else
+                             'NORMAL')
+
+    # --- 3. Prepare Data for Model ---
+    user_data = pd.DataFrame({
+        'CROP TYPE': [crop_type_mapping.get(crop_type)],
+        'SOIL TYPE': [soil_type_mapping.get(soil_type)],
+        'TEMPERATURE': [temperature],
+        'WEATHER CONDITION': [weather_condition_mapping.get(weather_condition)]
+    })
+
+    # --- 4. Predict Water Requirement ---
+    water_requirement = svm_poly_model.predict(user_data)[0]
+
+    # --- 5. Calculate Motor On-Time ---
+    estimated_time_seconds = (water_requirement / motor_capacity) if motor_capacity > 0 else 0
+    if estimated_time_seconds < 120:
+        time_unit = "seconds"
+        display_time = estimated_time_seconds
+    else:
+        time_unit = "minutes"
+        display_time = estimated_time_seconds / 60
+
+    # --- 6. Store Parameters and Send WhatsApp ---
+    last_irrigation_params = {
+        "estimated_time_seconds": estimated_time_seconds,
+        "estimated_time_duration": display_time,
+        "time_unit": time_unit,
+        "crop_type": crop_type,
+        "city": city,
+    }
+
+    message_to_farmer = (
+        f"💧 Irrigation Prediction Ready 💧\n\n"
+        f"Crop: *{crop_type}*\n"
+        f"Location: *{city}*\n"
+        f"Weather: {description.capitalize()}, {temperature}°C\n"
+        f"Water Needed: *{water_requirement:.2f} m³/sq.m*\n"
+        f"Est. Motor Time: *{display_time:.2f} {time_unit}*\n\n"
+        "Reply *1* to START the motor.\n"
+        "Reply *0* to CANCEL."
+    )
+    send_whatsapp_message(USER_PHONE_NUMBER, message_to_farmer)
+
+    # --- 7. Create Gauge Charts for UI ---
+    water_gauge = go.Figure(go.Indicator(
+        mode="gauge+number", value=water_requirement, title={"text": "Water Req (m³/sq.m)"},
+        gauge={"axis": {"range": [None, 100]}, "bar": {"color": "royalblue"}}
+    ))
+    time_gauge = go.Figure(go.Indicator(
+        mode="gauge+number", value=round(display_time, 2), title={"text": f"Time ({time_unit})"},
+        gauge={"axis": {"range": [None, 60 if time_unit == 'seconds' else 120]}, "bar": {"color": "green"}}
+    ))
+
+    # --- 8. Render Results Page ---
+    return render_template('predict.html',
+                           water_requirement=round(water_requirement, 2),
+                           estimated_time_duration=round(display_time, 2),
+                           time_unit=time_unit,
+                           water_gauge=water_gauge.to_html(full_html=False),
+                           time_gauge=time_gauge.to_html(full_html=False),
+                           crop_type=crop_type, city=city)
+
+@app.route('/twilio_reply', methods=['POST'])
+def twilio_reply():
+    """Handles incoming WhatsApp replies to start or cancel the motor."""
+    global last_irrigation_params
+    message_body = request.values.get('Body', '').strip()
+    resp = MessagingResponse()
+
+    if message_body == "1":
+        if last_irrigation_params and 'estimated_time_seconds' in last_irrigation_params:
+            duration_sec = last_irrigation_params['estimated_time_seconds']
+            
+            # Start a background timer thread
+            timer = threading.Timer(duration_sec, trigger_irrigation_complete)
+            timer.daemon = True
+            timer.start()
+            
+            resp.message(f"✅ Motor started! Irrigation will run for {last_irrigation_params['estimated_time_duration']:.2f} {last_irrigation_params['time_unit']} and will stop automatically.")
+        else:
+            resp.message("❌ Error: No pending irrigation task found. Please submit a new prediction first.")
+    elif message_body == "0":
+        resp.message("👍 Motor start has been canceled.")
+        last_irrigation_params = {} # Clear params
+    else:
+        resp.message("Invalid reply. Please reply '1' to start the motor or '0' to cancel.")
+
+    return str(resp)
+
+# Dummy endpoints called from front-end JS, actual logic is handled via WhatsApp reply
+@app.route('/start_motor', methods=['POST'])
+def start_motor():
+    return jsonify({"status": "motor_start_request_logged"})
+
+@app.route('/irrigation_complete', methods=['POST'])
+def irrigation_complete():
+    return jsonify({"status": "irrigation_complete_request_logged"})
+
+
+if __name__ == "__main__":
+    # For development, use debug=True. For production, use a proper WSGI server like Gunicorn.
     app.run(host="0.0.0.0", port=7860, debug=True)