Update app.py

app.py

@@ -1,4 +1,4 @@
-from flask import Flask, render_template, request, jsonify, session
+from flask import Flask, render_template, request, jsonify
 import joblib
 import pandas as pd
 import requests
@@ -15,11 +15,21 @@ import threading
 import os
 import time
 import secrets
+import math
+from matplotlib.patches import Wedge, Circle
 
 app = Flask(__name__)
 
 app.secret_key = os.getenv('FLASK_SECRET_KEY', secrets.token_hex(24))
 
+# -------------------------
+# 🔑 Global irrigation state (quick fix)
+# -------------------------
+irrigation_state = {}
+
+# -------------------------
+# Load ML Model
+# -------------------------
 svm_poly_model = None
 try:
     svm_poly_model = joblib.load('svm_poly_model.pkl')
@@ -29,6 +39,9 @@ except FileNotFoundError:
 except Exception as e:
     print(f"Error loading SVM model: {e}")
 
+# -------------------------
+# Mappings
+# -------------------------
 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,
@@ -37,6 +50,9 @@ crop_type_mapping = {
 soil_type_mapping = {'DRY': 0, 'HUMID': 1, 'WET': 2}
 weather_condition_mapping = {'NORMAL': 0, 'RAINY': 1, 'SUNNY': 2, 'WINDY': 3}
 
+# -------------------------
+# API & Twilio Config
+# -------------------------
 WEATHER_API_KEY = os.getenv('WEATHER_API', 'ee75ffd59875aa5ca6c207e594336b30')
 TWILIO_ACCOUNT_SID = os.getenv('TWILIO_ACCOUNT_SID', 'ACe45f7038c5338a153d1126ca6d547c84')
 TWILIO_AUTH_TOKEN = os.getenv('TWILIO_AUTH_TOKEN', '48b9eea898885ef395d48edc74924340')
@@ -45,7 +61,9 @@ USER_PHONE_NUMBER = os.getenv('FARMER_PHONE_NUMBER', 'whatsapp:+919763059811')
 
 twilio_client = Client(TWILIO_ACCOUNT_SID, TWILIO_AUTH_TOKEN)
 
-
+# -------------------------
+# Helper Functions
+# -------------------------
 def get_weather(city: str):
     url = f"https://api.openweathermap.org/data/2.5/weather?q={city}&appid={WEATHER_API_KEY}&units=metric"
     try:
@@ -56,11 +74,9 @@ def get_weather(city: str):
             return (data['main']['temp'], data['main']['humidity'],
                     data['weather'][0]['description'], data['main']['pressure'])
         else:
-            print(f"Weather API returned an error: {data.get('message', 'Unknown error')}")
-    except requests.exceptions.RequestException as e:
+            print(f"Weather API error: {data.get('message', 'Unknown error')}")
+    except Exception as e:
         print(f"Error fetching weather data for {city}: {e}")
-    except (KeyError, json.JSONDecodeError) as e:
-        print(f"Error parsing weather data for {city}: {e}")
     return None, None, None, None
 
 
@@ -88,10 +104,7 @@ def trigger_irrigation_complete(crop_type, city, estimated_time_duration, time_u
     )
     send_whatsapp_message(user_phone, message_text)
     print(f"Irrigation complete message sent to {user_phone} after {estimated_time_duration:.2f} {time_unit}.")
-
-
-import math
-from matplotlib.patches import Wedge, Circle
+    irrigation_state.pop('current', None)  # clear state
 
 
 def fig_to_datauri(fig, fmt='png', dpi=150):
@@ -115,7 +128,6 @@ def draw_gauge(value, max_value, title="", unit=""):
 
     bg_wedge = Wedge((0, 0), 1.0, 180, 0, facecolor='#4CAF50', edgecolor='none', width=0.3)
     ax.add_patch(bg_wedge)
-
     fg_wedge = Wedge((0, 0), 1.0, 180, angle, facecolor='#FFFFFF', edgecolor='none', width=0.3)
     ax.add_patch(fg_wedge)
 
@@ -127,27 +139,26 @@ def draw_gauge(value, max_value, title="", unit=""):
         xi_inner, yi_inner = inner_r * math.cos(t_angle), inner_r * math.sin(t_angle)
         xi_outer, yi_outer = outer_r * math.cos(t_angle), outer_r * math.sin(t_angle)
         ax.plot([xi_inner, xi_outer], [yi_inner, yi_outer], color='#333', lw=1)
-
         lbl_r = 0.55
         xl, yl = lbl_r * math.cos(t_angle), lbl_r * math.sin(t_angle)
         lbl_val = int(round(max_value * t_ratio))
-        ax.text(xl, yl, str(lbl_val), horizontalalignment='center', verticalalignment='center', fontsize=8, color='#333')
+        ax.text(xl, yl, str(lbl_val), ha='center', va='center', fontsize=8, color='#333')
 
     needle_length = 0.85
     needle_angle = math.radians(angle)
     xn, yn = needle_length * math.cos(needle_angle), needle_length * math.sin(needle_angle)
     ax.plot([0, xn], [0, yn], color='red', lw=2)
-    center = Circle((0, 0), 0.05, color='black')
-    ax.add_patch(center)
-
-    ax.text(0, -0.15, f"{title}", horizontalalignment='center', verticalalignment='center', fontsize=10, weight='bold')
-    ax.text(0, -0.32, f"{val:.2f} {unit}", horizontalalignment='center', verticalalignment='center', fontsize=10, color='#216e39')
+    ax.add_patch(Circle((0, 0), 0.05, color='black'))
 
+    ax.text(0, -0.15, f"{title}", ha='center', va='center', fontsize=10, weight='bold')
+    ax.text(0, -0.32, f"{val:.2f} {unit}", ha='center', va='center', fontsize=10, color='#216e39')
     ax.set_xlim(-1.05, 1.05)
     ax.set_ylim(-0.35, 1.05)
-
     return fig
 
+# -------------------------
+# Routes
+# -------------------------
 @app.route('/')
 def index():
     return render_template('index.html')
@@ -166,8 +177,8 @@ def fetch_weather_route():
                 'pressure': pressure
             })
         else:
-            return jsonify({'error': 'Could not fetch weather data for the specified city.'}), 404
-    return jsonify({'error': 'City parameter is missing.'}), 400
+            return jsonify({'error': 'Could not fetch weather data.'}), 404
+    return jsonify({'error': 'City parameter missing.'}), 400
 
 
 @app.route('/predict', methods=['POST'])
@@ -175,8 +186,6 @@ def predict():
     if svm_poly_model is None:
         return "Model not loaded, cannot perform prediction.", 500
 
-    session.pop('irrigation_params', None)
-
     crop_type = request.form['crop_type']
     soil_type = request.form['soil_type']
     city = request.form['city']
@@ -186,39 +195,37 @@ def predict():
         if motor_capacity <= 0:
             return "Motor capacity must be a positive number.", 400
     except ValueError:
-        return "Invalid motor capacity. Please enter a number.", 400
+        return "Invalid motor capacity.", 400
 
     temperature, humidity, description, pressure = get_weather(city)
     if temperature is None:
-        print(f"Warning: Could not fetch live weather for {city}. Using default values.")
         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 or 'sun' in desc_lower else
                              'RAINY' if 'rain' in desc_lower or 'drizzle' in desc_lower else
-                             'WINDY' if 'wind' in desc_lower else
-                             'NORMAL')
+                             'WINDY' if 'wind' in desc_lower else 'NORMAL')
 
     if crop_type not in crop_type_mapping or soil_type not in soil_type_mapping:
         return "Invalid Crop Type or Soil Type.", 400
 
     user_data = pd.DataFrame({
-        'CROP TYPE': [crop_type_mapping.get(crop_type)],
-        'SOIL TYPE': [soil_type_mapping.get(soil_type)],
+        'CROP TYPE': [crop_type_mapping[crop_type]],
+        'SOIL TYPE': [soil_type_mapping[soil_type]],
         'TEMPERATURE': [temperature],
-        'WEATHER CONDITION': [weather_condition_mapping.get(weather_condition)]
+        'WEATHER CONDITION': [weather_condition_mapping[weather_condition]]
     })
 
     water_requirement = svm_poly_model.predict(user_data)[0]
-    estimated_time_seconds = (water_requirement / motor_capacity) if motor_capacity > 0 else 0
+    estimated_time_seconds = water_requirement / motor_capacity if motor_capacity > 0 else 0
 
     if estimated_time_seconds < 120:
         time_unit, display_time = "seconds", estimated_time_seconds
     else:
         time_unit, display_time = "minutes", estimated_time_seconds / 60
 
-    session['irrigation_params'] = {
+    irrigation_state['current'] = {
         "estimated_time_seconds": estimated_time_seconds,
         "estimated_time_duration": display_time,
         "time_unit": time_unit,
@@ -244,15 +251,14 @@ def predict():
     time_img = None
     try:
         max_water_axis = max(100, water_requirement * 1.5)
-        fig_w = draw_gauge(water_requirement, max_water_axis, title="Water Req (m³/sq.m)", unit="")
+        fig_w = draw_gauge(water_requirement, max_water_axis, title="Water Req (m³/sq.m)")
         water_img = fig_to_datauri(fig_w)
     except Exception as e:
         print(f"Could not generate water gauge: {e}")
 
     try:
         max_time_axis = 60 if time_unit == 'seconds' else max(120, display_time * 1.5)
-        time_val = round(display_time, 2)
-        fig_t = draw_gauge(time_val, max_time_axis, title=f"Motor Time ({time_unit})", unit=time_unit)
+        fig_t = draw_gauge(display_time, max_time_axis, title=f"Motor Time ({time_unit})", unit=time_unit)
         time_img = fig_to_datauri(fig_t)
     except Exception as e:
         print(f"Could not generate time gauge: {e}")
@@ -269,16 +275,14 @@ def predict():
 def twilio_reply():
     message_body = request.values.get('Body', '').strip()
     resp = MessagingResponse()
-
-    irrigation_params = session.get('irrigation_params')
+    irrigation_params = irrigation_state.get('current')
 
     if message_body == "1":
         if irrigation_params and 'estimated_time_seconds' in irrigation_params:
             duration_sec = irrigation_params['estimated_time_seconds']
-
             irrigation_params['monitoring_active'] = True
             irrigation_params['timer_start_time'] = time.time()
-            session['irrigation_params'] = irrigation_params
+            irrigation_state['current'] = irrigation_params
 
             timer = threading.Timer(duration_sec, trigger_irrigation_complete, args=[
                 irrigation_params['crop_type'],
@@ -291,12 +295,13 @@ def twilio_reply():
             timer.start()
 
             resp.message(
-                f"✅ Motor started! Irrigation will run for {irrigation_params['estimated_time_duration']:.2f} {irrigation_params['time_unit']}. The monitoring page is now active.")
+                f"✅ Motor started! Irrigation will run for {irrigation_params['estimated_time_duration']:.2f} {irrigation_params['time_unit']}."
+            )
         else:
-            resp.message("❌ Error: No pending irrigation task found. Please submit a new prediction first.")
+            resp.message("❌ Error: No pending irrigation task found.")
     elif message_body == "0":
         resp.message("👍 Motor start has been canceled.")
-        session.pop('irrigation_params', None)
+        irrigation_state.pop('current', None)
     else:
         resp.message("Invalid reply. Please reply '1' to start or '0' to cancel.")
 
@@ -305,13 +310,11 @@ def twilio_reply():
 
 @app.route('/monitoring_status')
 def monitoring_status():
-    irrigation_params = session.get('irrigation_params')
-
+    irrigation_params = irrigation_state.get('current')
     if not irrigation_params:
         return jsonify({"monitoring": False})
 
     is_active = irrigation_params.get("monitoring_active", False)
-
     time_remaining = None
     if is_active:
         start_time = irrigation_params.get("timer_start_time", 0)
@@ -320,8 +323,8 @@ def monitoring_status():
         time_remaining = max(0, total_duration - elapsed_time)
         if time_remaining <= 0:
             is_active = False
-            session.pop('irrigation_params', None)
-            print("Monitoring status detected irrigation completion and cleared session.")
+            irrigation_state.pop('current', None)
+            print("Monitoring finished, state cleared.")
 
     return jsonify({
         "monitoring": is_active,
@@ -331,4 +334,4 @@ def monitoring_status():
 
 
 if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=7860, debug=True)
+    app.run(host="0.0.0.0", port=7860, debug=True)