Update app.py

app.py

@@ -5,13 +5,14 @@ import numpy as np
 import joblib
 import google.generativeai as genai
 import gradio as gr
-from google.colab import drive, userdata
+from google.colab import drive
 from datetime import datetime, timedelta
 from tensorflow.keras.models import load_model
 from tensorflow.keras.preprocessing import image as keras_image
 from tensorflow.keras.applications.vgg16 import preprocess_input as vgg_preprocess
 from tensorflow.keras.applications.xception import preprocess_input as xce_preprocess
 from tensorflow.keras.losses import BinaryFocalCrossentropy
+from PIL import Image
 
 # --- CONFIGURATION ---
 # Coordinates for a representative forest area in Pakistan
@@ -27,7 +28,10 @@ API_URL = (
 )
 
 # --- GEMINI SETUP ---
-GOOGLE_API_KEY = userdata.get('GOOGLE_API_KEY')
+# Retrieve API key from environment variable (set in Hugging Face Secrets)
+GOOGLE_API_KEY = os.environ.get('GOOGLE_API_KEY')
+if not GOOGLE_API_KEY:
+    raise ValueError("Missing GOOGLE_API_KEY environment variable")
 genai.configure(api_key=GOOGLE_API_KEY)
 flash = genai.GenerativeModel('gemini-1.5-flash')
 
@@ -74,7 +78,7 @@ def detect_fire(img):
     x = keras_image.img_to_array(img.resize((128,128)))[None]
     x = vgg_preprocess(x)
     prob = float(vgg_model.predict(x)[0][0])
-    return prob >= 0.5, prob
+    return prob>=0.5, prob
 
 
 def classify_severity(img):
@@ -84,7 +88,7 @@ def classify_severity(img):
     rf_p = rf_model.predict(preds)[0]
     xgb_p = xgb_model.predict(preds)[0]
     ensemble = int(round((rf_p + xgb_p)/2))
-    return target_map.get(ensemble, 'moderate')
+    return target_map.get(ensemble,'moderate')
 
 
 def fetch_weather_trend(lat, lon):
@@ -135,7 +139,7 @@ def pipeline(image):
     img = Image.fromarray(image).convert('RGB')
     fire, prob = detect_fire(img)
     if not fire:
-        return f"No wildfire detected (prob={prob:.2f})", "N/A", "No wildfire detected. Stay alert."
+        return f"No wildfire detected (prob={prob:.2f})", "N/A", "**No wildfire detected. Stay alert.**"
     severity = classify_severity(img)
     trend = fetch_weather_trend(*FOREST_COORDS['Pakistan Forest'])
     recs = generate_recommendations(True, severity, trend)