Create app.py

app.py

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+import gradio as gr
+import requests
+import time
+import folium
+from folium import plugins
+import pandas as pd
+from groq import Groq
+
+# Initialize Groq client with your API key
+client = Groq(api_key="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")
+
+# Function to get AI response (Groq model)
+def get_response(user_input):
+    """Get response from Groq AI model."""
+    if 'messages' not in gradio_state:
+        gradio_state['messages'] = []
+        
+    gradio_state['messages'].append({"role": "user", "content": user_input})
+    
+    # Call Groq API to get the AI's response
+    chat_completion = client.chat.completions.create(
+        messages=gradio_state['messages'],
+        model="llama3-8b-8192"  # Specify model you want to use from Groq
+    )
+    
+    ai_message = chat_completion.choices[0].message.content
+    gradio_state['messages'].append({"role": "assistant", "content": ai_message})
+    
+    return ai_message
+
+# Emergency call function
+def emergency_call():
+    time.sleep(2)  # Simulating a short delay
+    return "Emergency services have been contacted. Help is on the way!"
+
+# Dangerous Area Map function
+def dangerous_area_map():
+    data = {
+        'latitude': [40.7128, 34.0522, 51.5074, 48.8566, 35.6762],
+        'longitude': [-74.0060, -118.2437, -0.1278, 2.3522, 139.6503],
+        'area': ['New York', 'Los Angeles', 'London', 'Paris', 'Tokyo'],
+        'danger_level': ['High', 'Medium', 'Low', 'High', 'Medium']
+    }
+    df = pd.DataFrame(data)
+    map_center = [df['latitude'].mean(), df['longitude'].mean()]
+    m = folium.Map(location=map_center, zoom_start=2)
+
+    def get_color(danger_level):
+        if danger_level == 'High':
+            return 'red'
+        elif danger_level == 'Medium':
+            return 'orange'
+        else:
+            return 'green'
+
+    for index, row in df.iterrows():
+        danger_color = get_color(row['danger_level'])
+        folium.CircleMarker(
+            location=[row['latitude'], row['longitude']],
+            radius=10,
+            color=danger_color,
+            fill=True,
+            fill_color=danger_color,
+            fill_opacity=0.7,
+            popup=f"Area: {row['area']}<br> Danger Level: {row['danger_level']}"
+        ).add_to(m)
+
+    heat_data = [[row['latitude'], row['longitude']] for index, row in df.iterrows()]
+    plugins.HeatMap(heat_data).add_to(m)
+
+    map_html = m._repr_html_()
+    return map_html
+
+# ORS Route function
+def ors_route(start_lat, start_lon, end_lat, end_lon):
+    api_key = '5b3ce3597851110001cf6248678e77a7fc474afbbb5ec203d721079c'
+    start_point = f'{start_lon},{start_lat}'  # ORS expects lon, lat
+    end_point = f'{end_lon},{end_lat}'
+    
+    # API request to OpenRouteService
+    url = f'https://api.openrouteservice.org/v2/directions/driving-car?api_key={api_key}&start={start_point}&end={end_point}'
+    response = requests.get(url)
+
+    if response.status_code == 200:
+        data = response.json()
+        # Extract the route information
+        route = data['features'][0]['geometry']['coordinates']
+        route_map = folium.Map(