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(