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import requests | |
import geopy | |
import joblib | |
import gradio as gr | |
# Load the trained model | |
model = joblib.load('hackathonrf.joblib') | |
# Function to get latitude and longitude from location name | |
def get_coordinates(location): | |
geolocator = geopy.geocoders.Nominatim(user_agent="air_quality_app") | |
location = geolocator.geocode(location) | |
return location.latitude, location.longitude | |
# Function to get AQI value from OpenWeatherMap API | |
def get_aqi(latitude, longitude, api_key): | |
url = f"http://api.openweathermap.org/data/2.5/air_pollution?lat={latitude}&lon={longitude}&appid={api_key}" | |
response = requests.get(url) | |
data = response.json() | |
aqi_value = data['list'][0]['main']['aqi'] | |
return aqi_value | |
# Function to make prediction | |
def predict_air_quality(location, api_key): | |
latitude, longitude = get_coordinates(location) | |
aqi_value = get_aqi(latitude, longitude, api_key) | |
prediction = model.predict([[aqi_value, aqi_value, aqi_value, aqi_value]]) | |
return prediction[0] | |
# Create Gradio interface | |
iface = gr.Interface(fn=predict_air_quality, | |
inputs=["text", "text"], | |
outputs="text", | |
title="Air Quality Prediction", | |
description="Enter location and OpenWeatherMap API key:") | |
iface.launch() | |