import gradio as gr
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

# Load your data here if not already loaded
# data = pd.read_csv('path_to_your_data.csv')

def analyze_sentiment(data):
    # Calculate summary global sentiment
    overall_sentiment = data['airline_sentiment'].value_counts().reset_index()
    overall_sentiment.columns = ['Sentiment', 'Freq']
    
    # Plot histogram
    plt.figure(figsize=(8, 6))
    sns.barplot(data=overall_sentiment, x='Sentiment', y='Freq', palette=['indianred', 'deepskyblue'])
    plt.xlabel('Sentiment')
    plt.ylabel('Frequency')
    plt.title('Airline Sentiment Analysis')
    plt.tight_layout()
    
    # Save the plot
    plt.savefig('sentiment_analysis.png')
    
    return 'sentiment_analysis.png'

iface = gr.Interface(
    fn=analyze_sentiment,
    inputs=gr.inputs.Dataframe(type='csv'),
    outputs='image'
)

iface.launch()