import gradio as gr
from transformers import pipeline
import matplotlib.pyplot as plt
import torch
from pydub import AudioSegment
import numpy as np

# Load sentiment analysis model
sentiment_pipeline = pipeline("sentiment-analysis")

# Function to analyze sentiment
def analyze_sentiment(text):
    result = sentiment_pipeline(text)[0]
    sentiment, confidence = result['label'], result['score']

    # Sentiment Mapping for UI Display
    sentiment_map = {
        "POSITIVE": ("🟢 Positive 😊", "green"),
        "NEGATIVE": ("🔴 Negative 😠", "red"),
        "NEUTRAL": ("🟡 Neutral 😐", "orange")
    }
    
    sentiment_label, color = sentiment_map.get(sentiment.upper(), ("⚪ Unknown ❓", "gray"))

    # Generate Confidence Score Bar Chart
    fig, ax = plt.subplots(figsize=(4, 2))
    ax.bar(sentiment, confidence, color=color)
    ax.set_ylim([0, 1])
    ax.set_ylabel("Confidence Score")
    ax.set_title("Sentiment Confidence")

    return sentiment_label, f"Confidence: {confidence:.2f}", fig

# Function to process audio input
def process_audio(audio_path):
    try:
        audio = AudioSegment.from_file(audio_path)
        audio = audio.set_channels(1).set_frame_rate(16000)
        audio_array = np.array(audio.get_array_of_samples(), dtype=np.float32) / 32768.0
        return analyze_sentiment("Speech-to-text processing not available in this version.")
    except Exception as e:
        return "Error processing audio", str(e), None

# Gradio UI
with gr.Blocks(theme=gr.themes.Soft()) as iface:
    gr.Markdown("# 📢 Text Sentiment Analyzer")
    gr.Markdown("Analyze the sentiment of your text input and visualize the confidence score.")

    with gr.Row():
        text_input = gr.Textbox(lines=2, placeholder="Enter text here...", label="Your Input")
        audio_input = gr.Audio(source="microphone", type="filepath", label="Or Speak")

    analyze_button = gr.Button("Analyze Sentiment ✨")

    with gr.Row():
        sentiment_output = gr.Textbox(label="Sentiment Result", interactive=False)
        confidence_output = gr.Textbox(label="Confidence Score", interactive=False)
    
    chart_output = gr.Plot(label="Confidence Score Chart")

    analyze_button.click(analyze_sentiment, inputs=text_input, outputs=[sentiment_output, confidence_output, chart_output])
    analyze_button.click(process_audio, inputs=audio_input, outputs=[sentiment_output, confidence_output, chart_output])

# Launch the app
if __name__ == "__main__":
    iface.launch()