from transformers import pipeline
import gradio as gr

# Load summarization models
models = {
    "BART Large CNN": pipeline("summarization", model="facebook/bart-large-cnn"),
    "T5 Small": pipeline("summarization", model="t5-small")
}

# Sentiment analysis pipeline
sentiment_analyzer = pipeline("sentiment-analysis")

def summarize_compare(text):
    summaries = {}
    sentiments = {}
    
    for model_name, summarizer in models.items():
        summary = summarizer(text, max_length=100, min_length=30, do_sample=False)[0]['summary_text']
        sentiment = sentiment_analyzer(summary)[0]
        summaries[model_name] = summary
        sentiments[model_name] = f"{sentiment['label']} ({round(sentiment['score'], 2)})"
    
    return summaries["BART Large CNN"], sentiments["BART Large CNN"], summaries["T5 Small"], sentiments["T5 Small"]

demo = gr.Interface(
    fn=summarize_compare,
    inputs=gr.Textbox(lines=10, placeholder="Paste your text here..."),
    outputs=[
        gr.Textbox(label="BART Large CNN Summary"),
        gr.Textbox(label="BART Large CNN Sentiment"),
        gr.Textbox(label="T5 Small Summary"),
        gr.Textbox(label="T5 Small Sentiment")
    ],
    title="Multi-Model Text Summarizer + Sentiment Analyzer",
    description="Compare summaries from multiple models and see the sentiment of each summary."
)

demo.launch()