import gradio as gr
from transformers import pipeline

# Load a Hugging Face model pipeline (sentiment analysis in this example)
model = pipeline("sentiment-analysis")

# If you don't hafe HF_TOKEN in your enviroment, define it explicitly like this
# hf_token = "your_hf_token"
# model = pipeline("sentiment-analysis", use_auth_token=hf_token)

# Function to perform sentiment analysis
def analyze_sentiment(text):
    results = model(text)
    return f"Label: {results[0]['label']}, Score: {results[0]['score']:.4f}"

# Define the Gradio interface
with gr.Blocks() as demo:
    # Components
    gr.Markdown("# Welcome to the Sentiment Analysis App!")
    gr.Markdown("## Enter your text and we'll analyze the sentiment behind it.")
    with gr.Row():
        with gr.Column():
            input_text = gr.Textbox(lines=2, placeholder="Enter text to analyze...", label="Input Text")
            analyze_button = gr.Button("Analyze", elem_id="analyze-btn")
        with gr.Column():
            output_text = gr.Textbox(label="Analysis Result", interactive=False)

    # Attach function
    analyze_button.click(fn=analyze_sentiment, inputs=input_text, outputs=output_text)

    # Add some CSS to style your interface
    demo.css = """
    #analyze-btn {
        background-color: #4CAF50;
        color: white;
    }
    #analyze-btn:hover {
        background-color: #45a049;
    }
    """

# Launch the app, use share=True to obtain shareable link that works for 72 hours
demo.launch(share=True)