import gradio as gr
from transformers import pipeline

# Choose a reliable model (you can change this)
MODEL_NAME = "distilbert-base-uncased-finetuned-sst-2-english"

# Load the model once
sentiment_analyzer = pipeline("sentiment-analysis", model=MODEL_NAME)

# Function to analyze text
def analyze_text(text):
    try:
        result = sentiment_analyzer(text)[0]
        label = result.get("label", "UNKNOWN")
        score = round(result.get("score", 3))
        return f"{label} ({score})"
    except Exception as e:
        return f"Error during inference: {e}"

# Gradio interface
with gr.Blocks(title="CIS1160 LLM Inference Demo") as demo:
    gr.Markdown(
        """
        ### Explore Inference
        Enter any sentence and see how a trained model interprets it.
        Try clearly positive, negative, and neutral examples.
        """
    )

    input_text = gr.Textbox(label="Enter text to analyze", lines=2)
    output_text = gr.Textbox(label="Model Prediction")

    run_button = gr.Button("Run Inference")
    run_button.click(analyze_text, inputs=input_text, outputs=output_text)

if __name__ == "__main__":
    demo.launch()