app.py

import gradio as gr
from transformers import pipeline

# Load the zero-shot classifier for bias detection using Facebook's BART MNLI.
classifier = pipeline(
    "zero-shot-classification",
    model="facebook/bart-large-mnli"
)

def process_text(text):
    # Define candidate labels for bias classification.
    candidate_labels = ["biased", "neutral"]
    
    # Run zero-shot classification.
    classification = classifier(text, candidate_labels)
    detected_bias = classification["labels"][0]
    confidence = classification["scores"][0]
    
    # Return the results.
    return {
        "Detected Bias": detected_bias,
        "Confidence": round(confidence, 2),
    }

# Build the Gradio UI.
with gr.Blocks() as demo:
    gr.Markdown("# Bias Bin")
    gr.Markdown(
        "Detect gender stereotypes in narrative text. "
        "Enter a story or sentence below and click the **Submit** button."
    )
    
    text_input = gr.Textbox(
        label="Enter Story Text",
        placeholder="Type a story or sentence here...",
        lines=5
    )
    
    submit_btn = gr.Button("Submit")
    result_output = gr.JSON(label="Output")
    
    submit_btn.click(fn=process_text, inputs=[text_input], outputs=[result_output])
    
demo.launch()