app.py

import gradio as gr
from transformers import pipeline

# Load the text classification model
classifier = pipeline('text-classification', model='ardavey/bert-large-depression-classification-model')

# Define a function for text classification
def classify_text(text):
    predictions = classifier([text])
    label = 'Depressed' if predictions[0]['label'] == 'LABEL_1' else 'Not Depressed'
    score = predictions[0]['score']
    return f"Prediction: {label}, Score: {score:.4f}"

# Create a Gradio interface
interface = gr.Interface(
    fn=classify_text,
    inputs=gr.Textbox(lines=5, placeholder="Enter your text here..."),
    outputs="text",
    title="Depression Text Classifier",
    description="Enter a text sample to check for signs of depression."
)

# Launch the Gradio app
interface.launch()