app.py

import gradio as gr
from transformers import pipeline

# Initialize the sentiment analysis pipeline
sentiment_pipeline = pipeline(
    "text-classification",
    model="hasanmustafa0503/SentimentModel",
    tokenizer="hasanmustafa0503/SentimentModel"
)

# Function to classify sentiment of text
def classify_sentiment(text):
    result = sentiment_pipeline(text)
    return result[0]['label'], result[0]['score']

# Define Gradio interface
iface = gr.Interface(
    fn=classify_sentiment,  # Function to call
    inputs=gr.Textbox(lines=2, placeholder="Enter text here..."),  # Text input box
    outputs=[gr.Label(), gr.Number()],  # Label for sentiment and score
    title="Sentiment Analysis",  # Title for the app
    description="Enter some text, and this tool will predict the sentiment as POSITIVE or NEGATIVE along with the confidence score.",  # Description
)

# Launch the app
iface.launch()