app.py

import gradio as gr
from transformers import pipeline

# Load the models
model1 = pipeline("sentiment-analysis", model="mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis")
model2 = pipeline("sentiment-analysis", model="mr8488/distilroberta-finetuned-financial-news-sentiment-analysis")

# Define the function to generate responses
def analyze_sentiment(input_text):
    result1 = model1(input_text)[0]
    result2 = model2(input_text)[0]
    return {"Model 1": f"{result1['label']} ({result1['score']:.2f})",
            "Model 2": f"{result2['label']} ({result2['score']:.2f})"}

# Create the Gradio interface
iface = gr.Interface(
    fn=analyze_sentiment,
    inputs=gr.inputs.Textbox(lines=5, label="Input Text"),
    outputs=[gr.outputs.Textbox(label="mrm"), gr.outputs.Textbox(label="mr")],
    title="Financial News Sentiment Analysis Models Comparison",
    description="Compare sentiment analysis results of two models."
)

# Launch the interface
iface.launch()