app.py

import gradio as gr
from PIL import Image
from transformers import pipeline

# Initialize sentiment pipeline from transformers
sentiment_analyzer = pipeline("sentiment-analysis")

def analyze_sentiment(text):
    result = sentiment_analyzer(text)
    return result[0]['label'], result[0]['score']

def process_image(image):
    # Example: Convert to grayscale (just a demo)
    gray_image = image.convert("L")
    return gray_image

with gr.Blocks() as demo:
    gr.Markdown("## Crypto News API with Image and Sentiment Analysis")

    with gr.Tab("Sentiment Analysis"):
        text_input = gr.Textbox(label="Enter Text")
        sentiment_output = gr.Label()
        sentiment_score = gr.Textbox(label="Confidence Score")

        text_input.submit(analyze_sentiment, inputs=text_input, outputs=[sentiment_output, sentiment_score])

    with gr.Tab("Image Processing"):
        image_input = gr.Image(type="pil")
        image_output = gr.Image()

        image_input.change(process_image, inputs=image_input, outputs=image_output)

demo.launch()