import gradio as gr
from transformers import pipeline
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware

# Initialize the model
summarizer = pipeline("summarization", model="facebook/bart-large-cnn")

# Define the summarization function
def summarize_text(text, max_length=100, min_length=30):
    try:
        summary = summarizer(
            text,
            max_length=max_length,
            min_length=min_length,
            do_sample=False
        )
        return summary[0]["summary_text"]
    except Exception as e:
        return f"Error: {str(e)}"

# Create Gradio interface
demo = gr.Interface(
    fn=summarize_text,
    inputs=[
        gr.Textbox(label="Input Text", lines=10),
        gr.Slider(minimum=50, maximum=500, value=100, label="Max Length"),
        gr.Slider(minimum=10, maximum=200, value=30, label="Min Length")
    ],
    outputs=gr.Textbox(label="Summary"),
    title="Text Summarization",
    description="Enter your text to get a summary using BART model"
)

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860, share=True)