app.py

import gradio as gr
from utils import process_large_text, generate_lesson_from_transcript as generate_lesson_from_transcript_logic
from pdfminer.high_level import extract_text  


def pdf_to_text(pdf_path):
    try:
        return extract_text(pdf_path)
    except Exception as e:
        raise ValueError(f"PDF extraction error: {str(e)}")

def generate_lesson(doc_text=None, pdf_file=None):
    try:
        if pdf_file and doc_text:
            return "Please provide either a text input or a PDF file, not both.", None
        
        if pdf_file:
            doc_text = pdf_to_text(pdf_file.name)
        
        processed_text = process_large_text(doc_text)
        generated_text, output_path = generate_lesson_from_transcript_logic(processed_text)

        return (generated_text, gr.File(output_path)) if output_path else (generated_text, None)

    except Exception as e:
        return f"Error occurred: {str(e)}", None

gr.Interface(
    fn=generate_lesson,
    inputs=[gr.Textbox(label="Input Text"), gr.File(label="Upload PDF")],
    outputs=["text", "file"],
).launch()