app.py

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


def pdf_to_text(pdf_path):
    return extract_text(pdf_path)

def generate_lesson(doc_text=None, pdf_file=None):
    try:
        if pdf_file:
            doc_text = pdf_to_text(pdf_file.name)
        
        # Process large text
        processed_text = process_large_text(doc_text)

        # Generate lesson
        generated_text, output_path = generate_lesson_from_transcript_logic(processed_text)

        if output_path:
            return generated_text, gr.File(output_path)
        else:
            return 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()