src/mainFunctions.py

import os
import gradio as gr
import tempfile
from src.video_processing import process_video_file
from src.documentProcessing import process_pdf_file, process_docx_file
from src.audioProcessing import process_audio_file
from src.quiz_processing import analyze_document

def combined_process_video_file(video_file, output_format, elevenlabs_api_key, model_id, 
                              gemini_api_key, claude_api_key, course_name, section_name, 
                              lesson_name, language):
    result = process_video_file(
        video_file, output_format, elevenlabs_api_key, model_id
    )
    
    audio_path = result[0]
    audio_msg = result[1]
    transcript_file = result[2]
    transcript_msg = result[3]
    transcript_text = result[4]
    
    if not transcript_text:
        return audio_path, audio_msg, transcript_file, transcript_msg, "No transcript text to analyze", None, None
    
    enriched_transcript = f"""
    COURSE: {course_name}
    SECTION: {section_name}
    LESSON: {lesson_name}
    
    TRANSCRIPT:
    {transcript_text}
    """
    
    formatted_quiz, quiz_file, json_file = analyze_document(
        enriched_transcript, 
        gemini_api_key,
        claude_api_key,
        course_name, 
        section_name, 
        lesson_name,
        language
    )
    
    return audio_path, audio_msg, transcript_file, transcript_msg, formatted_quiz, quiz_file, json_file

def process_pdf_document(pdf_file, gemini_api_key, claude_api_key, course_name, 
                       section_name, lesson_name, language):
    if not pdf_file:
        return "No file uploaded", None, None, None
    
    text_file, text_content = process_pdf_file(pdf_file)
    
    if not text_content or text_file is None:
        return f"Error: {text_content}", None, None, None
    
    extraction_msg = f"Text extracted from PDF successfully. Length: {len(text_content)} characters."
    
    enriched_content = f"""
    COURSE: {course_name}
    SECTION: {section_name}
    LESSON: {lesson_name}
    
    CONTENT:
    {text_content}
    """
    
    formatted_quiz, quiz_file, json_file = analyze_document(
        enriched_content, 
        gemini_api_key,
        claude_api_key,
        course_name, 
        section_name, 
        lesson_name,
        language
    )
    
    return extraction_msg, text_file, formatted_quiz, quiz_file, json_file

def process_docx_document(docx_file, gemini_api_key, claude_api_key, course_name, 
                        section_name, lesson_name, language):
    if not docx_file:
        return "No file uploaded", None, None, None
    
    text_file, text_content = process_docx_file(docx_file)
    
    if not text_content or text_file is None:
        return f"Error: {text_content}", None, None, None
    
    extraction_msg = f"Text extracted from Word document successfully. Length: {len(text_content)} characters."
    
    enriched_content = f"""
    COURSE: {course_name}
    SECTION: {section_name}
    LESSON: {lesson_name}
    
    CONTENT:
    {text_content}
    """
    
    formatted_quiz, quiz_file, json_file = analyze_document(
        enriched_content, 
        gemini_api_key,
        claude_api_key,
        course_name, 
        section_name, 
        lesson_name,
        language
    )
    
    return extraction_msg, text_file, formatted_quiz, quiz_file, json_file

def process_audio_document(audio_file, elevenlabs_api_key, model_id, gemini_api_key, 
                         claude_api_key, course_name, section_name, lesson_name, language):
    if not audio_file:
        return "No file uploaded", None, None, None, None
    
    transcript_file, transcript_msg, transcript_text = process_audio_file(
        audio_file, elevenlabs_api_key, model_id
    )
    
    if not transcript_text or transcript_file is None:
        return transcript_msg, None, None, None, None
    
    enriched_content = f"""
    COURSE: {course_name}
    SECTION: {section_name}
    LESSON: {lesson_name}
    
    TRANSCRIPT:
    {transcript_text}
    """
    
    formatted_quiz, quiz_file, json_file = analyze_document(
        enriched_content, 
        gemini_api_key,
        claude_api_key,
        course_name, 
        section_name, 
        lesson_name,
        language
    )
    
    return transcript_msg, transcript_file, formatted_quiz, quiz_file, json_file