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import docx
import PyPDF2
import os
import re
import json
import time
import tempfile
from typing import Dict, Any, List, Optional
from src.quiz_processing import analyze_document
def extract_text_from_pdf(pdf_path):
text = ""
try:
with open(pdf_path, 'rb') as file:
reader = PyPDF2.PdfReader(file)
for page_num in range(len(reader.pages)):
text += reader.pages[page_num].extract_text() + "\n"
return text
except Exception as e:
raise Exception(f"Error extracting text from PDF: {str(e)}")
def extract_text_from_docx(docx_path):
try:
doc = docx.Document(docx_path)
text = "\n".join([paragraph.text for paragraph in doc.paragraphs])
return text
except Exception as e:
raise Exception(f"Error extracting text from DOCX: {str(e)}")
def extract_text_from_txt(txt_path):
try:
with open(txt_path, 'r', encoding='utf-8') as file:
text = file.read()
return text
except Exception as e:
raise Exception(f"Error extracting text from TXT: {str(e)}")
def process_document(document_path, gemini_api_key, language, content_type):
try:
# Create a temporary file
file_extension = os.path.splitext(document_path.name)[-1].lower()
temp_file = tempfile.mktemp(suffix=file_extension)
# Handle different file-like objects
if hasattr(document_path, 'read'):
# If it's a file-like object with read method
with open(temp_file, 'wb') as f:
f.write(document_path.read())
elif hasattr(document_path, 'file'):
# If it's a Django or similar web framework file upload
with open(temp_file, 'wb') as f:
for chunk in document_path.file.chunks():
f.write(chunk)
elif isinstance(document_path, str):
# If it's a file path string
temp_file = document_path
else:
raise Exception("Unsupported document_path type")
# Process based on file type
if file_extension == '.pdf':
text = extract_text_from_pdf(temp_file)
elif file_extension == '.docx':
text = extract_text_from_docx(temp_file)
elif file_extension == '.txt':
text = extract_text_from_txt(temp_file)
else:
raise Exception(f"Unsupported file type: {file_extension}")
text_file_path = tempfile.mktemp(suffix='.txt')
with open(text_file_path, 'w', encoding='utf-8') as f:
f.write(text)
# Assume this function is defined elsewhere
formatted_output, json_path, txt_path = analyze_document(
text, gemini_api_key, language, content_type
)
return f"Document processed successfully", text_file_path, formatted_output, txt_path, json_path
except Exception as e:
error_message = f"Error processing document: {str(e)}"
return error_message, None, error_message, None, None |