Update app.py

app.py

@@ -13,7 +13,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer, AutoModel
 from diffusers import StableDiffusionPipeline
 from torch.utils.data import Dataset, DataLoader
 import csv
-from pdf2image import convert_from_path  # Replaced fitz with pdf2image
+from pdf2image import convert_from_path
 import requests
 from PIL import Image
 import cv2
@@ -309,6 +309,10 @@ class DiffusionBuilder:
         return self.pipeline(prompt, num_inference_steps=20).images[0]
 
 # Utility Functions
+def generate_filename(sequence, ext="png"):
+    timestamp = time.strftime("%d%m%Y%H%M%S")
+    return f"{sequence}{timestamp}.{ext}"
+
 def get_download_link(file_path, mime_type="text/plain", label="Download"):
     with open(file_path, 'rb') as f:
         data = f.read()
@@ -426,7 +430,7 @@ async def process_pdf_snapshot(pdf_path, mode="thumbnail"):
     start_time = time.time()
     status = st.empty()
     status.text(f"Processing PDF Snapshot ({mode})... (0s)")
-    images = convert_from_path(pdf_path, dpi=200)  # Convert PDF to images
+    images = convert_from_path(pdf_path, dpi=200)
     output_files = []
     if mode == "thumbnail":
         img = images[0].resize((int(images[0].width * 0.5), int(images[0].height * 0.5)), Image.Resampling.LANCZOS)