Update app.py

app.py

@@ -2,9 +2,8 @@ import spaces
 import torch
 import re
 import gradio as gr
-from PIL import Image
-import io
 from transformers import AutoTokenizer, AutoModelForCausalLM
+from PIL import Image
 
 if torch.cuda.is_available():
     device, dtype = "cuda", torch.float16
@@ -20,11 +19,10 @@ moondream = AutoModelForCausalLM.from_pretrained(
 moondream.eval()
 
 @spaces.GPU(duration=10)
-def answer_questions(images, prompt_text):
+def answer_questions(image_tuples, prompt_text):
     prompts = [p.strip() for p in prompt_text.split(',')]  # Splitting and cleaning prompts
-    # Extracting images from tuples and converting to PIL images
-    image_objects = [Image.open(io.BytesIO(img[0])) for img in images]
-    image_embeds = [moondream.encode_image(img) for img in image_objects]
+    images = [img[0] for img in image_tuples if img[0] is not None]  # Extracting images from tuples, ignoring None
+    image_embeds = [moondream.encode_image(img) for img in images]
     answers = moondream.batch_answer(
         images=image_embeds,
         prompts=prompts,