refactor a bit

app.py

@@ -20,10 +20,10 @@ def bot_streaming(message, history):
 
   if message.files:
     if len(message.files) == 1:
-      image = [message.files[0].path]
-    # interleaved images or video
+      img = [message.files[0].path]
+    # interleaved images
     elif len(message.files) > 1:
-      image = [msg.path for msg in message.files]
+      img = [msg.path for msg in message.files]
   else:
       
     def has_file_data(lst):
@@ -38,32 +38,31 @@ def bot_streaming(message, history):
         if all(isinstance(sub_item, str) for sub_item in item):
             latest_text_only_index = i
 
-    image = [path for i, item in enumerate(history) if i < latest_text_only_index and has_file_data(item) for path in extract_paths(item)]
+    img = [path for i, item in enumerate(history) if i < latest_text_only_index and has_file_data(item) for path in extract_paths(item)]
 
   if message.files is None:
-      gr.Error("You need to upload an image or video for LLaVA to work.")
+      gr.Error("You need to upload an image or multiple images at least once for LLaVA to work.")
       
   image_extensions = Image.registered_extensions()
   image_extensions = tuple([ex for ex, f in image_extensions.items()])
-  if len(image) == 1:
-      image = Image.open(image[0]).convert("RGB")
+  if len(img) == 1:
+      image = Image.open(img[0]).convert("RGB")
       prompt = f"{message.text}<image>"
 
-  elif len(image) > 1:
+  elif len(img) > 1:
     image_list = []
     user_prompt = message.text
 
-    for img in image:
-      img = Image.open(img).convert("RGB")
-      image_list.append(img)
+    for im in img:
+      image_list.append(Image.open(im).convert("RGB"))
       
     toks = "<image>" * len(image_list)
     prompt = user_prompt + toks
 
-    image = image_list
+    img = image_list
 
 
-  inputs = processor(prompt, image, return_tensors="pt").to("cuda", torch.float16)
+  inputs = processor(prompt, img, return_tensors="pt").to("cuda", torch.float16)
   streamer = TextIteratorStreamer(processor, {"skip_special_tokens": True})
   generation_kwargs = dict(inputs, streamer=streamer, max_new_tokens=250)
   generated_text = ""
@@ -78,7 +77,7 @@ def bot_streaming(message, history):
     
     buffer += new_text
     
-    generated_text_without_prompt = buffer#[len(ext_buffer):]
+    generated_text_without_prompt = buffer
     time.sleep(0.01)
     yield buffer