Update app.py

app.py

@@ -1,11 +1,18 @@
 import os
 import shutil
 import subprocess
+import torch
+import gradio as gr
 
+# Clone and install dependencies
+print("Cloning the repository...")
 subprocess.run(["git", "clone", "https://huggingface.co/irotem98/edge_vlm"])
+print("Installing dependencies...")
 subprocess.run(["pip", "install", "-r", "edge_vlm/requirements.txt"])
 subprocess.run(["pip", "install", "sentencepiece"])
 
+# Copy all files from edge_vlm to current directory
+print("Copying files...")
 source_dir = "edge_vlm"
 destination_dir = "."
 
@@ -13,44 +20,51 @@ for item in os.listdir(source_dir):
     source_item = os.path.join(source_dir, item)
     destination_item = os.path.join(destination_dir, item)
 
-    # If it's a directory, copy it recursively
     if os.path.isdir(source_item):
         if os.path.exists(destination_item):
-            shutil.rmtree(destination_item)  # Remove if it already exists
+            shutil.rmtree(destination_item)
         shutil.copytree(source_item, destination_item)
     else:
-        # If it's a file, copy it
         shutil.copy(source_item, destination_item)
 
+print("Files copied successfully.")
+
 # Now import the model from the copied files
 from model import MoondreamModel
-import torch
-import gradio as gr
 
 # Load the model and tokenizer
+print("Loading model...")
 model = MoondreamModel.load_model()
+print("Model loaded.")
+print("Loading tokenizer...")
 tokenizer = MoondreamModel.load_tokenizer()
+print("Tokenizer loaded.")
 
 # Define the default question
 default_question = "Describe the image."
 
 # Function to handle image and return generated caption
 def generate_caption_with_default(image):
-    # Preprocess the image
+    print("Preprocessing image...")
     preprocessed_image = MoondreamModel.preprocess_image(image)
+    print("Image preprocessed.")
     
-    # Generate caption
+    print("Generating caption...")
     caption = MoondreamModel.generate_caption(model, preprocessed_image, tokenizer)
+    print("Caption generated.")
     
     return caption
 
+# Create Gradio interface
+print("Setting up Gradio interface...")
 interface = gr.Interface(
     fn=generate_caption_with_default,
-    inputs=gr.Image(type="pil", label="Upload an Image"),  # Updated input
+    inputs=gr.Image(type="pil", label="Upload an Image"),
     outputs="text",
     title="Image Caption Generator",
     description=f"The default question is: '{default_question}'. Upload an image to generate a description."
 )
 
 # Launch the interface
-interface.launch()
+print("Launching interface...")
+interface.launch()