Update app.py

app.py

@@ -1,6 +1,5 @@
 import gradio as gr
 from transformers import BlipProcessor, BlipForConditionalGeneration
-import torch
 from PIL import Image
 
 # Load the BLIP image captioning model and processor
@@ -12,11 +11,8 @@ def describe_image(image: Image.Image):
     try:
         # Preprocess the image and pass it to the model
         inputs = processor(images=image, return_tensors="pt")
-        
-        # Generate caption using the model
         out = model.generate(**inputs)
         description = processor.decode(out[0], skip_special_tokens=True)
-        
         return description
     except Exception as e:
         return f"Error describing the image: {e}"
@@ -24,17 +20,17 @@ def describe_image(image: Image.Image):
 # Define chatbot interaction function
 def chat(user_input, chat_history, image):
     try:
-        # Generate text response (text processing happens via your custom function)
-        response = f"AI Response: {user_input}"  # Placeholder response for now
+        # Generate text response (placeholder for now)
+        response = f"AI Response: {user_input}" 
         
-        # If an image is uploaded, describe it using the image captioning model
+        # If an image is uploaded, describe it
         if image is not None:
             image_description = describe_image(image)
             response += f"\n\n[Image Description]: {image_description}"
         else:
             image_description = "No image uploaded."
 
-        # Update chat history with both user input and AI response
+        # Update chat history with user input and AI response
         chat_history.append(("User", user_input))
         chat_history.append(("AI", response))
         
@@ -46,7 +42,7 @@ def chat(user_input, chat_history, image):
     except Exception as e:
         return f"Error: {e}", chat_history
 
-# Create Gradio interface with updated light boundary design and image upload
+# Create Gradio interface with updated styles
 with gr.Blocks(css="""
     body {
         background-color: #f7f7f7;
@@ -65,12 +61,12 @@ with gr.Blocks(css="""
         padding: 30px;
         border-radius: 15px;
         box-shadow: 0px 10px 30px rgba(0, 0, 0, 0.1);
-        border: 1px solid #dcdcdc;  /* Light border */
+        border: 1px solid #dcdcdc;
     }
     .gradio-container .textbox, .gradio-container .button {
         background-color: #eeeeee;
         color: #333;
-        border: 1px solid #dcdcdc;  /* Light border */
+        border: 1px solid #dcdcdc;
         border-radius: 10px;
         padding: 12px;
         font-size: 16px;
@@ -90,7 +86,7 @@ with gr.Blocks(css="""
     #chatbox {
         height: 350px;
         overflow-y: auto;
-        border: 1px solid #dcdcdc;  /* Light border */
+        border: 1px solid #dcdcdc;
         padding: 20px;
         border-radius: 10px;
         background-color: #f9f9f9;
@@ -98,7 +94,6 @@ with gr.Blocks(css="""
         margin-bottom: 20px;
         font-size: 14px;
         line-height: 1.6;
-        font-family: 'Arial', sans-serif;
     }
     .user-message {
         background-color: #e0f7fa;
@@ -115,11 +110,19 @@ with gr.Blocks(css="""
         max-width: 75%;
         margin-left: auto;
     }
+    #image-upload {
+        margin-top: 10px;
+        border: 1px solid #dcdcdc;
+        border-radius: 10px;
+        padding: 12px;
+        background-color: #ffffff;
+        width: 100%;
+    }
 """) as demo:
     gr.Markdown("## 🤖 **Professional Groq Chatbot with Image Description**")
     gr.Markdown("Type your message below or upload an image to get a description!")
 
-    # Define layout with vertical alignment
+    # Layout with vertical alignment
     with gr.Column():
         user_input = gr.Textbox(
             label="Your Message",
@@ -141,7 +144,7 @@ with gr.Blocks(css="""
         # Image upload component
         image_input = gr.Image(
             label="Upload Image for Description",
-            type="pil",  # PIL (Python Imaging Library) type for image input
+            type="pil",
             interactive=True,
             elem_id="image-upload",
         )