Update app.py

app.py

@@ -1,32 +1,20 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
-import os
 
 hf_key = os.getenv("HF_KEY").strip()
 # Initialize the Hugging Face client
 client = InferenceClient(api_key=hf_key)
 
 # Define the chatbot function
-def chat_with_model(text, image=None):
+def chat_with_model(text, image_url=None):
+    # Prepare messages
     messages = [{"role": "user", "content": {"type": "text", "text": text}}]
-    
-    # If an image is uploaded, encode it and send it as part of the payload
-    if image:
-        import base64
-        from PIL import Image
-        from io import BytesIO
-
-        # Convert image to base64
-        buffered = BytesIO()
-        image.save(buffered, format="PNG")
-        img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
-
-        # Add the image content to the messages
+    if image_url:
         messages.append({
             "role": "user",
             "content": {
-                "type": "image_base64",
-                "image_base64": img_str
+                "type": "image_url",
+                "image_url": {"url": image_url}
             }
         })
     
@@ -44,11 +32,10 @@ ui = gr.Interface(
     fn=chat_with_model,
     inputs=[
         gr.Textbox(label="Enter your message"),
-        gr.Image(type="pil", label="Upload an Image (Optional)")
+        gr.Textbox(label="Optional Image URL (Leave empty if not needed)")
     ],
     outputs=gr.Textbox(label="Response from the chatbot"),
-    title="AI Chatbot with Direct Image Upload",
-    theme="TejAndrewsACC/zetaofficalthemeacc"
+    title="AI Chatbot with Image Processing"
 )
 
 # Launch the UI