Update app.py

app.py

@@ -1,30 +1,24 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load the model pipeline
+# Load the model pipeline with trust_remote_code=True
 pipe = pipeline("image-text-to-text", model="deepseek-ai/deepseek-vl2-small", trust_remote_code=True)
 
-def chatbot(user_input):
-    """
-    Function to process user input using the DeepSeek-VL2-Small model.
-    """
-    messages = [{"role": "user", "content": user_input}]
-    response = pipe(messages)
-    
-    if isinstance(response, list) and len(response) > 0:
-        return response[0]["generated_text"]  # Extract response text
-    else:
-        return "No response received."
+# Define the Gradio function
+def generate_response(message):
+    messages = [{"role": "user", "content": message}]
+    result = pipe(messages)
+    return result[0]["generated_text"] if isinstance(result, list) else result
 
-# Create a Gradio interface
-demo = gr.Interface(
-    fn=chatbot,
-    inputs=gr.Textbox(lines=2, placeholder="Ask something..."),
-    outputs="text",
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=generate_response,
+    inputs=gr.Textbox(label="Enter your message"),
+    outputs=gr.Textbox(label="Model Response"),
     title="DeepSeek-VL2 Chatbot",
-    description="Ask questions and get AI-generated responses using DeepSeek-VL2-Small."
+    description="Ask anything and get a response from the DeepSeek-VL2-Small model."
 )
 
-# Launch the Gradio app
+# Launch the app
 if __name__ == "__main__":
-    demo.launch()
+    iface.launch()