Update app.py

app.py

@@ -1,11 +1,9 @@
-# Requirement: !pip install gradio, groq
-
 # 1. Imports and API setup
 import gradio as gr
 from groq import Groq
 import base64
 import os
-import spaces
+import spaces  # Import spaces for ZeroGPU
 
 # Define models used in the process
 llava_model = 'llava-v1.5-7b-4096-preview'
@@ -17,6 +15,7 @@ def encode_image(image_path):
         return base64.b64encode(image_file.read()).decode('utf-8')
 
 # Image to text function
+@spaces.GPU  # Decorate this function to use ZeroGPU
 def image_to_text(client, model, base64_image, prompt):
     try:
         chat_completion = client.chat.completions.create(
@@ -43,6 +42,7 @@ def image_to_text(client, model, base64_image, prompt):
         return f"Error generating text from image: {str(e)}"
 
 # Technical review generation function
+@spaces.GPU  # Decorate this function to use ZeroGPU
 def technical_review_generation(client, image_description):
     keywords = ["econometrics", "finance", "marketing", "stock", "prediction", "chart", "graph", "time series"]
     if not any(keyword in image_description.lower() for keyword in keywords):
@@ -119,7 +119,6 @@ css = """
 """
 
 # Gradio Interface
-
 def gradio_interface():
     # Define the footer HTML
     footer = """
@@ -132,7 +131,7 @@ def gradio_interface():
         Made with 💖 by Pejman Ebrahimi
     </div>
     """
-    @spaces.GPU()
+
     with gr.Blocks(theme="gradio/soft", css=css) as demo:
         gr.HTML("<h1 id='title'>GroqLLaVA Econometrics Agent</h1>")
         gr.HTML("<p id='description'>Upload an economic chart and get a detailed analysis using Groq + LLaVA V1.5 7B multimodal.</p>")