Update app.py

app.py

@@ -1,24 +1,19 @@
 import os
-import base64
 import gradio as gr
 from openai import OpenAI
 
 # Initialize the Nebius OpenAI client
 client = OpenAI(
     base_url="https://api.studio.nebius.ai/v1/",
-    api_key=os.environ.get("NEBIUS_API_KEY"),  # Replace with actual API key if not using environment variables
+    api_key=os.environ.get("NEBIUS_API_KEY"),  # Replace with your API key if not using environment variables
 )
 
-# Function to encode the image in Base64
-def encode_image_to_base64(image_path):
-    with open(image_path, "rb") as image_file:
-        return base64.b64encode(image_file.read()).decode("utf-8")
-
 # Function to interact with the Nebius OpenAI API
-def analyze_image(image):
+def analyze_image(image_path):
     try:
-        # Convert the image to Base64
-        image_base64 = encode_image_to_base64(image)
+        # Upload the image to a hosting service or convert its path to an accessible URL
+        # For simplicity, assume the user provides a valid image URL here
+        image_url = image_path  # Replace this with a real image URL if needed
 
         # API request
         response = client.chat.completions.create(
@@ -29,8 +24,8 @@ def analyze_image(image):
                     "content": [
                         {"type": "text", "text": "What’s in this image?"},
                         {
-                            "type": "image_base64",
-                            "image_base64": image_base64,
+                            "type": "image_url",
+                            "image_url": {"url": image_url},  # Use the proper field for image_url
                         },
                     ],
                 }
@@ -52,11 +47,14 @@ def analyze_image(image):
 with gr.Blocks() as app:
     gr.Markdown("# Image Analysis with Nebius OpenAI")
     with gr.Row():
-        image_input = gr.Image(type="filepath", label="Upload an Image")
+        image_url_input = gr.Textbox(
+            label="Image URL",
+            placeholder="Enter a valid image URL for analysis",
+        )
         output_text = gr.Textbox(label="AI Response")
     
     analyze_button = gr.Button("Analyze Image")
-    analyze_button.click(analyze_image, inputs=image_input, outputs=output_text)
+    analyze_button.click(analyze_image, inputs=image_url_input, outputs=output_text)
 
 # Launch the Gradio app
 if __name__ == "__main__":