Update app.py

app.py

@@ -12,10 +12,11 @@ OWNER_PHONE_NUMBER = os.getenv("OWNER_PHONE_NUMBER")
 
 # --- AI Model Setup ---
 print("Loading AI Image Detection model...")
-image_detector: Pipeline = pipeline("image-classification", model="openai/clip-vit-base-patch32")
+# FIX 1: Use the correct pipeline for this task.
+# 'zero-shot-image-classification' is designed to work with 'candidate_labels'.
+image_detector: Pipeline = pipeline("zero-shot-image-classification", model="openai/clip-vit-base-patch32")
 print("✅ Model loaded successfully.")
 
-
 # --- Tool 1: The Main Analysis Function ---
 def analyze_image_authenticity(image_url: str) -> dict:
     """
@@ -32,7 +33,10 @@ def analyze_image_authenticity(image_url: str) -> dict:
     
     print(f"Analyzing image from URL: {image_url}")
     try:
-        image = Image.open(requests.get(image_url, stream=True, timeout=10).raw)
+        # FIX 2: Add a User-Agent header to mimic a real browser request.
+        # This prevents websites (including Puch's image hosting) from blocking the download.
+        headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36'}
+        image = Image.open(requests.get(image_url, stream=True, timeout=10, headers=headers).raw)
     except Exception as e:
         raise gr.Error(f"Could not load image from URL. Error: {str(e)}")
 
@@ -42,8 +46,7 @@ def analyze_image_authenticity(image_url: str) -> dict:
     print(f"Analysis successful. Results: {results}")
     return {"analysis_results": results}
 
-
-# --- Tool 2: The Validation Function for Sharing (NEW) ---
+# --- Tool 2: The Validation Function for Sharing ---
 def validate() -> str:
     """
     Validates the server ownership for sharing. Returns the owner's phone number.
@@ -53,24 +56,20 @@ def validate() -> str:
     """
     return OWNER_PHONE_NUMBER
 
-
 # --- Gradio Interface ---
-# We now create a list of Interfaces to expose both tools
 demo = gr.TabbedInterface(
     [
         gr.Interface(
             fn=analyze_image_authenticity,
             inputs=[gr.Textbox(label="Image URL")],
             outputs=[gr.JSON(label="Analysis Results")],
-            title="AI Image Authenticity Detector",
-            description="Tool to analyze an image's authenticity."
+            title="AI Image Authenticity Detector"
         ),
         gr.Interface(
             fn=validate,
             inputs=[],
             outputs="text",
-            title="Validation Tool",
-            description="Used by the Puch AI platform to validate shared servers."
+            title="Validation Tool"
         )
     ],
     ["Image Analyzer", "Validator"]