img

.vscode/settings.json

@@ -0,0 +1,3 @@
+{
+    "python-envs.pythonProjects": []
+}

app.py

@@ -256,8 +256,13 @@ class PicletGeneratorService:
     FLUX_SPACE = "black-forest-labs/FLUX.1-schnell"
 
     @staticmethod
-    async def generate_enhanced_caption(image_path: str, hf_token: str) -> str:
-        """Generate detailed image description using JoyCaption"""
+    async def generate_enhanced_caption(image_data, hf_token: str) -> str:
+        """Generate detailed image description using JoyCaption
+
+        Args:
+            image_data: PIL Image or file path
+            hf_token: User's HuggingFace token
+        """
         try:
             print(f"Connecting to JoyCaption space with user token...")
             client = Client(
@@ -267,7 +272,7 @@ class PicletGeneratorService:
 
             print(f"Generating caption for image...")
             result = await client.predict(
-                image=image_path,
+                image=image_data,
                 caption_type="Descriptive",
                 caption_length="medium-length",
                 extra_options=[],
@@ -808,12 +813,15 @@ async def generate_piclet(image, hf_token: str) -> dict:
         # Get user profile (creates if doesn't exist)
         user_profile = PicletDiscoveryService.get_or_create_user_profile(user_info)
 
-        # Extract image path from Gradio file input
+        # Extract image from Gradio input and read it immediately to avoid cleanup issues
+        # Gradio cleans up temp files, so we read the image data right away
+        from PIL import Image as PILImage
         image_path = image if isinstance(image, str) else image.name if hasattr(image, 'name') else str(image)
+        image_data = PILImage.open(image_path)
 
         # Step 1: Generate caption
         print("Step 1/5: Generating image caption...")
-        caption = await PicletGeneratorService.generate_enhanced_caption(image_path, hf_token)
+        caption = await PicletGeneratorService.generate_enhanced_caption(image_data, hf_token)
 
         # Step 2: Generate concept
         print("Step 2/5: Generating Piclet concept...")