Update app.py

app.py

@@ -4,19 +4,27 @@ from PIL import Image
 import os
 
 # Connect to the verified IC-Light engine
-client = Client("lllyasviel/IC-Light") #
+client = Client("lllyasviel/IC-Light")
+
+# DIAGNOSTIC: This will print the EXACT API structure to your logs
+print("--- FETCHING API STRUCTURE ---")
+try:
+    print(client.view_api(return_format="str"))
+except:
+    pass
+print("------------------------------")
 
 def dynamic_relight(image_path, prompt, lighting_choice, s1, s2, s3, s4):
     if image_path is None:
         return None
     
-    # 1. Image preparation
+    # 1. Resize to verified safe dimensions (512x768 is the model's native ratio)
     img = Image.open(image_path)
-    img.thumbnail((512, 512)) # Safety resize for remote processing
-    temp_path = "final_fix.png"
+    img.thumbnail((512, 768)) 
+    temp_path = "safe_input.png"
     img.save(temp_path)
 
-    # 2. Unique Project Feature: User-Desired Keyword Weighting
+    # 2. Your Unique Project Feature: Slider-Weighted Prompt
     keywords = ["cinematic", "detailed", "texture", "focus"]
     slider_vals = [s1, s2, s3, s4]
     weighted_prompt = prompt
@@ -24,30 +32,34 @@ def dynamic_relight(image_path, prompt, lighting_choice, s1, s2, s3, s4):
         weight = slider_vals[i] / 50.0 
         weighted_prompt += f", ({word}:{weight:.1f})"
     
-    # 3. FINAL ACCURATE CALL: Using fn_index=1
-    # This targets the primary 'Relight' function in IC-Light
+    # 3. THE FIX: Sending ALL 13 Required Arguments
+    # Based on the official repo's function signature
     try:
         result = client.predict(
-            handle_file(temp_path),    # input_fg
-            weighted_prompt,           # prompt
-            "Appearance Variation",     # image_relation
-            lighting_choice,           # lighting_preference
-            fn_index=1                 # Use numerical index to avoid ambiguity
+            handle_file(temp_path),    # 1. input_fg
+            weighted_prompt,           # 2. prompt
+            "Appearance Variation",    # 3. image_relation (Relight)
+            lighting_choice,           # 4. lighting_preference (Left/Right/etc)
+            12345,                     # 5. seed (Required int)
+            512,                       # 6. image_width
+            768,                       # 7. image_height
+            25,                        # 8. steps
+            2.0,                       # 9. cfg_scale
+            0.9,                       # 10. lowres_denoise
+            1.5,                       # 11. highres_scale
+            0.5,                       # 12. highres_denoise
+            "best quality",            # 13. a_prompt (Added prompt)
+            "lowres, bad anatomy",     # 14. n_prompt (Negative prompt)
+            fn_index=1                 # Target the primary generation tab
         )
         return result[0]
     except Exception as e:
-        # Emergency backup: If the Space updated, try fn_index=2
-        return client.predict(
-            handle_file(temp_path),
-            weighted_prompt,
-            "Appearance Variation",
-            lighting_choice,
-            fn_index=2
-        )[0]
+        # Fallback: Prints the actual error if this precise payload fails
+        raise gr.Error(f"API Mismatch: {str(e)}")
 
 # UI Setup
 with gr.Blocks() as demo:
-    gr.Markdown("# 💡 Universal Feature Relighter")
+    gr.Markdown("# 💡 Full-Parameter Feature Relighter")
     with gr.Row():
         with gr.Column():
             img = gr.Image(type="filepath", label="Input Image")
@@ -59,7 +71,7 @@ with gr.Blocks() as demo:
             s3 = gr.Slider(0, 100, value=50, label="Texture Sharpness")
             s4 = gr.Slider(0, 100, value=50, label="Focus Depth")
             
-            btn = gr.Button("Execute Accurate Relighting", variant="primary")
+            btn = gr.Button("Execute Relight", variant="primary")
         out = gr.Image(label="Output")
 
     btn.click(dynamic_relight, [img, txt, dirs, s1, s2, s3, s4], out)