Update app.py

app.py

@@ -1,30 +1,15 @@
 import gradio as gr
 from gradio_client import Client, handle_file
 from PIL import Image
-import os
 
 # Connect to the verified IC-Light engine
 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. Resize to verified safe dimensions (512x768 is the model's native ratio)
-    img = Image.open(image_path)
-    img.thumbnail((512, 768)) 
-    temp_path = "safe_input.png"
-    img.save(temp_path)
 
-    # 2. Your Unique Project Feature: Slider-Weighted Prompt
+    # 1. Slider Logic (Your Unique Feature)
     keywords = ["cinematic", "detailed", "texture", "focus"]
     slider_vals = [s1, s2, s3, s4]
     weighted_prompt = prompt
@@ -32,34 +17,44 @@ 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. THE FIX: Sending ALL 13 Required Arguments
-    # Based on the official repo's function signature
+    # 2. Safety Resize
+    # The log shows the default height is 640. We match this to avoid 'tensor size' errors.
+    img = Image.open(image_path)
+    img.thumbnail((512, 640)) 
+    safe_path = "safe_input.png"
+    img.save(safe_path)
+
+    # 3. THE VERIFIED API CALL
+    # Based strictly on the "Client.predict() Usage Info" you provided.
     try:
         result = client.predict(
-            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
+            input_fg=handle_file(safe_path),   # 1. input_fg (Required)
+            prompt=weighted_prompt,            # 2. prompt (Required)
+            image_width=512,                   # 3. image_width
+            image_height=640,                  # 4. image_height (Matches log default)
+            num_samples=1,                     # 5. num_samples
+            seed=12345,                        # 6. seed
+            steps=25,                          # 7. steps
+            a_prompt="best quality",           # 8. a_prompt
+            n_prompt="lowres, bad anatomy",    # 9. n_prompt
+            cfg=2.0,                           # 10. cfg
+            highres_scale=1.5,                 # 11. highres_scale
+            highres_denoise=0.5,               # 12. highres_denoise
+            lowres_denoise=0.9,                # 13. lowres_denoise
+            bg_source=lighting_choice,         # 14. bg_source (Left Light, etc.)
+            api_name="/process_relight"        # The CRITICAL name found in your logs
         )
-        return result[0]
+        
+        # The API returns a tuple: (preprocessed_bg, gallery_list)
+        # We want the final image from the gallery list
+        return result[1][0]['image']
+        
     except Exception as e:
-        # Fallback: Prints the actual error if this precise payload fails
-        raise gr.Error(f"API Mismatch: {str(e)}")
+        raise gr.Error(f"Execution Failed: {str(e)}")
 
 # UI Setup
 with gr.Blocks() as demo:
-    gr.Markdown("# 💡 Full-Parameter Feature Relighter")
+    gr.Markdown("# 💡 Final Accurate Feature Relighter")
     with gr.Row():
         with gr.Column():
             img = gr.Image(type="filepath", label="Input Image")
@@ -76,4 +71,4 @@ with gr.Blocks() as demo:
 
     btn.click(dynamic_relight, [img, txt, dirs, s1, s2, s3, s4], out)
 
-demo.launch()
+demo.launch(show_error=True)