Update app.py

app.py

@@ -1,3 +1,5 @@
+# app.py
+
 import gradio as gr
 from PIL import Image
 import base64
@@ -7,14 +9,15 @@ from io import BytesIO
 
 from utils.planner import extract_scene_plan  # 🧠 Brain Layer
 
-CONTROLNET_MODEL = "lllyasviel/controlnet-sdxl-1.0-canny"
-HF_API = f"https://api-inference.huggingface.co/models/{CONTROLNET_MODEL}"
-API_KEY = os.getenv("HF_API_KEY")
-headers = {"Authorization": f"Bearer {API_KEY}"}
-
+# 🔐 Hugging Face + OpenAI keys (use Secrets)
+HF_API_KEY = os.getenv("HF_API_KEY")
+SDXL_MODEL_ID = "stabilityai/stable-diffusion-xl-base-1.0"
+SDXL_API_URL = f"https://api-inference.huggingface.co/models/{SDXL_MODEL_ID}"
+HEADERS = {"Authorization": f"Bearer {HF_API_KEY}"}
 
+# 🚀 Image generation (no ControlNet)
 def process_image(prompt, image, num_variations):
-    # Step 1: Brain Layer – extract structured JSON
+    # Step 1: Extract planning JSON from Brain Layer
     reasoning_json = extract_scene_plan(prompt)
 
     # Step 2: Encode image once
@@ -23,6 +26,7 @@ def process_image(prompt, image, num_variations):
     img_bytes = buffered.getvalue()
     encoded_image = base64.b64encode(img_bytes).decode("utf-8")
 
+    # Step 3: Generate multiple variations using base SDXL
     outputs = []
 
     for i in range(num_variations):
@@ -36,31 +40,36 @@ def process_image(prompt, image, num_variations):
         }
 
         try:
-            response = requests.post(HF_API, headers=headers, json=payload)
+            response = requests.post(SDXL_API_URL, headers=HEADERS, json=payload)
             if response.status_code == 200:
                 result_image = Image.open(BytesIO(response.content))
                 outputs.append(result_image)
             else:
-                outputs.append(f"Error: {response.status_code} - {response.text}")
+                outputs.append(f"Error {response.status_code}: {response.text}")
         except Exception as e:
             outputs.append(f"Exception: {e}")
 
     return outputs, reasoning_json
 
 
-# Gradio UI
+# 🎨 Gradio UI
 with gr.Blocks() as demo:
-    gr.Markdown("# 🧠 NewCrux AI Demo: Product → Lifestyle Image Generator")
+    gr.Markdown("# 🧠 NewCrux AI Demo: Image-to-Image using Base SDXL + Brain Layer")
 
     with gr.Row():
         with gr.Column():
             prompt_input = gr.Textbox(label="Enter Prompt")
             image_input = gr.Image(type="pil", label="Upload Product Image")
-            variation_slider = gr.Slider(1, 4, step=1, label="Number of Variations", value=1)
+            variation_slider = gr.Slider(1, 4, step=1, value=1, label="Number of Variations")
             generate_btn = gr.Button("Generate")
 
         with gr.Column():
-            output_gallery = gr.Gallery(label="Generated Images", columns=2, rows=2, height="auto")
+            output_gallery = gr.Gallery(
+                label="Generated Image Variations",
+                columns=2,
+                rows=2,
+                height="auto"
+            )
             json_output = gr.JSON(label="Brain Layer Reasoning (Scene Plan)")
 
     generate_btn.click(