Update app.py

app.py

@@ -1,26 +1,42 @@
 import gradio as gr
-from PIL import Image, ImageEnhance
+from gradio_client import Client, handle_file
 import requests
+from PIL import Image
 from io import BytesIO
 
-# Core image edit function (simulate behavior — replace with your model!)
-def run_edit(image, prompt, negative_prompt, guidance_scale=7, steps=20):
-    print("Prompt:", prompt)
-    print("Negative Prompt:", negative_prompt)
-    print("Guidance Scale:", guidance_scale)
-    print("Steps:", steps)
+# Load external Hugging Face Space
+hf_client = Client("multimodalart/cosxl")
 
-    # Dummy transformation: increase contrast and add a pink overlay
-    image = image.convert("RGB")
-    enhancer = ImageEnhance.Contrast(image)
-    image = enhancer.enhance(1.3)
+# Function that proxies the input to multimodalart/cosxl Space
+def run_edit(image, prompt, negative_prompt, guidance_scale=7.0, steps=20):
+    print("→ Sending to external model...")
 
-    pink_overlay = Image.new("RGB", image.size, (255, 182, 193))  # Light pink
-    edited = Image.blend(image, pink_overlay, alpha=0.2)
+    # Save uploaded PIL image to a temp file
+    image_path = "/tmp/input_image.png"
+    image.save(image_path)
 
-    return edited
+    # Call the external API using gradio_client
+    result = hf_client.predict(
+        image=handle_file(image_path),
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        guidance_scale=guidance_scale,
+        steps=steps,
+        api_name="/run_edit"
+    )
 
-# Gradio Interface matching Hugging Face API structure
+    # `result` is a dict with a `url` key (or `path`)
+    image_url = result.get("url")
+    if not image_url:
+        raise ValueError("No image returned from remote API.")
+
+    # Download the result image
+    response = requests.get(image_url)
+    edited_image = Image.open(BytesIO(response.content)).convert("RGB")
+
+    return edited_image
+
+# Build the Gradio interface
 interface = gr.Interface(
     fn=run_edit,
     inputs=[
@@ -31,11 +47,11 @@ interface = gr.Interface(
         gr.Slider(label="Steps", value=20, minimum=1, maximum=100)
     ],
     outputs=gr.Image(label="Your result image"),
-    title="Image Editing with Prompt",
-    description="Edit an image using prompts. Adjust the scale and steps as needed.",
+    title="Image Editing with Remote API",
+    description="This Gradio app sends inputs to the multimodalart/cosxl model and shows the real result.",
 )
 
-# Assign API name so Hugging Face Client can call it via `/run_edit`
+# API name for use via gradio_client
 interface.api_name = "/run_edit"
 
 # Launch app (required for HF Spaces)