Create app.py

app.py

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+import gradio as gr
+from PIL import Image, ImageEnhance
+import requests
+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)
+
+    # Dummy transformation: increase contrast and add a pink overlay
+    image = image.convert("RGB")
+    enhancer = ImageEnhance.Contrast(image)
+    image = enhancer.enhance(1.3)
+
+    pink_overlay = Image.new("RGB", image.size, (255, 182, 193))  # Light pink
+    edited = Image.blend(image, pink_overlay, alpha=0.2)
+
+    return edited
+
+# Gradio Interface matching Hugging Face API structure
+interface = gr.Interface(
+    fn=run_edit,
+    inputs=[
+        gr.Image(label="Image you would like to edit", type="pil"),
+        gr.Textbox(label="Prompt", placeholder="Describe what to change"),
+        gr.Textbox(label="Negative Prompt", placeholder="What to avoid"),
+        gr.Number(label="Guidance Scale", value=7.0),
+        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.",
+)
+
+# Assign API name so Hugging Face Client can call it via `/run_edit`
+interface.api_name = "/run_edit"
+
+# Launch app (required for HF Spaces)
+interface.launch()