Update app.py

app.py

@@ -1,14 +1,36 @@
 import gradio as gr
+from transformers import pipeline
 
-def simple_greet(name):
-    return f"Hello, {name}! The API is working."
+# --- Model Loading ---
+MODEL_ID = "MadhavRupala/SD15-ControlNet" 
+print(f"Loading model '{MODEL_ID}' on CPU...")
+try:
+    pipe = pipeline("text2text-generation", model=MODEL_ID, device=-1)
+    print("✅ Model loaded successfully!")
+except Exception as e:
+    print(f"❌ Error loading model: {e}")
+    pipe = None
 
-# Using gr.Interface is the most reliable way to create a functional API endpoint.
+# --- Inference Function ---
+# The parameter name 'prompt' is important for the client.
+def run_inference(prompt: str):
+    if pipe is None:
+        return "Error: The model could not be loaded."
+    if not prompt:
+        return "Please enter a prompt."
+    try:
+        result = pipe(prompt, max_length=100)
+        return result[0]['generated_text']
+    except Exception as e:
+        return f"An error occurred during inference: {e}"
+
+# --- Gradio Interface ---
 iface = gr.Interface(
-    fn=simple_greet,
-    title="API Test",
-    inputs=gr.Textbox(label="Your Name"),
-    outputs=gr.Textbox(label="Greeting"),
+    fn=run_inference,
+    title=f"🤖 Self-Hosted Model API: `{MODEL_ID}`",
+    description="This Space hosts a model for unlimited access.",
+    inputs=gr.Textbox(label="Your Prompt", lines=4),
+    outputs=gr.Textbox(label="Model Response", lines=4),
     allow_flagging="never"
 )