Update app.py

app.py

@@ -1,30 +1,25 @@
 import gradio as gr
-import torch
-from diffusers import DiffusionPipeline
+from transformers import pipeline
 
-# Load model once
-pipe = DiffusionPipeline.from_pretrained(
-    "stabilityai/stable-diffusion-xl-base-1.0",
-    torch_dtype=torch.float16,
-    variant="fp16",
-    use_safetensors=True
-).to("cuda")
+# Load the model from the hub
+generator = pipeline("text2text-generation", model="DetectiveShadow/inspiration-message-generator")
 
-# Load the LoRA weights
-pipe.load_lora_weights("ZB-Tech/Text-to-Image")
+def generate_message(age, profession, archetype):
+    prompt = f"Age: {age} | Profession: {profession} | Archetype: {archetype}"
+    result = generator(prompt, max_new_tokens=100)[0]["generated_text"]
+    return result
 
-# Define generation function
-def generate_image(prompt):
-    image = pipe(prompt).images[0]
-    return image
-
-# Gradio UI
-demo = gr.Interface(
-    fn=generate_image,
-    inputs=gr.Textbox(label="Enter a prompt", placeholder="e.g. Draw a picture of some coding on a screen with a horror background"),
-    outputs=gr.Image(type="pil", label="Generated Image"),
-    title="🎨 AI Image Generator",
-    description="This demo uses Stable Diffusion XL with custom LoRA weights to generate images from your prompts."
+# Gradio interface
+iface = gr.Interface(
+    fn=generate_message,
+    inputs=[
+        gr.Textbox(label="Age"),
+        gr.Textbox(label="Profession"),
+        gr.Textbox(label="Archetype")
+    ],
+    outputs="text",
+    title="Inspiration Message Generator",
+    description="Enter age, profession, and archetype to get a personalized inspirational message."
 )
 
-demo.launch()
+iface.launch()