Delete app.py

app.py

@@ -1,49 +0,0 @@
-import streamlit as st
-import torch
-import time
-from diffusers import StableDiffusionPipeline, EulerDiscreteScheduler
-
-# Set Streamlit page title and description
-st.set_page_config(page_title="AI Image Generator", page_icon="🎨")
-st.title("🎨 AI Image Generator with SDXL Turbo (CPU)")
-
-st.write("Enter a prompt below to generate an AI image using **Stable Diffusion XL Turbo** (optimized for CPU).")
-
-# Load Stable Diffusion XL Turbo model (optimized for CPU)
-@st.cache_resource
-def load_model():
-    try:
-        model_id = "stabilityai/sdxl-turbo"
-        pipe = StableDiffusionPipeline.from_pretrained(
-            model_id, 
-            torch_dtype=torch.float32  # Use float32 for CPU
-        )
-
-        pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config)
-        pipe.to("cpu")  # Force CPU usage
-        
-        return pipe
-    except Exception as e:
-        st.error(f"Error loading model: {str(e)}")
-        return None  # Return None if the model fails to load
-
-pipe = load_model()
-
-# User Input for Text Prompt
-prompt = st.text_input("Enter your text prompt:", "A futuristic city at sunset")
-num_steps = st.slider("Inference Steps:", min_value=1, max_value=10, value=4, step=1)
-guidance_scale = st.slider("Guidance Scale:", min_value=1.0, max_value=10.0, value=5.0, step=0.5)
-
-# Generate Image Button
-if st.button("Generate Image"):
-    if pipe is None:
-        st.error("Model failed to load. Please refresh and try again.")
-    else:
-        with st.spinner("Generating... Please wait (CPU processing takes time)"):
-            start_time = time.time()
-            try:
-                image = pipe(prompt, num_inference_steps=num_steps, guidance_scale=guidance_scale).images[0]
-                st.image(image, caption="Generated Image", use_column_width=True)
-                st.success(f"✅ Image generated in {time.time() - start_time:.2f} seconds!")
-            except Exception as e:
-                st.error(f"An error occurred during generation: {str(e)}")