Create app.py

app.py

@@ -0,0 +1,30 @@
+import streamlit as st
+from diffusers import StableDiffusionPipeline
+import torch
+
+# Function to load the model
+@st.cache_resource
+def load_model():
+    model_id = "CompVis/stable-diffusion-v1-4"
+    pipe = StableDiffusionPipeline.from_pretrained(model_id)
+    pipe.to("cpu")  # Ensure the model runs on CPU
+    return pipe
+
+# Load the model
+pipe = load_model()
+
+# Streamlit UI
+st.title("Text-to-Image Generator")
+st.write("Enter a description, and the AI model will generate an image!")
+
+# User input
+text_input = st.text_input("Enter your description:")
+
+# Generate and display image
+if text_input:
+    with st.spinner("Generating image... Please wait ⏳"):
+        try:
+            image = pipe(text_input).images[0]  # Generate image
+            st.image(image, caption="Generated Image", use_column_width=True)
+        except Exception as e:
+            st.error(f"Error generating image: {e}")