Update app.py

app.py

@@ -0,0 +1,51 @@
+import streamlit as st
+from diffusers import StableDiffusionPipeline
+import torch
+
+# Load the model
+@st.cache_resource
+def load_pipeline():
+    model_name = "runwayml/stable-diffusion-v1-5"  # Replace with the desired Stable Diffusion model
+    pipeline = StableDiffusionPipeline.from_pretrained(
+        model_name,
+        torch_dtype=torch.float16,
+        use_auth_token=True  # Use Hugging Face token if required for the model
+    )
+    pipeline = pipeline.to("cuda" if torch.cuda.is_available() else "cpu")
+    return pipeline
+
+pipeline = load_pipeline()
+
+# App title
+st.title("🎨 Open Source Text-to-Image Generator")
+st.write("Generate images from text prompts using Stable Diffusion.")
+
+# Input prompt
+prompt = st.text_input("Enter your prompt:", placeholder="A futuristic cityscape at sunset")
+
+# Image generation button
+if st.button("Generate Image"):
+    if prompt:
+        with st.spinner("Generating image..."):
+            try:
+                # Generate image
+                result = pipeline(prompt, num_inference_steps=50, guidance_scale=7.5)
+                image = result.images[0]
+
+                # Display the image
+                st.image(image, caption="Generated Image", use_column_width=True)
+            except Exception as e:
+                st.error(f"An error occurred: {e}")
+    else:
+        st.warning("Please enter a prompt to generate an image.")
+
+# Sidebar configuration
+st.sidebar.title("Settings")
+st.sidebar.write("Customize your generation:")
+guidance_scale = st.sidebar.slider("Guidance Scale", 5.0, 15.0, 7.5)
+num_inference_steps = st.sidebar.slider("Inference Steps", 10, 100, 50)
+
+# Clear cache button
+if st.sidebar.button("Clear Cache"):
+    st.cache_resource.clear()
+    st.success("Cache cleared!")