Create app.py

app.py

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+import streamlit as st
+from diffusers import DiffusionPipeline
+from PIL import Image
+import torch
+
+# Load the diffusion pipeline model
+@st.cache_resource
+def load_pipeline():
+    pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
+    pipe.load_lora_weights("Melonie/text_to_image_finetuned")
+    return pipe
+
+pipe = load_pipeline()
+
+# Streamlit app
+st.title("Text-to-Image Generation App")
+
+# User input for prompt
+user_prompt = st.text_input("Enter your image prompt", value="Astronaut in a jungle, cold color palette, muted colors, detailed, 8k")
+
+# Button to generate the image
+if st.button("Generate Image"):
+    if user_prompt:
+        with st.spinner("Generating image..."):
+            # Generate the image
+            image = pipe(user_prompt).images[0]
+            
+            # Display the generated image
+            st.image(image, caption="Generated Image", use_column_width=True)
+    else:
+        st.error("Please enter a valid prompt.")