Update app.py

app.py

@@ -1,34 +1,24 @@
 import gradio as gr
-import replicate
-import os
+from diffusers import StableDiffusionPipeline
+import torch
+
+# This will use CPU and download ~5GB model files
+pipe = StableDiffusionPipeline.from_pretrained(
+    "CompVis/stable-diffusion-v1-4", 
+    torch_dtype=torch.float32,
+    use_safetensors=True
+)
 
-# Stable Diffusion generation function
 def generate_image(prompt):
-    output = replicate.run(
-        "stability-ai/stable-diffusion-3-5-large:ac732df83cea7fff18b8472768c88ad041fa750ff7682a21affe81863cbe77e4",
-        input={"prompt": prompt}
-    )
-    return output[0]
+    return pipe(prompt).images[0]
 
-# Gradio interface
-with gr.Blocks(fill_height=True) as demo:
-    with gr.Sidebar():
-        gr.Markdown("# Stable Diffusion 3.5")
-        gr.Markdown("Generate images with SD 3.5 via Replicate API")
-        api_key = gr.Textbox(
-            label="Enter Replicate API key",
-            type="password",
-            placeholder="Paste your Replicate API key here (or set as environment variable)"
-        )
-    
-    prompt = gr.Textbox(label="Prompt", placeholder="A cute corgi in a astronaut helmet")
-    generate_btn = gr.Button("Generate")
-    output = gr.Image(label="Generated Image")
+with gr.Blocks() as demo:
+    gr.Markdown("## 🐢 Local CPU Generator (SD 1.4)")
+    with gr.Row():
+        prompt = gr.Textbox(label="Prompt")
+        btn = gr.Button("Generate (May take 2-5 mins)")
+    output = gr.Image(label="Result")
     
-    generate_btn.click(
-        fn=generate_image,
-        inputs=prompt,
-        outputs=output
-    )
+    btn.click(fn=generate_image, inputs=prompt, outputs=output)
 
 demo.launch()