Create app.py

app.py

@@ -0,0 +1,67 @@
+import os
+import io
+import IPython.display
+from PIL import Image
+import base64
+from diffusers import DiffusionPipeline
+
+hf_api_key = "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"
+
+from diffusers import DiffusionPipeline
+
+pipeline = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
+
+def get_completion(prompt):
+    return pipeline(prompt).images[0]
+
+import gradio as gr
+
+#A helper function to convert the PIL image to base64
+#so you can send it to the API
+
+#A helper function to convert the PIL image to base64 
+# so you can send it to the API
+def base64_to_pil(img_base64):
+    base64_decoded = base64.b64decode(img_base64)
+    byte_stream = io.BytesIO(base64_decoded)
+    pil_image = Image.open(byte_stream)
+    return pil_image
+
+def generate(prompt, negative_prompt, steps, guidance, width, height):
+    params = {
+        "negative_prompt": negative_prompt,
+        "num_inference_steps": steps,
+        "guidance_scale": guidance,
+        "width": width,
+        "height": height
+    }
+    
+    output = get_completion(prompt, params)
+    pil_image = base64_to_pil(output)
+    return pil_image
+
+gr.close_all()
+with gr.Blocks() as demo:
+    gr.Markdown("# Image Generation with Stable Diffusion")
+    with gr.Row():
+        with gr.Column(scale=4):
+            prompt = gr.Textbox(label="Your prompt") #Give prompt some real estate
+        with gr.Column(scale=1, min_width=50):
+            btn = gr.Button("Submit") #Submit button side by side!
+    with gr.Accordion("Advanced options", open=False): #Let's hide the advanced options!
+            negative_prompt = gr.Textbox(label="Negative prompt")
+            with gr.Row():
+                with gr.Column():
+                    steps = gr.Slider(label="Inference Steps", minimum=1, maximum=100, value=25,
+                      info="In many steps will the denoiser denoise the image?")
+                    guidance = gr.Slider(label="Guidance Scale", minimum=1, maximum=20, value=7,
+                      info="Controls how much the text prompt influences the result")
+                with gr.Column():
+                    width = gr.Slider(label="Width", minimum=64, maximum=512, step=64, value=512)
+                    height = gr.Slider(label="Height", minimum=64, maximum=512, step=64, value=512)
+    output = gr.Image(label="Result") #Move the output up too
+            
+    btn.click(fn=generate, inputs=[prompt,negative_prompt,steps,guidance,width,height], outputs=[output])
+
+gr.close_all()
+demo.launch()