Create app.py

app.py

@@ -0,0 +1,51 @@
+import gradio as gr
+from transformers import pipeline
+import os
+import io
+import IPython.display
+from PIL import Image
+import base64
+
+hf_api_key = "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"
+import requests, json
+
+def get_completion(inputs, parameters=None, ENDPOINT_URL="https://api-inference.huggingface.co/models/runwayml/stable-diffusion-v1-5"):
+    headers = {
+      "Authorization": f"Bearer {hf_api_key}",
+      "Content-Type": "application/json"
+    }
+    data = { "inputs": inputs }
+    if parameters is not None:
+        data.update({"parameters": parameters})
+    response = requests.request("POST",
+                                ENDPOINT_URL,
+                                headers=headers,
+                                data=json.dumps(data))
+    return response.content
+
+import gradio as gr
+
+# 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):
+    output = get_completion(prompt)
+    result_image = Image.open(io.BytesIO(output))
+    return result_image
+
+gr.close_all()
+demo = gr.Interface(
+    fn=generate,
+    inputs=[gr.Textbox(label="Your prompt")],
+    outputs=[gr.Image(label="Result")],
+    title="Image Generation with Stable Diffusion",
+    description="Generate any image with Stable Diffusion",
+    allow_flagging="never",
+)
+
+demo.launch(inline = False)