Update app.py

app.py

@@ -2,10 +2,19 @@
 import requests
 import gradio as gr
 from PIL import Image
-import io
+# from dotenv import load_dotenv
+import os
+token = os.environ['HF_TOKEN']
 
+
+
+# load_dotenv()
+# token = os.environ.get("HF_TOKEN", "")
+# print(token)
 API_URL = "https://api-inference.huggingface.co/models/playgroundai/playground-v2-1024px-aesthetic"
-headers = {"Authorization": "Bearer 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"}
+
+# token = 
+headers = {"Authorization": "Bearer {token}"}
 
 def query(payload):
     response = requests.post(API_URL, headers=headers, json=payload)
@@ -15,50 +24,8 @@ def query(payload):
     image = Image.open(io.BytesIO(image_bytes))
     return image
 
-# user_input = "a man on the mars"
-# image_bytes = query({
-	# "inputs": user_input,
-# })
-
-
-# print(image_bytes)
-
-
-
-# demo = gr.Interface(fn=query, inputs="text", outputs="image")
-
-
-# # You can access the image with PIL.Image for example
-# import io
-# from PIL import Image
-# image = Image.open(io.BytesIO(image_bytes))
-
-
-
-
-
-
-
-
-
-# import numpy as np
-
-
-# def sepia(input_img):
-#     sepia_filter = np.array([
-#         [0.393, 0.769, 0.189], 
-#         [0.349, 0.686, 0.168], 
-#         [0.272, 0.534, 0.131]
-#     ])
-#     sepia_img = input_img.dot(sepia_filter.T)
-#     sepia_img /= sepia_img.max()
-#     return sepia_img
 
-# demo = gr.Interface(image, gr.Image(), "image")
-# demo.launch() 
-# demo = gr.Image(image)
 
-# demo.launch()
 with gr.Blocks() as demo:
     gr.Interface(fn=query, inputs="text", outputs="image")