Update app.py

app.py

@@ -14,6 +14,7 @@ from gradio_imageslider import ImageSlider
 
 translator = Translator()
 HF_TOKEN = os.environ.get("HF_TOKEN")
+HF_TOKEN_UPSCALER = os.environ.get("HF_TOKEN_UPSCALER")
 MAX_SEED = np.iinfo(np.int32).max
 CSS = "footer { visibility: hidden; }"
 JS = "function () { gradioURL = window.location.href; if (!gradioURL.endsWith('?__theme=dark')) { window.location.replace(gradioURL + '?__theme=dark'); } }"
@@ -47,7 +48,7 @@ async def gen(prompt, basemodel, lora_add, lora_word, width, height, scales, ste
     return [image_path, upscale_image]
 
 def get_upscale_finegrain(prompt, img_path, upscale_factor):
-    client = Client("finegrain/finegrain-image-enhancer")
+    client = Client("finegrain/finegrain-image-enhancer", hf_token=HF_TOKEN_UPSCALER)
     result = client.predict(input_image=handle_file(img_path), prompt=prompt, negative_prompt="", seed=42, upscale_factor=upscale_factor, controlnet_scale=0.6, controlnet_decay=1, condition_scale=6, tile_width=112, tile_height=144, denoise_strength=0.35, num_inference_steps=18, solver="DDIM", api_name="/process")
     return result[1]