Update handler.py

handler.py

@@ -93,10 +93,10 @@ class EndpointHandler():
         
         
         # hyperparamters
-        negatice_prompt = data.pop("negative_prompt", canvas frame, (high contrast:1.2), (over saturated:1.2), (glossy:1.1), cartoon, 3d, ((disfigured)), ((bad art)), ((b&w)), blurry, ((bad anatomy)), (((bad proportions))), ((extra limbs)), cloned face, (((disfigured))), extra limbs, (bad anatomy), gross proportions, (malformed limbs), ((missing arms)), ((missing legs)), (((extra arms))), (((extra legs))), mutated hands, (fused fingers), (too many fingers), (((long neck))), Photoshop, video game, ugly, tiling, poorly drawn hands, 3d render)
+        negatice_prompt = data.pop("negative_prompt", None)
         num_inference_steps = data.pop("num_inference_steps", 30)
         guidance_scale = data.pop("guidance_scale", 9.0)
-        negative_prompt = data.pop("negative_prompt", canvas frame, (high contrast:1.2), (over saturated:1.2), (glossy:1.1), cartoon, 3d, ((disfigured)), ((bad art)), ((b&w)), blurry, ((bad anatomy)), (((bad proportions))), ((extra limbs)), cloned face, (((disfigured))), extra limbs, (bad anatomy), gross proportions, (malformed limbs), ((missing arms)), ((missing legs)), (((extra arms))), (((extra legs))), mutated hands, (fused fingers), (too many fingers), (((long neck))), Photoshop, video game, ugly, tiling, poorly drawn hands, 3d render)
+        negative_prompt = data.pop("negative_prompt", None)
         height = data.pop("height", None)
         width = data.pop("width", None)
         controlnet_conditioning_scale = data.pop("controlnet_conditioning_scale", 0.6)