Update app.py

app.py

@@ -17,6 +17,7 @@ from diffusers import EulerAncestralDiscreteScheduler
 from typing import Tuple
 import paramiko
 import datetime
+import cyper
 
 torch.backends.cuda.matmul.allow_tf32 = False
 torch.backends.cuda.matmul.allow_bf16_reduced_precision_reduction = False
@@ -183,7 +184,25 @@ def uploadNote(prompt,num_inference_steps,guidance_scale,timestamp):
         f.write(f"Model VAE: sdxl-vae-bf16\n")
         f.write(f"To cuda and bfloat \n")
     upload_to_ftp(filename) 
-    
+
+code = r'''
+def uploadNote(prompt,num_inference_steps,guidance_scale,timestamp):
+    filename= f'rv_C_{timestamp}.txt'
+    with open(filename, "w") as f:
+        f.write(f"Realvis 5.0 (Tester C) \n")
+        f.write(f"Date/time: {timestamp} \n")
+        f.write(f"Prompt: {prompt} \n")
+        f.write(f"Steps: {num_inference_steps} \n")
+        f.write(f"Guidance Scale: {guidance_scale} \n")
+        f.write(f"SPACE SETUP: \n")
+        f.write(f"Model Scheduler: Euler_a all_custom before cuda \n")
+        f.write(f"Model VAE: sdxl-vae-bf16\n")
+        f.write(f"To cuda and bfloat \n")
+    upload_to_ftp(filename) 
+'''
+
+pyx = cyper.inline(code)
+
 @spaces.GPU(duration=30)
 def generate_30(
     prompt: str,
@@ -215,7 +234,8 @@ def generate_30(
         options["use_resolution_binning"] = True
     images = []
     timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
-    uploadNote(prompt,num_inference_steps,guidance_scale,timestamp)
+    pyx.func(prompt,num_inference_steps,guidance_scale,timestamp)
+    #uploadNote(prompt,num_inference_steps,guidance_scale,timestamp)
     batch_options = options.copy()
     rv_image = pipe(**batch_options).images[0]
     sd_image_path = f"rv_C_{timestamp}.png"