Update app.py

app.py

@@ -17,16 +17,6 @@ url: str = os.getenv('SUPABASE_URL')
 key: str = os.getenv('SUPABASE_KEY')
 supabase: Client = create_client(url, key)
 
-# Initialize GSheet Connexion
-#Authorization
-gc = pygsheets.authorize(service_account_env_var='GSHEET_AUTH')
-
-#Open the google spreadsheet
-sh = gc.open('AndroFLUX-Logs')
-
-#Select the first sheet 
-wks = sh[0]
-
 # Initialize the base model and specific LoRA
 base_model = "black-forest-labs/FLUX.1-dev"
 pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
@@ -46,9 +36,6 @@ def run_lora(prompt, cfg_scale, steps, randomize_seed, seed, width, height, lora
         seed = random.randint(0, MAX_SEED)
     generator = torch.Generator(device="cuda").manual_seed(seed)
 
-    # Log prompt
-    print('PROMPT: ' + prompt + 'SEED:' + str(seed) + 'CFG: '+ str(cfg_scale))
-
     #Moderation 
 
     moderation_client = client_gradio("duchaba/Friendly_Text_Moderation")
@@ -60,16 +47,14 @@ def run_lora(prompt, cfg_scale, steps, randomize_seed, seed, width, height, lora
 
     if float(json.loads(result[1])['sexual_minors']) > 0.03 : 
         print('Minors')
+        response_data = (supabase.table("requests")
+        .insert({"prompt":prompt, "cfg_scale":cfg_scale, "steps":steps, "randomized_seed": randomize_seed, "seed":seed, "lora_scale" : lora_scale, "moderated" : 'true'})
+        .execute()
         raise gr.Error("Unauthorized request 💥!")
 
     # Update progress bar (0% saat mulai)
     progress(0, "Starting image generation...")
 
-    # Generate image with progress updates
-    for i in range(1, steps + 1):
-        # Simulate the processing step (in a real scenario, you would integrate this with your image generation process)
-        if i % (steps // 10) == 0:  # Update every 10% of the steps
-            progress(i / steps * 100, f"Processing step {i} of {steps}...")
 
     # Generate image using the pipeline
     image = pipe(
@@ -96,32 +81,24 @@ def run_lora(prompt, cfg_scale, steps, randomize_seed, seed, width, height, lora
     #Save the tmp image
     image.save(image_path, pnginfo=metadata)
 
-    #Save image in supabase
-    response = supabase.storage.from_('generated_images').upload(image_filename, image_path,file_options={"content-type":"image/png;charset=UTF-8"})
-    print(response.dict)
-    #Log request in supabase
-    response_data = (supabase.table("requests")
-    .insert({"prompt":prompt, "cfg_scale":cfg_scale, "steps":steps, "randomized_seed": randomize_seed, "seed":seed, "lora_scale" : lora_scale, "image_url" : response.full_path})
-    .execute()
-)
-
+    
 
-    # Construct the URL to access the image
-    space_url = "https://killwithabass-flux-1-dev-lora-androflux.hf.space"  # Replace with your actual space URL
-    image_url = f"{space_url}/gradio_api/file={image_path}"
 
     #Log queries
     try:
         if "girl" not in prompt and "woman" not in prompt:
-            wks.append_table(values=[prompt, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale,image_url])
+            #Save image in supabase
+            response = supabase.storage.from_('generated_images').upload(image_filename, image_path,file_options={"content-type":"image/png;charset=UTF-8"})
+            print(response.dict)
+            #Log request in supabase
+            response_data = (supabase.table("requests")
+            .insert({"prompt":prompt, "cfg_scale":cfg_scale, "steps":steps, "randomized_seed": randomize_seed, "seed":seed, "lora_scale" : lora_scale, "image_url" : response.full_path})
+            .execute()
+            )
 
     except Exception as error:
         # handle the exception
         print("An exception occurred:", error)
-        print(f"Image URL: {image_url}") # Log the file URL
-
-    # Final update (100%)
-    progress(100, "Completed!")
 
     yield image, seed