revert to stable (might be hub issues)

app.py

@@ -9,7 +9,7 @@ import time
 import re
 from discord import Embed, Color
 from discord.ext import commands
-# restart #unstick #unstick
+# restart #unstick
 from gradio_client import Client
 from PIL import Image
 #from ratelimiter import RateLimiter
@@ -18,7 +18,6 @@ from datetime import datetime
 from pytz import timezone
 #
 import asyncio
-semaphore = asyncio.Semaphore(1) # for concurrent tasks
 
 zurich_tz = timezone("Europe/Zurich")
 
@@ -36,32 +35,30 @@ intents.message_content = True
 bot = commands.Bot(command_prefix='!', intents=intents)
 
 
-#-------------------------------------------------------------------------------------------------------------------------------------------
+#----------------------------------------------------------------------------------------------------------------------------------------------
+
 @bot.event
 async def on_ready():
     print('Logged on as', bot.user)
     bot.log_channel = bot.get_channel(1100458786826747945) # 1100458786826747945 = bot-test, 1107006391547342910 = lunarbot server
 
-#------------------------------------------------------------------------------------------------------------------------------------------- 
+#---------------------------------------------------------------------------------------------------------------------------------------------- 
 # Stage 1
 @bot.command()
 async def deepfloydif(ctx, *, prompt: str):
     try:
-        await ctx.message.add_reaction('👍')
-        
         prompt = prompt.strip()[:100]  # Limit the prompt length to 100 characters
         prompt = re.sub(r'[^\w\s]', '', prompt)  # Remove special characters
 
         def check_reaction(reaction, user):
             return user == ctx.author and str(reaction.emoji) in ['1️⃣', '2️⃣', '3️⃣', '4️⃣']   
             
+        
         number_of_images = 4
         current_time = int(time.time())
         random.seed(current_time)
         seed = random.randint(0, 2**32 - 1)
-        stage_1_results, stage_1_param_path, stage_1_result_path = df.predict
-        (prompt, "blur", seed, number_of_images, 7.0, 'smart100', 50, api_name="/generate64")
-        
+        stage_1_results, stage_1_param_path, stage_1_result_path = df.predict(prompt, "blur", seed, number_of_images, 7.0, 'smart100', 50, api_name="/generate64")
         png_files = [f for f in os.listdir(stage_1_results) if f.endswith('.png')]
 
         if png_files:
@@ -145,10 +142,8 @@ async def dfif2(ctx, index: int, stage_1_result_path):
         print(f"Error: {e}")
         await ctx.reply('An error occurred while processing stage 2 upscaling. Please try again later.')
 #----------------------------------------------------------------------------------------------------------------------------
-async def process_dfif2(ctx, index, stage_1_result_path):
-    async with semaphore:
-        await dfif2(ctx, index, stage_1_result_path)
-#----------------------------------------------------------------------------------------------------------------------------
+
+