[MyClient] -> revert to stable

app.py

@@ -38,155 +38,128 @@ sdlu = Client("huggingface-projects/stable-diffusion-latent-upscaler", HF_TOKEN)
 
 # Set up discord bot 
 class MyClient(discord.Client):
-    desired_messages = {}
-    
     async def on_ready(self):
         print('Logged on as', self.user)
 
 
     async def on_message(self, message):
-        try:
-            #safety checks----------------------------------------------------------------------------------------------------
-    
-            #   tldr, bot should run if
-            #1) it does not have @offline role
-            #2) user has @verified role
-            #3) bot is in #bot-test channel
+
+        #safety checks----------------------------------------------------------------------------------------------------
+
+        #   tldr, bot should run if
+        #1) it does not have @offline role
+        #2) user has @verified role
+        #3) bot is in #bot-test channel
+        
+        # bot won't respond to itself, prevents feedback loop + API spam
+        if message.author == self.user:
+            return       
+
+        # if the bot has this role, it won't run
+        OFFLINE_ROLE_ID = 1103676632667017266  # 1103676632667017266 = @offline / under maintenance
+        guild = message.guild
+        bot_member = guild.get_member(self.user.id)
+        if any(role.id == OFFLINE_ROLE_ID for role in bot_member.roles):
+            return
+        
+        # the message author needs this role in order to use the bot
+        REQUIRED_ROLE_ID = 897376942817419265 # 900063512829755413 = @verified, 897376942817419265 = @huggingfolks
+        if not any(role.id == REQUIRED_ROLE_ID for role in message.author.roles):
+            return            
+
+        # channels where bot will accept commands
+        ALLOWED_CHANNEL_IDS = [1100458786826747945] # 1100458786826747945 = #bot-test
+        if message.channel.id not in ALLOWED_CHANNEL_IDS:
+            return
+
+        # function for reacting
+        async def bot_react(message):
+            emojis = ['1️⃣', '2️⃣', '3️⃣', '4️⃣']
+            for emoji in emojis:
+                await message.add_reaction(emoji)        
+
+        #deepfloydif----------------------------------------------------------------------------------------------------
             
-            # bot won't respond to itself, prevents feedback loop + API spam
-            if message.author == self.user:
-                return       
-    
-            # if the bot has this role, it won't run
-            OFFLINE_ROLE_ID = 1103676632667017266  # 1103676632667017266 = @offline / under maintenance
-            guild = message.guild
-            bot_member = guild.get_member(self.user.id)
-            if any(role.id == OFFLINE_ROLE_ID for role in bot_member.roles):
-                return
+        if message.content.startswith('!deepfloydif'): # change to application commands, more intuitive
+
+            #(prompt, negative_prompt, seed, number_of_images, guidance_scale,custom_timesteps_1, number_of_inference_steps, api_name="/generate64") 
+            #-> (stage_1_results, stage_1_param_path, stage_1_result_path)
+
+            # input prompt
+            prompt = message.content[12:].strip()  
             
-            # the message author needs this role in order to use the bot
-            REQUIRED_ROLE_ID = 897376942817419265 # 900063512829755413 = @verified, 897376942817419265 = @huggingfolks
-            if not any(role.id == REQUIRED_ROLE_ID for role in message.author.roles):
-                return            
-    
-            # channels where bot will accept commands
-            ALLOWED_CHANNEL_IDS = [1100458786826747945] # 1100458786826747945 = #bot-test
-            if message.channel.id not in ALLOWED_CHANNEL_IDS:
-                return
-    
-            # function for reacting
-            async def bot_react(message):
-                emojis = ['1️⃣', '2️⃣', '3️⃣', '4️⃣']
-                for emoji in emojis:
-                    await message.add_reaction(emoji)        
-    
-            #deepfloydif----------------------------------------------------------------------------------------------------      
-                
-            if message.content.startswith('!deepfloydif'): # change to application commands, more intuitive
-    
-                #(prompt, negative_prompt, seed, number_of_images, guidance_scale,custom_timesteps_1, number_of_inference_steps, api_name="/generate64") 
-                #-> (stage_1_results, stage_1_param_path, stage_1_result_path)
-    
-                # input prompt
-                prompt = message.content[12:].strip()  
-                
-                negative_prompt = ''
-                seed = random.randint(0, 2**32 - 1)
-                number_of_images = 4
-                guidance_scale = 7
-                custom_timesteps_1 = 'smart50'
-                number_of_inference_steps = 50
-                
-                stage_1_results, stage_1_param_path, stage_1_result_path = df.predict(
-                    prompt,
-                    negative_prompt,
-                    seed,
-                    number_of_images,
-                    guidance_scale,
-                    custom_timesteps_1,
-                    number_of_inference_steps,
-                    api_name='/generate64')
-    
-                #stage_1_results, stage_1_param_path, stage_1_result_path = df.predict("gradio written on a wall", "blur", 1,1,7.0, 'smart100',50, api_name="/generate64")
-                
-                # stage_1_results -> path to directory with png files, so we isolate those
-                png_files = [f for f in os.listdir(stage_1_results) if f.endswith('.png')]
-    
-                # merge images into larger, 2x2 image the way midjourney does it
-                if png_files:
-                    first_png = png_files[0]
-                    second_png = png_files[1]
-                    third_png = png_files[2]
-                    fourth_png = png_files[3]
-    
-                    '''
-                    [],[],[],[] -> [][]
-                                   [][]
-                    
-                    '''
-                
-                    first_png_path = os.path.join(stage_1_results, first_png)
-                    second_png_path = os.path.join(stage_1_results, second_png)
-                    third_png_path = os.path.join(stage_1_results, third_png)
-                    fourth_png_path = os.path.join(stage_1_results, fourth_png)
-                
-                    img1 = Image.open(first_png_path)
-                    img2 = Image.open(second_png_path)
-                    img3 = Image.open(third_png_path)
-                    img4 = Image.open(fourth_png_path)
-                
-                    # create a new blank image with the size of the combined images (2x2)
-                    combined_image = Image.new('RGB', (img1.width * 2, img1.height * 2))
-                
-                    # paste the individual images into the combined image
-                    combined_image.paste(img1, (0, 0))
-                    combined_image.paste(img2, (img1.width, 0))
-                    combined_image.paste(img3, (0, img1.height))
-                    combined_image.paste(img4, (img1.width, img1.height))
-                
-                    # save the combined image
-                    combined_image_path = os.path.join(stage_1_results, 'combined_image.png')
-                    combined_image.save(combined_image_path)
+            negative_prompt = ''
+            seed = random.randint(0, 2**32 - 1)
+            number_of_images = 4
+            guidance_scale = 7
+            custom_timesteps_1 = 'smart50'
+            number_of_inference_steps = 50
+            
+            stage_1_results, stage_1_param_path, stage_1_result_path = df.predict(
+                prompt,
+                negative_prompt,
+                seed,
+                number_of_images,
+                guidance_scale,
+                custom_timesteps_1,
+                number_of_inference_steps,
+                api_name='/generate64')
+
+            #stage_1_results, stage_1_param_path, stage_1_result_path = df.predict("gradio written on a wall", "blur", 1,1,7.0, 'smart100',50, api_name="/generate64")
+            
+            # stage_1_results -> path to directory with png files, so we isolate those
+            png_files = [f for f in os.listdir(stage_1_results) if f.endswith('.png')]
+
+            # merge images into larger, 2x2 image the way midjourney does it
+            if png_files:
+                first_png = png_files[0]
+                second_png = png_files[1]
+                third_png = png_files[2]
+                fourth_png = png_files[3]
+
+                '''
+                [],[],[],[] -> [][]
+                               [][]
                 
-                # send the combined image file as a discord attachment
-                with open(combined_image_path, 'rb') as f:
-                    sent_message = await message.reply('Here is the combined image', file=discord.File(f, 'combined_image.png'))
-    
-                self.desired_messages[message.author.id] = sent_message.id
-
-                await bot_react(sent_message) 
-    
-        except Exception as e:
-            print(f'An error occurred while processing the message: {e}')
-            await message.reply('An error occurred during stage 1.')        
-        
+                '''
+            
+                first_png_path = os.path.join(stage_1_results, first_png)
+                second_png_path = os.path.join(stage_1_results, second_png)
+                third_png_path = os.path.join(stage_1_results, third_png)
+                fourth_png_path = os.path.join(stage_1_results, fourth_png)
+            
+                img1 = Image.open(first_png_path)
+                img2 = Image.open(second_png_path)
+                img3 = Image.open(third_png_path)
+                img4 = Image.open(fourth_png_path)
+            
+                # create a new blank image with the size of the combined images (2x2)
+                combined_image = Image.new('RGB', (img1.width * 2, img1.height * 2))
+            
+                # paste the individual images into the combined image
+                combined_image.paste(img1, (0, 0))
+                combined_image.paste(img2, (img1.width, 0))
+                combined_image.paste(img3, (0, img1.height))
+                combined_image.paste(img4, (img1.width, img1.height))
+            
+                # save the combined image
+                combined_image_path = os.path.join(stage_1_results, 'combined_image.png')
+                combined_image.save(combined_image_path)
+            
+            # send the combined image file as a discord attachment
+            with open(combined_image_path, 'rb') as f:
+                sent_message = await message.reply('Here is the combined image', file=discord.File(f, 'combined_image.png'))
 
-               
+            await bot_react(sent_message)                
     #-------------------------------------------------------------------------------------------------------------
-    async def on_reaction_add(self, reaction, user):
-        try:  
-            if user != self.user:
-                # Check if the reaction is from one of the desired users and to the correct message
-                for user_id, message_id in self.desired_messages.items():
-                    if user.id == user_id and reaction.message.id == message_id:
-                        # Remove the user ID from the dictionary after processing the reaction
-                        del self.desired_messages[user_id]
-    
-                        # Get the index corresponding to the reacted emoji
-                        emoji_index = get_index_from_emoji(reaction.emoji)
-    
-                        # Use the index for the stage 2 upscaling
-                        result_path = df.predict(stage_1_result_path, emoji_index, seed_2, 
-                                                 guidance_scale_2, custom_timesteps_2, number_of_inference_steps_2, api_name='/upscale256')
-    
-                        with open(result_path, 'rb') as f:
-                            await reaction.message.reply('Here is the upscaled image!', file=discord.File(f, 'result.png'))
-                        break  # Exit the loop once a matching user and message pair is found
-      
-        except Exception as e:
-            print(f'An error occurred while processing the reaction: {e}')
-            await reaction.message.reply('An error occurred during stage 2.')
-          
+
+            
+       
+
+
+    # deepfloydif -> bot_react -> 
+    # await bot_react
+    # on_react -> if we react to a message, then we call dfif2            
 
 DISCORD_TOKEN = os.environ.get("GRADIOTEST_TOKEN", None)
 intents = discord.Intents.default()