File size: 6,978 Bytes
5546580
 
f1578a9
5546580
 
 
b6ca34b
5654dca
 
 
 
 
 
 
 
 
 
db9a3a6
b939335
 
 
5546580
 
 
db9a3a6
 
b6ca34b
 
 
5654dca
 
5546580
 
 
 
 
b6ca34b
5546580
ac7dd69
b6ca34b
 
 
 
 
 
88edf1a
ac7dd69
 
 
 
 
 
5546580
 
 
 
88edf1a
3484400
 
 
 
acb1ed0
 
 
 
 
b6ca34b
 
 
5546580
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5654dca
 
 
 
 
 
5546580
 
 
 
b939335
b6ca34b
b939335
5654dca
b939335
 
 
 
 
 
 
 
 
5654dca
 
 
 
 
 
b6ca34b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5654dca
 
 
eae5c52
5654dca
 
 
 
 
 
 
 
 
 
eae5c52
5654dca
 
 
 
3d08d5f
5654dca
 
 
 
 
 
b6ca34b
 
 
 
 
 
 
 
5654dca
5546580
05024ea
5546580
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
import discord
import gradio_client
from gradio_client import Client
import gradio as gr
import os
import threading

#for deepfloydif
import requests
import json
import random
from PIL import Image
import matplotlib.pyplot as plt
import matplotlib.image as mpimg




#todos
#alert

# Get Gradio client
jojogan = gradio_client.Client("akhaliq/JoJoGAN")

#token update
DFIF_TOKEN = os.getenv('DFIF_TOKEN')
#deepfloydif
#df = Client("DeepFloyd/IF") #not reliable at the moment
df = Client("huggingface-projects/IF", hf_token=DFIF_TOKEN)


# Set up discord bot 
class MyClient(discord.Client):
    async def on_ready(self):
        print('Logged on as', self.user)

    #----------------------------------------------------------------------------------------------------
    async def on_message(self, message):

        #tldr, bot should run if
        #1) it does not have @offline role
        #2) user has @verified role
        #3) bot is in #bot-test channel
        

        # if the bot has this role, it won't run
        OFFLINE_ROLE_ID = 1103676632667017266  # 1103676632667017266 = @offline-bot
        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
        
        # don't respond to ourselves
        if message.author == self.user:
            return

        # if the message author doesn't have this role, the bot won't run
        REQUIRED_ROLE_ID = 900063512829755413 # 900063512829755413 = @verified
        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

        #----------------------------------------------------------------------------------------------------
        #jojogan
        
        if message.content.find("!help") != -1:
            await message.reply("Use !jojo !disney !spidey or !sketch. Have fun!", mention_author=True)

        style = None
        if message.content.startswith('!jojo'):
            style = 'JoJo'
        if message.content.startswith('!disney'):
            style = 'Disney'
        if message.content.startswith('!spidey'):
            style = 'Spider-Verse'
        if message.content.startswith('!sketch'):
            style = 'sketch'

        if style:
            if message.attachments:
                attachment = message.attachments[0]

                # jojogan = gradio_client.Client("akhaliq/JoJoGAN")
                # predict(img, model, api_name="/predict") -> output
                # im = jojogan.predict(img, model) -> output
                # im = jojogan.predict(attachment.url, style) -> output
                
                im = jojogan.predict(attachment.url, style)
                await message.reply(f'Here is the {style} version of it', file=discord.File(im))
            else:
                await message.channel.send("No attachments to be found...Can't animify dat! Try sending me an image πŸ˜‰")

        #----------------------------------------------------------------------------------------------------
        #deepfloydif
        '''
        if message.content.startswith('!deepfloydif'):
            text_input = message.content[12:].strip()
            if text_input:
                im = deepfloydif.predict(text_input)
                im_bytes = BytesIO()
                im.save(im_bytes, 'PNG')
                im_bytes.seek(0)
                await message.reply(f'Here is the image generated for the input "{text_input}"', file=discord.File(im_bytes, 'output.png'))
            else:
                await message.channel.send("No text input provided. Please provide some text after the !deepfloydif command.")        
        
        '''
        #deepfloydif
        # start with preset values for now
        if message.content.startswith('!deepfloydif'):

            #predict
            stage_1_results, stage_1_param_path, stage_1_result_path = df.predict("gradio written on a wall", "blur", 1,4,7.0, 'smart100',50, api_name="/generate64")
            
            # Assuming stage_1_results contains the path to the directory
            png_files = [f for f in os.listdir(stage_1_results) if f.endswith('.png')]

            # Assuming png_files contains the list of all PNG files in the directory
            if png_files:
                first_png = png_files[0]
                first_png_path = os.path.join(stage_1_results, first_png)

            # Send the image file as a Discord attachment
            with open(first_png_path, 'rb') as f:
                await message.reply(f'Here is the first generated image', file=discord.File(f, 'first_png.png'))   








            '''
            # stage 1
            prompt = "llama"
            negative_prompt = "blue"
            seed = 7  # maybe random seed each time?    seed = 7       seed = random.randint(0, 2**32 - 1)
            number_of_images = 4
            guidance_scale = 7
            custom_timesteps_1 = 'smart100'
            number_of_inference_steps = 100

            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 2
            selected_index_for_stage_2 = -1
            custom_timesteps_2 = 'smart100' # could reset to smart50 if index was the issue
            seed = 362572064 # again, could randomize this        seed = 362572064      seed = random.randint(0, 2**32 - 1)
            
            # predict(stage_1_result_path, selected_index_for_stage_2, seed, guidance_scale, custom_timesteps_2, number_of_inference_steps, api_name="/upscale256") -> result
            
            img = df.predict(stage_1_result_path, selected_index_for_stage_2, seed, guidance_scale, custom_timesteps_2, number_of_inference_steps, api_name="/upscale256")
    
            # Save the generated image to a file
            img_path = "/tmp/generated_image.png"
            img.save(img_path)
            
            # Send the image file as a Discord attachment
            with open(img_path, 'rb') as f:
                await message.reply(f'Here is the generated image', file=discord.File(f, 'generated_image.png'))                
            
            
            
            
            
            '''
       
            

DISCORD_TOKEN = os.environ.get("GRADIOTEST_TOKEN", None)
intents = discord.Intents.default()
intents.message_content = True
client = MyClient(intents=intents)

def run_bot():
  client.run(DISCORD_TOKEN)

threading.Thread(target=run_bot).start()

def greet(name):
    return "Hello " + name + "!"

demo = gr.Interface(fn=greet, inputs="text", outputs="text")
demo.launch()