huggingbots / app.py
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lunarflu HF Staff
reaction emojis update (feeling good about this direction)
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import discord
import os
import threading
import gradio as gr
import requests
import json
import random
import time
import re
from discord import Embed, Color
from discord.ext import commands
# restart #unstick
from gradio_client import Client
from PIL import Image
#from ratelimiter import RateLimiter
#
from datetime import datetime
from pytz import timezone
#
import asyncio
zurich_tz = timezone("Europe/Zurich")
def convert_to_timezone(dt, tz):
return dt.astimezone(tz).strftime("%Y-%m-%d %H:%M:%S %Z")
DFIF_TOKEN = os.getenv('HF_TOKEN')
df = Client("huggingface-projects/IF", DFIF_TOKEN)
sdlu = Client("huggingface-projects/stable-diffusion-latent-upscaler", DFIF_TOKEN)
DISCORD_TOKEN = os.environ.get("GRADIOTEST_TOKEN", None)
intents = discord.Intents.default()
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
@bot.command()
async def deepfloydif(ctx, *, prompt: str):
try:
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 str(reaction.emoji) == '👍' and user == ctx.author
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")
png_files = [f for f in os.listdir(stage_1_results) if f.endswith('.png')]
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)
combined_image = Image.new('RGB', (img1.width * 2, img1.height * 2))
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))
combined_image_path = os.path.join(stage_1_results, 'combined_image.png')
combined_image.save(combined_image_path)
# Trigger the second stage prediction
#await dfif2(ctx, stage_1_result_path)
await ctx.reply('Here is the combined image. React with the image you want to upscale!')
with open(combined_image_path, 'rb') as f:
await ctx.send(file=discord.File(f, 'combined_image.png'))
# bot reacts with appropriate emojis to the post, both showing the user what options they have,
# as well as showing which post to react to.
for emoji in ['1️⃣', '2️⃣', '3️⃣', '4️⃣']:
await sent_message.add_reaction(emoji)
reaction, user = await bot.wait_for('reaction_add', check=check_reaction)
await ctx.send(f"{user.mention} reacted with a thumbs-up!")
reaction, user = await bot.wait_for('reaction_add', check=check_reaction)
if str(reaction.emoji) == '1️⃣':
await ctx.send("You want the first image!")
elif str(reaction.emoji) == '2️⃣':
await ctx.send("You want the second image!")
elif str(reaction.emoji) == '3️⃣':
await ctx.send("You want the third image!")
elif str(reaction.emoji) == '4️⃣':
await ctx.send("You want the fourth image!")
except Exception as e:
print(f"Error: {e}")
await ctx.reply('An error occurred while processing your request. Please wait 5 seconds before retrying.')
#new stage 2----------------------------------------------------------------------------------------------------------------------------------------------
# Stage 2
@bot.command()
async def dfif2(ctx, index: int, stage_1_result_path, image_paths):
try:
image_path = image_paths[index]
selected_index_for_stage_2 = image_path
seed_2 = 0
guidance_scale_2 = 4
custom_timesteps_2 = 'smart50'
number_of_inference_steps_2 = 50
result_path = df.predict(stage_1_result_path, selected_index_for_stage_2, seed_2, guidance_scale_2, custom_timesteps_2, number_of_inference_steps_2, api_name='/upscale256')
# Process the result_path or perform any additional operations
with open(result_path, 'rb') as f:
await ctx.reply('Here is the result of the second stage', file=discord.File(f, 'result.png'))
except Exception as e:
print(f"Error: {e}")
await ctx.reply('An error occurred while processing stage 2 upscaling. Please try again later.')
def run_bot():
bot.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()