huggingbots / app.py
lunarflu's picture
lunarflu HF Staff
await -> sent_message = await
918ede3
raw
history blame
5.74 kB
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 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)
message = await ctx.reply('Here is the combined image. React with the image you want to upscale!')
with open(combined_image_path, 'rb') as f:
sent_message = 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)
if str(reaction.emoji) == '1️⃣':
await ctx.send("You chose the first image!")
elif str(reaction.emoji) == '2️⃣':
await ctx.send("You chose the second image!")
elif str(reaction.emoji) == '3️⃣':
await ctx.send("You chose the third image!")
elif str(reaction.emoji) == '4️⃣':
await ctx.send("You chose 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()