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import discord |
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import os |
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import threading |
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import gradio as gr |
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import requests |
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import json |
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import random |
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import time |
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import re |
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from discord import Embed, Color |
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from discord.ext import commands |
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from gradio_client import Client |
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from PIL import Image |
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from datetime import datetime |
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from pytz import timezone |
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import asyncio |
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zurich_tz = timezone("Europe/Zurich") |
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def convert_to_timezone(dt, tz): |
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return dt.astimezone(tz).strftime("%Y-%m-%d %H:%M:%S %Z") |
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DFIF_TOKEN = os.getenv('HF_TOKEN') |
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df = Client("huggingface-projects/IF", DFIF_TOKEN) |
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sdlu = Client("huggingface-projects/stable-diffusion-latent-upscaler", DFIF_TOKEN) |
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DISCORD_TOKEN = os.environ.get("GRADIOTEST_TOKEN", None) |
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intents = discord.Intents.default() |
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intents.message_content = True |
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bot = commands.Bot(command_prefix='!', intents=intents) |
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@bot.event |
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async def on_ready(): |
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print('Logged on as', bot.user) |
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bot.log_channel = bot.get_channel(1100458786826747945) |
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@bot.command() |
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async def deepfloydif(ctx, *, prompt: str): |
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try: |
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prompt = prompt.strip()[:100] |
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prompt = re.sub(r'[^\w\s]', '', prompt) |
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def check_reaction(reaction, user): |
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return user == ctx.author and str(reaction.emoji) in ['1️⃣', '2️⃣', '3️⃣', '4️⃣'] |
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await ctx.message.add_reaction('👍') |
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number_of_images = 4 |
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current_time = int(time.time()) |
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random.seed(current_time) |
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seed = random.randint(0, 2**32 - 1) |
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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") |
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png_files = [f for f in os.listdir(stage_1_results) if f.endswith('.png')] |
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if png_files: |
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first_png = png_files[0] |
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second_png = png_files[1] |
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third_png = png_files[2] |
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fourth_png = png_files[3] |
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first_png_path = os.path.join(stage_1_results, first_png) |
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second_png_path = os.path.join(stage_1_results, second_png) |
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third_png_path = os.path.join(stage_1_results, third_png) |
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fourth_png_path = os.path.join(stage_1_results, fourth_png) |
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img1 = Image.open(first_png_path) |
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img2 = Image.open(second_png_path) |
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img3 = Image.open(third_png_path) |
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img4 = Image.open(fourth_png_path) |
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combined_image = Image.new('RGB', (img1.width * 2, img1.height * 2)) |
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combined_image.paste(img1, (0, 0)) |
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combined_image.paste(img2, (img1.width, 0)) |
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combined_image.paste(img3, (0, img1.height)) |
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combined_image.paste(img4, (img1.width, img1.height)) |
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combined_image_path = os.path.join(stage_1_results, 'combined_image.png') |
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combined_image.save(combined_image_path) |
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await create_thread_dfif(ctx, combined_image_path) |
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with open(combined_image_path, 'rb') as f: |
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thread_channel = await ctx.channel.create_thread(name='Image Thread') |
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sent_message = await ctx.reply('Here is the combined image. React with the image number you want to upscale!', file=discord.File(f, 'combined_image.png')) |
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for emoji in ['1️⃣', '2️⃣', '3️⃣', '4️⃣']: |
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await sent_message.add_reaction(emoji) |
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reaction, user = await bot.wait_for('reaction_add', check=check_reaction) |
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if str(reaction.emoji) == '1️⃣': |
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await ctx.reply("Upscaling the first image...") |
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index = 0 |
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await dfif2(ctx, index, stage_1_result_path) |
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elif str(reaction.emoji) == '2️⃣': |
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await ctx.reply("Upscaling the second image...") |
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index = 1 |
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await dfif2(ctx, index, stage_1_result_path) |
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elif str(reaction.emoji) == '3️⃣': |
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await ctx.reply("Upscaling the third image...") |
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index = 2 |
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await dfif2(ctx, index, stage_1_result_path) |
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elif str(reaction.emoji) == '4️⃣': |
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await ctx.reply("Upscaling the fourth image...") |
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index = 3 |
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await dfif2(ctx, index, stage_1_result_path) |
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except Exception as e: |
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print(f"Error: {e}") |
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await ctx.reply('An error occurred while processing your request. Please wait 5 seconds before retrying.') |
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async def dfif2(ctx, index: int, stage_1_result_path): |
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try: |
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selected_index_for_stage_2 = index |
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seed_2 = 0 |
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guidance_scale_2 = 4 |
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custom_timesteps_2 = 'smart50' |
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number_of_inference_steps_2 = 50 |
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result_path = df.predict(stage_1_result_path, selected_index_for_stage_2, seed_2, |
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guidance_scale_2, custom_timesteps_2, number_of_inference_steps_2, api_name='/upscale256') |
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with open(result_path, 'rb') as f: |
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await ctx.reply('Here is the result of the second stage', file=discord.File(f, 'result.png')) |
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except Exception as e: |
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print(f"Error: {e}") |
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await ctx.reply('An error occurred while processing stage 2 upscaling. Please try again later.') |
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def run_bot(): |
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bot.run(DISCORD_TOKEN) |
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threading.Thread(target=run_bot).start() |
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def greet(name): |
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return "Hello " + name + "!" |
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demo = gr.Interface(fn=greet, inputs="text", outputs="text") |
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demo.launch() |