mirror of https://github.com/skygpu/skynet.git
Initial commit
commit
66f21ff9de
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@ -0,0 +1,23 @@
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from pytorch/pytorch:latest
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run apt-get update && apt-get install -y git curl
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run pip install --upgrade \
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diffusers[torch] \
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transformers \
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huggingface_hub \
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pyTelegramBotAPI \
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pymongo \
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pdbpp
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run mkdir /scripts
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run mkdir /outputs
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run mkdir /inputs
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env HF_HOME /hf_home
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run mkdir /hf_home
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workdir /scripts
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env PYTORCH_CUDA_ALLOC_CONF max_split_size_mb:128
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@ -0,0 +1,11 @@
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docker run \
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-it \
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--rm \
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--gpus=all \
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--env HF_TOKEN='' \
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--env DB_USER='' \
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--env DB_PASS='' \
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--mount type=bind,source="$(pwd)"/outputs,target=/outputs \
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--mount type=bind,source="$(pwd)"/hf_home,target=/hf_home \
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--mount type=bind,source="$(pwd)"/scripts,target=/scripts \
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skynet-art-bot:0.1a3 $1
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docker run
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-d \
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--rm \
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-p 27017:27017 \
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--name mongodb-skynet \
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--mount type=bind,source="$(pwd)"/mongodb,target=/data/db \
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-e MONGO_INITDB_ROOT_USERNAME="" \
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-e MONGO_INITDB_ROOT_PASSWORD="" \
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mongo
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@ -0,0 +1,382 @@
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#!/usr/bin/python
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import os
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import logging
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import random
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from torch.multiprocessing import spawn
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import telebot
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from telebot.types import InputFile
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import sys
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import uuid
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from pathlib import Path
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import torch
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from torch.multiprocessing.spawn import ProcessRaisedException
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from diffusers import StableDiffusionPipeline, EulerAncestralDiscreteScheduler
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from huggingface_hub import login
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from datetime import datetime
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from pymongo import MongoClient
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db_user = os.environ['DB_USER']
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db_pass = os.environ['DB_PASS']
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logging.basicConfig(level=logging.INFO)
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MEM_FRACTION = .33
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HELP_TEXT = '''
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test art bot v0.1a3
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commands work on a user per user basis!
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config is individual to each user!
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/txt2img {prompt} - request an image based on a prompt
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/redo - redo last primpt
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/cool - list of cool words to use
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/stats - user statistics
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/config step {number} - set amount of iterations
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/config seed {number} - set the seed, deterministic results!
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/config size {width} {height} - set size in pixels
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/config guidance {number} - prompt text importance
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'''
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COOL_WORDS = [
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'cyberpunk',
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'soviet propaganda poster',
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'rastafari',
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'cannabis',
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'art deco',
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'H R Giger Necronom IV',
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'dimethyltryptamine',
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'lysergic',
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'slut',
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'psilocybin',
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'trippy',
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'lucy in the sky with diamonds',
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'fractal',
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'da vinci',
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'pencil illustration',
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'blueprint',
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'internal diagram',
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'baroque',
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'the last judgment',
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'michelangelo'
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]
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GROUP_ID = -889553587
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MIN_STEP = 1
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MAX_STEP = 100
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MAX_SIZE = (512, 656)
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MAX_GUIDANCE = 20
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DEFAULT_SIZE = (512, 512)
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DEFAULT_GUIDANCE = 7.5
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DEFAULT_STEP = 75
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DEFAULT_CREDITS = 10
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def generate_image(i, prompt, name, step, size, guidance, seed):
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assert torch.cuda.is_available()
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torch.cuda.empty_cache()
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torch.cuda.set_per_process_memory_fraction(MEM_FRACTION)
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pipe = StableDiffusionPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5",
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torch_dtype=torch.float16,
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revision="fp16",
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safety_checker=None
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)
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pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
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pipe = pipe.to("cuda")
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w, h = size
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print(f'generating image... of size {w, h}')
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image = pipe(
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prompt,
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width=w,
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height=h,
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guidance_scale=guidance, num_inference_steps=step,
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generator=torch.Generator("cuda").manual_seed(seed)
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).images[0]
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image.save(f'/outputs/{name}.png')
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print('saved')
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if __name__ == '__main__':
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API_TOKEN = '5880619053:AAFge2UfObw1kCn9Kb7AAyqaIHs_HgM0Fx0'
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bot = telebot.TeleBot(API_TOKEN)
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db_client = MongoClient(f'mongodb://{db_user}:{db_pass}@localhost:27017')
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rr_id = 0
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tgdb = db_client.get_database('telegram')
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collections = tgdb.list_collection_names()
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if 'users' in collections:
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tg_users = tgdb.get_collection('users')
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# tg_users.delete_many({})
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else:
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tg_users = tgdb.create_collection('users')
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# db functions
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def get_user(uid: int):
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return tg_users.find_one({'uid': uid})
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def new_user(uid: int):
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if get_user(uid):
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raise ValueError('User already present on db')
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res = tg_users.insert_one({
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'generated': 0,
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'uid': uid,
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'credits': DEFAULT_CREDITS,
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'joined': datetime.utcnow().isoformat(),
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'last_prompt': None,
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'config': {
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'step': DEFAULT_STEP,
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'size': DEFAULT_SIZE,
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'seed': None,
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'guidance': DEFAULT_GUIDANCE
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}
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})
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assert res.acknowledged
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return get_user(uid)
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def get_or_create_user(uid: int):
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db_user = get_user(uid)
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if not db_user:
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db_user = new_user(uid)
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return db_user
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def update_user(uid: int, updt_cmd: dict):
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user = get_user(uid)
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if not user:
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raise ValueError('User not present on db')
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return tg_users.find_one_and_update(
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{'uid': uid}, updt_cmd)
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# bot handler
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def img_for_user_with_prompt(
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uid: int,
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prompt: str, step: int, size: tuple[int, int], guidance: int, seed: int
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):
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name = uuid.uuid4()
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spawn(
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generate_image,
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args=(prompt, name, step, size, guidance, seed))
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logging.info(f'done generating. got {name}, sending...')
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if len(prompt) > 256:
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reply_txt = f'prompt: \"{prompt[:256]}...\"\n(full prompt too big to show on reply...)\n'
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else:
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reply_txt = f'prompt: \"{prompt}\"\n'
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reply_txt += f'seed: {seed}\n'
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reply_txt += f'iterations: {step}\n'
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reply_txt += f'size: {size}\n'
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reply_txt += f'guidance: {guidance}\n'
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reply_txt += f'stable-diff v1.5 uncensored\n'
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reply_txt += f'euler ancestral discrete'
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return reply_txt, name
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@bot.message_handler(commands=['help'])
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def send_help(message):
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bot.reply_to(message, HELP_TEXT)
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@bot.message_handler(commands=['cool'])
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def send_help(message):
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bot.reply_to(message, '\n'.join(COOL_WORDS))
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@bot.message_handler(commands=['txt2img'])
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def send_txt2img(message):
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# check msg comes from testing group
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chat = message.chat
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if chat.type != 'group' and chat.id != GROUP_ID:
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return
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prompt = ' '.join(message.text.split(' ')[1:])
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if len(prompt) == 0:
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bot.reply_to(message, 'empty text prompt ignored.')
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return
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user = message.from_user
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db_user = get_or_create_user(user.id)
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logging.info(f"{user.first_name} ({user.id}) on chat {chat.id} txt2img: {prompt}")
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user_conf = db_user['config']
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step = user_conf['step']
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size = user_conf['size']
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seed = user_conf['seed'] if user_conf['seed'] else random.randint(0, 999999999)
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guidance = user_conf['guidance']
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try:
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reply_txt, name = img_for_user_with_prompt(
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user.id, prompt, step, size, guidance, seed)
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update_user(
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user.id,
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{'$set': {
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'generated': db_user['generated'] + 1,
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'last_prompt': prompt
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}})
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bot.send_photo(
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chat.id,
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caption=f'sent by: {user.first_name}\n' + reply_txt,
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photo=InputFile(f'/outputs/{name}.png'))
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except BaseException as e:
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logging.error(e)
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bot.reply_to(message, 'that command caused an error :(\nchange settings and try again (?')
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@bot.message_handler(commands=['redo'])
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def redo_txt2img(message):
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# check msg comes from testing group
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chat = message.chat
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if chat.type != 'group' and chat.id != GROUP_ID:
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return
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user = message.from_user
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db_user = get_or_create_user(user.id)
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prompt = db_user['last_prompt']
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if not prompt:
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bot.reply_to(message, 'do a /txt2img command first silly!')
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return
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user_conf = db_user['config']
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step = user_conf['step']
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size = user_conf['size']
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seed = user_conf['seed'] if user_conf['seed'] else random.randint(0, 999999999)
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guidance = user_conf['guidance']
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logging.info(f"{user.first_name} ({user.id}) on chat {chat.id} redo: {prompt}")
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try:
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reply_txt, name = img_for_user_with_prompt(
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user.id, prompt, step, size, guidance, seed)
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update_user(
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user.id,
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{'$set': {
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'generated': db_user['generated'] + 1,
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}})
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bot.send_photo(
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chat.id,
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caption=f'sent by: {user.first_name}\n' + reply_txt,
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photo=InputFile(f'/outputs/{name}.png'))
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except BaseException as e:
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logging.error(e)
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bot.reply_to(message, 'that command caused an error :(\nchange settings and try again (?')
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@bot.message_handler(commands=['config'])
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def set_config(message):
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params = message.text.split(' ')
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if len(params) < 3:
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bot.reply_to(message, 'wrong msg format')
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else:
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user = message.from_user
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chat = message.chat
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db_user = get_user(user.id)
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if not db_user:
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db_user = new_user(user.id)
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try:
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attr = params[1]
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if attr == 'step':
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val = int(params[2])
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val = max(min(val, MAX_STEP), MIN_STEP)
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res = update_user(user.id, {'$set': {'config.step': val}})
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elif attr == 'size':
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max_w, max_h = MAX_SIZE
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w = max(min(int(params[2]), max_w), 16)
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h = max(min(int(params[3]), max_h), 16)
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val = (w, h)
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if (w % 8 != 0) or (h % 8 != 0):
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bot.reply_to(message, 'size must be divisible by 8!')
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return
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res = update_user(user.id, {'$set': {'config.size': val}})
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elif attr == 'seed':
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val = params[2]
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if val == 'auto':
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val = None
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else:
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val = int(params[2])
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res = update_user(user.id, {'$set': {'config.seed': val}})
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elif attr == 'guidance':
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val = float(params[2])
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val = max(min(val, MAX_GUIDANCE), 0)
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res = update_user(user.id, {'$set': {'config.guidance': val}})
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bot.reply_to(message, f"config updated! {attr} to {val}")
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except ValueError:
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bot.reply_to(message, f"\"{val}\" is not a number silly")
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@bot.message_handler(commands=['stats'])
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def user_stats(message):
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user = message.from_user
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db_user = get_user(user.id)
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|
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if not db_user:
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db_user = new_user(user.id)
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joined_date_str = datetime.fromisoformat(db_user['joined']).strftime('%B the %dth %Y, %H:%M:%S')
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user_stats_str = f'generated: {db_user["generated"]}\n'
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user_stats_str += f'joined: {joined_date_str}\n'
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user_stats_str += f'credits: {db_user["credits"]}\n'
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bot.reply_to(
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message, user_stats_str)
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|
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|
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login(token=os.environ['HF_TOKEN'])
|
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bot.infinity_polling()
|
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|
|
@ -0,0 +1,30 @@
|
|||
import os
|
||||
import sys
|
||||
|
||||
from pathlib import Path
|
||||
|
||||
import torch
|
||||
from diffusers import StableDiffusionPipeline
|
||||
|
||||
from huggingface_hub import login
|
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|
||||
assert torch.cuda.is_available()
|
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|
||||
login(token=os.environ['HF_TOKEN'])
|
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|
||||
pipe = StableDiffusionPipeline.from_pretrained(
|
||||
"runwayml/stable-diffusion-v1-5",
|
||||
torch_dtype=torch.float16,
|
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revision="fp16"
|
||||
)
|
||||
pipe = pipe.to("cuda")
|
||||
|
||||
prompt = sys.argv[1]
|
||||
image = pipe(
|
||||
prompt,
|
||||
width=640,
|
||||
height=640,
|
||||
guidance_scale=7.5, num_inference_steps=120
|
||||
).images[0]
|
||||
|
||||
image.save("/outputs/img.png")
|
||||
Loading…
Reference in New Issue