#!/usr/bin/python3
#==================================================================#
# KoboldAI
# Version: 1.16.4
# By: KoboldAIDev and the KoboldAI Community
#==================================================================#
# External packages
import eventlet
eventlet.monkey_patch(all=True, thread=False)
import os
os.system("")
os.environ['EVENTLET_THREADPOOL_SIZE'] = '50'
from eventlet import tpool
from os import path, getcwd
import re
import json
import collections
import zipfile
import packaging
import contextlib
import traceback
import threading
from typing import Any, Callable, TypeVar, Tuple, Union, Dict, Set, List
import requests
import html
import argparse
import sys
import gc
import lupa
# KoboldAI
import fileops
import gensettings
from utils import debounce
import utils
import structures
if lupa.LUA_VERSION[:2] != (5, 4):
print(f"Please install lupa==1.10. You have lupa {lupa.__version__}.", file=sys.stderr)
#==================================================================#
# Variables & Storage
#==================================================================#
# Terminal tags for colored text
class colors:
PURPLE = '\033[95m'
BLUE = '\033[94m'
CYAN = '\033[96m'
GREEN = '\033[92m'
YELLOW = '\033[93m'
RED = '\033[91m'
END = '\033[0m'
UNDERLINE = '\033[4m'
# AI models
modellist = [
["Load a model from its directory", "NeoCustom", ""],
["Load an old GPT-2 model (eg CloverEdition)", "GPT2Custom", ""],
["Skein 6B (Hybrid)", "KoboldAI/GPT-J-6B-Skein", "12GB"],
["Adventure 6B", "KoboldAI/GPT-J-6B-Adventure", "12GB"],
["Lit 6B (NSFW)", "hakurei/lit-6B", "12GB"],
["C1 6B (Chatbot)", "hakurei/c1-6B", "12GB"],
["Picard 2.7B (Novel)", "KoboldAI/GPT-Neo-2.7B-Picard", "6GB"],
["Horni 2.7B (NSFW)", "KoboldAI/GPT-Neo-2.7B-Horni", "6GB"],
["Horni-LN 2.7B (Novel)", "KoboldAI/GPT-Neo-2.7B-Horni-LN", "6GB"],
["Shinen 2.7B (NSFW)", "KoboldAI/GPT-Neo-2.7B-Shinen", "6GB"],
["GPT-J 6B", "EleutherAI/gpt-j-6B", "12GB"],
["GPT-Neo 2.7B", "EleutherAI/gpt-neo-2.7B", "6GB"],
["GPT-Neo 1.3B", "EleutherAI/gpt-neo-1.3B", "3GB"],
["GPT-2 XL", "gpt2-xl", "8GB"],
["GPT-2 Large", "gpt2-large", "4GB"],
["GPT-2 Med", "gpt2-medium", "2GB"],
["GPT-2", "gpt2", "1GB"],
["OpenAI API (requires API key)", "OAI", ""],
["InferKit API (requires API key)", "InferKit", ""],
["KoboldAI Server API (Old Google Colab)", "Colab", ""],
["Read Only (No AI)", "ReadOnly", ""]
]
# Variables
class vars:
lastact = "" # The last action received from the user
submission = "" # Same as above, but after applying input formatting
lastctx = "" # The last context submitted to the generator
model = "" # Model ID string chosen at startup
model_type = "" # Model Type (Automatically taken from the model config)
noai = False # Runs the script without starting up the transformers pipeline
aibusy = False # Stops submissions while the AI is working
max_length = 1024 # Maximum number of tokens to submit per action
ikmax = 3000 # Maximum number of characters to submit to InferKit
genamt = 80 # Amount of text for each action to generate
ikgen = 200 # Number of characters for InferKit to generate
rep_pen = 1.1 # Default generator repetition_penalty
temp = 0.5 # Default generator temperature
top_p = 0.9 # Default generator top_p
top_k = 0 # Default generator top_k
tfs = 1.0 # Default generator tfs (tail-free sampling)
numseqs = 1 # Number of sequences to ask the generator to create
gamestarted = False # Whether the game has started (disables UI elements)
serverstarted = False # Whether or not the Flask server has started
prompt = "" # Prompt
memory = "" # Text submitted to memory field
authornote = "" # Text submitted to Author's Note field
authornotetemplate = "[Author's note: <|>]" # Author's note template
setauthornotetemplate = authornotetemplate # Saved author's note template in settings
andepth = 3 # How far back in history to append author's note
actions = structures.KoboldStoryRegister() # Actions submitted by user and AI
worldinfo = [] # List of World Info key/value objects
worldinfo_i = [] # List of World Info key/value objects sans uninitialized entries
worldinfo_u = {} # Dictionary of World Info UID - key/value pairs
wifolders_d = {} # Dictionary of World Info folder UID-info pairs
wifolders_l = [] # List of World Info folder UIDs
wifolders_u = {} # Dictionary of pairs of folder UID - list of WI UID
lua_state = None # Lua state of the Lua scripting system
lua_koboldbridge = None # `koboldbridge` from bridge.lua
lua_kobold = None # `kobold` from` bridge.lua
lua_koboldcore = None # `koboldcore` from bridge.lua
lua_logname = ... # Name of previous userscript that logged to terminal
lua_running = False # Whether or not Lua is running (i.e. wasn't stopped due to an error)
lua_edited = set() # Set of chunk numbers that were edited from a Lua generation modifier
lua_deleted = set() # Set of chunk numbers that were deleted from a Lua generation modifier
generated_tkns = 0 # If using a backend that supports Lua generation modifiers, how many tokens have already been generated, otherwise 0
spfilename = "" # Filename of soft prompt to load, or an empty string if not using a soft prompt
userscripts = [] # List of userscripts to load
last_userscripts = [] # List of previous userscript filenames from the previous time userscripts were send via usstatitems
corescript = "default.lua" # Filename of corescript to load
# badwords = [] # Array of str/chr values that should be removed from output
badwordsids = [[13460], [6880], [50256], [42496], [4613], [17414], [22039], [16410], [27], [29], [38430], [37922], [15913], [24618], [28725], [58], [47175], [36937], [26700], [12878], [16471], [37981], [5218], [29795], [13412], [45160], [3693], [49778], [4211], [20598], [36475], [33409], [44167], [32406], [29847], [29342], [42669], [685], [25787], [7359], [3784], [5320], [33994], [33490], [34516], [43734], [17635], [24293], [9959], [23785], [21737], [28401], [18161], [26358], [32509], [1279], [38155], [18189], [26894], [6927], [14610], [23834], [11037], [14631], [26933], [46904], [22330], [25915], [47934], [38214], [1875], [14692], [41832], [13163], [25970], [29565], [44926], [19841], [37250], [49029], [9609], [44438], [16791], [17816], [30109], [41888], [47527], [42924], [23984], [49074], [33717], [31161], [49082], [30138], [31175], [12240], [14804], [7131], [26076], [33250], [3556], [38381], [36338], [32756], [46581], [17912], [49146]] # Tokenized array of badwords used to prevent AI artifacting
deletewi = None # Temporary storage for UID to delete
wirmvwhtsp = False # Whether to remove leading whitespace from WI entries
widepth = 3 # How many historical actions to scan for WI hits
mode = "play" # Whether the interface is in play, memory, or edit mode
editln = 0 # Which line was last selected in Edit Mode
gpu_device = 0 # Which PyTorch device to use when using pure GPU generation
url = "https://api.inferkit.com/v1/models/standard/generate" # InferKit API URL
oaiurl = "" # OpenAI API URL
oaiengines = "https://api.openai.com/v1/engines"
colaburl = "" # Ngrok url for Google Colab mode
apikey = "" # API key to use for InferKit API calls
oaiapikey = "" # API key to use for OpenAI API calls
savedir = getcwd()+"\stories"
hascuda = False # Whether torch has detected CUDA on the system
usegpu = False # Whether to launch pipeline with GPU support
custmodpth = "" # Filesystem location of custom model to run
formatoptns = {'frmttriminc': True, 'frmtrmblln': False, 'frmtrmspch': False, 'frmtadsnsp': False, 'singleline': False} # Container for state of formatting options
importnum = -1 # Selection on import popup list
importjs = {} # Temporary storage for import data
loadselect = "" # Temporary storage for story filename to load
spselect = "" # Temporary storage for soft prompt filename to load
spmeta = None # Metadata of current soft prompt, or None if not using a soft prompt
sp = None # Current soft prompt tensor (as a NumPy array)
sp_length = 0 # Length of current soft prompt in tokens, or 0 if not using a soft prompt
svowname = "" # Filename that was flagged for overwrite confirm
saveow = False # Whether or not overwrite confirm has been displayed
genseqs = [] # Temporary storage for generated sequences
recentback = False # Whether Back button was recently used without Submitting or Retrying after
recentrng = None # If a new random game was recently generated without Submitting after, this is the topic used (as a string), otherwise this is None
recentrngm = None # If a new random game was recently generated without Submitting after, this is the memory used (as a string), otherwise this is None
useprompt = False # Whether to send the full prompt with every submit action
breakmodel = False # For GPU users, whether to use both system RAM and VRAM to conserve VRAM while offering speedup compared to CPU-only
bmsupported = False # Whether the breakmodel option is supported (GPT-Neo/GPT-J only, currently)
smandelete = False # Whether stories can be deleted from inside the browser
smanrename = False # Whether stories can be renamed from inside the browser
allowsp = False # Whether we are allowed to use soft prompts (by default enabled if we're using GPT-2, GPT-Neo or GPT-J)
modeldim = -1 # Embedding dimension of your model (e.g. it's 4096 for GPT-J-6B and 2560 for GPT-Neo-2.7B)
laststory = None # Filename (without extension) of most recent story JSON file we loaded
regex_sl = re.compile(r'\n*(?<=.) *\n(.|\n)*') # Pattern for limiting the output to a single line
acregex_ai = re.compile(r'\n* *>(.|\n)*') # Pattern for matching adventure actions from the AI so we can remove them
acregex_ui = re.compile(r'^ *(>.*)$', re.MULTILINE) # Pattern for matching actions in the HTML-escaped story so we can apply colouring, etc (make sure to encase part to format in parentheses)
comregex_ai = re.compile(r'(?:\n<\|(?:.|\n)*?\|>(?=\n|$))|(?:<\|(?:.|\n)*?\|>\n?)') # Pattern for matching comments to remove them before sending them to the AI
comregex_ui = re.compile(r'(<\|(?:.|\n)*?\|>)') # Pattern for matching comments in the editor
chatmode = False
chatname = "You"
adventure = False
actionmode = 1
dynamicscan = False
remote = False
nopromptgen = False
rngpersist = False
#==================================================================#
# Function to get model selection at startup
#==================================================================#
def getModelSelection():
print(" # Model V/RAM\n =========================================")
i = 1
for m in modellist:
print(" {0} - {1}\t\t{2}".format("{:<2}".format(i), m[0].ljust(15), m[2]))
i += 1
print(" ");
modelsel = 0
vars.model = ''
while(vars.model == ''):
modelsel = input("Model #> ")
if(modelsel.isnumeric() and int(modelsel) > 0 and int(modelsel) <= len(modellist)):
vars.model = modellist[int(modelsel)-1][1]
else:
print("{0}Please enter a valid selection.{1}".format(colors.RED, colors.END))
# If custom model was selected, get the filesystem location and store it
if(vars.model == "NeoCustom" or vars.model == "GPT2Custom"):
print("{0}Please choose the folder where pytorch_model.bin is located:{1}\n".format(colors.CYAN, colors.END))
modpath = fileops.getdirpath(getcwd(), "Select Model Folder")
if(modpath):
# Save directory to vars
vars.custmodpth = modpath
else:
# Print error and retry model selection
print("{0}Model select cancelled!{1}".format(colors.RED, colors.END))
print("{0}Select an AI model to continue:{1}\n".format(colors.CYAN, colors.END))
getModelSelection()
#==================================================================#
# Return all keys in tokenizer dictionary containing char
#==================================================================#
def gettokenids(char):
keys = []
for key in vocab_keys:
if(key.find(char) != -1):
keys.append(key)
return keys
#==================================================================#
# Return Model Name
#==================================================================#
def getmodelname():
if(args.configname):
modelname = args.configname
return modelname
if(vars.model in ("NeoCustom", "GPT2Custom", "TPUMeshTransformerGPTJ")):
modelname = os.path.basename(os.path.normpath(vars.custmodpth))
return modelname
else:
modelname = vars.model
return modelname
#==================================================================#
# Breakmodel configuration functions
#==================================================================#
def device_list(n_layers, primary=None, selected=None):
device_count = torch.cuda.device_count()
if(device_count < 2):
primary = None
gpu_blocks = breakmodel.gpu_blocks + (device_count - len(breakmodel.gpu_blocks))*[0]
print(f"{colors.YELLOW} DEVICE ID | LAYERS | DEVICE NAME{colors.END}")
for i in range(device_count):
name = torch.cuda.get_device_name(i)
if(len(name) > 47):
name = "..." + name[-44:]
row_color = colors.END
sep_color = colors.YELLOW
print(f"{row_color}{colors.YELLOW + '->' + row_color if i == selected else ' '} {'(primary)' if i == primary else ' '*9} {i:3} {sep_color}|{row_color} {gpu_blocks[i]:3} {sep_color}|{row_color} {name}{colors.END}")
row_color = colors.END
sep_color = colors.YELLOW
print(f"{row_color} {' '*9} N/A {sep_color}|{row_color} {n_layers:3} {sep_color}|{row_color} (CPU){colors.END}")
def device_config(model):
global breakmodel, generator
import breakmodel
n_layers = model.config.num_layers if hasattr(model.config, "num_layers") else model.config.n_layer
if(args.breakmodel_gpulayers is not None):
try:
breakmodel.gpu_blocks = list(map(int, args.breakmodel_gpulayers.split(',')))
assert len(breakmodel.gpu_blocks) <= torch.cuda.device_count()
s = n_layers
for i in range(len(breakmodel.gpu_blocks)):
if(breakmodel.gpu_blocks[i] <= -1):
breakmodel.gpu_blocks[i] = s
break
else:
s -= breakmodel.gpu_blocks[i]
assert sum(breakmodel.gpu_blocks) <= n_layers
n_layers -= sum(breakmodel.gpu_blocks)
except:
print("WARNING: --layers is malformatted. Please use the --help option to see correct usage of --layers. Defaulting to all layers on device 0.", file=sys.stderr)
breakmodel.gpu_blocks = [n_layers]
n_layers = 0
elif(args.breakmodel_layers is not None):
breakmodel.gpu_blocks = [n_layers - max(0, min(n_layers, args.breakmodel_layers))]
n_layers -= sum(breakmodel.gpu_blocks)
elif(args.model is not None):
print("Breakmodel not specified, assuming GPU 0")
breakmodel.gpu_blocks = [n_layers]
n_layers = 0
else:
device_count = torch.cuda.device_count()
if(device_count > 1):
print(colors.CYAN + "\nPlease select one of your GPUs to be your primary GPU.")
print("VRAM usage in your primary GPU will be higher than for your other ones.")
print("It is recommended you make your fastest GPU your primary GPU.")
device_list(n_layers)
while(True):
primaryselect = input("device ID> ")
if(primaryselect.isnumeric() and 0 <= int(primaryselect) < device_count):
breakmodel.primary_device = int(primaryselect)
break
else:
print(f"{colors.RED}Please enter an integer between 0 and {device_count-1}.{colors.END}")
else:
breakmodel.primary_device = 0
print(colors.PURPLE + "\nIf you don't have enough VRAM to run the model on a single GPU")
print("you can split the model between your CPU and your GPU(s), or between")
print("multiple GPUs if you have more than one.")
print("By putting more 'layers' on a GPU or CPU, more computations will be")
print("done on that device and more VRAM or RAM will be required on that device")
print("(roughly proportional to number of layers).")
print("It should be noted that GPUs are orders of magnitude faster than the CPU.")
print(f"This model has{colors.YELLOW} {n_layers} {colors.PURPLE}layers.{colors.END}\n")
for i in range(device_count):
device_list(n_layers, primary=breakmodel.primary_device, selected=i)
print(f"{colors.CYAN}\nHow many of the remaining{colors.YELLOW} {n_layers} {colors.CYAN}layers would you like to put into device {i}?\nYou can also enter -1 to allocate all remaining layers to this device.{colors.END}\n")
while(True):
layerselect = input("# of layers> ")
if((layerselect.isnumeric() or layerselect.strip() == '-1') and -1 <= int(layerselect) <= n_layers):
layerselect = int(layerselect)
layerselect = n_layers if layerselect == -1 else layerselect
breakmodel.gpu_blocks.append(layerselect)
n_layers -= layerselect
break
else:
print(f"{colors.RED}Please enter an integer between -1 and {n_layers}.{colors.END}")
if(n_layers == 0):
break
print(colors.PURPLE + "\nFinal device configuration:")
device_list(n_layers)
# If all layers are on the same device, use the old GPU generation mode
while(len(breakmodel.gpu_blocks) and breakmodel.gpu_blocks[-1] == 0):
breakmodel.gpu_blocks.pop()
if(len(breakmodel.gpu_blocks) and breakmodel.gpu_blocks[-1] in (-1, model.config.num_layers if hasattr(model.config, "num_layers") else model.config.n_layer)):
vars.breakmodel = False
vars.usegpu = True
vars.gpu_device = len(breakmodel.gpu_blocks)-1
model = model.half().to(vars.gpu_device)
generator = model.generate
return
if(not breakmodel.gpu_blocks):
print("Nothing assigned to a GPU, reverting to CPU only mode")
vars.breakmodel = False
vars.usegpu = False
model = model.to('cpu').float()
generator = model.generate
return
model.half().to('cpu')
gc.collect()
model.transformer.wte.to(breakmodel.primary_device)
model.transformer.ln_f.to(breakmodel.primary_device)
if(hasattr(model, 'lm_head')):
model.lm_head.to(breakmodel.primary_device)
if(hasattr(model.transformer, 'wpe')):
model.transformer.wpe.to(breakmodel.primary_device)
gc.collect()
GPTNeoModel.forward = breakmodel.new_forward
if("GPTJModel" in globals()):
GPTJModel.forward = breakmodel.new_forward
generator = model.generate
breakmodel.move_hidden_layers(model.transformer)
#==================================================================#
# Startup
#==================================================================#
# Parsing Parameters
parser = argparse.ArgumentParser(description="KoboldAI Server")
parser.add_argument("--remote", action='store_true', help="Optimizes KoboldAI for Remote Play")
parser.add_argument("--ngrok", action='store_true', help="Optimizes KoboldAI for Remote Play using Ngrok")
parser.add_argument("--model", help="Specify the Model Type to skip the Menu")
parser.add_argument("--path", help="Specify the Path for local models (For model NeoCustom or GPT2Custom)")
parser.add_argument("--cpu", action='store_true', help="By default unattended launches are on the GPU use this option to force CPU usage.")
parser.add_argument("--breakmodel", action='store_true', help=argparse.SUPPRESS)
parser.add_argument("--breakmodel_layers", type=int, help=argparse.SUPPRESS)
parser.add_argument("--breakmodel_gpulayers", type=str, help="If using a model that supports hybrid generation, this is a comma-separated list that specifies how many layers to put on each GPU device. For example to put 8 layers on device 0, 9 layers on device 1 and 11 layers on device 2, use --layers 8,9,11")
parser.add_argument("--override_delete", action='store_true', help="Deleting stories from inside the browser is disabled if you are using --remote and enabled otherwise. Using this option will instead allow deleting stories if using --remote and prevent deleting stories otherwise.")
parser.add_argument("--override_rename", action='store_true', help="Renaming stories from inside the browser is disabled if you are using --remote and enabled otherwise. Using this option will instead allow renaming stories if using --remote and prevent renaming stories otherwise.")
parser.add_argument("--configname", help="Force a fixed configuration name to aid with config management.")
args: argparse.Namespace = None
if(os.environ.get("KOBOLDAI_ARGS") is not None):
import shlex
args = parser.parse_args(shlex.split(os.environ["KOBOLDAI_ARGS"]))
else:
args = parser.parse_args()
vars.model = args.model;
if args.remote:
vars.remote = True;
if args.ngrok:
vars.remote = True;
vars.smandelete = vars.remote == args.override_delete
vars.smanrename = vars.remote == args.override_rename
# Select a model to run
if args.model:
print("Welcome to KoboldAI!\nYou have selected the following Model:", vars.model)
if args.path:
print("You have selected the following path for your Model :", args.path)
vars.custmodpth = args.path;
vars.colaburl = args.path + "/request"; # Lets just use the same parameter to keep it simple
else:
print("{0}Welcome to the KoboldAI Server!\nSelect an AI model to continue:{1}\n".format(colors.CYAN, colors.END))
getModelSelection()
# If transformers model was selected & GPU available, ask to use CPU or GPU
if(not vars.model in ["InferKit", "Colab", "OAI", "ReadOnly", "TPUMeshTransformerGPTJ"]):
vars.allowsp = True
# Test for GPU support
import torch
# Make model path the same as the model name to make this consistent with the other loading method if it isn't a known model type
# This code is not just a workaround for below, it is also used to make the behavior consistent with other loading methods - Henk717
if(not vars.model in ["NeoCustom", "GPT2Custom"]):
vars.custmodpth = vars.model
elif(vars.model == "NeoCustom"):
vars.model = os.path.basename(os.path.normpath(vars.custmodpth))
# Get the model_type from the config or assume a model type if it isn't present
from transformers import AutoConfig
if(os.path.isdir(vars.custmodpth.replace('/', '_'))):
try:
model_config = AutoConfig.from_pretrained(vars.custmodpth.replace('/', '_'), cache_dir="cache/")
vars.model_type = model_config.model_type
except ValueError as e:
vars.model_type = "not_found"
else:
try:
model_config = AutoConfig.from_pretrained(vars.custmodpth, cache_dir="cache/")
vars.model_type = model_config.model_type
except ValueError as e:
vars.model_type = "not_found"
if(vars.model_type == "not_found" and vars.model == "NeoCustom"):
vars.model_type = "gpt_neo"
elif(vars.model_type == "not_found" and vars.model == "GPT2Custom"):
vars.model_type = "gpt2"
elif(vars.model_type == "not_found"):
print("WARNING: No model type detected, assuming Neo (If this is a GPT2 model use the other menu option or --model GPT2Custom)")
vars.model_type = "gpt_neo"
print("{0}Looking for GPU support...{1}".format(colors.PURPLE, colors.END), end="")
vars.hascuda = torch.cuda.is_available()
vars.bmsupported = vars.model_type in ("gpt_neo", "gptj")
if(args.breakmodel is not None and args.breakmodel):
print("WARNING: --breakmodel is no longer supported. Breakmodel mode is now automatically enabled when --layers is used (see --help for details).", file=sys.stderr)
if(args.breakmodel_layers is not None):
print("WARNING: --breakmodel_layers is deprecated. Use --layers instead (see --help for details).", file=sys.stderr)
if(not vars.bmsupported and (args.breakmodel_gpulayers is not None or args.breakmodel_layers is not None)):
print("WARNING: This model does not support hybrid generation. --layers will be ignored.", file=sys.stderr)
if(vars.hascuda):
print("{0}FOUND!{1}".format(colors.GREEN, colors.END))
else:
print("{0}NOT FOUND!{1}".format(colors.YELLOW, colors.END))
if args.model:
if(vars.hascuda):
genselected = True
vars.usegpu = True
vars.breakmodel = False
if(vars.bmsupported):
vars.usegpu = False
vars.breakmodel = True
if(args.cpu):
vars.usegpu = False
vars.breakmodel = False
elif(vars.hascuda):
if(vars.bmsupported):
genselected = True
vars.usegpu = False
vars.breakmodel = True
else:
print(" 1 - GPU\n 2 - CPU\n")
genselected = False
else:
genselected = False
if(vars.hascuda):
while(genselected == False):
genselect = input("Mode> ")
if(genselect == ""):
vars.breakmodel = False
vars.usegpu = True
genselected = True
elif(genselect.isnumeric() and int(genselect) == 1):
if(vars.bmsupported):
vars.breakmodel = True
vars.usegpu = False
genselected = True
else:
vars.breakmodel = False
vars.usegpu = True
genselected = True
elif(genselect.isnumeric() and int(genselect) == 2):
vars.breakmodel = False
vars.usegpu = False
genselected = True
else:
print("{0}Please enter a valid selection.{1}".format(colors.RED, colors.END))
# Ask for API key if InferKit was selected
if(vars.model == "InferKit"):
if(not path.exists("settings/" + getmodelname().replace('/', '_') + ".settings")):
# If the client settings file doesn't exist, create it
print("{0}Please enter your InferKit API key:{1}\n".format(colors.CYAN, colors.END))
vars.apikey = input("Key> ")
# Write API key to file
os.makedirs('settings', exist_ok=True)
file = open("settings/" + getmodelname().replace('/', '_') + ".settings", "w")
try:
js = {"apikey": vars.apikey}
file.write(json.dumps(js, indent=3))
finally:
file.close()
else:
# Otherwise open it up
file = open("settings/" + getmodelname().replace('/', '_') + ".settings", "r")
# Check if API key exists
js = json.load(file)
if("apikey" in js and js["apikey"] != ""):
# API key exists, grab it and close the file
vars.apikey = js["apikey"]
file.close()
else:
# Get API key, add it to settings object, and write it to disk
print("{0}Please enter your InferKit API key:{1}\n".format(colors.CYAN, colors.END))
vars.apikey = input("Key> ")
js["apikey"] = vars.apikey
# Write API key to file
file = open("settings/" + getmodelname().replace('/', '_') + ".settings", "w")
try:
file.write(json.dumps(js, indent=3))
finally:
file.close()
# Ask for API key if OpenAI was selected
if(vars.model == "OAI"):
if(not path.exists("settings/" + getmodelname().replace('/', '_') + ".settings")):
# If the client settings file doesn't exist, create it
print("{0}Please enter your OpenAI API key:{1}\n".format(colors.CYAN, colors.END))
vars.oaiapikey = input("Key> ")
# Write API key to file
os.makedirs('settings', exist_ok=True)
file = open("settings/" + getmodelname().replace('/', '_') + ".settings", "w")
try:
js = {"oaiapikey": vars.oaiapikey}
file.write(json.dumps(js, indent=3))
finally:
file.close()
else:
# Otherwise open it up
file = open("settings/" + getmodelname().replace('/', '_') + ".settings", "r")
# Check if API key exists
js = json.load(file)
if("oaiapikey" in js and js["oaiapikey"] != ""):
# API key exists, grab it and close the file
vars.oaiapikey = js["oaiapikey"]
file.close()
else:
# Get API key, add it to settings object, and write it to disk
print("{0}Please enter your OpenAI API key:{1}\n".format(colors.CYAN, colors.END))
vars.oaiapikey = input("Key> ")
js["oaiapikey"] = vars.oaiapikey
# Write API key to file
file = open("settings/" + getmodelname().replace('/', '_') + ".settings", "w")
try:
file.write(json.dumps(js, indent=3))
finally:
file.close()
# Get list of models from OAI
print("{0}Retrieving engine list...{1}".format(colors.PURPLE, colors.END), end="")
req = requests.get(
vars.oaiengines,
headers = {
'Authorization': 'Bearer '+vars.oaiapikey
}
)
if(req.status_code == 200):
print("{0}OK!{1}".format(colors.GREEN, colors.END))
print("{0}Please select an engine to use:{1}\n".format(colors.CYAN, colors.END))
engines = req.json()["data"]
# Print list of engines
i = 0
for en in engines:
print(" {0} - {1} ({2})".format(i, en["id"], "\033[92mready\033[0m" if en["ready"] == True else "\033[91mnot ready\033[0m"))
i += 1
# Get engine to use
print("")
engselected = False
while(engselected == False):
engine = input("Engine #> ")
if(engine.isnumeric() and int(engine) < len(engines)):
vars.oaiurl = "https://api.openai.com/v1/engines/{0}/completions".format(engines[int(engine)]["id"])
engselected = True
else:
print("{0}Please enter a valid selection.{1}".format(colors.RED, colors.END))
else:
# Something went wrong, print the message and quit since we can't initialize an engine
print("{0}ERROR!{1}".format(colors.RED, colors.END))
print(req.json())
quit()
# Ask for ngrok url if Google Colab was selected
if(vars.model == "Colab"):
if(vars.colaburl == ""):
print("{0}NOTE: For the modern KoboldAI Colab's you open the links directly in your browser.\nThis option is only for the KoboldAI Server API, not all features are supported in this mode.\n".format(colors.YELLOW, colors.END))
print("{0}Enter the URL of the server (For example a trycloudflare link):{1}\n".format(colors.CYAN, colors.END))
vars.colaburl = input("URL> ") + "/request"
if(vars.model == "ReadOnly"):
vars.noai = True
# Set logging level to reduce chatter from Flask
import logging
log = logging.getLogger('werkzeug')
log.setLevel(logging.ERROR)
# Start flask & SocketIO
print("{0}Initializing Flask... {1}".format(colors.PURPLE, colors.END), end="")
from flask import Flask, render_template, Response, request
from flask_socketio import SocketIO, emit
app = Flask(__name__)
app.config['SECRET KEY'] = 'secret!'
socketio = SocketIO(app, async_method="eventlet")
print("{0}OK!{1}".format(colors.GREEN, colors.END))
# Start transformers and create pipeline
if(not vars.model in ["InferKit", "Colab", "OAI", "ReadOnly", "TPUMeshTransformerGPTJ"]):
if(not vars.noai):
print("{0}Initializing transformers, please wait...{1}".format(colors.PURPLE, colors.END))
from transformers import StoppingCriteria, GPT2TokenizerFast, GPT2LMHeadModel, GPTNeoForCausalLM, GPTNeoModel, AutoModelForCausalLM, AutoTokenizer
try:
from transformers import GPTJModel
except:
pass
import transformers.generation_utils
from transformers import __version__ as transformers_version
# Patch transformers to use our soft prompt
def patch_causallm(cls):
old_forward = cls.forward
def new_causallm_forward(self, *args, **kwargs):
input_ids = kwargs.get('input_ids').to(self.device)
assert input_ids is not None
kwargs['input_ids'] = None
if(vars.sp is not None):
shifted_input_ids = input_ids - self.config.vocab_size
input_ids.clamp_(max=self.config.vocab_size-1)
inputs_embeds = self.transformer.wte(input_ids)
if(vars.sp is not None):
vars.sp = vars.sp.to(inputs_embeds.dtype).to(inputs_embeds.device)
inputs_embeds = torch.where(
(shifted_input_ids >= 0)[..., None],
vars.sp[shifted_input_ids.clamp(min=0)],
inputs_embeds,
)
kwargs['inputs_embeds'] = inputs_embeds
return old_forward(self, *args, **kwargs)
cls.forward = new_causallm_forward
for cls in (GPT2LMHeadModel, GPTNeoForCausalLM):
patch_causallm(cls)
try:
from transformers import GPTJForCausalLM
patch_causallm(GPTJForCausalLM)
except:
pass
# Patch transformers to use our custom logit warpers
from transformers import LogitsProcessorList, LogitsWarper, LogitsProcessor, TopKLogitsWarper, TopPLogitsWarper, TemperatureLogitsWarper, RepetitionPenaltyLogitsProcessor
def dynamic_processor_wrap(cls, field_name, var_name, cond=None):
old_call = cls.__call__
def new_call(self, *args, **kwargs):
setattr(self, field_name, getattr(vars, var_name))
assert len(args) == 2
if(cond is None or cond(getattr(vars, var_name))):
return old_call(self, *args, **kwargs)
return args[1]
cls.__call__ = new_call
dynamic_processor_wrap(RepetitionPenaltyLogitsProcessor, "penalty", "rep_pen", cond=lambda x: x != 1.0)
dynamic_processor_wrap(TopKLogitsWarper, "top_k", "top_k", cond=lambda x: x > 0)
dynamic_processor_wrap(TopPLogitsWarper, "top_p", "top_p", cond=lambda x: x < 1.0)
dynamic_processor_wrap(TemperatureLogitsWarper, "temperature", "temp", cond=lambda x: x != 1.0)
class TailFreeLogitsWarper(LogitsWarper):
def __init__(self, tfs: float, filter_value: float = -float("Inf"), min_tokens_to_keep: int = 1):
tfs = float(tfs)
if tfs < 0 or tfs > 1.0:
raise ValueError(f"`tfs` has to be a float > 0 and < 1, but is {tfs}")
self.tfs = tfs
self.filter_value = filter_value
self.min_tokens_to_keep = min_tokens_to_keep
def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor) -> torch.FloatTensor:
self.tfs = vars.tfs
if self.filter_value >= 1.0:
return scores
sorted_logits, sorted_indices = torch.sort(scores, descending=True)
probs = sorted_logits.softmax(dim=-1)
# Compute second derivative normalized CDF
d2 = probs.diff().diff().abs()
normalized_d2 = d2 / d2.sum(dim=-1, keepdim=True)
normalized_d2_cdf = normalized_d2.cumsum(dim=-1)
# Remove tokens with CDF value above the threshold (token with 0 are kept)
sorted_indices_to_remove = normalized_d2_cdf > self.tfs
# Centre the distribution around the cutoff as in the original implementation of the algorithm
sorted_indices_to_remove = torch.cat(
(
torch.zeros(scores.shape[0], 1, dtype=torch.bool, device=scores.device),
sorted_indices_to_remove,
torch.ones(scores.shape[0], 1, dtype=torch.bool, device=scores.device),
),
dim=-1,
)
if self.min_tokens_to_keep > 1:
# Keep at least min_tokens_to_keep
sorted_indices_to_remove[..., : self.min_tokens_to_keep] = 0
indices_to_remove = sorted_indices_to_remove.scatter(1, sorted_indices, sorted_indices_to_remove)
scores = scores.masked_fill(indices_to_remove, self.filter_value)
return scores
class LuaLogitsProcessor(LogitsProcessor):
def __init__(self):
pass
def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor) -> torch.FloatTensor:
assert scores.ndim == 2
assert input_ids.ndim == 2
self.regeneration_required = False
self.halt = False
scores_shape = scores.shape
scores_list = scores.tolist()
vars.lua_koboldbridge.logits = vars.lua_state.table()
for r, row in enumerate(scores_list):
vars.lua_koboldbridge.logits[r+1] = vars.lua_state.table(*row)
vars.lua_koboldbridge.vocab_size = scores_shape[-1]
execute_genmod()
scores = torch.tensor(
tuple(tuple(row.values()) for row in vars.lua_koboldbridge.logits.values()),
device=scores.device,
dtype=scores.dtype,
)
assert scores.shape == scores_shape
return scores
def new_get_logits_processor(*args, **kwargs) -> LogitsProcessorList:
processors = new_get_logits_processor.old_get_logits_processor(*args, **kwargs)
processors.insert(0, LuaLogitsProcessor())
return processors
new_get_logits_processor.old_get_logits_processor = transformers.generation_utils.GenerationMixin._get_logits_processor
transformers.generation_utils.GenerationMixin._get_logits_processor = new_get_logits_processor
def new_get_logits_warper(beams: int = 1,) -> LogitsProcessorList:
warper_list = LogitsProcessorList()
warper_list.append(TopKLogitsWarper(top_k=1, min_tokens_to_keep=1 + (beams > 1)))
warper_list.append(TopPLogitsWarper(top_p=0.5, min_tokens_to_keep=1 + (beams > 1)))
warper_list.append(TailFreeLogitsWarper(tfs=0.5, min_tokens_to_keep=1 + (beams > 1)))
warper_list.append(TemperatureLogitsWarper(temperature=0.5))
return warper_list
def new_sample(self, *args, **kwargs):
assert kwargs.pop("logits_warper", None) is not None
kwargs["logits_warper"] = new_get_logits_warper(
beams=1,
)
return new_sample.old_sample(self, *args, **kwargs)
new_sample.old_sample = transformers.generation_utils.GenerationMixin.sample
transformers.generation_utils.GenerationMixin.sample = new_sample
# Allow bad words filter to ban <|endoftext|> token
import transformers.generation_logits_process
def new_init(self, bad_words_ids: List[List[int]], eos_token_id: int):
return new_init.old_init(self, bad_words_ids, -1)
new_init.old_init = transformers.generation_logits_process.NoBadWordsLogitsProcessor.__init__
transformers.generation_logits_process.NoBadWordsLogitsProcessor.__init__ = new_init
# Sets up dynamic world info scanner
class DynamicWorldInfoScanCriteria(StoppingCriteria):
def __init__(
self,
tokenizer,
excluded_world_info: List[Set],
head_length: int,
):
self.regeneration_required = False
self.halt = False
self.tokenizer = tokenizer
self.excluded_world_info = excluded_world_info
self.head_length = head_length
def __call__(
self,
input_ids: torch.LongTensor,
scores: torch.FloatTensor,
**kwargs,
) -> bool:
vars.generated_tkns += 1
if(vars.lua_koboldbridge.generated_cols and vars.generated_tkns != vars.lua_koboldbridge.generated_cols):
raise RuntimeError(f"Inconsistency detected between KoboldAI Python and Lua backends ({vars.generated_tkns} != {vars.lua_koboldbridge.generated_cols})")
if(vars.generated_tkns >= vars.genamt):
self.regeneration_required = False
self.halt = False
return True
assert input_ids.ndim == 2
assert len(self.excluded_world_info) == input_ids.shape[0]
self.regeneration_required = vars.lua_koboldbridge.regeneration_required
self.halt = not vars.lua_koboldbridge.generating
vars.lua_koboldbridge.regeneration_required = False
for i in range(vars.numseqs):
vars.lua_koboldbridge.generated[i+1][vars.generated_tkns] = int(input_ids[i, -1].item())
if(not vars.dynamicscan):
return self.regeneration_required or self.halt
tail = input_ids[..., self.head_length:]
for i, t in enumerate(tail):
decoded = tokenizer.decode(t)
_, found = checkworldinfo(decoded, force_use_txt=True)
found -= self.excluded_world_info[i]
if(len(found) != 0):
self.regeneration_required = True
break
return self.regeneration_required or self.halt
old_get_stopping_criteria = transformers.generation_utils.GenerationMixin._get_stopping_criteria
def new_get_stopping_criteria(self, *args, **kwargs):
stopping_criteria = old_get_stopping_criteria(self, *args, **kwargs)
global tokenizer
self.kai_scanner = DynamicWorldInfoScanCriteria(
tokenizer=tokenizer,
excluded_world_info=self.kai_scanner_excluded_world_info,
head_length=self.kai_scanner_head_length,
)
stopping_criteria.insert(0, self.kai_scanner)
return stopping_criteria
transformers.generation_utils.GenerationMixin._get_stopping_criteria = new_get_stopping_criteria
def get_hidden_size_from_model(model):
try:
return int(model.transformer.hidden_size)
except:
try:
return int(model.transformer.embed_dim)
except:
return int(model.lm_head.in_features)
def maybe_low_cpu_mem_usage() -> Dict[str, Any]:
if(packaging.version.parse(transformers_version) < packaging.version.parse("4.11.0")):
print(f"\nWARNING: Please upgrade to transformers 4.11.0 for lower RAM usage. You have transformers {transformers_version}.", file=sys.stderr)
return {}
return {"low_cpu_mem_usage": True}
@contextlib.contextmanager
def maybe_use_float16(always_use=False):
if(always_use or (vars.hascuda and (vars.usegpu or vars.breakmodel))):
original_dtype = torch.get_default_dtype()
torch.set_default_dtype(torch.float16)
yield True
torch.set_default_dtype(original_dtype)
else:
yield False
# If custom GPT2 model was chosen
if(vars.model == "GPT2Custom"):
model_config = open(vars.custmodpth + "/config.json", "r")
js = json.load(model_config)
with(maybe_use_float16()):
model = GPT2LMHeadModel.from_pretrained(vars.custmodpth, cache_dir="cache/")
tokenizer = GPT2TokenizerFast.from_pretrained(vars.custmodpth, cache_dir="cache/")
vars.modeldim = get_hidden_size_from_model(model)
# Is CUDA available? If so, use GPU, otherwise fall back to CPU
if(vars.hascuda and vars.usegpu):
model = model.half().to(vars.gpu_device)
generator = model.generate
else:
model = model.to('cpu').float()
generator = model.generate
# Use the Generic implementation
else:
lowmem = maybe_low_cpu_mem_usage()
# We must disable low_cpu_mem_usage (by setting lowmem to {}) if
# using a GPT-2 model because GPT-2 is not compatible with this
# feature yet
if("/" not in vars.model and vars.model.lower().startswith("gpt2")):
lowmem = {}
# Download model from Huggingface if it does not exist, otherwise load locally
if(os.path.isdir(vars.custmodpth)):
with(maybe_use_float16()):
try:
tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, cache_dir="cache/")
except ValueError as e:
tokenizer = GPT2TokenizerFast.from_pretrained(vars.custmodpth, cache_dir="cache/")
try:
model = AutoModelForCausalLM.from_pretrained(vars.custmodpth, cache_dir="cache/", **lowmem)
except ValueError as e:
model = GPTNeoForCausalLM.from_pretrained(vars.custmodpth, cache_dir="cache/", **lowmem)
elif(os.path.isdir(vars.model.replace('/', '_'))):
with(maybe_use_float16()):
try:
tokenizer = AutoTokenizer.from_pretrained(vars.model.replace('/', '_'), cache_dir="cache/")
except ValueError as e:
tokenizer = GPT2TokenizerFast.from_pretrained(vars.model.replace('/', '_'), cache_dir="cache/")
try:
model = AutoModelForCausalLM.from_pretrained(vars.model.replace('/', '_'), cache_dir="cache/", **lowmem)
except ValueError as e:
model = GPTNeoForCausalLM.from_pretrained(vars.model.replace('/', '_'), cache_dir="cache/", **lowmem)
else:
print("Model does not exist locally, attempting to download from Huggingface...")
try:
tokenizer = AutoTokenizer.from_pretrained(vars.model, cache_dir="cache/")
except ValueError as e:
tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, cache_dir="cache/")
with(maybe_use_float16()):
try:
model = AutoModelForCausalLM.from_pretrained(vars.model, cache_dir="cache/", **lowmem)
except ValueError as e:
model = GPTNeoForCausalLM.from_pretrained(vars.model, cache_dir="cache/", **lowmem)
model = model.half()
import shutil
shutil.rmtree("cache/")
model.save_pretrained(vars.model.replace('/', '_'))
tokenizer.save_pretrained(vars.model.replace('/', '_'))
if(vars.hascuda):
if(vars.usegpu):
vars.modeldim = get_hidden_size_from_model(model)
model = model.half().to(vars.gpu_device)
generator = model.generate
elif(vars.breakmodel): # Use both RAM and VRAM (breakmodel)
vars.modeldim = get_hidden_size_from_model(model)
device_config(model)
else:
model = model.to('cpu').float()
vars.modeldim = get_hidden_size_from_model(model)
generator = model.generate
else:
model.to('cpu').float()
vars.modeldim = get_hidden_size_from_model(model)
generator = model.generate
# Suppress Author's Note by flagging square brackets (Old implementation)
#vocab = tokenizer.get_vocab()
#vocab_keys = vocab.keys()
#vars.badwords = gettokenids("[")
#for key in vars.badwords:
# vars.badwordsids.append([vocab[key]])
print("{0}OK! {1} pipeline created!{2}".format(colors.GREEN, vars.model, colors.END))
else:
from transformers import GPT2TokenizerFast
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", cache_dir="cache/")
else:
def tpumtjgetsofttokens():
soft_tokens = None
if(vars.sp is None):
global np
if 'np' not in globals():
import numpy as np
tensor = np.zeros((1, tpu_mtj_backend.params["d_model"]), dtype=np.float32)
rows = tensor.shape[0]
padding_amount = tpu_mtj_backend.params["seq"] - (tpu_mtj_backend.params["seq"] % -tpu_mtj_backend.params["cores_per_replica"]) - rows
tensor = np.pad(tensor, ((0, padding_amount), (0, 0)))
tensor = tensor.reshape(
tpu_mtj_backend.params["cores_per_replica"],
-1,
tpu_mtj_backend.params["d_model"],
)
vars.sp = tpu_mtj_backend.shard_xmap(tensor)
soft_tokens = np.arange(
tpu_mtj_backend.params["n_vocab"] + tpu_mtj_backend.params["n_vocab_padding"],
tpu_mtj_backend.params["n_vocab"] + tpu_mtj_backend.params["n_vocab_padding"] + vars.sp_length,
dtype=np.uint32
)
return soft_tokens
def tpumtjgenerate_warper_callback(scores) -> "np.array":
scores_shape = scores.shape
scores_list = scores.tolist()
vars.lua_koboldbridge.logits = vars.lua_state.table()
for r, row in enumerate(scores_list):
vars.lua_koboldbridge.logits[r+1] = vars.lua_state.table(*row)
vars.lua_koboldbridge.vocab_size = scores_shape[-1]
execute_genmod()
scores = np.array(
tuple(tuple(row.values()) for row in vars.lua_koboldbridge.logits.values()),
dtype=scores.dtype,
)
assert scores.shape == scores_shape
return scores
def tpumtjgenerate_stopping_callback(generated, n_generated, excluded_world_info) -> Tuple[List[set], bool, bool]:
vars.generated_tkns += 1
assert len(excluded_world_info) == len(generated)
regeneration_required = vars.lua_koboldbridge.regeneration_required
halt = not vars.lua_koboldbridge.generating or vars.generated_tkns >= vars.genamt
vars.lua_koboldbridge.regeneration_required = False
global past
for i in range(vars.numseqs):
vars.lua_koboldbridge.generated[i+1][vars.generated_tkns] = int(generated[i, tpu_mtj_backend.params["seq"] + n_generated - 1].item())
if(not vars.dynamicscan or halt):
return excluded_world_info, regeneration_required, halt
for i, t in enumerate(generated):
decoded = tokenizer.decode(past[i]) + tokenizer.decode(t[tpu_mtj_backend.params["seq"] : tpu_mtj_backend.params["seq"] + n_generated])
_, found = checkworldinfo(decoded, force_use_txt=True)
found -= excluded_world_info[i]
if(len(found) != 0):
regeneration_required = True
break
return excluded_world_info, regeneration_required, halt
# If we're running Colab or OAI, we still need a tokenizer.
if(vars.model == "Colab"):
from transformers import GPT2TokenizerFast
tokenizer = GPT2TokenizerFast.from_pretrained("EleutherAI/gpt-neo-2.7B", cache_dir="cache/")
elif(vars.model == "OAI"):
from transformers import GPT2TokenizerFast
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", cache_dir="cache/")
# Load the TPU backend if requested
elif(vars.model == "TPUMeshTransformerGPTJ"):
print("{0}Initializing Mesh Transformer JAX, please wait...{1}".format(colors.PURPLE, colors.END))
assert vars.model == "TPUMeshTransformerGPTJ" and vars.custmodpth and os.path.isdir(vars.custmodpth)
import tpu_mtj_backend
tpu_mtj_backend.warper_callback = tpumtjgenerate_warper_callback
tpu_mtj_backend.stopping_callback = tpumtjgenerate_stopping_callback
tpu_mtj_backend.load_model(vars.custmodpth)
vars.allowsp = True
vars.modeldim = int(tpu_mtj_backend.params["d_model"])
tokenizer = tpu_mtj_backend.tokenizer
soft_tokens = tpumtjgetsofttokens()
threading.Thread( # Compile backend code in background
target=tpu_mtj_backend.infer,
args=(np.tile(np.uint32((23403, 727, 20185)), (vars.numseqs, 1)),),
kwargs={
"soft_embeddings": vars.sp,
"soft_tokens": soft_tokens,
"use_callback": False,
"gen_len": 1,
"numseqs": vars.numseqs,
"excluded_world_info": list(set() for _ in range(vars.numseqs)),
},
).start()
# Set up Flask routes
@app.route('/')
@app.route('/index')
def index():
return render_template('index.html')
@app.route('/download')
def download():
save_format = request.args.get("format", "json").strip().lower()
if(save_format == "plaintext"):
txt = vars.prompt + "".join(vars.actions.values())
save = Response(txt)
filename = path.basename(vars.savedir)
if filename[-5:] == ".json":
filename = filename[:-5]
save.headers.set('Content-Disposition', 'attachment', filename='%s.txt' % filename)
return(save)
# Build json to write
js = {}
js["gamestarted"] = vars.gamestarted
js["prompt"] = vars.prompt
js["memory"] = vars.memory
js["authorsnote"] = vars.authornote
js["anotetemplate"] = vars.authornotetemplate
js["actions"] = tuple(vars.actions.values())
js["worldinfo"] = []
# Extract only the important bits of WI
for wi in vars.worldinfo:
if(wi["constant"] or wi["key"] != ""):
js["worldinfo"].append({
"key": wi["key"],
"keysecondary": wi["keysecondary"],
"content": wi["content"],
"comment": wi["comment"],
"folder": wi["folder"],
"selective": wi["selective"],
"constant": wi["constant"]
})
save = Response(json.dumps(js, indent=3))
filename = path.basename(vars.savedir)
if filename[-5:] == ".json":
filename = filename[:-5]
save.headers.set('Content-Disposition', 'attachment', filename='%s.json' % filename)
return(save)
#============================ LUA API =============================#
if(path.exists("settings/" + getmodelname().replace('/', '_') + ".settings")):
file = open("settings/" + getmodelname().replace('/', '_') + ".settings", "r")
js = json.load(file)
if("userscripts" in js):
vars.userscripts = []
for userscript in js["userscripts"]:
if type(userscript) is not str:
continue
userscript = userscript.strip()
if len(userscript) != 0 and all(q not in userscript for q in ("..", ":")) and all(userscript[0] not in q for q in ("/", "\\")) and os.path.exists(fileops.uspath(userscript)):
vars.userscripts.append(userscript)
if("corescript" in js and type(js["corescript"]) is str and all(q not in js["corescript"] for q in ("..", ":")) and all(js["corescript"][0] not in q for q in ("/", "\\"))):
vars.corescript = js["corescript"]
else:
vars.corescript = "default.lua"
file.close()
def lua_log_format_name(name):
return f"[{name}]" if type(name) is str else "CORE"
_bridged = {}
F = TypeVar("F", bound=Callable)
def bridged_kwarg(name=None):
def _bridged_kwarg(f: F):
_bridged[name if name is not None else f.__name__[4:] if f.__name__[:4] == "lua_" else f.__name__] = f
return f
return _bridged_kwarg
#==================================================================#
# Event triggered when a userscript is loaded
#==================================================================#
@bridged_kwarg()
def load_callback(filename, modulename):
print(colors.GREEN + f"Loading Userscript [{modulename}] <{filename}>" + colors.END)
#==================================================================#
# Load all Lua scripts
#==================================================================#
def load_lua_scripts():
print(colors.GREEN + "Loading Core Script" + colors.END)
filenames = []
modulenames = []
descriptions = []
lst = fileops.getusfiles(long_desc=True)
filenames_dict = {ob["filename"]: i for i, ob in enumerate(lst)}
for filename in vars.userscripts:
if filename in filenames_dict:
i = filenames_dict[filename]
filenames.append(filename)
modulenames.append(lst[i]["modulename"])
descriptions.append(lst[i]["description"])
try:
vars.lua_koboldbridge.obliterate_multiverse()
tpool.execute(vars.lua_koboldbridge.load_corescript, vars.corescript)
tpool.execute(vars.lua_koboldbridge.load_userscripts, filenames, modulenames, descriptions)
vars.lua_running = True
except lupa.LuaError as e:
vars.lua_koboldbridge.obliterate_multiverse()
vars.lua_running = False
if(vars.serverstarted):
emit('from_server', {'cmd': 'errmsg', 'data': 'Lua script error, please check console.'}, broadcast=True)
sendUSStatItems()
print("{0}{1}{2}".format(colors.RED, "***LUA ERROR***: ", colors.END), end="", file=sys.stderr)
print("{0}{1}{2}".format(colors.RED, str(e).replace("\033", ""), colors.END), file=sys.stderr)
print("{0}{1}{2}".format(colors.YELLOW, "Lua engine stopped; please open 'Userscripts' and press Load to reinitialize scripts.", colors.END), file=sys.stderr)
if(vars.serverstarted):
set_aibusy(0)
#==================================================================#
# Print message that originates from the userscript with the given name
#==================================================================#
@bridged_kwarg()
def lua_print(msg):
if(vars.lua_logname != vars.lua_koboldbridge.logging_name):
vars.lua_logname = vars.lua_koboldbridge.logging_name
print(colors.BLUE + lua_log_format_name(vars.lua_logname) + ":" + colors.END, file=sys.stderr)
print(colors.PURPLE + msg.replace("\033", "") + colors.END)
#==================================================================#
# Print warning that originates from the userscript with the given name
#==================================================================#
@bridged_kwarg()
def lua_warn(msg):
if(vars.lua_logname != vars.lua_koboldbridge.logging_name):
vars.lua_logname = vars.lua_koboldbridge.logging_name
print(colors.BLUE + lua_log_format_name(vars.lua_logname) + ":" + colors.END, file=sys.stderr)
print(colors.YELLOW + msg.replace("\033", "") + colors.END)
#==================================================================#
# Decode tokens into a string using current tokenizer
#==================================================================#
@bridged_kwarg()
def lua_decode(tokens):
tokens = list(tokens.values())
assert type(tokens) is list
if("tokenizer" not in globals()):
from transformers import GPT2TokenizerFast
global tokenizer
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", cache_dir="cache/")
return tokenizer.decode(tokens)
#==================================================================#
# Encode string into list of token IDs using current tokenizer
#==================================================================#
@bridged_kwarg()
def lua_encode(string):
assert type(string) is str
if("tokenizer" not in globals()):
from transformers import GPT2TokenizerFast
global tokenizer
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", cache_dir="cache/")
return tokenizer.encode(string, max_length=int(4e9), truncation=True)
#==================================================================#
# Computes context given a submission, Lua array of entry UIDs and a Lua array
# of folder UIDs
#==================================================================#
@bridged_kwarg()
def lua_compute_context(submission, entries, folders, kwargs):
assert type(submission) is str
if(kwargs is None):
kwargs = vars.lua_state.table()
actions = vars._actions if vars.lua_koboldbridge.userstate == "genmod" else vars.actions
allowed_entries = None
allowed_folders = None
if(entries is not None):
allowed_entries = set()
i = 1
while(entries[i] is not None):
allowed_entries.add(int(entries[i]))
i += 1
if(folders is not None):
allowed_folders = set()
i = 1
while(folders[i] is not None):
allowed_folders.add(int(folders[i]))
i += 1
winfo, mem, anotetxt, _ = calcsubmitbudgetheader(
submission,
allowed_entries=allowed_entries,
allowed_folders=allowed_folders,
force_use_txt=True,
scan_story=kwargs["scan_story"] if kwargs["scan_story"] != None else True,
)
txt, _, _ = calcsubmitbudget(
len(actions),
winfo,
mem,
anotetxt,
actions,
)
return tokenizer.decode(txt)
#==================================================================#
# Get property of a world info entry given its UID and property name
#==================================================================#
@bridged_kwarg()
def lua_get_attr(uid, k):
assert type(uid) is int and type(k) is str
if(uid in vars.worldinfo_u and k in (
"key",
"keysecondary",
"content",
"comment",
"folder",
"num",
"selective",
"constant",
"uid",
)):
return vars.worldinfo_u[uid][k]
#==================================================================#
# Set property of a world info entry given its UID, property name and new value
#==================================================================#
@bridged_kwarg()
def lua_set_attr(uid, k, v):
assert type(uid) is int and type(k) is str
assert uid in vars.worldinfo_u and k in (
"key",
"keysecondary",
"content",
"comment",
"selective",
"constant",
)
if(type(vars.worldinfo_u[uid][k]) is int and type(v) is float):
v = int(v)
assert type(vars.worldinfo_u[uid][k]) is type(v)
vars.worldinfo_u[uid][k] = v
print(colors.GREEN + f"{lua_log_format_name(vars.lua_koboldbridge.logging_name)} set {k} of world info entry {uid} to {v}" + colors.END)
#==================================================================#
# Get property of a world info folder given its UID and property name
#==================================================================#
@bridged_kwarg()
def lua_folder_get_attr(uid, k):
assert type(uid) is int and type(k) is str
if(uid in vars.wifolders_d and k in (
"name",
)):
return vars.wifolders_d[uid][k]
#==================================================================#
# Set property of a world info folder given its UID, property name and new value
#==================================================================#
@bridged_kwarg()
def lua_folder_set_attr(uid, k, v):
assert type(uid) is int and type(k) is str
assert uid in vars.wifolders_d and k in (
"name",
)
if(type(vars.wifolders_d[uid][k]) is int and type(v) is float):
v = int(v)
assert type(vars.wifolders_d[uid][k]) is type(v)
vars.wifolders_d[uid][k] = v
print(colors.GREEN + f"{lua_log_format_name(vars.lua_koboldbridge.logging_name)} set {k} of world info folder {uid} to {v}" + colors.END)
#==================================================================#
# Get the "Amount to Generate"
#==================================================================#
@bridged_kwarg()
def lua_get_genamt():
return vars.genamt
#==================================================================#
# Set the "Amount to Generate"
#==================================================================#
@bridged_kwarg()
def lua_set_genamt(genamt):
assert vars.lua_koboldbridge.userstate != "genmod" and type(genamt) in (int, float) and genamt >= 0
print(colors.GREEN + f"{lua_log_format_name(vars.lua_koboldbridge.logging_name)} set genamt to {int(genamt)}" + colors.END)
vars.genamt = int(genamt)
#==================================================================#
# Get the "Gens Per Action"
#==================================================================#
@bridged_kwarg()
def lua_get_numseqs():
return vars.numseqs
#==================================================================#
# Set the "Gens Per Action"
#==================================================================#
@bridged_kwarg()
def lua_set_numseqs(numseqs):
assert type(numseqs) in (int, float) and numseqs >= 1
print(colors.GREEN + f"{lua_log_format_name(vars.lua_koboldbridge.logging_name)} set numseqs to {int(numseqs)}" + colors.END)
vars.numseqs = int(numseqs)
#==================================================================#
# Check if a setting exists with the given name
#==================================================================#
@bridged_kwarg()
def lua_has_setting(setting):
return setting in (
"anotedepth",
"settemp",
"settopp",
"settopk",
"settfs",
"setreppen",
"settknmax",
"setwidepth",
"setuseprompt",
"setadventure",
"setchatmode",
"setdynamicscan",
"setnopromptgen",
"setrngpersist",
"temp",
"topp",
"top_p",
"topk",
"top_k",
"tfs",
"reppen",
"tknmax",
"widepth",
"useprompt",
"chatmode",
"chatname",
"adventure",
"dynamicscan",
"nopromptgen",
"rngpersist",
"frmttriminc",
"frmtrmblln",
"frmtrmspch",
"frmtadsnsp",
"frmtsingleline",
"triminc",
"rmblln",
"rmspch",
"adsnsp",
"singleline",
)
#==================================================================#
# Return the setting with the given name if it exists
#==================================================================#
@bridged_kwarg()
def lua_get_setting(setting):
if(setting in ("settemp", "temp")): return vars.temp
if(setting in ("settopp", "topp", "top_p")): return vars.top_p
if(setting in ("settopk", "topk", "top_k")): return vars.top_k
if(setting in ("settfs", "tfs")): return vars.tfs
if(setting in ("setreppen", "reppen")): return vars.rep_pen
if(setting in ("settknmax", "tknmax")): return vars.max_length
if(setting == "anotedepth"): return vars.andepth
if(setting in ("setwidepth", "widepth")): return vars.widepth
if(setting in ("setuseprompt", "useprompt")): return vars.useprompt
if(setting in ("setadventure", "adventure")): return vars.adventure
if(setting in ("setchatmode", "chatmode")): return vars.chatmode
if(setting in ("setdynamicscan", "dynamicscan")): return vars.dynamicscan
if(setting in ("setnopromptgen", "nopromptgen")): return vars.nopromptgen
if(setting in ("setrngpersist", "rngpersist")): return vars.rngpersist
if(setting in ("frmttriminc", "triminc")): return vars.formatoptns["frmttriminc"]
if(setting in ("frmtrmblln", "rmblln")): return vars.formatoptns["frmttrmblln"]
if(setting in ("frmtrmspch", "rmspch")): return vars.formatoptns["frmttrmspch"]
if(setting in ("frmtadsnsp", "adsnsp")): return vars.formatoptns["frmtadsnsp"]
if(setting in ("frmtsingleline", "singleline")): return vars.formatoptns["singleline"]
#==================================================================#
# Set the setting with the given name if it exists
#==================================================================#
@bridged_kwarg()
def lua_set_setting(setting, v):
actual_type = type(lua_get_setting(setting))
assert v is not None and (actual_type is type(v) or (actual_type is int and type(v) is float))
v = actual_type(v)
print(colors.GREEN + f"{lua_log_format_name(vars.lua_koboldbridge.logging_name)} set {setting} to {v}" + colors.END)
if(setting in ("setadventure", "adventure") and v):
vars.actionmode = 1
if(setting in ("settemp", "temp")): vars.temp = v
if(setting in ("settopp", "topp")): vars.top_p = v
if(setting in ("settopk", "topk")): vars.top_k = v
if(setting in ("settfs", "tfs")): vars.tfs = v
if(setting in ("setreppen", "reppen")): vars.rep_pen = v
if(setting in ("settknmax", "tknmax")): vars.max_length = v; return True
if(setting == "anotedepth"): vars.andepth = v; return True
if(setting in ("setwidepth", "widepth")): vars.widepth = v; return True
if(setting in ("setuseprompt", "useprompt")): vars.useprompt = v; return True
if(setting in ("setadventure", "adventure")): vars.adventure = v
if(setting in ("setdynamicscan", "dynamicscan")): vars.dynamicscan = v
if(setting in ("setnopromptgen", "nopromptgen")): vars.nopromptgen = v
if(setting in ("setrngpersist", "rngpersist")): vars.rngpersist = v
if(setting in ("setchatmode", "chatmode")): vars.chatmode = v
if(setting in ("frmttriminc", "triminc")): vars.formatoptns["frmttriminc"] = v
if(setting in ("frmtrmblln", "rmblln")): vars.formatoptns["frmttrmblln"] = v
if(setting in ("frmtrmspch", "rmspch")): vars.formatoptns["frmttrmspch"] = v
if(setting in ("frmtadsnsp", "adsnsp")): vars.formatoptns["frmtadsnsp"] = v
if(setting in ("frmtsingleline", "singleline")): vars.formatoptns["singleline"] = v
#==================================================================#
# Get contents of memory
#==================================================================#
@bridged_kwarg()
def lua_get_memory():
return vars.memory
#==================================================================#
# Set contents of memory
#==================================================================#
@bridged_kwarg()
def lua_set_memory(m):
assert type(m) is str
vars.memory = m
#==================================================================#
# Get contents of author's note
#==================================================================#
@bridged_kwarg()
def lua_get_authorsnote():
return vars.authornote
#==================================================================#
# Set contents of author's note
#==================================================================#
@bridged_kwarg()
def lua_set_authorsnote(m):
assert type(m) is str
vars.authornote = m
#==================================================================#
# Get contents of author's note template
#==================================================================#
@bridged_kwarg()
def lua_get_authorsnotetemplate():
return vars.authornotetemplate
#==================================================================#
# Set contents of author's note template
#==================================================================#
@bridged_kwarg()
def lua_set_authorsnotetemplate(m):
assert type(m) is str
vars.authornotetemplate = m
#==================================================================#
# Save settings and send them to client
#==================================================================#
@bridged_kwarg()
def lua_resend_settings():
settingschanged()
refresh_settings()
#==================================================================#
# Set story chunk text and delete the chunk if the new chunk is empty
#==================================================================#
@bridged_kwarg()
def lua_set_chunk(k, v):
assert type(k) in (int, None) and type(v) is str
assert k >= 0
assert k != 0 or len(v) != 0
if(len(v) == 0):
print(colors.GREEN + f"{lua_log_format_name(vars.lua_koboldbridge.logging_name)} deleted story chunk {k}" + colors.END)
chunk = int(k)
if(vars.lua_koboldbridge.userstate == "genmod"):
del vars._actions[chunk-1]
vars.lua_deleted.add(chunk)
if(not hasattr(vars, "_actions") or vars._actions is not vars.actions):
del vars.actions[chunk-1]
else:
if(k == 0):
print(colors.GREEN + f"{lua_log_format_name(vars.lua_koboldbridge.logging_name)} edited prompt chunk" + colors.END)
else:
print(colors.GREEN + f"{lua_log_format_name(vars.lua_koboldbridge.logging_name)} edited story chunk {k}" + colors.END)
chunk = int(k)
if(chunk == 0):
if(vars.lua_koboldbridge.userstate == "genmod"):
vars._prompt = v
vars.lua_edited.add(chunk)
vars.prompt = v
else:
if(vars.lua_koboldbridge.userstate == "genmod"):
vars._actions[chunk-1] = v
vars.lua_edited.add(chunk)
vars.actions[chunk-1] = v
#==================================================================#
# Get model type as "gpt-2-xl", "gpt-neo-2.7B", etc.
#==================================================================#
@bridged_kwarg()
def lua_get_modeltype():
if(vars.noai):
return "readonly"
if(vars.model in ("Colab", "OAI", "InferKit")):
return "api"
if(vars.model not in ("TPUMeshTransformerGPTJ",) and (vars.model in ("GPT2Custom", "NeoCustom") or vars.model_type in ("gpt2", "gpt_neo", "gptj"))):
hidden_size = get_hidden_size_from_model(model)
if(vars.model in ("gpt2",) or (vars.model_type == "gpt2" and hidden_size == 768)):
return "gpt2"
if(vars.model in ("gpt2-medium",) or (vars.model_type == "gpt2" and hidden_size == 1024)):
return "gpt2-medium"
if(vars.model in ("gpt2-large",) or (vars.model_type == "gpt2" and hidden_size == 1280)):
return "gpt2-large"
if(vars.model in ("gpt2-xl",) or (vars.model_type == "gpt2" and hidden_size == 1600)):
return "gpt2-xl"
if(vars.model_type == "gpt_neo" and hidden_size == 768):
return "gpt-neo-125M"
if(vars.model in ("EleutherAI/gpt-neo-1.3B",) or (vars.model_type == "gpt_neo" and hidden_size == 2048)):
return "gpt-neo-1.3B"
if(vars.model in ("EleutherAI/gpt-neo-2.7B",) or (vars.model_type == "gpt_neo" and hidden_size == 2560)):
return "gpt-neo-2.7B"
if(vars.model in ("EleutherAI/gpt-j-6B",) or (vars.model == "TPUMeshTransformerGPTJ" and tpu_mtj_backend.params["d_model"] == 4096) or (vars.model_type in ("gpt_neo", "gptj") and hidden_size == 4096)):
return "gpt-j-6B"
return "unknown"
#==================================================================#
# Get model backend as "transformers" or "mtj"
#==================================================================#
@bridged_kwarg()
def lua_get_modelbackend():
if(vars.noai):
return "readonly"
if(vars.model in ("Colab", "OAI", "InferKit")):
return "api"
if(vars.model in ("TPUMeshTransformerGPTJ",)):
return "mtj"
return "transformers"
#==================================================================#
# Check whether model is loaded from a custom path
#==================================================================#
@bridged_kwarg()
def lua_is_custommodel():
return vars.model in ("GPT2Custom", "NeoCustom", "TPUMeshTransformerGPTJ")
#==================================================================#
#
#==================================================================#
def execute_inmod():
vars.lua_logname = ...
vars.lua_edited = set()
vars.lua_deleted = set()
try:
tpool.execute(vars.lua_koboldbridge.execute_inmod)
except lupa.LuaError as e:
vars.lua_koboldbridge.obliterate_multiverse()
vars.lua_running = False
emit('from_server', {'cmd': 'errmsg', 'data': 'Lua script error, please check console.'}, broadcast=True)
sendUSStatItems()
print("{0}{1}{2}".format(colors.RED, "***LUA ERROR***: ", colors.END), end="", file=sys.stderr)
print("{0}{1}{2}".format(colors.RED, str(e).replace("\033", ""), colors.END), file=sys.stderr)
print("{0}{1}{2}".format(colors.YELLOW, "Lua engine stopped; please open 'Userscripts' and press Load to reinitialize scripts.", colors.END), file=sys.stderr)
set_aibusy(0)
def execute_genmod():
vars.lua_koboldbridge.execute_genmod()
def execute_outmod():
try:
tpool.execute(vars.lua_koboldbridge.execute_outmod)
except lupa.LuaError as e:
vars.lua_koboldbridge.obliterate_multiverse()
vars.lua_running = False
emit('from_server', {'cmd': 'errmsg', 'data': 'Lua script error, please check console.'}, broadcast=True)
sendUSStatItems()
print("{0}{1}{2}".format(colors.RED, "***LUA ERROR***: ", colors.END), end="", file=sys.stderr)
print("{0}{1}{2}".format(colors.RED, str(e).replace("\033", ""), colors.END), file=sys.stderr)
print("{0}{1}{2}".format(colors.YELLOW, "Lua engine stopped; please open 'Userscripts' and press Load to reinitialize scripts.", colors.END), file=sys.stderr)
set_aibusy(0)
if(vars.lua_koboldbridge.resend_settings_required):
vars.lua_koboldbridge.resend_settings_required = False
lua_resend_settings()
for k in vars.lua_edited:
inlineedit(k, vars.actions[k])
for k in vars.lua_deleted:
inlinedelete(k)
#==================================================================#
# Lua runtime startup
#==================================================================#
print("", end="", flush=True)
print(colors.PURPLE + "Initializing Lua Bridge... " + colors.END, end="", flush=True)
# Set up Lua state
vars.lua_state = lupa.LuaRuntime(unpack_returned_tuples=True)
# Load bridge.lua
bridged = {
"corescript_path": os.path.join(os.path.dirname(os.path.realpath(__file__)), "cores"),
"userscript_path": os.path.join(os.path.dirname(os.path.realpath(__file__)), "userscripts"),
"config_path": os.path.join(os.path.dirname(os.path.realpath(__file__)), "userscripts"),
"lib_paths": vars.lua_state.table(os.path.join(os.path.dirname(os.path.realpath(__file__)), "lualibs"), os.path.join(os.path.dirname(os.path.realpath(__file__)), "extern", "lualibs")),
"vars": vars,
}
for kwarg in _bridged:
bridged[kwarg] = _bridged[kwarg]
try:
vars.lua_kobold, vars.lua_koboldcore, vars.lua_koboldbridge = vars.lua_state.globals().dofile(os.path.join(os.path.dirname(os.path.realpath(__file__)), "bridge.lua"))(
vars.lua_state.globals().python,
bridged,
)
except lupa.LuaError as e:
print(colors.RED + "ERROR!" + colors.END)
vars.lua_koboldbridge.obliterate_multiverse()
print("{0}{1}{2}".format(colors.RED, "***LUA ERROR***: ", colors.END), end="", file=sys.stderr)
print("{0}{1}{2}".format(colors.RED, str(e).replace("\033", ""), colors.END), file=sys.stderr)
exit(1)
print(colors.GREEN + "OK!" + colors.END)
# Load scripts
load_lua_scripts()
#============================ METHODS =============================#
#==================================================================#
# Event triggered when browser SocketIO is loaded and connects to server
#==================================================================#
@socketio.on('connect')
def do_connect():
print("{0}Client connected!{1}".format(colors.GREEN, colors.END))
emit('from_server', {'cmd': 'setchatname', 'data': vars.chatname})
emit('from_server', {'cmd': 'setanotetemplate', 'data': vars.authornotetemplate})
emit('from_server', {'cmd': 'connected', 'smandelete': vars.smandelete, 'smanrename': vars.smanrename})
if(vars.remote):
emit('from_server', {'cmd': 'runs_remotely'})
if(vars.allowsp):
emit('from_server', {'cmd': 'allowsp', 'data': vars.allowsp})
sendUSStatItems()
emit('from_server', {'cmd': 'spstatitems', 'data': {vars.spfilename: vars.spmeta} if vars.allowsp and len(vars.spfilename) else {}}, broadcast=True)
if(not vars.gamestarted):
setStartState()
sendsettings()
refresh_settings()
vars.laststory = None
emit('from_server', {'cmd': 'setstoryname', 'data': vars.laststory})
sendwi()
emit('from_server', {'cmd': 'setmemory', 'data': vars.memory})
emit('from_server', {'cmd': 'setanote', 'data': vars.authornote})
vars.mode = "play"
else:
# Game in session, send current game data and ready state to browser
refresh_story()
sendsettings()
refresh_settings()
emit('from_server', {'cmd': 'setstoryname', 'data': vars.laststory})
sendwi()
emit('from_server', {'cmd': 'setmemory', 'data': vars.memory})
emit('from_server', {'cmd': 'setanote', 'data': vars.authornote})
if(vars.mode == "play"):
if(not vars.aibusy):
emit('from_server', {'cmd': 'setgamestate', 'data': 'ready'})
else:
emit('from_server', {'cmd': 'setgamestate', 'data': 'wait'})
elif(vars.mode == "edit"):
emit('from_server', {'cmd': 'editmode', 'data': 'true'})
elif(vars.mode == "memory"):
emit('from_server', {'cmd': 'memmode', 'data': 'true'})
elif(vars.mode == "wi"):
emit('from_server', {'cmd': 'wimode', 'data': 'true'})
#==================================================================#
# Event triggered when browser SocketIO sends data to the server
#==================================================================#
@socketio.on('message')
def get_message(msg):
print("{0}Data received:{1}{2}".format(colors.GREEN, msg, colors.END))
# Submit action
if(msg['cmd'] == 'submit'):
if(vars.mode == "play"):
vars.lua_koboldbridge.feedback = None
if(vars.chatmode):
if(type(msg['chatname']) is not str):
raise ValueError("Chatname must be a string")
vars.chatname = msg['chatname']
settingschanged()
emit('from_server', {'cmd': 'setchatname', 'data': vars.chatname})
vars.recentrng = vars.recentrngm = None
actionsubmit(msg['data'], actionmode=msg['actionmode'])
elif(vars.mode == "edit"):
editsubmit(msg['data'])
elif(vars.mode == "memory"):
memsubmit(msg['data'])
# Retry Action
elif(msg['cmd'] == 'retry'):
if(vars.chatmode):
if(type(msg['chatname']) is not str):
raise ValueError("Chatname must be a string")
vars.chatname = msg['chatname']
settingschanged()
emit('from_server', {'cmd': 'setchatname', 'data': vars.chatname})
actionretry(msg['data'])
# Back/Undo Action
elif(msg['cmd'] == 'back'):
actionback()
# EditMode Action (old)
elif(msg['cmd'] == 'edit'):
if(vars.mode == "play"):
vars.mode = "edit"
emit('from_server', {'cmd': 'editmode', 'data': 'true'}, broadcast=True)
elif(vars.mode == "edit"):
vars.mode = "play"
emit('from_server', {'cmd': 'editmode', 'data': 'false'}, broadcast=True)
# EditLine Action (old)
elif(msg['cmd'] == 'editline'):
editrequest(int(msg['data']))
# Inline edit
elif(msg['cmd'] == 'inlineedit'):
inlineedit(msg['chunk'], msg['data'])
elif(msg['cmd'] == 'inlinedelete'):
inlinedelete(msg['data'])
# DeleteLine Action (old)
elif(msg['cmd'] == 'delete'):
deleterequest()
elif(msg['cmd'] == 'memory'):
togglememorymode()
elif(not vars.remote and msg['cmd'] == 'savetofile'):
savetofile()
elif(not vars.remote and msg['cmd'] == 'loadfromfile'):
loadfromfile()
elif(msg['cmd'] == 'loadfromstring'):
loadRequest(json.loads(msg['data']), filename=msg['filename'])
elif(not vars.remote and msg['cmd'] == 'import'):
importRequest()
elif(msg['cmd'] == 'newgame'):
newGameRequest()
elif(msg['cmd'] == 'rndgame'):
randomGameRequest(msg['data'], memory=msg['memory'])
elif(msg['cmd'] == 'settemp'):
vars.temp = float(msg['data'])
emit('from_server', {'cmd': 'setlabeltemp', 'data': msg['data']}, broadcast=True)
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'settopp'):
vars.top_p = float(msg['data'])
emit('from_server', {'cmd': 'setlabeltopp', 'data': msg['data']}, broadcast=True)
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'settopk'):
vars.top_k = int(msg['data'])
emit('from_server', {'cmd': 'setlabeltopk', 'data': msg['data']}, broadcast=True)
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'settfs'):
vars.tfs = float(msg['data'])
emit('from_server', {'cmd': 'setlabeltfs', 'data': msg['data']}, broadcast=True)
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'setreppen'):
vars.rep_pen = float(msg['data'])
emit('from_server', {'cmd': 'setlabelreppen', 'data': msg['data']}, broadcast=True)
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'setoutput'):
vars.genamt = int(msg['data'])
emit('from_server', {'cmd': 'setlabeloutput', 'data': msg['data']}, broadcast=True)
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'settknmax'):
vars.max_length = int(msg['data'])
emit('from_server', {'cmd': 'setlabeltknmax', 'data': msg['data']}, broadcast=True)
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'setikgen'):
vars.ikgen = int(msg['data'])
emit('from_server', {'cmd': 'setlabelikgen', 'data': msg['data']}, broadcast=True)
settingschanged()
refresh_settings()
# Author's Note field update
elif(msg['cmd'] == 'anote'):
anotesubmit(msg['data'], template=msg['template'])
# Author's Note depth update
elif(msg['cmd'] == 'anotedepth'):
vars.andepth = int(msg['data'])
emit('from_server', {'cmd': 'setlabelanotedepth', 'data': msg['data']}, broadcast=True)
settingschanged()
refresh_settings()
# Format - Trim incomplete sentences
elif(msg['cmd'] == 'frmttriminc'):
if('frmttriminc' in vars.formatoptns):
vars.formatoptns["frmttriminc"] = msg['data']
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'frmtrmblln'):
if('frmtrmblln' in vars.formatoptns):
vars.formatoptns["frmtrmblln"] = msg['data']
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'frmtrmspch'):
if('frmtrmspch' in vars.formatoptns):
vars.formatoptns["frmtrmspch"] = msg['data']
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'frmtadsnsp'):
if('frmtadsnsp' in vars.formatoptns):
vars.formatoptns["frmtadsnsp"] = msg['data']
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'singleline'):
if('singleline' in vars.formatoptns):
vars.formatoptns["singleline"] = msg['data']
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'importselect'):
vars.importnum = int(msg["data"].replace("import", ""))
elif(msg['cmd'] == 'importcancel'):
emit('from_server', {'cmd': 'popupshow', 'data': False})
vars.importjs = {}
elif(msg['cmd'] == 'importaccept'):
emit('from_server', {'cmd': 'popupshow', 'data': False})
importgame()
elif(msg['cmd'] == 'wi'):
togglewimode()
elif(msg['cmd'] == 'wiinit'):
if(int(msg['data']) < len(vars.worldinfo)):
vars.worldinfo[msg['data']]["init"] = True
addwiitem(folder_uid=msg['folder'])
elif(msg['cmd'] == 'wifolderinit'):
addwifolder()
elif(msg['cmd'] == 'wimoveitem'):
movewiitem(msg['destination'], msg['data'])
elif(msg['cmd'] == 'wimovefolder'):
movewifolder(msg['destination'], msg['data'])
elif(msg['cmd'] == 'widelete'):
deletewi(msg['data'])
elif(msg['cmd'] == 'wifolderdelete'):
deletewifolder(msg['data'])
elif(msg['cmd'] == 'wiexpand'):
assert 0 <= int(msg['data']) < len(vars.worldinfo)
emit('from_server', {'cmd': 'wiexpand', 'data': msg['data']}, broadcast=True)
elif(msg['cmd'] == 'wiexpandfolder'):
assert 0 <= int(msg['data']) < len(vars.worldinfo)
emit('from_server', {'cmd': 'wiexpandfolder', 'data': msg['data']}, broadcast=True)
elif(msg['cmd'] == 'wifoldercollapsecontent'):
vars.wifolders_d[msg['data']]['collapsed'] = True
emit('from_server', {'cmd': 'wifoldercollapsecontent', 'data': msg['data']}, broadcast=True)
elif(msg['cmd'] == 'wifolderexpandcontent'):
vars.wifolders_d[msg['data']]['collapsed'] = False
emit('from_server', {'cmd': 'wifolderexpandcontent', 'data': msg['data']}, broadcast=True)
elif(msg['cmd'] == 'wiupdate'):
num = int(msg['num'])
fields = ("key", "keysecondary", "content", "comment")
for field in fields:
if(field in msg['data'] and type(msg['data'][field]) is str):
vars.worldinfo[num][field] = msg['data'][field]
emit('from_server', {'cmd': 'wiupdate', 'num': msg['num'], 'data': {field: vars.worldinfo[num][field] for field in fields}}, broadcast=True)
elif(msg['cmd'] == 'wifolderupdate'):
uid = int(msg['uid'])
fields = ("name", "collapsed")
for field in fields:
if(field in msg['data'] and type(msg['data'][field]) is (str if field != "collapsed" else bool)):
vars.wifolders_d[uid][field] = msg['data'][field]
emit('from_server', {'cmd': 'wifolderupdate', 'uid': msg['uid'], 'data': {field: vars.wifolders_d[uid][field] for field in fields}}, broadcast=True)
elif(msg['cmd'] == 'wiselon'):
vars.worldinfo[msg['data']]["selective"] = True
emit('from_server', {'cmd': 'wiselon', 'data': msg['data']}, broadcast=True)
elif(msg['cmd'] == 'wiseloff'):
vars.worldinfo[msg['data']]["selective"] = False
emit('from_server', {'cmd': 'wiseloff', 'data': msg['data']}, broadcast=True)
elif(msg['cmd'] == 'wiconstanton'):
vars.worldinfo[msg['data']]["constant"] = True
emit('from_server', {'cmd': 'wiconstanton', 'data': msg['data']}, broadcast=True)
elif(msg['cmd'] == 'wiconstantoff'):
vars.worldinfo[msg['data']]["constant"] = False
emit('from_server', {'cmd': 'wiconstantoff', 'data': msg['data']}, broadcast=True)
elif(msg['cmd'] == 'sendwilist'):
commitwi(msg['data'])
elif(msg['cmd'] == 'aidgimport'):
importAidgRequest(msg['data'])
elif(msg['cmd'] == 'saveasrequest'):
saveas(msg['data'])
elif(msg['cmd'] == 'saverequest'):
save()
elif(msg['cmd'] == 'loadlistrequest'):
getloadlist()
elif(msg['cmd'] == 'splistrequest'):
getsplist()
elif(msg['cmd'] == 'uslistrequest'):
unloaded, loaded = getuslist()
emit('from_server', {'cmd': 'buildus', 'data': {"unloaded": unloaded, "loaded": loaded}})
elif(msg['cmd'] == 'usloaded'):
vars.userscripts = []
for userscript in msg['data']:
if type(userscript) is not str:
continue
userscript = userscript.strip()
if len(userscript) != 0 and all(q not in userscript for q in ("..", ":")) and all(userscript[0] not in q for q in ("/", "\\")) and os.path.exists(fileops.uspath(userscript)):
vars.userscripts.append(userscript)
settingschanged()
elif(msg['cmd'] == 'usload'):
load_lua_scripts()
unloaded, loaded = getuslist()
sendUSStatItems()
elif(msg['cmd'] == 'loadselect'):
vars.loadselect = msg["data"]
elif(msg['cmd'] == 'spselect'):
vars.spselect = msg["data"]
elif(msg['cmd'] == 'loadrequest'):
loadRequest(fileops.storypath(vars.loadselect))
elif(msg['cmd'] == 'sprequest'):
spRequest(vars.spselect)
emit('from_server', {'cmd': 'spstatitems', 'data': {vars.spfilename: vars.spmeta} if vars.allowsp and len(vars.spfilename) else {}}, broadcast=True)
elif(msg['cmd'] == 'deletestory'):
deletesave(msg['data'])
elif(msg['cmd'] == 'renamestory'):
renamesave(msg['data'], msg['newname'])
elif(msg['cmd'] == 'clearoverwrite'):
vars.svowname = ""
vars.saveow = False
elif(msg['cmd'] == 'seqsel'):
selectsequence(msg['data'])
elif(msg['cmd'] == 'setnumseq'):
vars.numseqs = int(msg['data'])
emit('from_server', {'cmd': 'setlabelnumseq', 'data': msg['data']})
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'setwidepth'):
vars.widepth = int(msg['data'])
emit('from_server', {'cmd': 'setlabelwidepth', 'data': msg['data']})
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'setuseprompt'):
vars.useprompt = msg['data']
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'setadventure'):
vars.adventure = msg['data']
vars.chatmode = False
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'setchatmode'):
vars.chatmode = msg['data']
vars.adventure = False
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'setdynamicscan'):
vars.dynamicscan = msg['data']
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'setnopromptgen'):
vars.nopromptgen = msg['data']
settingschanged()
refresh_settings()
elif(msg['cmd'] == 'setrngpersist'):
vars.rngpersist = msg['data']
settingschanged()
refresh_settings()
elif(not vars.remote and msg['cmd'] == 'importwi'):
wiimportrequest()
#==================================================================#
# Send userscripts list to client
#==================================================================#
def sendUSStatItems():
_, loaded = getuslist()
loaded = loaded if vars.lua_running else []
last_userscripts = [e["filename"] for e in loaded]
emit('from_server', {'cmd': 'usstatitems', 'data': loaded, 'flash': last_userscripts != vars.last_userscripts}, broadcast=True)
vars.last_userscripts = last_userscripts
#==================================================================#
# Send start message and tell Javascript to set UI state
#==================================================================#
def setStartState():
txt = "Welcome to KoboldAI! You are running "+getmodelname()+".
"
if(not vars.noai):
txt = txt + "Please load a game or enter a prompt below to begin!"
else:
txt = txt + "Please load or import a story to read. There is no AI in this mode."
emit('from_server', {'cmd': 'updatescreen', 'gamestarted': vars.gamestarted, 'data': txt}, broadcast=True)
emit('from_server', {'cmd': 'setgamestate', 'data': 'start'}, broadcast=True)
#==================================================================#
# Transmit applicable settings to SocketIO to build UI sliders/toggles
#==================================================================#
def sendsettings():
# Send settings for selected AI type
if(vars.model != "InferKit"):
for set in gensettings.gensettingstf:
emit('from_server', {'cmd': 'addsetting', 'data': set})
else:
for set in gensettings.gensettingsik:
emit('from_server', {'cmd': 'addsetting', 'data': set})
# Send formatting options
for frm in gensettings.formatcontrols:
emit('from_server', {'cmd': 'addformat', 'data': frm})
# Add format key to vars if it wasn't loaded with client.settings
if(not frm["id"] in vars.formatoptns):
vars.formatoptns[frm["id"]] = False;
#==================================================================#
# Take settings from vars and write them to client settings file
#==================================================================#
def savesettings():
# Build json to write
js = {}
js["apikey"] = vars.apikey
js["andepth"] = vars.andepth
js["temp"] = vars.temp
js["top_p"] = vars.top_p
js["top_k"] = vars.top_k
js["tfs"] = vars.tfs
js["rep_pen"] = vars.rep_pen
js["genamt"] = vars.genamt
js["max_length"] = vars.max_length
js["ikgen"] = vars.ikgen
js["formatoptns"] = vars.formatoptns
js["numseqs"] = vars.numseqs
js["widepth"] = vars.widepth
js["useprompt"] = vars.useprompt
js["adventure"] = vars.adventure
js["chatmode"] = vars.chatmode
js["chatname"] = vars.chatname
js["dynamicscan"] = vars.dynamicscan
js["nopromptgen"] = vars.nopromptgen
js["rngpersist"] = vars.rngpersist
js["antemplate"] = vars.setauthornotetemplate
js["userscripts"] = vars.userscripts
js["corescript"] = vars.corescript
js["softprompt"] = vars.spfilename
# Write it
if not os.path.exists('settings'):
os.mkdir('settings')
file = open("settings/" + getmodelname().replace('/', '_') + ".settings", "w")
try:
file.write(json.dumps(js, indent=3))
finally:
file.close()
#==================================================================#
# Read settings from client file JSON and send to vars
#==================================================================#
def loadsettings():
if(path.exists("settings/" + getmodelname().replace('/', '_') + ".settings")):
# Read file contents into JSON object
file = open("settings/" + getmodelname().replace('/', '_') + ".settings", "r")
js = json.load(file)
# Copy file contents to vars
if("apikey" in js):
vars.apikey = js["apikey"]
if("andepth" in js):
vars.andepth = js["andepth"]
if("temp" in js):
vars.temp = js["temp"]
if("top_p" in js):
vars.top_p = js["top_p"]
if("top_k" in js):
vars.top_k = js["top_k"]
if("tfs" in js):
vars.tfs = js["tfs"]
if("rep_pen" in js):
vars.rep_pen = js["rep_pen"]
if("genamt" in js):
vars.genamt = js["genamt"]
if("max_length" in js):
vars.max_length = js["max_length"]
if("ikgen" in js):
vars.ikgen = js["ikgen"]
if("formatoptns" in js):
vars.formatoptns = js["formatoptns"]
if("numseqs" in js):
vars.numseqs = js["numseqs"]
if("widepth" in js):
vars.widepth = js["widepth"]
if("useprompt" in js):
vars.useprompt = js["useprompt"]
if("adventure" in js):
vars.adventure = js["adventure"]
if("chatmode" in js):
vars.chatmode = js["chatmode"]
if("chatname" in js):
vars.chatname = js["chatname"]
if("dynamicscan" in js):
vars.dynamicscan = js["dynamicscan"]
if("nopromptgen" in js):
vars.nopromptgen = js["nopromptgen"]
if("rngpersist" in js):
vars.rngpersist = js["rngpersist"]
if("antemplate" in js):
vars.setauthornotetemplate = js["antemplate"]
if(not vars.gamestarted):
vars.authornotetemplate = vars.setauthornotetemplate
if("userscripts" in js):
vars.userscripts = []
for userscript in js["userscripts"]:
if type(userscript) is not str:
continue
userscript = userscript.strip()
if len(userscript) != 0 and all(q not in userscript for q in ("..", ":")) and all(userscript[0] not in q for q in ("/", "\\")) and os.path.exists(fileops.uspath(userscript)):
vars.userscripts.append(userscript)
if("corescript" in js and type(js["corescript"]) is str and all(q not in js["corescript"] for q in ("..", ":")) and all(js["corescript"][0] not in q for q in ("/", "\\"))):
vars.corescript = js["corescript"]
else:
vars.corescript = "default.lua"
if(vars.allowsp and "softprompt" in js and type(js["softprompt"]) is str and all(q not in js["softprompt"] for q in ("..", ":")) and (len(js["softprompt"]) == 0 or all(js["softprompt"][0] not in q for q in ("/", "\\")))):
spRequest(js["softprompt"])
else:
vars.spfilename = ""
file.close()
#==================================================================#
# Allow the models to override some settings
#==================================================================#
def loadmodelsettings():
if(path.exists(vars.custmodpth.replace('/', '_') + "/config.json")):
model_config = open(vars.custmodpth.replace('/', '_') + "/config.json", "r")
js = json.load(model_config)
if("badwordsids" in js):
vars.badwordsids = js["badwordsids"]
if("temp" in js):
vars.temp = js["temp"]
if("top_p" in js):
vars.top_p = js["top_p"]
if("top_k" in js):
vars.top_k = js["top_k"]
if("tfs" in js):
vars.tfs = js["tfs"]
if("rep_pen" in js):
vars.rep_pen = js["rep_pen"]
if("adventure" in js):
vars.adventure = js["adventure"]
if("chatmode" in js):
vars.chatmode = js["chatmode"]
if("dynamicscan" in js):
vars.dynamicscan = js["dynamicscan"]
if("formatoptns" in js):
vars.formatoptns = js["formatoptns"]
if("antemplate" in js):
vars.setauthornotetemplate = js["antemplate"]
if(not vars.gamestarted):
vars.authornotetemplate = vars.setauthornotetemplate
model_config.close()
#==================================================================#
# Don't save settings unless 2 seconds have passed without modification
#==================================================================#
@debounce(2)
def settingschanged():
print("{0}Saving settings!{1}".format(colors.GREEN, colors.END))
savesettings()
#==================================================================#
# Take input text from SocketIO and decide what to do with it
#==================================================================#
def actionsubmit(data, actionmode=0, force_submit=False, force_prompt_gen=False, disable_recentrng=False):
# Ignore new submissions if the AI is currently busy
if(vars.aibusy):
return
while(True):
set_aibusy(1)
if(disable_recentrng):
vars.recentrng = vars.recentrngm = None
vars.recentback = False
vars.recentedit = False
vars.actionmode = actionmode
# "Action" mode
if(actionmode == 1):
data = data.strip().lstrip('>')
data = re.sub(r'\n+', ' ', data)
if(len(data)):
data = f"\n\n> {data}\n"
# "Chat" mode
if(vars.chatmode and vars.gamestarted):
data = re.sub(r'\n+', ' ', data)
if(len(data)):
data = f"\n{vars.chatname} : {data}\n"
# If we're not continuing, store a copy of the raw input
if(data != ""):
vars.lastact = data
if(not vars.gamestarted):
vars.submission = data
execute_inmod()
data = vars.submission
if(not force_submit and len(data.strip()) == 0):
assert False
# Start the game
vars.gamestarted = True
if(not vars.noai and vars.lua_koboldbridge.generating and (not vars.nopromptgen or force_prompt_gen)):
# Save this first action as the prompt
vars.prompt = data
# Clear the startup text from game screen
emit('from_server', {'cmd': 'updatescreen', 'gamestarted': False, 'data': 'Please wait, generating story...'}, broadcast=True)
calcsubmit(data) # Run the first action through the generator
if(vars.lua_koboldbridge.restart_sequence is not None and len(vars.genseqs) == 0):
data = ""
force_submit = True
disable_recentrng = True
continue
emit('from_server', {'cmd': 'scrolldown', 'data': ''}, broadcast=True)
break
else:
# Save this first action as the prompt
vars.prompt = data
for i in range(vars.numseqs):
vars.lua_koboldbridge.outputs[i+1] = ""
execute_outmod()
vars.lua_koboldbridge.regeneration_required = False
genout = []
for i in range(vars.numseqs):
genout.append({"generated_text": vars.lua_koboldbridge.outputs[i+1]})
assert type(genout[-1]["generated_text"]) is str
if(len(genout) == 1):
genresult(genout[0]["generated_text"], flash=False)
refresh_story()
if(len(vars.actions) > 0):
emit('from_server', {'cmd': 'texteffect', 'data': vars.actions.get_last_key() + 1}, broadcast=True)
if(vars.lua_koboldbridge.restart_sequence is not None):
data = ""
force_submit = True
disable_recentrng = True
continue
else:
if(vars.lua_koboldbridge.restart_sequence is not None and vars.lua_koboldbridge.restart_sequence > 0):
genresult(genout[vars.lua_koboldbridge.restart_sequence-1]["generated_text"], flash=False)
refresh_story()
data = ""
force_submit = True
disable_recentrng = True
continue
genselect(genout)
refresh_story()
set_aibusy(0)
emit('from_server', {'cmd': 'scrolldown', 'data': ''}, broadcast=True)
break
else:
# Apply input formatting & scripts before sending to tokenizer
if(vars.actionmode == 0):
data = applyinputformatting(data)
vars.submission = data
execute_inmod()
data = vars.submission
# Dont append submission if it's a blank/continue action
if(data != ""):
# Store the result in the Action log
if(len(vars.prompt.strip()) == 0):
vars.prompt = data
else:
vars.actions.append(data)
update_story_chunk('last')
if(not vars.noai and vars.lua_koboldbridge.generating):
# Off to the tokenizer!
calcsubmit(data)
if(vars.lua_koboldbridge.restart_sequence is not None and len(vars.genseqs) == 0):
data = ""
force_submit = True
disable_recentrng = True
continue
emit('from_server', {'cmd': 'scrolldown', 'data': ''}, broadcast=True)
break
else:
for i in range(vars.numseqs):
vars.lua_koboldbridge.outputs[i+1] = ""
execute_outmod()
vars.lua_koboldbridge.regeneration_required = False
genout = []
for i in range(vars.numseqs):
genout.append({"generated_text": vars.lua_koboldbridge.outputs[i+1]})
assert type(genout[-1]["generated_text"]) is str
if(len(genout) == 1):
genresult(genout[0]["generated_text"])
if(vars.lua_koboldbridge.restart_sequence is not None):
data = ""
force_submit = True
disable_recentrng = True
continue
else:
if(vars.lua_koboldbridge.restart_sequence is not None and vars.lua_koboldbridge.restart_sequence > 0):
genresult(genout[vars.lua_koboldbridge.restart_sequence-1]["generated_text"])
data = ""
force_submit = True
disable_recentrng = True
continue
genselect(genout)
set_aibusy(0)
emit('from_server', {'cmd': 'scrolldown', 'data': ''}, broadcast=True)
break
#==================================================================#
#
#==================================================================#
def actionretry(data):
if(vars.noai):
emit('from_server', {'cmd': 'errmsg', 'data': "Retry function unavailable in Read Only mode."})
return
if(vars.aibusy):
return
if(vars.recentrng is not None):
randomGameRequest(vars.recentrng, memory=vars.recentrngm)
return
# Remove last action if possible and resubmit
if(vars.gamestarted if vars.useprompt else len(vars.actions) > 0):
if(not vars.recentback and len(vars.actions) != 0 and len(vars.genseqs) == 0): # Don't pop if we're in the "Select sequence to keep" menu or if there are no non-prompt actions
last_key = vars.actions.get_last_key()
vars.actions.pop()
remove_story_chunk(last_key + 1)
vars.recentback = False
vars.recentedit = False
vars.lua_koboldbridge.feedback = None
actionsubmit("", actionmode=vars.actionmode, force_submit=True)
elif(not vars.useprompt):
emit('from_server', {'cmd': 'errmsg', 'data': "Please enable \"Always Add Prompt\" to retry with your prompt."})
#==================================================================#
#
#==================================================================#
def actionback():
if(vars.aibusy):
return
# Remove last index of actions and refresh game screen
if(len(vars.genseqs) == 0 and len(vars.actions) > 0):
last_key = vars.actions.get_last_key()
vars.actions.pop()
vars.recentback = True
remove_story_chunk(last_key + 1)
elif(len(vars.genseqs) == 0):
emit('from_server', {'cmd': 'errmsg', 'data': "Cannot delete the prompt."})
else:
vars.genseqs = []
#==================================================================#
#
#==================================================================#
def calcsubmitbudgetheader(txt, **kwargs):
# Scan for WorldInfo matches
winfo, found_entries = checkworldinfo(txt, **kwargs)
# Add a newline to the end of memory
if(vars.memory != "" and vars.memory[-1] != "\n"):
mem = vars.memory + "\n"
else:
mem = vars.memory
# Build Author's Note if set
if(vars.authornote != ""):
anotetxt = ("\n" + vars.authornotetemplate + "\n").replace("<|>", vars.authornote)
else:
anotetxt = ""
return winfo, mem, anotetxt, found_entries
def calcsubmitbudget(actionlen, winfo, mem, anotetxt, actions, submission=None, budget_deduction=0):
forceanote = False # In case we don't have enough actions to hit A.N. depth
anoteadded = False # In case our budget runs out before we hit A.N. depth
anotetkns = [] # Placeholder for Author's Note tokens
lnanote = 0 # Placeholder for Author's Note length
lnsp = vars.sp.shape[0] if vars.sp is not None else 0
if("tokenizer" not in globals()):
from transformers import GPT2TokenizerFast
global tokenizer
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", cache_dir="cache/")
# Calculate token budget
prompttkns = tokenizer.encode(vars.comregex_ai.sub('', vars.prompt), max_length=int(2e9), truncation=True)
lnprompt = len(prompttkns)
memtokens = tokenizer.encode(mem, max_length=int(2e9), truncation=True)
lnmem = len(memtokens)
if(lnmem > vars.max_length - lnsp - vars.genamt - budget_deduction):
raise OverflowError("The memory in your story is too long. Please either write a shorter memory text or increase the Max Tokens setting. If you are using a soft prompt, additionally consider using a smaller soft prompt.")
witokens = tokenizer.encode(winfo, max_length=int(2e9), truncation=True)
lnwi = len(witokens)
if(lnmem + lnwi > vars.max_length - lnsp - vars.genamt - budget_deduction):
raise OverflowError("The current active world info keys take up too many tokens. Please either write shorter world info, decrease World Info Depth or increase the Max Tokens setting. If you are using a soft prompt, additionally consider using a smaller soft prompt.")
if(anotetxt != ""):
anotetkns = tokenizer.encode(anotetxt, max_length=int(2e9), truncation=True)
lnanote = len(anotetkns)
if(lnmem + lnwi + lnanote > vars.max_length - lnsp - vars.genamt - budget_deduction):
raise OverflowError("The author's note in your story is too long. Please either write a shorter author's note or increase the Max Tokens setting. If you are using a soft prompt, additionally consider using a smaller soft prompt.")
if(vars.useprompt):
budget = vars.max_length - lnsp - lnprompt - lnmem - lnanote - lnwi - vars.genamt - budget_deduction
else:
budget = vars.max_length - lnsp - lnmem - lnanote - lnwi - vars.genamt - budget_deduction
lnsubmission = len(tokenizer.encode(vars.comregex_ai.sub('', submission), max_length=int(2e9), truncation=True)) if submission is not None else 0
maybe_lnprompt = lnprompt if vars.useprompt and actionlen > 0 else 0
if(lnmem + lnwi + lnanote + maybe_lnprompt + lnsubmission > vars.max_length - lnsp - vars.genamt - budget_deduction):
raise OverflowError("Your submission is too long. Please either write a shorter submission or increase the Max Tokens setting. If you are using a soft prompt, additionally consider using a smaller soft prompt. If you are using the Always Add Prompt setting, turning it off may help.")
assert budget >= 0
if(actionlen == 0):
# First/Prompt action
tokens = memtokens + witokens + anotetkns + prompttkns
assert len(tokens) <= vars.max_length - lnsp - vars.genamt - budget_deduction
ln = len(tokens) + lnsp
return tokens, ln+1, ln+vars.genamt
else:
tokens = []
# Check if we have the action depth to hit our A.N. depth
if(anotetxt != "" and actionlen < vars.andepth):
forceanote = True
# Get most recent action tokens up to our budget
n = 0
for key in reversed(actions):
chunk = vars.comregex_ai.sub('', actions[key])
assert budget >= 0
if(budget <= 0):
break
acttkns = tokenizer.encode(chunk, max_length=int(2e9), truncation=True)
tknlen = len(acttkns)
if(tknlen < budget):
tokens = acttkns + tokens
budget -= tknlen
else:
count = budget * -1
tokens = acttkns[count:] + tokens
budget = 0
break
# Inject Author's Note if we've reached the desired depth
if(n == vars.andepth-1):
if(anotetxt != ""):
tokens = anotetkns + tokens # A.N. len already taken from bdgt
anoteadded = True
n += 1
# If we're not using the prompt every time and there's still budget left,
# add some prompt.
if(not vars.useprompt):
if(budget > 0):
prompttkns = prompttkns[-budget:]
else:
prompttkns = []
# Did we get to add the A.N.? If not, do it here
if(anotetxt != ""):
if((not anoteadded) or forceanote):
tokens = memtokens + witokens + anotetkns + prompttkns + tokens
else:
tokens = memtokens + witokens + prompttkns + tokens
else:
# Prepend Memory, WI, and Prompt before action tokens
tokens = memtokens + witokens + prompttkns + tokens
# Send completed bundle to generator
assert len(tokens) <= vars.max_length - lnsp - vars.genamt - budget_deduction
ln = len(tokens) + lnsp
return tokens, ln+1, ln+vars.genamt
#==================================================================#
# Take submitted text and build the text to be given to generator
#==================================================================#
def calcsubmit(txt):
anotetxt = "" # Placeholder for Author's Note text
forceanote = False # In case we don't have enough actions to hit A.N. depth
anoteadded = False # In case our budget runs out before we hit A.N. depth
actionlen = len(vars.actions)
winfo, mem, anotetxt, found_entries = calcsubmitbudgetheader(txt)
# For all transformers models
if(vars.model != "InferKit"):
subtxt, min, max = calcsubmitbudget(actionlen, winfo, mem, anotetxt, vars.actions, submission=txt)
if(actionlen == 0):
if(not vars.model in ["Colab", "OAI", "TPUMeshTransformerGPTJ"]):
generate(subtxt, min, max, found_entries=found_entries)
elif(vars.model == "Colab"):
sendtocolab(tokenizer.decode(subtxt), min, max)
elif(vars.model == "OAI"):
oairequest(tokenizer.decode(subtxt), min, max)
elif(vars.model == "TPUMeshTransformerGPTJ"):
tpumtjgenerate(subtxt, min, max, found_entries=found_entries)
else:
if(not vars.model in ["Colab", "OAI", "TPUMeshTransformerGPTJ"]):
generate(subtxt, min, max, found_entries=found_entries)
elif(vars.model == "Colab"):
sendtocolab(tokenizer.decode(subtxt), min, max)
elif(vars.model == "OAI"):
oairequest(tokenizer.decode(subtxt), min, max)
elif(vars.model == "TPUMeshTransformerGPTJ"):
tpumtjgenerate(subtxt, min, max, found_entries=found_entries)
# For InferKit web API
else:
# Check if we have the action depth to hit our A.N. depth
if(anotetxt != "" and actionlen < vars.andepth):
forceanote = True
if(vars.useprompt):
budget = vars.ikmax - len(vars.comregex_ai.sub('', vars.prompt)) - len(anotetxt) - len(mem) - len(winfo) - 1
else:
budget = vars.ikmax - len(anotetxt) - len(mem) - len(winfo) - 1
subtxt = ""
prompt = vars.comregex_ai.sub('', vars.prompt)
n = 0
for key in reversed(vars.actions):
chunk = vars.actions[key]
if(budget <= 0):
break
actlen = len(chunk)
if(actlen < budget):
subtxt = chunk + subtxt
budget -= actlen
else:
count = budget * -1
subtxt = chunk[count:] + subtxt
budget = 0
break
# If we're not using the prompt every time and there's still budget left,
# add some prompt.
if(not vars.useprompt):
if(budget > 0):
prompt = vars.comregex_ai.sub('', vars.prompt)[-budget:]
else:
prompt = ""
# Inject Author's Note if we've reached the desired depth
if(n == vars.andepth-1):
if(anotetxt != ""):
subtxt = anotetxt + subtxt # A.N. len already taken from bdgt
anoteadded = True
n += 1
# Did we get to add the A.N.? If not, do it here
if(anotetxt != ""):
if((not anoteadded) or forceanote):
subtxt = mem + winfo + anotetxt + prompt + subtxt
else:
subtxt = mem + winfo + prompt + subtxt
else:
subtxt = mem + winfo + prompt + subtxt
# Send it!
ikrequest(subtxt)
#==================================================================#
# Send text to generator and deal with output
#==================================================================#
def _generate(txt, minimum, maximum, found_entries):
gen_in = torch.tensor(txt, dtype=torch.long)[None]
if(vars.sp is not None):
soft_tokens = torch.arange(
model.config.vocab_size,
model.config.vocab_size + vars.sp.shape[0],
)
gen_in = torch.cat((soft_tokens[None], gen_in), dim=-1)
assert gen_in.shape[-1] + vars.genamt <= vars.max_length
if(vars.hascuda and vars.usegpu):
gen_in = gen_in.to(vars.gpu_device)
elif(vars.hascuda and vars.breakmodel):
gen_in = gen_in.to(breakmodel.primary_device)
else:
gen_in = gen_in.to('cpu')
model.kai_scanner_head_length = gen_in.shape[-1]
model.kai_scanner_excluded_world_info = found_entries
vars._actions = vars.actions
vars._prompt = vars.prompt
if(vars.dynamicscan):
vars._actions = vars._actions.copy()
with torch.no_grad():
already_generated = 0
numseqs = vars.numseqs
while True:
genout = generator(
gen_in,
do_sample=True,
min_length=minimum,
max_length=int(2e9),
repetition_penalty=1.1,
bad_words_ids=vars.badwordsids,
use_cache=True,
num_return_sequences=numseqs
)
already_generated += len(genout[0]) - len(gen_in[0])
assert already_generated <= vars.genamt
if(model.kai_scanner.halt or not model.kai_scanner.regeneration_required):
break
assert genout.ndim >= 2
assert genout.shape[0] == vars.numseqs
if(vars.lua_koboldbridge.generated_cols and vars.generated_tkns != vars.lua_koboldbridge.generated_cols):
raise RuntimeError("Inconsistency detected between KoboldAI Python and Lua backends")
if(already_generated != vars.generated_tkns):
raise RuntimeError("WI scanning error")
for r in range(vars.numseqs):
for c in range(already_generated):
assert vars.lua_koboldbridge.generated[r+1][c+1] is not None
genout[r][genout.shape[-1] - already_generated + c] = vars.lua_koboldbridge.generated[r+1][c+1]
encoded = []
for i in range(vars.numseqs):
txt = tokenizer.decode(genout[i, -already_generated:])
winfo, mem, anotetxt, _found_entries = calcsubmitbudgetheader(txt, force_use_txt=True)
found_entries[i].update(_found_entries)
txt, _, _ = calcsubmitbudget(len(vars._actions), winfo, mem, anotetxt, vars._actions, submission=txt)
encoded.append(torch.tensor(txt, dtype=torch.long, device=genout.device))
max_length = len(max(encoded, key=len))
encoded = torch.stack(tuple(torch.nn.functional.pad(e, (max_length - len(e), 0), value=model.config.pad_token_id or model.config.eos_token_id) for e in encoded))
genout = torch.cat(
(
encoded,
genout[..., -already_generated:],
),
dim=-1
)
if(vars.sp is not None):
soft_tokens = torch.arange(
model.config.vocab_size,
model.config.vocab_size + vars.sp.shape[0],
device=genout.device,
)
genout = torch.cat((soft_tokens.tile(vars.numseqs, 1), genout), dim=-1)
assert genout.shape[-1] + vars.genamt - already_generated <= vars.max_length
diff = genout.shape[-1] - gen_in.shape[-1]
minimum += diff
maximum += diff
gen_in = genout
model.kai_scanner_head_length = encoded.shape[-1]
numseqs = 1
return genout, already_generated
def generate(txt, minimum, maximum, found_entries=None):
vars.generated_tkns = 0
if(found_entries is None):
found_entries = set()
found_entries = tuple(found_entries.copy() for _ in range(vars.numseqs))
print("{0}Min:{1}, Max:{2}, Txt:{3}{4}".format(colors.YELLOW, minimum, maximum, tokenizer.decode(txt), colors.END))
# Store context in memory to use it for comparison with generated content
vars.lastctx = tokenizer.decode(txt)
# Clear CUDA cache if using GPU
if(vars.hascuda and (vars.usegpu or vars.breakmodel)):
gc.collect()
torch.cuda.empty_cache()
# Submit input text to generator
try:
genout, already_generated = tpool.execute(_generate, txt, minimum, maximum, found_entries)
except Exception as e:
if(issubclass(type(e), lupa.LuaError)):
vars.lua_koboldbridge.obliterate_multiverse()
vars.lua_running = False
emit('from_server', {'cmd': 'errmsg', 'data': 'Lua script error, please check console.'}, broadcast=True)
sendUSStatItems()
print("{0}{1}{2}".format(colors.RED, "***LUA ERROR***: ", colors.END), end="", file=sys.stderr)
print("{0}{1}{2}".format(colors.RED, str(e).replace("\033", ""), colors.END), file=sys.stderr)
print("{0}{1}{2}".format(colors.YELLOW, "Lua engine stopped; please open 'Userscripts' and press Load to reinitialize scripts.", colors.END), file=sys.stderr)
else:
emit('from_server', {'cmd': 'errmsg', 'data': 'Error occured during generator call, please check console.'}, broadcast=True)
print("{0}{1}{2}".format(colors.RED, traceback.format_exc().replace("\033", ""), colors.END), file=sys.stderr)
set_aibusy(0)
return
for i in range(vars.numseqs):
vars.lua_koboldbridge.generated[i+1][vars.generated_tkns] = int(genout[i, -1].item())
vars.lua_koboldbridge.outputs[i+1] = tokenizer.decode(genout[i, -already_generated:])
execute_outmod()
if(vars.lua_koboldbridge.regeneration_required):
vars.lua_koboldbridge.regeneration_required = False
genout = []
for i in range(vars.numseqs):
genout.append({"generated_text": vars.lua_koboldbridge.outputs[i+1]})
assert type(genout[-1]["generated_text"]) is str
else:
genout = [{"generated_text": tokenizer.decode(tokens[-already_generated:])} for tokens in genout]
if(len(genout) == 1):
genresult(genout[0]["generated_text"])
else:
if(vars.lua_koboldbridge.restart_sequence is not None and vars.lua_koboldbridge.restart_sequence > 0):
genresult(genout[vars.lua_koboldbridge.restart_sequence-1]["generated_text"])
else:
genselect(genout)
# Clear CUDA cache again if using GPU
if(vars.hascuda and (vars.usegpu or vars.breakmodel)):
del genout
gc.collect()
torch.cuda.empty_cache()
set_aibusy(0)
#==================================================================#
# Deal with a single return sequence from generate()
#==================================================================#
def genresult(genout, flash=True):
print("{0}{1}{2}".format(colors.CYAN, genout, colors.END))
# Format output before continuing
genout = applyoutputformatting(genout)
vars.lua_koboldbridge.feedback = genout
if(len(genout) == 0):
return
# Add formatted text to Actions array and refresh the game screen
if(len(vars.prompt.strip()) == 0):
vars.prompt = genout
else:
vars.actions.append(genout)
update_story_chunk('last')
if(flash):
emit('from_server', {'cmd': 'texteffect', 'data': vars.actions.get_last_key() + 1 if len(vars.actions) else 0}, broadcast=True)
#==================================================================#
# Send generator sequences to the UI for selection
#==================================================================#
def genselect(genout):
i = 0
for result in genout:
# Apply output formatting rules to sequences
result["generated_text"] = applyoutputformatting(result["generated_text"])
print("{0}[Result {1}]\n{2}{3}".format(colors.CYAN, i, result["generated_text"], colors.END))
i += 1
# Store sequences in memory until selection is made
vars.genseqs = genout
# Send sequences to UI for selection
emit('from_server', {'cmd': 'genseqs', 'data': genout}, broadcast=True)
#==================================================================#
# Send selected sequence to action log and refresh UI
#==================================================================#
def selectsequence(n):
if(len(vars.genseqs) == 0):
return
vars.lua_koboldbridge.feedback = vars.genseqs[int(n)]["generated_text"]
if(len(vars.lua_koboldbridge.feedback) != 0):
vars.actions.append(vars.lua_koboldbridge.feedback)
update_story_chunk('last')
emit('from_server', {'cmd': 'texteffect', 'data': vars.actions.get_last_key() + 1 if len(vars.actions) else 0}, broadcast=True)
emit('from_server', {'cmd': 'hidegenseqs', 'data': ''}, broadcast=True)
vars.genseqs = []
if(vars.lua_koboldbridge.restart_sequence is not None):
actionsubmit("", actionmode=vars.actionmode, force_submit=True, disable_recentrng=True)
#==================================================================#
# Send transformers-style request to ngrok/colab host
#==================================================================#
def sendtocolab(txt, min, max):
# Log request to console
print("{0}Tokens:{1}, Txt:{2}{3}".format(colors.YELLOW, min-1, txt, colors.END))
# Store context in memory to use it for comparison with generated content
vars.lastctx = txt
# Build request JSON data
reqdata = {
'text': txt,
'min': min,
'max': max,
'rep_pen': vars.rep_pen,
'temperature': vars.temp,
'top_p': vars.top_p,
'top_k': vars.top_k,
'tfs': vars.tfs,
'numseqs': vars.numseqs,
'retfultxt': False
}
# Create request
req = requests.post(
vars.colaburl,
json = reqdata
)
# Deal with the response
if(req.status_code == 200):
js = req.json()["data"]
# Try to be backwards compatible with outdated colab
if("text" in js):
genout = [getnewcontent(js["text"])]
else:
genout = js["seqs"]
for i in range(vars.numseqs):
vars.lua_koboldbridge.outputs[i+1] = genout[i]
execute_outmod()
if(vars.lua_koboldbridge.regeneration_required):
vars.lua_koboldbridge.regeneration_required = False
genout = []
for i in range(vars.numseqs):
genout.append(vars.lua_koboldbridge.outputs[i+1])
assert type(genout[-1]) is str
if(len(genout) == 1):
genresult(genout[0])
else:
# Convert torch output format to transformers
seqs = []
for seq in genout:
seqs.append({"generated_text": seq})
if(vars.lua_koboldbridge.restart_sequence is not None and vars.lua_koboldbridge.restart_sequence > 0):
genresult(genout[vars.lua_koboldbridge.restart_sequence-1]["generated_text"])
else:
genselect(genout)
# Format output before continuing
#genout = applyoutputformatting(getnewcontent(genout))
# Add formatted text to Actions array and refresh the game screen
#vars.actions.append(genout)
#refresh_story()
#emit('from_server', {'cmd': 'texteffect', 'data': vars.actions.get_last_key() + 1 if len(vars.actions) else 0})
set_aibusy(0)
else:
errmsg = "Colab API Error: Failed to get a reply from the server. Please check the colab console."
print("{0}{1}{2}".format(colors.RED, errmsg, colors.END))
emit('from_server', {'cmd': 'errmsg', 'data': errmsg}, broadcast=True)
set_aibusy(0)
#==================================================================#
# Send text to TPU mesh transformer backend
#==================================================================#
def tpumtjgenerate(txt, minimum, maximum, found_entries=None):
vars.generated_tkns = 0
if(found_entries is None):
found_entries = set()
found_entries = tuple(found_entries.copy() for _ in range(vars.numseqs))
print("{0}Min:{1}, Max:{2}, Txt:{3}{4}".format(colors.YELLOW, minimum, maximum, tokenizer.decode(txt), colors.END))
vars._actions = vars.actions
vars._prompt = vars.prompt
if(vars.dynamicscan):
vars._actions = vars._actions.copy()
# Submit input text to generator
try:
context = np.tile(np.uint32(txt), (vars.numseqs, 1))
soft_tokens = tpumtjgetsofttokens()
global past
past = np.empty((vars.numseqs, 0), dtype=np.uint32)
while(True):
genout, n_generated, regeneration_required, halt = tpool.execute(
tpu_mtj_backend.infer,
context,
gen_len = maximum-minimum+1,
temp=vars.temp,
top_p=vars.top_p,
top_k=vars.top_k,
tfs=vars.tfs,
numseqs=vars.numseqs,
repetition_penalty=vars.rep_pen,
soft_embeddings=vars.sp,
soft_tokens=soft_tokens,
excluded_world_info=found_entries,
)
past = np.pad(past, ((0, 0), (0, n_generated)))
for r in range(vars.numseqs):
for c in range(vars.lua_koboldbridge.generated_cols):
assert vars.lua_koboldbridge.generated[r+1][c+1] is not None
past[r, c] = vars.lua_koboldbridge.generated[r+1][c+1]
if(halt or not regeneration_required):
break
print("(regeneration triggered)")
encoded = []
for i in range(vars.numseqs):
txt = tokenizer.decode(past[i])
winfo, mem, anotetxt, _found_entries = calcsubmitbudgetheader(txt, force_use_txt=True)
found_entries[i].update(_found_entries)
txt, _, _ = calcsubmitbudget(len(vars._actions), winfo, mem, anotetxt, vars._actions, submission=txt)
encoded.append(np.array(txt, dtype=np.uint32))
max_length = len(max(encoded, key=len))
encoded = np.stack(tuple(np.pad(e, (max_length - len(e), 0), constant_values=tpu_mtj_backend.pad_token_id) for e in encoded))
context = np.concatenate(
(
encoded,
past,
),
axis=-1,
)
except Exception as e:
if(issubclass(type(e), lupa.LuaError)):
vars.lua_koboldbridge.obliterate_multiverse()
vars.lua_running = False
emit('from_server', {'cmd': 'errmsg', 'data': 'Lua script error, please check console.'}, broadcast=True)
sendUSStatItems()
print("{0}{1}{2}".format(colors.RED, "***LUA ERROR***: ", colors.END), end="", file=sys.stderr)
print("{0}{1}{2}".format(colors.RED, str(e).replace("\033", ""), colors.END), file=sys.stderr)
print("{0}{1}{2}".format(colors.YELLOW, "Lua engine stopped; please open 'Userscripts' and press Load to reinitialize scripts.", colors.END), file=sys.stderr)
else:
emit('from_server', {'cmd': 'errmsg', 'data': 'Error occured during generator call, please check console.'}, broadcast=True)
print("{0}{1}{2}".format(colors.RED, traceback.format_exc().replace("\033", ""), colors.END), file=sys.stderr)
set_aibusy(0)
return
for i in range(vars.numseqs):
vars.lua_koboldbridge.outputs[i+1] = tokenizer.decode(past[i])
genout = past
execute_outmod()
if(vars.lua_koboldbridge.regeneration_required):
vars.lua_koboldbridge.regeneration_required = False
genout = []
for i in range(vars.numseqs):
genout.append({"generated_text": vars.lua_koboldbridge.outputs[i+1]})
assert type(genout[-1]["generated_text"]) is str
else:
genout = [{"generated_text": tokenizer.decode(txt)} for txt in genout]
if(len(genout) == 1):
genresult(genout[0]["generated_text"])
else:
if(vars.lua_koboldbridge.restart_sequence is not None and vars.lua_koboldbridge.restart_sequence > 0):
genresult(genout[vars.lua_koboldbridge.restart_sequence-1]["generated_text"])
else:
genselect(genout)
set_aibusy(0)
#==================================================================#
# Replaces returns and newlines with HTML breaks
#==================================================================#
def formatforhtml(txt):
return txt.replace("\\r\\n", "
").replace("\\r", "
").replace("\\n", "
").replace("\r\n", "
").replace('\n', '
').replace('\r', '
')
#==================================================================#
# Strips submitted text from the text returned by the AI
#==================================================================#
def getnewcontent(txt):
# If the submitted context was blank, then everything is new
if(vars.lastctx == ""):
return txt
# Tokenize the last context and the generated content
ctxtokens = tokenizer.encode(vars.lastctx, max_length=int(2e9), truncation=True)
txttokens = tokenizer.encode(txt, max_length=int(2e9), truncation=True)
dif = (len(txttokens) - len(ctxtokens)) * -1
# Remove the context from the returned text
newtokens = txttokens[dif:]
return tokenizer.decode(newtokens)
#==================================================================#
# Applies chosen formatting options to text submitted to AI
#==================================================================#
def applyinputformatting(txt):
# Add sentence spacing
if(vars.formatoptns["frmtadsnsp"]):
txt = utils.addsentencespacing(txt, vars)
return txt
#==================================================================#
# Applies chosen formatting options to text returned from AI
#==================================================================#
def applyoutputformatting(txt):
# Use standard quotes and apostrophes
txt = utils.fixquotes(txt)
# Adventure mode clipping of all characters after '>'
if(vars.adventure):
txt = vars.acregex_ai.sub('', txt)
# Trim incomplete sentences
if(vars.formatoptns["frmttriminc"] and not vars.chatmode):
txt = utils.trimincompletesentence(txt)
# Replace blank lines
if(vars.formatoptns["frmtrmblln"] or vars.chatmode):
txt = utils.replaceblanklines(txt)
# Remove special characters
if(vars.formatoptns["frmtrmspch"]):
txt = utils.removespecialchars(txt, vars)
# Single Line Mode
if(vars.formatoptns["singleline"] or vars.chatmode):
txt = utils.singlelineprocessing(txt, vars)
return txt
#==================================================================#
# Sends the current story content to the Game Screen
#==================================================================#
def refresh_story():
text_parts = ['', vars.comregex_ui.sub(lambda m: '\n'.join('' + l + '' for l in m.group().split('\n')), html.escape(vars.prompt)), '']
for idx in vars.actions:
item = vars.actions[idx]
idx += 1
item = html.escape(item)
item = vars.comregex_ui.sub(lambda m: '\n'.join('' + l + '' for l in m.group().split('\n')), item) # Add special formatting to comments
item = vars.acregex_ui.sub('\\1', item) # Add special formatting to adventure actions
text_parts.extend(('', item, ''))
emit('from_server', {'cmd': 'updatescreen', 'gamestarted': vars.gamestarted, 'data': formatforhtml(''.join(text_parts))}, broadcast=True)
#==================================================================#
# Signals the Game Screen to update one of the chunks
#==================================================================#
def update_story_chunk(idx: Union[int, str]):
if idx == 'last':
if len(vars.actions) <= 1:
# In this case, we are better off just refreshing the whole thing as the
# prompt might not have been shown yet (with a "Generating story..."
# message instead).
refresh_story()
return
idx = (vars.actions.get_last_key() if len(vars.actions) else 0) + 1
if idx == 0:
text = vars.prompt
else:
# Actions are 0 based, but in chunks 0 is the prompt.
# So the chunk index is one more than the corresponding action index.
text = vars.actions[idx - 1]
item = html.escape(text)
item = vars.comregex_ui.sub(lambda m: '\n'.join('' + l + '' for l in m.group().split('\n')), item) # Add special formatting to comments
item = vars.acregex_ui.sub('\\1', item) # Add special formatting to adventure actions
chunk_text = f'{formatforhtml(item)}'
emit('from_server', {'cmd': 'updatechunk', 'data': {'index': idx, 'html': chunk_text}}, broadcast=True)
#==================================================================#
# Signals the Game Screen to remove one of the chunks
#==================================================================#
def remove_story_chunk(idx: int):
emit('from_server', {'cmd': 'removechunk', 'data': idx}, broadcast=True)
#==================================================================#
# Sends the current generator settings to the Game Menu
#==================================================================#
def refresh_settings():
# Suppress toggle change events while loading state
emit('from_server', {'cmd': 'allowtoggle', 'data': False}, broadcast=True)
if(vars.model != "InferKit"):
emit('from_server', {'cmd': 'updatetemp', 'data': vars.temp}, broadcast=True)
emit('from_server', {'cmd': 'updatetopp', 'data': vars.top_p}, broadcast=True)
emit('from_server', {'cmd': 'updatetopk', 'data': vars.top_k}, broadcast=True)
emit('from_server', {'cmd': 'updatetfs', 'data': vars.tfs}, broadcast=True)
emit('from_server', {'cmd': 'updatereppen', 'data': vars.rep_pen}, broadcast=True)
emit('from_server', {'cmd': 'updateoutlen', 'data': vars.genamt}, broadcast=True)
emit('from_server', {'cmd': 'updatetknmax', 'data': vars.max_length}, broadcast=True)
emit('from_server', {'cmd': 'updatenumseq', 'data': vars.numseqs}, broadcast=True)
else:
emit('from_server', {'cmd': 'updatetemp', 'data': vars.temp}, broadcast=True)
emit('from_server', {'cmd': 'updatetopp', 'data': vars.top_p}, broadcast=True)
emit('from_server', {'cmd': 'updateikgen', 'data': vars.ikgen}, broadcast=True)
emit('from_server', {'cmd': 'updateanotedepth', 'data': vars.andepth}, broadcast=True)
emit('from_server', {'cmd': 'updatewidepth', 'data': vars.widepth}, broadcast=True)
emit('from_server', {'cmd': 'updateuseprompt', 'data': vars.useprompt}, broadcast=True)
emit('from_server', {'cmd': 'updateadventure', 'data': vars.adventure}, broadcast=True)
emit('from_server', {'cmd': 'updatechatmode', 'data': vars.chatmode}, broadcast=True)
emit('from_server', {'cmd': 'updatedynamicscan', 'data': vars.dynamicscan}, broadcast=True)
emit('from_server', {'cmd': 'updatenopromptgen', 'data': vars.nopromptgen}, broadcast=True)
emit('from_server', {'cmd': 'updaterngpersist', 'data': vars.rngpersist}, broadcast=True)
emit('from_server', {'cmd': 'updatefrmttriminc', 'data': vars.formatoptns["frmttriminc"]}, broadcast=True)
emit('from_server', {'cmd': 'updatefrmtrmblln', 'data': vars.formatoptns["frmtrmblln"]}, broadcast=True)
emit('from_server', {'cmd': 'updatefrmtrmspch', 'data': vars.formatoptns["frmtrmspch"]}, broadcast=True)
emit('from_server', {'cmd': 'updatefrmtadsnsp', 'data': vars.formatoptns["frmtadsnsp"]}, broadcast=True)
emit('from_server', {'cmd': 'updatesingleline', 'data': vars.formatoptns["singleline"]}, broadcast=True)
# Allow toggle events again
emit('from_server', {'cmd': 'allowtoggle', 'data': True}, broadcast=True)
#==================================================================#
# Sets the logical and display states for the AI Busy condition
#==================================================================#
def set_aibusy(state):
if(state):
vars.aibusy = True
emit('from_server', {'cmd': 'setgamestate', 'data': 'wait'}, broadcast=True)
else:
vars.aibusy = False
emit('from_server', {'cmd': 'setgamestate', 'data': 'ready'}, broadcast=True)
#==================================================================#
#
#==================================================================#
def editrequest(n):
if(n == 0):
txt = vars.prompt
else:
txt = vars.actions[n-1]
vars.editln = n
emit('from_server', {'cmd': 'setinputtext', 'data': txt}, broadcast=True)
emit('from_server', {'cmd': 'enablesubmit', 'data': ''}, broadcast=True)
#==================================================================#
#
#==================================================================#
def editsubmit(data):
vars.recentedit = True
if(vars.editln == 0):
vars.prompt = data
else:
vars.actions[vars.editln-1] = data
vars.mode = "play"
update_story_chunk(vars.editln)
emit('from_server', {'cmd': 'texteffect', 'data': vars.editln}, broadcast=True)
emit('from_server', {'cmd': 'editmode', 'data': 'false'})
#==================================================================#
#
#==================================================================#
def deleterequest():
vars.recentedit = True
# Don't delete prompt
if(vars.editln == 0):
# Send error message
pass
else:
del vars.actions[vars.editln-1]
vars.mode = "play"
remove_story_chunk(vars.editln)
emit('from_server', {'cmd': 'editmode', 'data': 'false'})
#==================================================================#
#
#==================================================================#
def inlineedit(chunk, data):
vars.recentedit = True
chunk = int(chunk)
if(chunk == 0):
if(len(data.strip()) == 0):
return
vars.prompt = data
else:
if(chunk-1 in vars.actions):
vars.actions[chunk-1] = data
update_story_chunk(chunk)
emit('from_server', {'cmd': 'texteffect', 'data': chunk}, broadcast=True)
emit('from_server', {'cmd': 'editmode', 'data': 'false'}, broadcast=True)
#==================================================================#
#
#==================================================================#
def inlinedelete(chunk):
vars.recentedit = True
chunk = int(chunk)
# Don't delete prompt
if(chunk == 0):
# Send error message
update_story_chunk(chunk)
emit('from_server', {'cmd': 'errmsg', 'data': "Cannot delete the prompt."})
emit('from_server', {'cmd': 'editmode', 'data': 'false'}, broadcast=True)
else:
if(chunk-1 in vars.actions):
del vars.actions[chunk-1]
remove_story_chunk(chunk)
emit('from_server', {'cmd': 'editmode', 'data': 'false'}, broadcast=True)
#==================================================================#
# Toggles the game mode for memory editing and sends UI commands
#==================================================================#
def togglememorymode():
if(vars.mode == "play"):
vars.mode = "memory"
emit('from_server', {'cmd': 'memmode', 'data': 'true'}, broadcast=True)
emit('from_server', {'cmd': 'setinputtext', 'data': vars.memory}, broadcast=True)
emit('from_server', {'cmd': 'setanote', 'data': vars.authornote}, broadcast=True)
emit('from_server', {'cmd': 'setanotetemplate', 'data': vars.authornotetemplate}, broadcast=True)
elif(vars.mode == "memory"):
vars.mode = "play"
emit('from_server', {'cmd': 'memmode', 'data': 'false'}, broadcast=True)
#==================================================================#
# Toggles the game mode for WI editing and sends UI commands
#==================================================================#
def togglewimode():
if(vars.mode == "play"):
vars.mode = "wi"
emit('from_server', {'cmd': 'wimode', 'data': 'true'}, broadcast=True)
elif(vars.mode == "wi"):
# Commit WI fields first
requestwi()
# Then set UI state back to Play
vars.mode = "play"
emit('from_server', {'cmd': 'wimode', 'data': 'false'}, broadcast=True)
sendwi()
#==================================================================#
#
#==================================================================#
def addwiitem(folder_uid=None):
assert folder_uid is None or folder_uid in vars.wifolders_d
ob = {"key": "", "keysecondary": "", "content": "", "comment": "", "folder": folder_uid, "num": len(vars.worldinfo), "init": False, "selective": False, "constant": False}
vars.worldinfo.append(ob)
while(True):
uid = int.from_bytes(os.urandom(4), "little", signed=True)
if(uid not in vars.worldinfo_u):
break
vars.worldinfo_u[uid] = vars.worldinfo[-1]
vars.worldinfo[-1]["uid"] = uid
if(folder_uid is not None):
vars.wifolders_u[folder_uid].append(vars.worldinfo[-1])
emit('from_server', {'cmd': 'addwiitem', 'data': ob}, broadcast=True)
#==================================================================#
# Creates a new WI folder with an unused cryptographically secure random UID
#==================================================================#
def addwifolder():
while(True):
uid = int.from_bytes(os.urandom(4), "little", signed=True)
if(uid not in vars.wifolders_d):
break
ob = {"name": "", "collapsed": False}
vars.wifolders_d[uid] = ob
vars.wifolders_l.append(uid)
vars.wifolders_u[uid] = []
emit('from_server', {'cmd': 'addwifolder', 'uid': uid, 'data': ob}, broadcast=True)
addwiitem(folder_uid=uid)
#==================================================================#
# Move the WI entry with UID src so that it immediately precedes
# the WI entry with UID dst
#==================================================================#
def movewiitem(dst, src):
if(vars.worldinfo_u[src]["folder"] is not None):
for i, e in enumerate(vars.wifolders_u[vars.worldinfo_u[src]["folder"]]):
if(e is vars.worldinfo_u[src]):
vars.wifolders_u[vars.worldinfo_u[src]["folder"]].pop(i)
break
if(vars.worldinfo_u[dst]["folder"] is not None):
vars.wifolders_u[vars.worldinfo_u[dst]["folder"]].append(vars.worldinfo_u[src])
vars.worldinfo_u[src]["folder"] = vars.worldinfo_u[dst]["folder"]
for i, e in enumerate(vars.worldinfo):
if(e is vars.worldinfo_u[src]):
_src = i
elif(e is vars.worldinfo_u[dst]):
_dst = i
vars.worldinfo.insert(_dst - (_dst >= _src), vars.worldinfo.pop(_src))
sendwi()
#==================================================================#
# Move the WI folder with UID src so that it immediately precedes
# the WI folder with UID dst
#==================================================================#
def movewifolder(dst, src):
vars.wifolders_l.remove(src)
if(dst is None):
# If dst is None, that means we should move src to be the last folder
vars.wifolders_l.append(src)
else:
vars.wifolders_l.insert(vars.wifolders_l.index(dst), src)
sendwi()
#==================================================================#
#
#==================================================================#
def sendwi():
# Cache len of WI
ln = len(vars.worldinfo)
# Clear contents of WI container
emit('from_server', {'cmd': 'wistart', 'wifolders_d': vars.wifolders_d, 'wifolders_l': vars.wifolders_l, 'data': ''}, broadcast=True)
# Stable-sort WI entries in order of folder
stablesortwi()
vars.worldinfo_i = [wi for wi in vars.worldinfo if wi["init"]]
# If there are no WI entries, send an empty WI object
if(ln == 0):
addwiitem()
else:
# Send contents of WI array
last_folder = ...
for wi in vars.worldinfo:
if(wi["folder"] != last_folder):
emit('from_server', {'cmd': 'addwifolder', 'uid': wi["folder"], 'data': vars.wifolders_d[wi["folder"]] if wi["folder"] is not None else None}, broadcast=True)
last_folder = wi["folder"]
ob = wi
emit('from_server', {'cmd': 'addwiitem', 'data': ob}, broadcast=True)
emit('from_server', {'cmd': 'wifinish', 'data': ''}, broadcast=True)
#==================================================================#
# Request current contents of all WI HTML elements
#==================================================================#
def requestwi():
list = []
for wi in vars.worldinfo:
list.append(wi["num"])
emit('from_server', {'cmd': 'requestwiitem', 'data': list})
#==================================================================#
# Stable-sort WI items so that items in the same folder are adjacent,
# and items in different folders are sorted based on the order of the folders
#==================================================================#
def stablesortwi():
mapping = {uid: index for index, uid in enumerate(vars.wifolders_l)}
vars.worldinfo.sort(key=lambda x: mapping[x["folder"]] if x["folder"] is not None else float("inf"))
last_folder = ...
last_wi = None
for i, wi in enumerate(vars.worldinfo):
wi["num"] = i
wi["init"] = True
if(wi["folder"] != last_folder):
if(last_wi is not None and last_folder is not ...):
last_wi["init"] = False
last_folder = wi["folder"]
last_wi = wi
if(last_wi is not None):
last_wi["init"] = False
for folder in vars.wifolders_u:
vars.wifolders_u[folder].sort(key=lambda x: x["num"])
#==================================================================#
# Extract object from server and send it to WI objects
#==================================================================#
def commitwi(ar):
for ob in ar:
ob["uid"] = int(ob["uid"])
vars.worldinfo_u[ob["uid"]]["key"] = ob["key"]
vars.worldinfo_u[ob["uid"]]["keysecondary"] = ob["keysecondary"]
vars.worldinfo_u[ob["uid"]]["content"] = ob["content"]
vars.worldinfo_u[ob["uid"]]["comment"] = ob.get("comment", "")
vars.worldinfo_u[ob["uid"]]["folder"] = ob.get("folder", None)
vars.worldinfo_u[ob["uid"]]["selective"] = ob["selective"]
vars.worldinfo_u[ob["uid"]]["constant"] = ob.get("constant", False)
stablesortwi()
vars.worldinfo_i = [wi for wi in vars.worldinfo if wi["init"]]
#==================================================================#
#
#==================================================================#
def deletewi(uid):
if(uid in vars.worldinfo_u):
# Store UID of deletion request
vars.deletewi = uid
if(vars.deletewi is not None):
if(vars.worldinfo_u[vars.deletewi]["folder"] is not None):
for i, e in enumerate(vars.wifolders_u[vars.worldinfo_u[vars.deletewi]["folder"]]):
if(e is vars.worldinfo_u[vars.deletewi]):
vars.wifolders_u[vars.worldinfo_u[vars.deletewi]["folder"]].pop(i)
for i, e in enumerate(vars.worldinfo):
if(e is vars.worldinfo_u[vars.deletewi]):
del vars.worldinfo[i]
break
del vars.worldinfo_u[vars.deletewi]
# Send the new WI array structure
sendwi()
# And reset deletewi
vars.deletewi = None
#==================================================================#
#
#==================================================================#
def deletewifolder(uid):
uid = int(uid)
del vars.wifolders_u[uid]
del vars.wifolders_d[uid]
del vars.wifolders_l[vars.wifolders_l.index(uid)]
# Delete uninitialized entries in the folder we're going to delete
vars.worldinfo = [wi for wi in vars.worldinfo if wi["folder"] != uid or wi["init"]]
vars.worldinfo_i = [wi for wi in vars.worldinfo if wi["init"]]
# Move WI entries that are inside of the folder we're going to delete
# so that they're outside of all folders
for wi in vars.worldinfo:
if(wi["folder"] == uid):
wi["folder"] = None
sendwi()
#==================================================================#
# Look for WI keys in text to generator
#==================================================================#
def checkworldinfo(txt, allowed_entries=None, allowed_folders=None, force_use_txt=False, scan_story=True):
original_txt = txt
# Dont go any further if WI is empty
if(len(vars.worldinfo) == 0):
return "", set()
# Cache actions length
ln = len(vars.actions)
# Don't bother calculating action history if widepth is 0
if(vars.widepth > 0 and scan_story):
depth = vars.widepth
# If this is not a continue, add 1 to widepth since submitted
# text is already in action history @ -1
if(not force_use_txt and (txt != "" and vars.prompt != txt)):
txt = ""
depth += 1
if(ln > 0):
chunks = collections.deque()
i = 0
for key in reversed(vars.actions):
chunk = vars.actions[key]
chunks.appendleft(chunk)
i += 1
if(i == depth):
break
if(ln >= depth):
txt = "".join(chunks)
elif(ln > 0):
txt = vars.comregex_ai.sub('', vars.prompt) + "".join(chunks)
elif(ln == 0):
txt = vars.comregex_ai.sub('', vars.prompt)
if(force_use_txt):
txt += original_txt
# Scan text for matches on WI keys
wimem = ""
found_entries = set()
for wi in vars.worldinfo:
if(allowed_entries is not None and wi["uid"] not in allowed_entries):
continue
if(allowed_folders is not None and wi["folder"] not in allowed_folders):
continue
if(wi.get("constant", False)):
wimem = wimem + wi["content"] + "\n"
found_entries.add(id(wi))
continue
if(len(wi["key"].strip()) > 0 and (not wi.get("selective", False) or len(wi.get("keysecondary", "").strip()) > 0)):
# Split comma-separated keys
keys = wi["key"].split(",")
keys_secondary = wi.get("keysecondary", "").split(",")
for k in keys:
ky = k
# Remove leading/trailing spaces if the option is enabled
if(vars.wirmvwhtsp):
ky = k.strip()
if ky in txt:
if wi.get("selective", False) and len(keys_secondary):
found = False
for ks in keys_secondary:
ksy = ks
if(vars.wirmvwhtsp):
ksy = ks.strip()
if ksy in txt:
wimem = wimem + wi["content"] + "\n"
found_entries.add(id(wi))
found = True
break
if found:
break
else:
wimem = wimem + wi["content"] + "\n"
found_entries.add(id(wi))
break
return wimem, found_entries
#==================================================================#
# Commit changes to Memory storage
#==================================================================#
def memsubmit(data):
# Maybe check for length at some point
# For now just send it to storage
vars.memory = data
vars.mode = "play"
emit('from_server', {'cmd': 'memmode', 'data': 'false'}, broadcast=True)
# Ask for contents of Author's Note field
emit('from_server', {'cmd': 'getanote', 'data': ''})
#==================================================================#
# Commit changes to Author's Note
#==================================================================#
def anotesubmit(data, template=""):
assert type(data) is str and type(template) is str
# Maybe check for length at some point
# For now just send it to storage
vars.authornote = data
if(vars.authornotetemplate != template):
vars.setauthornotetemplate = template
settingschanged()
vars.authornotetemplate = template
#==================================================================#
# Assembles game data into a request to InferKit API
#==================================================================#
def ikrequest(txt):
# Log request to console
print("{0}Len:{1}, Txt:{2}{3}".format(colors.YELLOW, len(txt), txt, colors.END))
# Build request JSON data
reqdata = {
'forceNoEnd': True,
'length': vars.ikgen,
'prompt': {
'isContinuation': False,
'text': txt
},
'startFromBeginning': False,
'streamResponse': False,
'temperature': vars.temp,
'topP': vars.top_p
}
# Create request
req = requests.post(
vars.url,
json = reqdata,
headers = {
'Authorization': 'Bearer '+vars.apikey
}
)
# Deal with the response
if(req.status_code == 200):
genout = req.json()["data"]["text"]
vars.lua_koboldbridge.outputs[1] = genout
execute_outmod()
if(vars.lua_koboldbridge.regeneration_required):
vars.lua_koboldbridge.regeneration_required = False
genout = vars.lua_koboldbridge.outputs[1]
assert genout is str
print("{0}{1}{2}".format(colors.CYAN, genout, colors.END))
vars.actions.append(genout)
update_story_chunk('last')
emit('from_server', {'cmd': 'texteffect', 'data': vars.actions.get_last_key() + 1 if len(vars.actions) else 0}, broadcast=True)
set_aibusy(0)
else:
# Send error message to web client
er = req.json()
if("error" in er):
code = er["error"]["extensions"]["code"]
elif("errors" in er):
code = er["errors"][0]["extensions"]["code"]
errmsg = "InferKit API Error: {0} - {1}".format(req.status_code, code)
emit('from_server', {'cmd': 'errmsg', 'data': errmsg}, broadcast=True)
set_aibusy(0)
#==================================================================#
# Assembles game data into a request to OpenAI API
#==================================================================#
def oairequest(txt, min, max):
# Log request to console
print("{0}Len:{1}, Txt:{2}{3}".format(colors.YELLOW, len(txt), txt, colors.END))
# Store context in memory to use it for comparison with generated content
vars.lastctx = txt
# Build request JSON data
reqdata = {
'prompt': txt,
'max_tokens': max,
'temperature': vars.temp,
'top_p': vars.top_p,
'n': 1,
'stream': False
}
req = requests.post(
vars.oaiurl,
json = reqdata,
headers = {
'Authorization': 'Bearer '+vars.oaiapikey,
'Content-Type': 'application/json'
}
)
# Deal with the response
if(req.status_code == 200):
genout = req.json()["choices"][0]["text"]
vars.lua_koboldbridge.outputs[1] = genout
execute_outmod()
if(vars.lua_koboldbridge.regeneration_required):
vars.lua_koboldbridge.regeneration_required = False
genout = vars.lua_koboldbridge.outputs[1]
assert genout is str
print("{0}{1}{2}".format(colors.CYAN, genout, colors.END))
vars.actions.append(genout)
update_story_chunk('last')
emit('from_server', {'cmd': 'texteffect', 'data': vars.actions.get_last_key() + 1 if len(vars.actions) else 0}, broadcast=True)
set_aibusy(0)
else:
# Send error message to web client
er = req.json()
if("error" in er):
type = er["error"]["type"]
message = er["error"]["message"]
errmsg = "OpenAI API Error: {0} - {1}".format(type, message)
emit('from_server', {'cmd': 'errmsg', 'data': errmsg}, broadcast=True)
set_aibusy(0)
#==================================================================#
# Forces UI to Play mode
#==================================================================#
def exitModes():
if(vars.mode == "edit"):
emit('from_server', {'cmd': 'editmode', 'data': 'false'}, broadcast=True)
elif(vars.mode == "memory"):
emit('from_server', {'cmd': 'memmode', 'data': 'false'}, broadcast=True)
elif(vars.mode == "wi"):
emit('from_server', {'cmd': 'wimode', 'data': 'false'}, broadcast=True)
vars.mode = "play"
#==================================================================#
# Launch in-browser save prompt
#==================================================================#
def saveas(name):
# Check if filename exists already
name = utils.cleanfilename(name)
if(not fileops.saveexists(name) or (vars.saveow and vars.svowname == name)):
# All clear to save
e = saveRequest(fileops.storypath(name))
vars.saveow = False
vars.svowname = ""
if(e is None):
emit('from_server', {'cmd': 'hidesaveas', 'data': ''})
else:
print("{0}{1}{2}".format(colors.RED, str(e), colors.END))
emit('from_server', {'cmd': 'popuperror', 'data': str(e)})
else:
# File exists, prompt for overwrite
vars.saveow = True
vars.svowname = name
emit('from_server', {'cmd': 'askforoverwrite', 'data': ''})
#==================================================================#
# Launch in-browser story-delete prompt
#==================================================================#
def deletesave(name):
name = utils.cleanfilename(name)
e = fileops.deletesave(name)
if(e is None):
if(vars.smandelete):
emit('from_server', {'cmd': 'hidepopupdelete', 'data': ''})
getloadlist()
else:
emit('from_server', {'cmd': 'popuperror', 'data': "The server denied your request to delete this story"})
else:
print("{0}{1}{2}".format(colors.RED, str(e), colors.END))
emit('from_server', {'cmd': 'popuperror', 'data': str(e)})
#==================================================================#
# Launch in-browser story-rename prompt
#==================================================================#
def renamesave(name, newname):
# Check if filename exists already
name = utils.cleanfilename(name)
newname = utils.cleanfilename(newname)
if(not fileops.saveexists(newname) or name == newname or (vars.saveow and vars.svowname == newname)):
e = fileops.renamesave(name, newname)
vars.saveow = False
vars.svowname = ""
if(e is None):
if(vars.smanrename):
emit('from_server', {'cmd': 'hidepopuprename', 'data': ''})
getloadlist()
else:
emit('from_server', {'cmd': 'popuperror', 'data': "The server denied your request to rename this story"})
else:
print("{0}{1}{2}".format(colors.RED, str(e), colors.END))
emit('from_server', {'cmd': 'popuperror', 'data': str(e)})
else:
# File exists, prompt for overwrite
vars.saveow = True
vars.svowname = newname
emit('from_server', {'cmd': 'askforoverwrite', 'data': ''})
#==================================================================#
# Save the currently running story
#==================================================================#
def save():
# Check if a file is currently open
if(".json" in vars.savedir):
saveRequest(vars.savedir)
else:
emit('from_server', {'cmd': 'saveas', 'data': ''})
#==================================================================#
# Save the story via file browser
#==================================================================#
def savetofile():
savpath = fileops.getsavepath(vars.savedir, "Save Story As", [("Json", "*.json")])
saveRequest(savpath)
#==================================================================#
# Save the story to specified path
#==================================================================#
def saveRequest(savpath):
if(savpath):
# Leave Edit/Memory mode before continuing
exitModes()
# Save path for future saves
vars.savedir = savpath
txtpath = os.path.splitext(savpath)[0] + ".txt"
# Build json to write
js = {}
js["gamestarted"] = vars.gamestarted
js["prompt"] = vars.prompt
js["memory"] = vars.memory
js["authorsnote"] = vars.authornote
js["anotetemplate"] = vars.authornotetemplate
js["actions"] = tuple(vars.actions.values())
js["worldinfo"] = []
js["wifolders_d"] = vars.wifolders_d
js["wifolders_l"] = vars.wifolders_l
# Extract only the important bits of WI
for wi in vars.worldinfo:
if(wi["constant"] or wi["key"] != ""):
js["worldinfo"].append({
"key": wi["key"],
"keysecondary": wi["keysecondary"],
"content": wi["content"],
"comment": wi["comment"],
"folder": wi["folder"],
"selective": wi["selective"],
"constant": wi["constant"]
})
txt = vars.prompt + "".join(vars.actions.values())
# Write it
try:
file = open(savpath, "w")
except Exception as e:
return e
try:
file.write(json.dumps(js, indent=3))
except Exception as e:
file.close()
return e
file.close()
try:
file = open(txtpath, "w")
except Exception as e:
return e
try:
file.write(txt)
except Exception as e:
file.close()
return e
file.close()
filename = path.basename(savpath)
if(filename.endswith('.json')):
filename = filename[:-5]
vars.laststory = filename
emit('from_server', {'cmd': 'setstoryname', 'data': vars.laststory}, broadcast=True)
print("{0}Story saved to {1}!{2}".format(colors.GREEN, path.basename(savpath), colors.END))
#==================================================================#
# Show list of saved stories
#==================================================================#
def getloadlist():
emit('from_server', {'cmd': 'buildload', 'data': fileops.getstoryfiles()})
#==================================================================#
# Show list of soft prompts
#==================================================================#
def getsplist():
if(vars.allowsp):
emit('from_server', {'cmd': 'buildsp', 'data': fileops.getspfiles(vars.modeldim)})
#==================================================================#
# Get list of userscripts
#==================================================================#
def getuslist():
files = {i: v for i, v in enumerate(fileops.getusfiles())}
loaded = []
unloaded = []
userscripts = set(vars.userscripts)
for i in range(len(files)):
if files[i]["filename"] not in userscripts:
unloaded.append(files[i])
files = {files[k]["filename"]: files[k] for k in files}
userscripts = set(files.keys())
for filename in vars.userscripts:
if filename in userscripts:
loaded.append(files[filename])
return unloaded, loaded
#==================================================================#
# Load a saved story via file browser
#==================================================================#
def loadfromfile():
loadpath = fileops.getloadpath(vars.savedir, "Select Story File", [("Json", "*.json")])
loadRequest(loadpath)
#==================================================================#
# Load a stored story from a file
#==================================================================#
def loadRequest(loadpath, filename=None):
if(loadpath):
# Leave Edit/Memory mode before continuing
exitModes()
# Read file contents into JSON object
if(isinstance(loadpath, str)):
with open(loadpath, "r") as file:
js = json.load(file)
if(filename is None):
filename = path.basename(loadpath)
else:
js = loadpath
if(filename is None):
filename = "untitled.json"
# Copy file contents to vars
vars.gamestarted = js["gamestarted"]
vars.prompt = js["prompt"]
vars.memory = js["memory"]
vars.worldinfo = []
vars.worldinfo = []
vars.worldinfo_u = {}
vars.wifolders_d = {int(k): v for k, v in js.get("wifolders_d", {}).items()}
vars.wifolders_l = js.get("wifolders_l", [])
vars.wifolders_u = {uid: [] for uid in vars.wifolders_d}
vars.lastact = ""
vars.submission = ""
vars.lastctx = ""
del vars.actions
vars.actions = structures.KoboldStoryRegister()
actions = collections.deque(js["actions"])
if(len(vars.prompt.strip()) == 0):
while(len(actions)):
action = actions.popleft()
if(len(action.strip()) != 0):
vars.prompt = action
break
else:
vars.gamestarted = False
if(vars.gamestarted):
for s in actions:
vars.actions.append(s)
# Try not to break older save files
if("authorsnote" in js):
vars.authornote = js["authorsnote"]
else:
vars.authornote = ""
if("anotetemplate" in js):
vars.authornotetemplate = js["anotetemplate"]
else:
vars.authornotetemplate = "[Author's note: <|>]"
if("worldinfo" in js):
num = 0
for wi in js["worldinfo"]:
vars.worldinfo.append({
"key": wi["key"],
"keysecondary": wi.get("keysecondary", ""),
"content": wi["content"],
"comment": wi.get("comment", ""),
"folder": wi.get("folder", None),
"num": num,
"init": True,
"selective": wi.get("selective", False),
"constant": wi.get("constant", False),
"uid": None,
})
while(True):
uid = int.from_bytes(os.urandom(4), "little", signed=True)
if(uid not in vars.worldinfo_u):
break
vars.worldinfo_u[uid] = vars.worldinfo[-1]
vars.worldinfo[-1]["uid"] = uid
if(vars.worldinfo[-1]["folder"] is not None):
vars.wifolders_u[vars.worldinfo[-1]["folder"]].append(vars.worldinfo[-1])
num += 1
for uid in vars.wifolders_l + [None]:
vars.worldinfo.append({"key": "", "keysecondary": "", "content": "", "comment": "", "folder": uid, "num": None, "init": False, "selective": False, "constant": False, "uid": None})
while(True):
uid = int.from_bytes(os.urandom(4), "little", signed=True)
if(uid not in vars.worldinfo_u):
break
vars.worldinfo_u[uid] = vars.worldinfo[-1]
vars.worldinfo[-1]["uid"] = uid
if(vars.worldinfo[-1]["folder"] is not None):
vars.wifolders_u[vars.worldinfo[-1]["folder"]].append(vars.worldinfo[-1])
stablesortwi()
vars.worldinfo_i = [wi for wi in vars.worldinfo if wi["init"]]
# Save path for save button
vars.savedir = loadpath
# Clear loadselect var
vars.loadselect = ""
# Refresh game screen
_filename = filename
if(filename.endswith('.json')):
_filename = filename[:-5]
vars.laststory = _filename
emit('from_server', {'cmd': 'setstoryname', 'data': vars.laststory}, broadcast=True)
sendwi()
emit('from_server', {'cmd': 'setmemory', 'data': vars.memory}, broadcast=True)
emit('from_server', {'cmd': 'setanote', 'data': vars.authornote}, broadcast=True)
emit('from_server', {'cmd': 'setanotetemplate', 'data': vars.authornotetemplate}, broadcast=True)
refresh_story()
emit('from_server', {'cmd': 'setgamestate', 'data': 'ready'}, broadcast=True)
emit('from_server', {'cmd': 'hidegenseqs', 'data': ''}, broadcast=True)
print("{0}Story loaded from {1}!{2}".format(colors.GREEN, filename, colors.END))
#==================================================================#
# Load a soft prompt from a file
#==================================================================#
def spRequest(filename):
vars.spfilename = ""
settingschanged()
if(len(filename) == 0):
vars.sp = None
vars.sp_length = 0
return
global np
if 'np' not in globals():
import numpy as np
z, version, shape, fortran_order, dtype = fileops.checksp(filename, vars.modeldim)
assert isinstance(z, zipfile.ZipFile)
with z.open('meta.json') as f:
vars.spmeta = json.load(f)
z.close()
with np.load(fileops.sppath(filename), allow_pickle=False) as f:
tensor = f['tensor.npy']
# If the tensor is in bfloat16 format, convert it to float32
if(tensor.dtype == 'V2'):
tensor.dtype = np.uint16
tensor = np.uint32(tensor) << 16
tensor.dtype = np.float32
if(tensor.dtype != np.float16):
tensor = np.float32(tensor)
assert not np.isinf(tensor).any() and not np.isnan(tensor).any()
vars.sp_length = tensor.shape[0]
if(vars.model in ("TPUMeshTransformerGPTJ",)):
rows = tensor.shape[0]
padding_amount = tpu_mtj_backend.params["seq"] - (tpu_mtj_backend.params["seq"] % -tpu_mtj_backend.params["cores_per_replica"]) - rows
tensor = np.pad(tensor, ((0, padding_amount), (0, 0)))
tensor = tensor.reshape(
tpu_mtj_backend.params["cores_per_replica"],
-1,
tpu_mtj_backend.params["d_model"],
)
vars.sp = tpu_mtj_backend.shard_xmap(np.float32(tensor))
else:
vars.sp = torch.from_numpy(tensor)
vars.spfilename = filename
settingschanged()
#==================================================================#
# Import an AIDungon game exported with Mimi's tool
#==================================================================#
def importRequest():
importpath = fileops.getloadpath(vars.savedir, "Select AID CAT File", [("Json", "*.json")])
if(importpath):
# Leave Edit/Memory mode before continuing
exitModes()
# Read file contents into JSON object
file = open(importpath, "rb")
vars.importjs = json.load(file)
# If a bundle file is being imported, select just the Adventures object
if type(vars.importjs) is dict and "stories" in vars.importjs:
vars.importjs = vars.importjs["stories"]
# Clear Popup Contents
emit('from_server', {'cmd': 'clearpopup', 'data': ''}, broadcast=True)
# Initialize vars
num = 0
vars.importnum = -1
# Get list of stories
for story in vars.importjs:
ob = {}
ob["num"] = num
if(story["title"] != "" and story["title"] != None):
ob["title"] = story["title"]
else:
ob["title"] = "(No Title)"
if(story["description"] != "" and story["description"] != None):
ob["descr"] = story["description"]
else:
ob["descr"] = "(No Description)"
if("actions" in story):
ob["acts"] = len(story["actions"])
elif("actionWindow" in story):
ob["acts"] = len(story["actionWindow"])
emit('from_server', {'cmd': 'addimportline', 'data': ob})
num += 1
# Show Popup
emit('from_server', {'cmd': 'popupshow', 'data': True})
#==================================================================#
# Import an AIDungon game selected in popup
#==================================================================#
def importgame():
if(vars.importnum >= 0):
# Cache reference to selected game
ref = vars.importjs[vars.importnum]
# Copy game contents to vars
vars.gamestarted = True
# Support for different versions of export script
if("actions" in ref):
if(len(ref["actions"]) > 0):
vars.prompt = ref["actions"][0]["text"]
else:
vars.prompt = ""
elif("actionWindow" in ref):
if(len(ref["actionWindow"]) > 0):
vars.prompt = ref["actionWindow"][0]["text"]
else:
vars.prompt = ""
else:
vars.prompt = ""
vars.memory = ref["memory"]
vars.authornote = ref["authorsNote"] if type(ref["authorsNote"]) is str else ""
vars.authornotetemplate = "[Author's note: <|>]"
vars.actions = structures.KoboldStoryRegister()
vars.worldinfo = []
vars.worldinfo_i = []
vars.worldinfo_u = {}
vars.wifolders_d = {}
vars.wifolders_l = []
vars.wifolders_u = {uid: [] for uid in vars.wifolders_d}
vars.lastact = ""
vars.submission = ""
vars.lastctx = ""
# Get all actions except for prompt
if("actions" in ref):
if(len(ref["actions"]) > 1):
for act in ref["actions"][1:]:
vars.actions.append(act["text"])
elif("actionWindow" in ref):
if(len(ref["actionWindow"]) > 1):
for act in ref["actionWindow"][1:]:
vars.actions.append(act["text"])
# Get just the important parts of world info
if(ref["worldInfo"] != None):
if(len(ref["worldInfo"]) > 1):
num = 0
for wi in ref["worldInfo"]:
vars.worldinfo.append({
"key": wi["keys"],
"keysecondary": wi.get("keysecondary", ""),
"content": wi["entry"],
"comment": wi.get("comment", ""),
"folder": wi.get("folder", None),
"num": num,
"init": True,
"selective": wi.get("selective", False),
"constant": wi.get("constant", False),
"uid": None,
})
while(True):
uid = int.from_bytes(os.urandom(4), "little", signed=True)
if(uid not in vars.worldinfo_u):
break
vars.worldinfo_u[uid] = vars.worldinfo[-1]
vars.worldinfo[-1]["uid"] = uid
if(vars.worldinfo[-1]["folder"]) is not None:
vars.wifolders_u[vars.worldinfo[-1]["folder"]].append(vars.worldinfo[-1])
num += 1
for uid in vars.wifolders_l + [None]:
vars.worldinfo.append({"key": "", "keysecondary": "", "content": "", "comment": "", "folder": uid, "num": None, "init": False, "selective": False, "constant": False, "uid": None})
while(True):
uid = int.from_bytes(os.urandom(4), "little", signed=True)
if(uid not in vars.worldinfo_u):
break
vars.worldinfo_u[uid] = vars.worldinfo[-1]
vars.worldinfo[-1]["uid"] = uid
if(vars.worldinfo[-1]["folder"] is not None):
vars.wifolders_u[vars.worldinfo[-1]["folder"]].append(vars.worldinfo[-1])
stablesortwi()
vars.worldinfo_i = [wi for wi in vars.worldinfo if wi["init"]]
# Clear import data
vars.importjs = {}
# Reset current save
vars.savedir = getcwd()+"\stories"
# Refresh game screen
vars.laststory = None
emit('from_server', {'cmd': 'setstoryname', 'data': vars.laststory}, broadcast=True)
sendwi()
emit('from_server', {'cmd': 'setmemory', 'data': vars.memory}, broadcast=True)
emit('from_server', {'cmd': 'setanote', 'data': vars.authornote}, broadcast=True)
emit('from_server', {'cmd': 'setanotetemplate', 'data': vars.authornotetemplate}, broadcast=True)
refresh_story()
emit('from_server', {'cmd': 'setgamestate', 'data': 'ready'}, broadcast=True)
emit('from_server', {'cmd': 'hidegenseqs', 'data': ''}, broadcast=True)
#==================================================================#
# Import an aidg.club prompt and start a new game with it.
#==================================================================#
def importAidgRequest(id):
exitModes()
urlformat = "https://prompts.aidg.club/api/"
req = requests.get(urlformat+id)
if(req.status_code == 200):
js = req.json()
# Import game state
vars.gamestarted = True
vars.prompt = js["promptContent"]
vars.memory = js["memory"]
vars.authornote = js["authorsNote"]
vars.authornotetemplate = "[Author's note: <|>]"
vars.actions = structures.KoboldStoryRegister()
vars.worldinfo = []
vars.worldinfo_i = []
vars.worldinfo_u = {}
vars.wifolders_d = {}
vars.wifolders_l = []
vars.wifolders_u = {uid: [] for uid in vars.wifolders_d}
vars.lastact = ""
vars.submission = ""
vars.lastctx = ""
num = 0
for wi in js["worldInfos"]:
vars.worldinfo.append({
"key": wi["keys"],
"keysecondary": wi.get("keysecondary", ""),
"content": wi["entry"],
"comment": wi.get("comment", ""),
"folder": wi.get("folder", None),
"num": num,
"init": True,
"selective": wi.get("selective", False),
"constant": wi.get("constant", False),
"uid": None,
})
while(True):
uid = int.from_bytes(os.urandom(4), "little", signed=True)
if(uid not in vars.worldinfo_u):
break
vars.worldinfo_u[uid] = vars.worldinfo[-1]
vars.worldinfo[-1]["uid"] = uid
if(vars.worldinfo[-1]["folder"]) is not None:
vars.wifolders_u[vars.worldinfo[-1]["folder"]].append(vars.worldinfo[-1])
num += 1
for uid in vars.wifolders_l + [None]:
vars.worldinfo.append({"key": "", "keysecondary": "", "content": "", "comment": "", "folder": uid, "num": None, "init": False, "selective": False, "constant": False, "uid": None})
while(True):
uid = int.from_bytes(os.urandom(4), "little", signed=True)
if(uid not in vars.worldinfo_u):
break
vars.worldinfo_u[uid] = vars.worldinfo[-1]
vars.worldinfo[-1]["uid"] = uid
if(vars.worldinfo[-1]["folder"] is not None):
vars.wifolders_u[vars.worldinfo[-1]["folder"]].append(vars.worldinfo[-1])
stablesortwi()
vars.worldinfo_i = [wi for wi in vars.worldinfo if wi["init"]]
# Reset current save
vars.savedir = getcwd()+"\stories"
# Refresh game screen
vars.laststory = None
emit('from_server', {'cmd': 'setstoryname', 'data': vars.laststory}, broadcast=True)
sendwi()
emit('from_server', {'cmd': 'setmemory', 'data': vars.memory}, broadcast=True)
emit('from_server', {'cmd': 'setanote', 'data': vars.authornote}, broadcast=True)
emit('from_server', {'cmd': 'setanotetemplate', 'data': vars.authornotetemplate}, broadcast=True)
refresh_story()
emit('from_server', {'cmd': 'setgamestate', 'data': 'ready'}, broadcast=True)
#==================================================================#
# Import World Info JSON file
#==================================================================#
def wiimportrequest():
importpath = fileops.getloadpath(vars.savedir, "Select World Info File", [("Json", "*.json")])
if(importpath):
file = open(importpath, "rb")
js = json.load(file)
if(len(js) > 0):
# If the most recent WI entry is blank, remove it.
if(not vars.worldinfo[-1]["init"]):
del vars.worldinfo[-1]
# Now grab the new stuff
num = len(vars.worldinfo)
for wi in js:
vars.worldinfo.append({
"key": wi["keys"],
"keysecondary": wi.get("keysecondary", ""),
"content": wi["entry"],
"comment": wi.get("comment", ""),
"folder": wi.get("folder", None),
"num": num,
"init": True,
"selective": wi.get("selective", False),
"constant": wi.get("constant", False),
"uid": None,
})
while(True):
uid = int.from_bytes(os.urandom(4), "little", signed=True)
if(uid not in vars.worldinfo_u):
break
vars.worldinfo_u[uid] = vars.worldinfo[-1]
vars.worldinfo[-1]["uid"] = uid
if(vars.worldinfo[-1]["folder"]) is not None:
vars.wifolders_u[vars.worldinfo[-1]["folder"]].append(vars.worldinfo[-1])
num += 1
for uid in [None]:
vars.worldinfo.append({"key": "", "keysecondary": "", "content": "", "comment": "", "folder": uid, "num": None, "init": False, "selective": False, "constant": False, "uid": None})
while(True):
uid = int.from_bytes(os.urandom(4), "little", signed=True)
if(uid not in vars.worldinfo_u):
break
vars.worldinfo_u[uid] = vars.worldinfo[-1]
vars.worldinfo[-1]["uid"] = uid
if(vars.worldinfo[-1]["folder"] is not None):
vars.wifolders_u[vars.worldinfo[-1]["folder"]].append(vars.worldinfo[-1])
print("{0}".format(vars.worldinfo[0]))
# Refresh game screen
sendwi()
#==================================================================#
# Starts a new story
#==================================================================#
def newGameRequest():
# Leave Edit/Memory mode before continuing
exitModes()
# Clear vars values
vars.gamestarted = False
vars.prompt = ""
vars.memory = ""
vars.actions = structures.KoboldStoryRegister()
vars.authornote = ""
vars.authornotetemplate = vars.setauthornotetemplate
vars.worldinfo = []
vars.worldinfo_i = []
vars.worldinfo_u = {}
vars.wifolders_d = {}
vars.wifolders_l = []
vars.lastact = ""
vars.submission = ""
vars.lastctx = ""
# Reset current save
vars.savedir = getcwd()+"\stories"
# Refresh game screen
vars.laststory = None
emit('from_server', {'cmd': 'setstoryname', 'data': vars.laststory}, broadcast=True)
sendwi()
emit('from_server', {'cmd': 'setmemory', 'data': vars.memory}, broadcast=True)
emit('from_server', {'cmd': 'setanote', 'data': vars.authornote}, broadcast=True)
emit('from_server', {'cmd': 'setanotetemplate', 'data': vars.authornotetemplate}, broadcast=True)
setStartState()
def randomGameRequest(topic, memory=""):
if(vars.noai):
newGameRequest()
return
vars.recentrng = topic
vars.recentrngm = memory
newGameRequest()
_memory = memory
if(len(memory) > 0):
_memory = memory.rstrip() + "\n\n"
vars.memory = _memory + "You generate the following " + topic + " story concept :"
vars.lua_koboldbridge.feedback = None
actionsubmit("", force_submit=True, force_prompt_gen=True)
vars.memory = memory
# Load settings from client.settings
loadmodelsettings()
loadsettings()
#==================================================================#
# Final startup commands to launch Flask app
#==================================================================#
print("", end="", flush=True)
if __name__ == "__main__":
print("{0}\nStarting webserver...{1}".format(colors.GREEN, colors.END), flush=True)
# Start Flask/SocketIO (Blocking, so this must be last method!)
#socketio.run(app, host='0.0.0.0', port=5000)
if(vars.remote):
if(args.ngrok):
from flask_ngrok import _run_ngrok
cloudflare = _run_ngrok()
else:
from flask_cloudflared import _run_cloudflared
cloudflare = _run_cloudflared(5000)
with open('cloudflare.log', 'w') as cloudflarelog:
cloudflarelog.write("KoboldAI has finished loading and is available at the following link : " + cloudflare)
print(format(colors.GREEN) + "KoboldAI has finished loading and is available at the following link : " + cloudflare + format(colors.END))
vars.serverstarted = True
socketio.run(app, host='0.0.0.0', port=5000)
else:
import webbrowser
webbrowser.open_new('http://localhost:5000')
print("{0}Server started!\nYou may now connect with a browser at http://127.0.0.1:5000/{1}".format(colors.GREEN, colors.END))
vars.serverstarted = True
socketio.run(app, port=5000)
else:
print("{0}\nServer started in WSGI mode!{1}".format(colors.GREEN, colors.END), flush=True)