2078 lines
84 KiB
Python
2078 lines
84 KiB
Python
#==================================================================#
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# KoboldAI Client
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# Version: 1.15.0
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# By: KoboldAIDev
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#==================================================================#
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# External packages
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from os import path, getcwd
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import re
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import tkinter as tk
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from tkinter import messagebox
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import json
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import requests
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import html
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import argparse
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import sys
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import gc
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# KoboldAI
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import fileops
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import gensettings
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from utils import debounce
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import utils
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import breakmodel
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#==================================================================#
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# Variables & Storage
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#==================================================================#
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# Terminal tags for colored text
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class colors:
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PURPLE = '\033[95m'
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BLUE = '\033[94m'
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CYAN = '\033[96m'
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GREEN = '\033[92m'
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YELLOW = '\033[93m'
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RED = '\033[91m'
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END = '\033[0m'
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UNDERLINE = '\033[4m'
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# AI models
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modellist = [
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["GPT Neo 1.3B", "EleutherAI/gpt-neo-1.3B", "8GB"],
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["GPT Neo 2.7B", "EleutherAI/gpt-neo-2.7B", "16GB"],
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["GPT-2", "gpt2", "1.2GB"],
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["GPT-2 Med", "gpt2-medium", "2GB"],
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["GPT-2 Large", "gpt2-large", "16GB"],
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["GPT-2 XL", "gpt2-xl", "16GB"],
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["InferKit API (requires API key)", "InferKit", ""],
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["Custom Neo (eg Neo-horni)", "NeoCustom", ""],
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["Custom GPT-2 (eg CloverEdition)", "GPT2Custom", ""],
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["Google Colab", "Colab", ""],
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["OpenAI API (requires API key)", "OAI", ""],
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["Read Only (No AI)", "ReadOnly", ""]
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]
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# Variables
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class vars:
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lastact = "" # The last action received from the user
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lastctx = "" # The last context submitted to the generator
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model = "" # Model ID string chosen at startup
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noai = False # Runs the script without starting up the transformers pipeline
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aibusy = False # Stops submissions while the AI is working
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max_length = 1024 # Maximum number of tokens to submit per action
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ikmax = 3000 # Maximum number of characters to submit to InferKit
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genamt = 80 # Amount of text for each action to generate
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ikgen = 200 # Number of characters for InferKit to generate
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rep_pen = 1.1 # Default generator repetition_penalty
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temp = 0.5 # Default generator temperature
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top_p = 0.9 # Default generator top_p
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top_k = 0 # Default generator top_k
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tfs = 0.0 # Default generator tfs (tail-free sampling)
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numseqs = 1 # Number of sequences to ask the generator to create
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gamestarted = False # Whether the game has started (disables UI elements)
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prompt = "" # Prompt
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memory = "" # Text submitted to memory field
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authornote = "" # Text submitted to Author's Note field
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andepth = 3 # How far back in history to append author's note
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actions = [] # Array of actions submitted by user and AI
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worldinfo = [] # Array of World Info key/value objects
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badwords = [] # Array of str/chr values that should be removed from output
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badwordsids = [] # Tokenized array of badwords
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deletewi = -1 # Temporary storage for index to delete
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wirmvwhtsp = False # Whether to remove leading whitespace from WI entries
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widepth = 3 # How many historical actions to scan for WI hits
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mode = "play" # Whether the interface is in play, memory, or edit mode
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editln = 0 # Which line was last selected in Edit Mode
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url = "https://api.inferkit.com/v1/models/standard/generate" # InferKit API URL
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oaiurl = "" # OpenAI API URL
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oaiengines = "https://api.openai.com/v1/engines"
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colaburl = "" # Ngrok url for Google Colab mode
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apikey = "" # API key to use for InferKit API calls
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oaiapikey = "" # API key to use for OpenAI API calls
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savedir = getcwd()+"\stories"
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hascuda = False # Whether torch has detected CUDA on the system
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usegpu = False # Whether to launch pipeline with GPU support
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custmodpth = "" # Filesystem location of custom model to run
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formatoptns = {} # Container for state of formatting options
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importnum = -1 # Selection on import popup list
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importjs = {} # Temporary storage for import data
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loadselect = "" # Temporary storage for filename to load
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svowname = "" # Filename that was flagged for overwrite confirm
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saveow = False # Whether or not overwrite confirm has been displayed
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genseqs = [] # Temporary storage for generated sequences
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useprompt = True # Whether to send the full prompt with every submit action
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breakmodel = False # For GPU users, whether to use both system RAM and VRAM to conserve VRAM while offering speedup compared to CPU-only
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bmsupported = False # Whether the breakmodel option is supported (GPT-Neo/GPT-J only, currently)
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acregex_ai = re.compile(r'\n* *>(.|\n)*') # Pattern for matching adventure actions from the AI so we can remove them
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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)
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actionmode = 1
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adventure = False
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remote = False
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#==================================================================#
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# Function to get model selection at startup
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#==================================================================#
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def getModelSelection():
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print(" # Model V/RAM\n =========================================")
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i = 1
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for m in modellist:
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print(" {0} - {1}\t\t{2}".format("{:<2}".format(i), m[0].ljust(15), m[2]))
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i += 1
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print(" ");
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modelsel = 0
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vars.model = ''
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while(vars.model == ''):
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modelsel = input("Model #> ")
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if(modelsel.isnumeric() and int(modelsel) > 0 and int(modelsel) <= len(modellist)):
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vars.model = modellist[int(modelsel)-1][1]
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else:
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print("{0}Please enter a valid selection.{1}".format(colors.RED, colors.END))
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# If custom model was selected, get the filesystem location and store it
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if(vars.model == "NeoCustom" or vars.model == "GPT2Custom"):
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print("{0}Please choose the folder where pytorch_model.bin is located:{1}\n".format(colors.CYAN, colors.END))
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modpath = fileops.getdirpath(getcwd(), "Select Model Folder")
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if(modpath):
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# Save directory to vars
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vars.custmodpth = modpath
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else:
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# Print error and retry model selection
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print("{0}Model select cancelled!{1}".format(colors.RED, colors.END))
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print("{0}Select an AI model to continue:{1}\n".format(colors.CYAN, colors.END))
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getModelSelection()
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#==================================================================#
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# Return all keys in tokenizer dictionary containing char
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#==================================================================#
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def gettokenids(char):
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keys = []
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for key in vocab_keys:
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if(key.find(char) != -1):
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keys.append(key)
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return keys
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#==================================================================#
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# Startup
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#==================================================================#
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# Parsing Parameters
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parser = argparse.ArgumentParser(description="KoboldAI Server")
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parser.add_argument("--remote", action='store_true', help="Optimizes KoboldAI for Remote Play")
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parser.add_argument("--model", help="Specify the Model Type to skip the Menu")
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parser.add_argument("--path", help="Specify the Path for local models (For model NeoCustom or GPT2Custom)")
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parser.add_argument("--cpu", action='store_true', help="By default unattended launches are on the GPU use this option to force CPU usage.")
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parser.add_argument("--breakmodel", action='store_true', help="For models that support GPU-CPU hybrid generation, use this feature instead of GPU or CPU generation")
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parser.add_argument("--breakmodel_layers", type=int, help="Specify the number of layers to commit to system RAM if --breakmodel is used")
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args = parser.parse_args()
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vars.model = args.model;
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if args.remote:
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vars.remote = True;
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# Select a model to run
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if args.model:
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print("Welcome to KoboldAI!\nYou have selected the following Model:", vars.model)
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if args.path:
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print("You have selected the following path for your Model :", args.path)
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vars.custmodpth = args.path;
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vars.colaburl = args.path + "/request"; # Lets just use the same parameter to keep it simple
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else:
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print("{0}Welcome to the KoboldAI Client!\nSelect an AI model to continue:{1}\n".format(colors.CYAN, colors.END))
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getModelSelection()
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# If transformers model was selected & GPU available, ask to use CPU or GPU
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if(not vars.model in ["InferKit", "Colab", "OAI", "ReadOnly"]):
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# Test for GPU support
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import torch
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print("{0}Looking for GPU support...{1}".format(colors.PURPLE, colors.END), end="")
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vars.hascuda = torch.cuda.is_available()
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vars.bmsupported = vars.model in ("EleutherAI/gpt-neo-1.3B", "EleutherAI/gpt-neo-2.7B", "NeoCustom")
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if(vars.hascuda):
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print("{0}FOUND!{1}".format(colors.GREEN, colors.END))
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else:
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print("{0}NOT FOUND!{1}".format(colors.YELLOW, colors.END))
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if args.model:
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if(vars.hascuda):
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genselected = True
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vars.usegpu = True
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vars.breakmodel = False
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if(args.cpu):
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vars.usegpu = False
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vars.breakmodel = False
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if(vars.bmsupported and args.breakmodel):
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vars.usegpu = False
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vars.breakmodel = True
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elif(vars.hascuda):
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if(vars.bmsupported):
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print(colors.YELLOW + "You're using a model that supports GPU-CPU hybrid generation!\nCurrently only GPT-Neo models and GPT-J-6B support this feature.")
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print("{0}Use GPU or CPU for generation?: (Default GPU){1}".format(colors.CYAN, colors.END))
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if(vars.bmsupported):
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print(f" 1 - GPU\n 2 - CPU\n 3 - Both (slower than GPU-only but uses less VRAM)\n")
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else:
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print(" 1 - GPU\n 2 - CPU\n")
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genselected = False
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if(vars.hascuda):
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while(genselected == False):
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genselect = input("Mode> ")
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if(genselect == ""):
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vars.breakmodel = False
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vars.usegpu = True
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genselected = True
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elif(genselect.isnumeric() and int(genselect) == 1):
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vars.breakmodel = False
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vars.usegpu = True
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genselected = True
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elif(genselect.isnumeric() and int(genselect) == 2):
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vars.breakmodel = False
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vars.usegpu = False
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genselected = True
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elif(vars.bmsupported and genselect.isnumeric() and int(genselect) == 3):
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vars.breakmodel = True
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vars.usegpu = False
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genselected = True
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else:
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print("{0}Please enter a valid selection.{1}".format(colors.RED, colors.END))
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# Ask for API key if InferKit was selected
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if(vars.model == "InferKit"):
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if(not path.exists("client.settings")):
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# If the client settings file doesn't exist, create it
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print("{0}Please enter your InferKit API key:{1}\n".format(colors.CYAN, colors.END))
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vars.apikey = input("Key> ")
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# Write API key to file
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file = open("client.settings", "w")
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try:
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js = {"apikey": vars.apikey}
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file.write(json.dumps(js, indent=3))
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finally:
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file.close()
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else:
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# Otherwise open it up
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file = open("client.settings", "r")
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# Check if API key exists
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js = json.load(file)
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if("apikey" in js and js["apikey"] != ""):
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# API key exists, grab it and close the file
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vars.apikey = js["apikey"]
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file.close()
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else:
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# Get API key, add it to settings object, and write it to disk
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print("{0}Please enter your InferKit API key:{1}\n".format(colors.CYAN, colors.END))
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vars.apikey = input("Key> ")
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js["apikey"] = vars.apikey
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# Write API key to file
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file = open("client.settings", "w")
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try:
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file.write(json.dumps(js, indent=3))
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finally:
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file.close()
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# Ask for API key if OpenAI was selected
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if(vars.model == "OAI"):
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if(not path.exists("client.settings")):
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# If the client settings file doesn't exist, create it
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print("{0}Please enter your OpenAI API key:{1}\n".format(colors.CYAN, colors.END))
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vars.oaiapikey = input("Key> ")
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# Write API key to file
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file = open("client.settings", "w")
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try:
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js = {"oaiapikey": vars.oaiapikey}
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file.write(json.dumps(js, indent=3))
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finally:
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file.close()
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else:
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# Otherwise open it up
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file = open("client.settings", "r")
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# Check if API key exists
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js = json.load(file)
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if("oaiapikey" in js and js["oaiapikey"] != ""):
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# API key exists, grab it and close the file
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vars.oaiapikey = js["oaiapikey"]
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file.close()
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else:
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# Get API key, add it to settings object, and write it to disk
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print("{0}Please enter your OpenAI API key:{1}\n".format(colors.CYAN, colors.END))
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vars.oaiapikey = input("Key> ")
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js["oaiapikey"] = vars.oaiapikey
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# Write API key to file
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file = open("client.settings", "w")
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try:
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file.write(json.dumps(js, indent=3))
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finally:
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file.close()
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# Get list of models from OAI
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print("{0}Retrieving engine list...{1}".format(colors.PURPLE, colors.END), end="")
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req = requests.get(
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vars.oaiengines,
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headers = {
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'Authorization': 'Bearer '+vars.oaiapikey
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}
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)
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if(req.status_code == 200):
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print("{0}OK!{1}".format(colors.GREEN, colors.END))
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print("{0}Please select an engine to use:{1}\n".format(colors.CYAN, colors.END))
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engines = req.json()["data"]
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# Print list of engines
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i = 0
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for en in engines:
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print(" {0} - {1} ({2})".format(i, en["id"], "\033[92mready\033[0m" if en["ready"] == True else "\033[91mnot ready\033[0m"))
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i += 1
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# Get engine to use
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print("")
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engselected = False
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while(engselected == False):
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engine = input("Engine #> ")
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if(engine.isnumeric() and int(engine) < len(engines)):
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vars.oaiurl = "https://api.openai.com/v1/engines/{0}/completions".format(engines[int(engine)]["id"])
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engselected = True
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else:
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print("{0}Please enter a valid selection.{1}".format(colors.RED, colors.END))
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else:
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# Something went wrong, print the message and quit since we can't initialize an engine
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print("{0}ERROR!{1}".format(colors.RED, colors.END))
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print(req.json())
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quit()
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# Ask for ngrok url if Google Colab was selected
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if(vars.model == "Colab"):
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if(vars.colaburl == ""):
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print("{0}Please enter the ngrok.io or trycloudflare.com URL displayed in Google Colab:{1}\n".format(colors.CYAN, colors.END))
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vars.colaburl = input("URL> ") + "/request"
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if(vars.model == "ReadOnly"):
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vars.noai = True
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# Set logging level to reduce chatter from Flask
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import logging
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log = logging.getLogger('werkzeug')
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log.setLevel(logging.ERROR)
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# Start flask & SocketIO
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print("{0}Initializing Flask... {1}".format(colors.PURPLE, colors.END), end="")
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from flask import Flask, render_template
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from flask_socketio import SocketIO, emit
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app = Flask(__name__)
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app.config['SECRET KEY'] = 'secret!'
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socketio = SocketIO(app)
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print("{0}OK!{1}".format(colors.GREEN, colors.END))
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# Start transformers and create pipeline
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if(not vars.model in ["InferKit", "Colab", "OAI", "ReadOnly"]):
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if(not vars.noai):
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print("{0}Initializing transformers, please wait...{1}".format(colors.PURPLE, colors.END))
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from transformers import pipeline, GPT2Tokenizer, GPT2LMHeadModel, GPTNeoForCausalLM, GPTNeoModel, AutoModel
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# If custom GPT Neo model was chosen
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if(vars.model == "NeoCustom"):
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model = GPTNeoForCausalLM.from_pretrained(vars.custmodpth)
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tokenizer = GPT2Tokenizer.from_pretrained(vars.custmodpth)
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# Is CUDA available? If so, use GPU, otherwise fall back to CPU
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if(vars.hascuda):
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if(vars.usegpu):
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generator = pipeline('text-generation', model=model, tokenizer=tokenizer, device=0)
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elif(vars.breakmodel): # Use both RAM and VRAM (breakmodel)
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n_layers = model.config.num_layers
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breakmodel.total_blocks = n_layers
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model.half().to('cpu')
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gc.collect()
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model.transformer.wte.to(breakmodel.gpu_device)
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model.transformer.ln_f.to(breakmodel.gpu_device)
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if(hasattr(model, 'lm_head')):
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model.lm_head.to(breakmodel.gpu_device)
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if(not hasattr(model.config, 'rotary') or not model.config.rotary):
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model.transformer.wpe.to(breakmodel.gpu_device)
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gc.collect()
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if(args.breakmodel_layers is not None):
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breakmodel.ram_blocks = max(0, min(n_layers, args.breakmodel_layers))
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else:
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print(colors.CYAN + "\nHow many layers would you like to put into system RAM?")
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print("The more of them you put into system RAM, the slower it will run,")
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print("but it will require less VRAM")
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print("(roughly proportional to number of layers).")
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print(f"This model has{colors.YELLOW} {n_layers} {colors.CYAN}layers.{colors.END}\n")
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while(True):
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layerselect = input("# of layers> ")
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if(layerselect.isnumeric() and 0 <= int(layerselect) <= n_layers):
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breakmodel.ram_blocks = int(layerselect)
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break
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else:
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print(f"{colors.RED}Please enter an integer between 0 and {n_layers}.{colors.END}")
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print(f"{colors.PURPLE}Will commit{colors.YELLOW} {breakmodel.ram_blocks} {colors.PURPLE}of{colors.YELLOW} {n_layers} {colors.PURPLE}layers to system RAM.{colors.END}")
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GPTNeoModel.forward = breakmodel.new_forward
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generator = model.generate
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else:
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generator = pipeline('text-generation', model=model, tokenizer=tokenizer)
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else:
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generator = pipeline('text-generation', model=model, tokenizer=tokenizer)
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# If custom GPT2 model was chosen
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elif(vars.model == "GPT2Custom"):
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model = GPT2LMHeadModel.from_pretrained(vars.custmodpth)
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tokenizer = GPT2Tokenizer.from_pretrained(vars.custmodpth)
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# Is CUDA available? If so, use GPU, otherwise fall back to CPU
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if(vars.hascuda and vars.usegpu):
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generator = pipeline('text-generation', model=model, tokenizer=tokenizer, device=0)
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else:
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generator = pipeline('text-generation', model=model, tokenizer=tokenizer)
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# If base HuggingFace model was chosen
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else:
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# Is CUDA available? If so, use GPU, otherwise fall back to CPU
|
|
tokenizer = GPT2Tokenizer.from_pretrained(vars.model)
|
|
if(vars.hascuda):
|
|
if(vars.usegpu):
|
|
generator = pipeline('text-generation', model=vars.model, device=0)
|
|
elif(vars.breakmodel): # Use both RAM and VRAM (breakmodel)
|
|
model = AutoModel.from_pretrained(vars.model)
|
|
n_layers = model.config.num_layers
|
|
breakmodel.total_blocks = n_layers
|
|
model.half().to('cpu')
|
|
gc.collect()
|
|
model.transformer.wte.to(breakmodel.gpu_device)
|
|
model.transformer.ln_f.to(breakmodel.gpu_device)
|
|
if(hasattr(model, 'lm_head')):
|
|
model.lm_head.to(breakmodel.gpu_device)
|
|
if(not hasattr(model.config, 'rotary') or not model.config.rotary):
|
|
model.transformer.wpe.to(breakmodel.gpu_device)
|
|
gc.collect()
|
|
if(args.breakmodel_layers is not None):
|
|
breakmodel.ram_blocks = max(0, min(n_layers, args.breakmodel_layers))
|
|
else:
|
|
print(colors.CYAN + "\nHow many layers would you like to put into system RAM?")
|
|
print("The more of them you put into system RAM, the slower it will run,")
|
|
print("but it will require less VRAM")
|
|
print("(roughly proportional to number of layers).")
|
|
print(f"This model has{colors.YELLOW} {n_layers} {colors.CYAN}layers.{colors.END}\n")
|
|
while(True):
|
|
layerselect = input("# of layers> ")
|
|
if(layerselect.isnumeric() and 0 <= int(layerselect) <= n_layers):
|
|
breakmodel.ram_blocks = int(layerselect)
|
|
break
|
|
else:
|
|
print(f"{colors.RED}Please enter an integer between 0 and {n_layers}.{colors.END}")
|
|
print(f"{colors.PURPLE}Will commit{colors.YELLOW} {breakmodel.ram_blocks} {colors.PURPLE}of{colors.YELLOW} {n_layers} {colors.PURPLE}layers to system RAM.{colors.END}")
|
|
GPTNeoModel.forward = breakmodel.new_forward
|
|
generator = model.generate
|
|
else:
|
|
generator = pipeline('text-generation', model=vars.model)
|
|
else:
|
|
generator = pipeline('text-generation', model=vars.model)
|
|
|
|
# Suppress Author's Note by flagging square brackets
|
|
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:
|
|
# If we're running Colab or OAI, we still need a tokenizer.
|
|
if(vars.model == "Colab"):
|
|
from transformers import GPT2Tokenizer
|
|
tokenizer = GPT2Tokenizer.from_pretrained("EleutherAI/gpt-neo-2.7B")
|
|
elif(vars.model == "OAI"):
|
|
from transformers import GPT2Tokenizer
|
|
tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
|
|
|
|
# Set up Flask routes
|
|
@app.route('/')
|
|
@app.route('/index')
|
|
def index():
|
|
return render_template('index.html')
|
|
|
|
#============================ 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': 'connected'})
|
|
if(vars.remote):
|
|
emit('from_server', {'cmd': 'runs_remotely'})
|
|
|
|
if(not vars.gamestarted):
|
|
setStartState()
|
|
sendsettings()
|
|
refresh_settings()
|
|
sendwi()
|
|
vars.mode = "play"
|
|
else:
|
|
# Game in session, send current game data and ready state to browser
|
|
refresh_story()
|
|
sendsettings()
|
|
refresh_settings()
|
|
sendwi()
|
|
if(vars.mode == "play"):
|
|
if(not vars.aibusy):
|
|
emit('from_server', {'cmd': 'setgamestate', 'data': 'ready'}, broadcast=True)
|
|
else:
|
|
emit('from_server', {'cmd': 'setgamestate', 'data': 'wait'}, broadcast=True)
|
|
elif(vars.mode == "edit"):
|
|
emit('from_server', {'cmd': 'editmode', 'data': 'true'}, broadcast=True)
|
|
elif(vars.mode == "memory"):
|
|
emit('from_server', {'cmd': 'memmode', 'data': 'true'}, broadcast=True)
|
|
elif(vars.mode == "wi"):
|
|
emit('from_server', {'cmd': 'wimode', 'data': 'true'}, broadcast=True)
|
|
|
|
#==================================================================#
|
|
# Event triggered when browser SocketIO sends data to the server
|
|
#==================================================================#
|
|
@socketio.on('message')
|
|
def get_message(msg):
|
|
print("{0}Data recieved:{1}{2}".format(colors.GREEN, msg, colors.END))
|
|
# Submit action
|
|
if(msg['cmd'] == 'submit'):
|
|
if(vars.mode == "play"):
|
|
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'):
|
|
actionretry(msg['data'])
|
|
# Back/Undo Action
|
|
elif(msg['cmd'] == 'back'):
|
|
actionback()
|
|
# EditMode Action
|
|
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
|
|
elif(msg['cmd'] == 'editline'):
|
|
editrequest(int(msg['data']))
|
|
# DeleteLine Action
|
|
elif(msg['cmd'] == 'delete'):
|
|
deleterequest()
|
|
elif(msg['cmd'] == 'memory'):
|
|
togglememorymode()
|
|
elif(msg['cmd'] == 'savetofile'):
|
|
savetofile()
|
|
elif(msg['cmd'] == 'loadfromfile'):
|
|
loadfromfile()
|
|
elif(msg['cmd'] == 'import'):
|
|
importRequest()
|
|
elif(msg['cmd'] == 'newgame'):
|
|
newGameRequest()
|
|
elif(msg['cmd'] == 'rndgame'):
|
|
randomGameRequest(msg['data'])
|
|
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'])
|
|
# 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'] == '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()
|
|
elif(msg['cmd'] == 'widelete'):
|
|
deletewi(msg['data'])
|
|
elif(msg['cmd'] == 'wiselon'):
|
|
vars.worldinfo[msg['data']]["selective"] = True
|
|
elif(msg['cmd'] == 'wiseloff'):
|
|
vars.worldinfo[msg['data']]["selective"] = False
|
|
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'] == 'loadselect'):
|
|
vars.loadselect = msg["data"]
|
|
elif(msg['cmd'] == 'loadrequest'):
|
|
loadRequest(getcwd()+"/stories/"+vars.loadselect+".json")
|
|
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']
|
|
settingschanged()
|
|
refresh_settings()
|
|
refresh_story()
|
|
elif(msg['cmd'] == 'importwi'):
|
|
wiimportrequest()
|
|
|
|
#==================================================================#
|
|
# Send start message and tell Javascript to set UI state
|
|
#==================================================================#
|
|
def setStartState():
|
|
txt = "<span>Welcome to <span class=\"color_cyan\">KoboldAI Client</span>! You are running <span class=\"color_green\">"+vars.model+"</span>.<br/>"
|
|
if(not vars.noai):
|
|
txt = txt + "Please load a game or enter a prompt below to begin!</span>"
|
|
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
|
|
|
|
# Write it
|
|
file = open("client.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("client.settings")):
|
|
# Read file contents into JSON object
|
|
file = open("client.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"]
|
|
|
|
file.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):
|
|
# Ignore new submissions if the AI is currently busy
|
|
if(vars.aibusy):
|
|
return
|
|
set_aibusy(1)
|
|
|
|
vars.actionmode = actionmode
|
|
|
|
# "Action" mode
|
|
if(actionmode == 1):
|
|
data = data.strip().lstrip('>')
|
|
data = re.sub(r'\n+', ' ', data)
|
|
data = f"\n\n> {data}\n"
|
|
|
|
# If we're not continuing, store a copy of the raw input
|
|
if(data != ""):
|
|
vars.lastact = data
|
|
|
|
if(not vars.gamestarted):
|
|
# Start the game
|
|
vars.gamestarted = True
|
|
# Save this first action as the prompt
|
|
vars.prompt = data
|
|
if(not vars.noai):
|
|
# Clear the startup text from game screen
|
|
emit('from_server', {'cmd': 'updatescreen', 'gamestarted': vars.gamestarted, 'data': 'Please wait, generating story...'}, broadcast=True)
|
|
calcsubmit(data) # Run the first action through the generator
|
|
else:
|
|
refresh_story()
|
|
set_aibusy(0)
|
|
else:
|
|
# Dont append submission if it's a blank/continue action
|
|
if(data != ""):
|
|
# Apply input formatting & scripts before sending to tokenizer
|
|
if(vars.actionmode == 0):
|
|
data = applyinputformatting(data)
|
|
# Store the result in the Action log
|
|
vars.actions.append(data)
|
|
|
|
if(not vars.noai):
|
|
# Off to the tokenizer!
|
|
calcsubmit(data)
|
|
else:
|
|
refresh_story()
|
|
set_aibusy(0)
|
|
|
|
#==================================================================#
|
|
#
|
|
#==================================================================#
|
|
def actionretry(data):
|
|
if(vars.noai):
|
|
emit('from_server', {'cmd': 'errmsg', 'data': "Retry function unavailable in Read Only mode."})
|
|
return
|
|
if(vars.aibusy):
|
|
return
|
|
set_aibusy(1)
|
|
# Remove last action if possible and resubmit
|
|
if(len(vars.actions) > 0):
|
|
vars.actions.pop()
|
|
refresh_story()
|
|
calcsubmit('')
|
|
|
|
#==================================================================#
|
|
#
|
|
#==================================================================#
|
|
def actionback():
|
|
if(vars.aibusy):
|
|
return
|
|
# Remove last index of actions and refresh game screen
|
|
if(len(vars.actions) > 0):
|
|
vars.actions.pop()
|
|
refresh_story()
|
|
|
|
#==================================================================#
|
|
# Take submitted text and build the text to be given to generator
|
|
#==================================================================#
|
|
def calcsubmit(txt):
|
|
anotetxt = "" # Placeholder for Author's Note text
|
|
lnanote = 0 # Placeholder for Author's Note length
|
|
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)
|
|
|
|
# Scan for WorldInfo matches
|
|
winfo = checkworldinfo(txt)
|
|
|
|
# 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[Author's note: "+vars.authornote+"]\n"
|
|
|
|
# For all transformers models
|
|
if(vars.model != "InferKit"):
|
|
anotetkns = [] # Placeholder for Author's Note tokens
|
|
|
|
# Calculate token budget
|
|
prompttkns = tokenizer.encode(vars.prompt)
|
|
lnprompt = len(prompttkns)
|
|
|
|
memtokens = tokenizer.encode(mem)
|
|
lnmem = len(memtokens)
|
|
|
|
witokens = tokenizer.encode(winfo)
|
|
lnwi = len(witokens)
|
|
|
|
if(anotetxt != ""):
|
|
anotetkns = tokenizer.encode(anotetxt)
|
|
lnanote = len(anotetkns)
|
|
|
|
if(vars.useprompt):
|
|
budget = vars.max_length - lnprompt - lnmem - lnanote - lnwi - vars.genamt
|
|
else:
|
|
budget = vars.max_length - lnmem - lnanote - lnwi - vars.genamt
|
|
|
|
if(actionlen == 0):
|
|
# First/Prompt action
|
|
subtxt = vars.memory + winfo + anotetxt + vars.prompt
|
|
lnsub = lnmem + lnwi + lnprompt + lnanote
|
|
|
|
if(not vars.model in ["Colab", "OAI"]):
|
|
generate(subtxt, lnsub+1, lnsub+vars.genamt)
|
|
elif(vars.model == "Colab"):
|
|
sendtocolab(subtxt, lnsub+1, lnsub+vars.genamt)
|
|
elif(vars.model == "OAI"):
|
|
oairequest(subtxt, lnsub+1, lnsub+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
|
|
for n in range(actionlen):
|
|
|
|
if(budget <= 0):
|
|
break
|
|
acttkns = tokenizer.encode(vars.actions[(-1-n)])
|
|
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
|
|
|
|
# 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
|
|
ln = len(tokens)
|
|
|
|
if(not vars.model in ["Colab", "OAI"]):
|
|
generate (
|
|
tokenizer.decode(tokens),
|
|
ln+1,
|
|
ln+vars.genamt
|
|
)
|
|
elif(vars.model == "Colab"):
|
|
sendtocolab(
|
|
tokenizer.decode(tokens),
|
|
ln+1,
|
|
ln+vars.genamt
|
|
)
|
|
elif(vars.model == "OAI"):
|
|
oairequest(
|
|
tokenizer.decode(tokens),
|
|
ln+1,
|
|
ln+vars.genamt
|
|
)
|
|
|
|
# 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.prompt) - len(anotetxt) - len(mem) - len(winfo) - 1
|
|
else:
|
|
budget = vars.ikmax - len(anotetxt) - len(mem) - len(winfo) - 1
|
|
|
|
subtxt = ""
|
|
prompt = vars.prompt
|
|
for n in range(actionlen):
|
|
|
|
if(budget <= 0):
|
|
break
|
|
actlen = len(vars.actions[(-1-n)])
|
|
if(actlen < budget):
|
|
subtxt = vars.actions[(-1-n)] + subtxt
|
|
budget -= actlen
|
|
else:
|
|
count = budget * -1
|
|
subtxt = vars.actions[(-1-n)][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.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
|
|
|
|
# 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, min, max):
|
|
print("{0}Min:{1}, Max:{2}, Txt:{3}{4}".format(colors.YELLOW, min, max, txt, colors.END))
|
|
|
|
# Store context in memory to use it for comparison with generated content
|
|
vars.lastctx = 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:
|
|
top_p = vars.top_p if vars.top_p > 0.0 else None
|
|
top_k = vars.top_k if vars.top_k > 0 else None
|
|
tfs = vars.tfs if vars.tfs > 0.0 else None
|
|
|
|
# generator() only accepts a torch tensor of tokens (long datatype) as
|
|
# its first argument if we're using breakmodel, otherwise a string
|
|
# is fine
|
|
if(vars.hascuda and vars.breakmodel):
|
|
gen_in = tokenizer.encode(txt, return_tensors="pt", truncation=True).long().to(breakmodel.gpu_device)
|
|
else:
|
|
gen_in = txt
|
|
|
|
with torch.no_grad():
|
|
genout = generator(
|
|
gen_in,
|
|
do_sample=True,
|
|
min_length=min,
|
|
max_length=max,
|
|
repetition_penalty=vars.rep_pen,
|
|
top_p=top_p,
|
|
top_k=top_k,
|
|
tfs=tfs,
|
|
temperature=vars.temp,
|
|
bad_words_ids=vars.badwordsids,
|
|
use_cache=True,
|
|
return_full_text=False,
|
|
num_return_sequences=vars.numseqs
|
|
)
|
|
except Exception as e:
|
|
emit('from_server', {'cmd': 'errmsg', 'data': 'Error occured during generator call, please check console.'}, broadcast=True)
|
|
print("{0}{1}{2}".format(colors.RED, e, colors.END))
|
|
set_aibusy(0)
|
|
return
|
|
|
|
# Need to manually strip and decode tokens if we're not using a pipeline
|
|
if(vars.hascuda and vars.breakmodel):
|
|
genout = [{"generated_text": tokenizer.decode(tokens[len(gen_in[0])-len(tokens):])} for tokens in genout]
|
|
|
|
if(len(genout) == 1):
|
|
genresult(genout[0]["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):
|
|
print("{0}{1}{2}".format(colors.CYAN, genout, colors.END))
|
|
|
|
# Format output before continuing
|
|
genout = applyoutputformatting(genout)
|
|
|
|
# Add formatted text to Actions array and refresh the game screen
|
|
vars.actions.append(genout)
|
|
refresh_story()
|
|
emit('from_server', {'cmd': 'texteffect', 'data': len(vars.actions)}, 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)
|
|
|
|
# Refresh story for any input text
|
|
refresh_story()
|
|
|
|
#==================================================================#
|
|
# Send selected sequence to action log and refresh UI
|
|
#==================================================================#
|
|
def selectsequence(n):
|
|
if(len(vars.genseqs) == 0):
|
|
return
|
|
vars.actions.append(vars.genseqs[int(n)]["generated_text"])
|
|
refresh_story()
|
|
emit('from_server', {'cmd': 'texteffect', 'data': len(vars.actions)}, broadcast=True)
|
|
emit('from_server', {'cmd': 'hidegenseqs', 'data': ''}, broadcast=True)
|
|
vars.genseqs = []
|
|
|
|
#==================================================================#
|
|
# 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"]
|
|
|
|
if(len(genout) == 1):
|
|
genresult(genout[0])
|
|
else:
|
|
# Convert torch output format to transformers
|
|
seqs = []
|
|
for seq in genout:
|
|
seqs.append({"generated_text": seq})
|
|
genselect(seqs)
|
|
|
|
# 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': len(vars.actions)})
|
|
|
|
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)
|
|
|
|
|
|
#==================================================================#
|
|
# Replaces returns and newlines with HTML breaks
|
|
#==================================================================#
|
|
def formatforhtml(txt):
|
|
return txt.replace("\\r", "<br/>").replace("\\n", "<br/>").replace('\n', '<br/>').replace('\r', '<br/>')
|
|
|
|
#==================================================================#
|
|
# 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)
|
|
txttokens = tokenizer.encode(txt)
|
|
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"]):
|
|
txt = utils.trimincompletesentence(txt)
|
|
# Replace blank lines
|
|
if(vars.formatoptns["frmtrmblln"]):
|
|
txt = utils.replaceblanklines(txt)
|
|
# Remove special characters
|
|
if(vars.formatoptns["frmtrmspch"]):
|
|
txt = utils.removespecialchars(txt, vars)
|
|
|
|
return txt
|
|
|
|
#==================================================================#
|
|
# Sends the current story content to the Game Screen
|
|
#==================================================================#
|
|
def refresh_story():
|
|
text_parts = ['<chunk n="0" id="n0">', html.escape(vars.prompt), '</chunk>']
|
|
for idx, item in enumerate(vars.actions, start=1):
|
|
if vars.adventure: # Add special formatting to adventure actions
|
|
item = vars.acregex_ui.sub('<action>\\1</action>', html.escape(item))
|
|
text_parts.extend(('<chunk n="', str(idx), '" id="n', str(idx), '">', item, '</chunk>'))
|
|
emit('from_server', {'cmd': 'updatescreen', 'gamestarted': vars.gamestarted, 'data': formatforhtml(''.join(text_parts))}, 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': '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)
|
|
|
|
# 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):
|
|
if(vars.editln == 0):
|
|
vars.prompt = data
|
|
else:
|
|
vars.actions[vars.editln-1] = data
|
|
|
|
vars.mode = "play"
|
|
refresh_story()
|
|
emit('from_server', {'cmd': 'texteffect', 'data': vars.editln}, broadcast=True)
|
|
emit('from_server', {'cmd': 'editmode', 'data': 'false'}, broadcast=True)
|
|
|
|
#==================================================================#
|
|
#
|
|
#==================================================================#
|
|
def deleterequest():
|
|
# Don't delete prompt
|
|
if(vars.editln == 0):
|
|
# Send error message
|
|
pass
|
|
else:
|
|
del vars.actions[vars.editln-1]
|
|
vars.mode = "play"
|
|
refresh_story()
|
|
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})
|
|
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():
|
|
ob = {"key": "", "keysecondary": "", "content": "", "num": len(vars.worldinfo), "init": False, "selective": False}
|
|
vars.worldinfo.append(ob);
|
|
emit('from_server', {'cmd': 'addwiitem', 'data': ob}, broadcast=True)
|
|
|
|
#==================================================================#
|
|
#
|
|
#==================================================================#
|
|
def sendwi():
|
|
# Cache len of WI
|
|
ln = len(vars.worldinfo)
|
|
|
|
# Clear contents of WI container
|
|
emit('from_server', {'cmd': 'clearwi', 'data': ''}, broadcast=True)
|
|
|
|
# If there are no WI entries, send an empty WI object
|
|
if(ln == 0):
|
|
addwiitem()
|
|
else:
|
|
# Send contents of WI array
|
|
for wi in vars.worldinfo:
|
|
ob = wi
|
|
emit('from_server', {'cmd': 'addwiitem', 'data': ob}, broadcast=True)
|
|
# Make sure last WI item is uninitialized
|
|
if(vars.worldinfo[-1]["init"]):
|
|
addwiitem()
|
|
|
|
#==================================================================#
|
|
# 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}, broadcast=True)
|
|
|
|
#==================================================================#
|
|
# Renumber WI items consecutively
|
|
#==================================================================#
|
|
def organizewi():
|
|
if(len(vars.worldinfo) > 0):
|
|
count = 0
|
|
for wi in vars.worldinfo:
|
|
wi["num"] = count
|
|
count += 1
|
|
|
|
|
|
#==================================================================#
|
|
# Extract object from server and send it to WI objects
|
|
#==================================================================#
|
|
def commitwi(ar):
|
|
for ob in ar:
|
|
vars.worldinfo[ob["num"]]["key"] = ob["key"]
|
|
vars.worldinfo[ob["num"]]["keysecondary"] = ob["keysecondary"]
|
|
vars.worldinfo[ob["num"]]["content"] = ob["content"]
|
|
vars.worldinfo[ob["num"]]["selective"] = ob["selective"]
|
|
# Was this a deletion request? If so, remove the requested index
|
|
if(vars.deletewi >= 0):
|
|
del vars.worldinfo[vars.deletewi]
|
|
organizewi()
|
|
# Send the new WI array structure
|
|
sendwi()
|
|
# And reset deletewi index
|
|
vars.deletewi = -1
|
|
|
|
#==================================================================#
|
|
#
|
|
#==================================================================#
|
|
def deletewi(num):
|
|
if(num < len(vars.worldinfo)):
|
|
# Store index of deletion request
|
|
vars.deletewi = num
|
|
# Get contents of WI HTML inputs
|
|
requestwi()
|
|
|
|
#==================================================================#
|
|
# Look for WI keys in text to generator
|
|
#==================================================================#
|
|
def checkworldinfo(txt):
|
|
# Dont go any further if WI is empty
|
|
if(len(vars.worldinfo) == 0):
|
|
return
|
|
|
|
# Cache actions length
|
|
ln = len(vars.actions)
|
|
|
|
# Don't bother calculating action history if widepth is 0
|
|
if(vars.widepth > 0):
|
|
depth = vars.widepth
|
|
# If this is not a continue, add 1 to widepth since submitted
|
|
# text is already in action history @ -1
|
|
if(txt != "" and vars.prompt != txt):
|
|
txt = ""
|
|
depth += 1
|
|
|
|
if(ln >= depth):
|
|
txt = "".join(vars.actions[(depth*-1):])
|
|
elif(ln > 0):
|
|
txt = vars.prompt + "".join(vars.actions[(depth*-1):])
|
|
elif(ln == 0):
|
|
txt = vars.prompt
|
|
|
|
# Scan text for matches on WI keys
|
|
wimem = ""
|
|
for wi in vars.worldinfo:
|
|
if(wi["key"] != ""):
|
|
# 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 = True
|
|
break
|
|
if found:
|
|
break
|
|
else:
|
|
wimem = wimem + wi["content"] + "\n"
|
|
break
|
|
|
|
return wimem
|
|
|
|
#==================================================================#
|
|
# 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': ''}, broadcast=True)
|
|
|
|
#==================================================================#
|
|
# Commit changes to Author's Note
|
|
#==================================================================#
|
|
def anotesubmit(data):
|
|
# Maybe check for length at some point
|
|
# For now just send it to storage
|
|
vars.authornote = data
|
|
|
|
#==================================================================#
|
|
# 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"]
|
|
print("{0}{1}{2}".format(colors.CYAN, genout, colors.END))
|
|
vars.actions.append(genout)
|
|
refresh_story()
|
|
emit('from_server', {'cmd': 'texteffect', 'data': len(vars.actions)}, 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"]
|
|
print("{0}{1}{2}".format(colors.CYAN, genout, colors.END))
|
|
vars.actions.append(genout)
|
|
refresh_story()
|
|
emit('from_server', {'cmd': 'texteffect', 'data': len(vars.actions)}, 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
|
|
saveRequest(getcwd()+"/stories/"+name+".json")
|
|
emit('from_server', {'cmd': 'hidesaveas', 'data': ''})
|
|
vars.saveow = False
|
|
vars.svowname = ""
|
|
else:
|
|
# File exists, prompt for overwrite
|
|
vars.saveow = True
|
|
vars.svowname = name
|
|
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
|
|
|
|
# Build json to write
|
|
js = {}
|
|
js["gamestarted"] = vars.gamestarted
|
|
js["prompt"] = vars.prompt
|
|
js["memory"] = vars.memory
|
|
js["authorsnote"] = vars.authornote
|
|
js["actions"] = vars.actions
|
|
js["worldinfo"] = []
|
|
|
|
# Extract only the important bits of WI
|
|
for wi in vars.worldinfo:
|
|
if(wi["key"] != ""):
|
|
js["worldinfo"].append({
|
|
"key": wi["key"],
|
|
"keysecondary": wi["keysecondary"],
|
|
"content": wi["content"],
|
|
"selective": wi["selective"]
|
|
})
|
|
|
|
# Write it
|
|
file = open(savpath, "w")
|
|
try:
|
|
file.write(json.dumps(js, indent=3))
|
|
finally:
|
|
file.close()
|
|
|
|
print("{0}Story saved to {1}!{2}".format(colors.GREEN, path.basename(savpath), colors.END))
|
|
|
|
#==================================================================#
|
|
# Load a saved story via file browser
|
|
#==================================================================#
|
|
def getloadlist():
|
|
emit('from_server', {'cmd': 'buildload', 'data': fileops.getstoryfiles()})
|
|
|
|
#==================================================================#
|
|
# 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):
|
|
if(loadpath):
|
|
# Leave Edit/Memory mode before continuing
|
|
exitModes()
|
|
|
|
# Read file contents into JSON object
|
|
file = open(loadpath, "r")
|
|
js = json.load(file)
|
|
|
|
# Copy file contents to vars
|
|
vars.gamestarted = js["gamestarted"]
|
|
vars.prompt = js["prompt"]
|
|
vars.memory = js["memory"]
|
|
vars.actions = js["actions"]
|
|
vars.worldinfo = []
|
|
vars.lastact = ""
|
|
vars.lastctx = ""
|
|
|
|
# Try not to break older save files
|
|
if("authorsnote" in js):
|
|
vars.authornote = js["authorsnote"]
|
|
else:
|
|
vars.authornote = ""
|
|
|
|
if("worldinfo" in js):
|
|
num = 0
|
|
for wi in js["worldinfo"]:
|
|
vars.worldinfo.append({
|
|
"key": wi["key"],
|
|
"keysecondary": wi.get("keysecondary", ""),
|
|
"content": wi["content"],
|
|
"num": num,
|
|
"init": True,
|
|
"selective": wi.get("selective", False)
|
|
})
|
|
num += 1
|
|
|
|
file.close()
|
|
|
|
# Save path for save button
|
|
vars.savedir = loadpath
|
|
|
|
# Clear loadselect var
|
|
vars.loadselect = ""
|
|
|
|
# Refresh game screen
|
|
sendwi()
|
|
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, path.basename(loadpath), colors.END))
|
|
|
|
#==================================================================#
|
|
# 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.actions = []
|
|
vars.worldinfo = []
|
|
vars.lastact = ""
|
|
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"],
|
|
"num": num,
|
|
"init": True,
|
|
"selective": wi.get("selective", False)
|
|
})
|
|
num += 1
|
|
|
|
# Clear import data
|
|
vars.importjs = {}
|
|
|
|
# Reset current save
|
|
vars.savedir = getcwd()+"\stories"
|
|
|
|
# Refresh game screen
|
|
sendwi()
|
|
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.actions = []
|
|
vars.worldinfo = []
|
|
vars.lastact = ""
|
|
vars.lastctx = ""
|
|
|
|
num = 0
|
|
for wi in js["worldInfos"]:
|
|
vars.worldinfo.append({
|
|
"key": wi["keys"],
|
|
"keysecondary": wi.get("keysecondary", ""),
|
|
"content": wi["entry"],
|
|
"num": num,
|
|
"init": True,
|
|
"selective": wi.get("selective", False)
|
|
})
|
|
num += 1
|
|
|
|
# Reset current save
|
|
vars.savedir = getcwd()+"\stories"
|
|
|
|
# Refresh game screen
|
|
sendwi()
|
|
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"],
|
|
"num": num,
|
|
"init": True,
|
|
"selective": wi.get("selective", False)
|
|
})
|
|
num += 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 = []
|
|
|
|
vars.authornote = ""
|
|
vars.worldinfo = []
|
|
vars.lastact = ""
|
|
vars.lastctx = ""
|
|
|
|
# Reset current save
|
|
vars.savedir = getcwd()+"\stories"
|
|
|
|
# Refresh game screen
|
|
sendwi()
|
|
setStartState()
|
|
|
|
def randomGameRequest(topic):
|
|
newGameRequest()
|
|
vars.memory = "You generate the following " + topic + " story concept :"
|
|
actionsubmit("")
|
|
vars.memory = ""
|
|
|
|
#==================================================================#
|
|
# Final startup commands to launch Flask app
|
|
#==================================================================#
|
|
if __name__ == "__main__":
|
|
|
|
# Load settings from client.settings
|
|
loadsettings()
|
|
|
|
# Start Flask/SocketIO (Blocking, so this must be last method!)
|
|
print("{0}Server started!\rYou may now connect with a browser at http://127.0.0.1:5000/{1}".format(colors.GREEN, colors.END))
|
|
#socketio.run(app, host='0.0.0.0', port=5000)
|
|
if(vars.remote):
|
|
from flask_cloudflared import start_cloudflared
|
|
start_cloudflared(5000)
|
|
socketio.run(app, host='0.0.0.0', port=5000)
|
|
else:
|
|
import webbrowser
|
|
webbrowser.open_new('http://localhost:5000')
|
|
socketio.run(app)
|