mirror of
https://github.com/KoboldAI/KoboldAI-Client.git
synced 2025-02-02 18:46:48 +01:00
Initial UI based model loading. Includes all parameters except breakmodel chunks, engine # for OAI, and url for ngrok url for google colab
This commit is contained in:
ebolam
parent
f6c95f18fa
commit
2ddf45141b
307
aiserver.py
307
aiserver.py
@ -39,6 +39,8 @@ import gc
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import lupa
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import torch
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# KoboldAI
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import fileops
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import gensettings
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@ -67,71 +69,67 @@ class colors:
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UNDERLINE = '\033[4m'
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# AI models
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mainmenu = [
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["Load a model from its directory", "NeoCustom", ""],
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["Load an old GPT-2 model (eg CloverEdition)", "GPT2Custom", ""],
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["Skein 6B (Hybrid)", "KoboldAI/GPT-J-6B-Skein", "16GB"],
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["Janeway 6B (Novel)", "KoboldAI/GPT-J-6B-Janeway", "16GB"],
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["Adventure 6B", "KoboldAI/GPT-J-6B-Adventure", "16GB"],
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["Lit 6B (NSFW)", "hakurei/lit-6B", "16GB"],
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["Shinen 6B (NSFW)", "KoboldAI/GPT-J-6B-Shinen", "16GB"],
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["C1 6B (Chatbot)", "hakurei/c1-6B", "16GB"],
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["Janeway Neo 2.7B (Novel)", "KoboldAI/GPT-Neo-2.7B-Janeway", "8GB"],
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["Janeway FSD 2.7B (Novel)", "KoboldAI/fairseq-dense-2.7B-Janeway", "8GB"],
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["Adventure 2.7B", "KoboldAI/GPT-Neo-2.7B-AID", "8GB"],
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["Picard 2.7B (Novel)", "KoboldAI/GPT-Neo-2.7B-Picard", "8GB"],
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["Horni 2.7B (NSFW)", "KoboldAI/GPT-Neo-2.7B-Horni", "8GB"],
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["Horni-LN 2.7B (Novel)", "KoboldAI/GPT-Neo-2.7B-Horni-LN", "8GB"],
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["Shinen 2.7B (NSFW)", "KoboldAI/GPT-Neo-2.7B-Shinen", "8GB"],
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["Untuned GPT-Neo/J", "gptneolist", ""],
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["Untuned Fairseq Dense", "fsdlist", ""],
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["Untuned XGLM", "xglmlist", ""],
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["Untuned GPT2", "gpt2list", ""],
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["Online Services", "apilist", ""],
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["Read Only (No AI)", "ReadOnly", ""]
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model_menu = {'mainmenu': [
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["Load a model from its directory", "NeoCustom", "", False],
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["Load an old GPT-2 model (eg CloverEdition)", "GPT2Custom", "", False],
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["Skein 6B (Hybrid)", "KoboldAI/GPT-J-6B-Skein", "16GB", False],
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["Janeway 6B (Novel)", "KoboldAI/GPT-J-6B-Janeway", "16GB", False],
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["Adventure 6B", "KoboldAI/GPT-J-6B-Adventure", "16GB", False],
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["Lit 6B (NSFW)", "hakurei/lit-6B", "16GB", False],
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["Shinen 6B (NSFW)", "KoboldAI/GPT-J-6B-Shinen", "16GB", False],
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["C1 6B (Chatbot)", "hakurei/c1-6B", "16GB", False],
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["Janeway Neo 2.7B (Novel)", "KoboldAI/GPT-Neo-2.7B-Janeway", "8GB", False],
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["Janeway FSD 2.7B (Novel)", "KoboldAI/fairseq-dense-2.7B-Janeway", "8GB", False],
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["Adventure 2.7B", "KoboldAI/GPT-Neo-2.7B-AID", "8GB", False],
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["Picard 2.7B (Novel)", "KoboldAI/GPT-Neo-2.7B-Picard", "8GB", False],
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["Horni 2.7B (NSFW)", "KoboldAI/GPT-Neo-2.7B-Horni", "8GB", False],
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["Horni-LN 2.7B (Novel)", "KoboldAI/GPT-Neo-2.7B-Horni-LN", "8GB", False],
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["Shinen 2.7B (NSFW)", "KoboldAI/GPT-Neo-2.7B-Shinen", "8GB", False],
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["Untuned GPT-Neo/J", "gptneolist", "", True],
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["Untuned Fairseq Dense", "fsdlist", "", True],
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["Untuned XGLM", "xglmlist", "", True],
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["Untuned GPT2", "gpt2list", "", True],
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["Online Services", "apilist", "", True],
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["Read Only (No AI)", "ReadOnly", "", False]
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],
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'gptneolist': [
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["GPT-J 6B", "EleutherAI/gpt-j-6B", "16GB", False],
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["GPT-Neo 2.7B", "EleutherAI/gpt-neo-2.7B", "8GB", False],
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["GPT-Neo 1.3B", "EleutherAI/gpt-neo-1.3B", "6GB", False],
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["Return to Main Menu", "mainmenu", "", True],
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],
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'gpt2list': [
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["GPT-2 XL", "gpt2-xl", "6GB", False],
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["GPT-2 Large", "gpt2-large", "4GB", False],
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["GPT-2 Med", "gpt2-medium", "2GB", False],
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["GPT-2", "gpt2", "2GB", False],
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["Return to Main Menu", "mainmenu", "", True],
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],
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'fsdlist': [
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["Fairseq Dense 13B", "KoboldAI/fairseq-dense-13B", "32GB", False],
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["Fairseq Dense 6.7B", "KoboldAI/fairseq-dense-6.7B", "16GB", False],
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["Fairseq Dense 2.7B", "KoboldAI/fairseq-dense-2.7B", "8GB", False],
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["Fairseq Dense 1.3B", "KoboldAI/fairseq-dense-1.3B", "6GB", False],
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["Fairseq Dense 355M", "KoboldAI/fairseq-dense-355M", "", False],
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["Fairseq Dense 125M", "KoboldAI/fairseq-dense-125M", "", False],
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["Return to Main Menu", "Return", "", True],
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],
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'xglmlist': [
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["XGLM 4.5B (Larger Dataset)", "facebook/xglm-4.5B", "", False],
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["XGLM 7.5B", "facebook/xglm-7.5B", "", False],
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["XGLM 2.9B", "facebook/xglm-2.9B", "", False],
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["XGLM 1.7B", "facebook/xglm-1.7B", "", False],
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["XGLM 564M", "facebook/xglm-564M", "", False],
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["Return to Main Menu", "mainmenu", "", True],
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],
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'apilist': [
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["OpenAI API (requires API key)", "OAI", "", False],
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["InferKit API (requires API key)", "InferKit", "", False],
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["KoboldAI Server API (Old Google Colab)", "Colab", "", False],
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["Return to Main Menu", "mainmenu", "", True],
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]
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}
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gptneolist = [
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["GPT-J 6B", "EleutherAI/gpt-j-6B", "16GB"],
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["GPT-Neo 2.7B", "EleutherAI/gpt-neo-2.7B", "8GB"],
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["GPT-Neo 1.3B", "EleutherAI/gpt-neo-1.3B", "6GB"],
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["Return to Main Menu", "Return", ""],
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]
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gpt2list = [
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["GPT-2 XL", "gpt2-xl", "6GB"],
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["GPT-2 Large", "gpt2-large", "4GB"],
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["GPT-2 Med", "gpt2-medium", "2GB"],
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["GPT-2", "gpt2", "2GB"],
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["Return to Main Menu", "Return", ""],
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]
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fsdlist = [
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["Fairseq Dense 13B", "KoboldAI/fairseq-dense-13B", "32GB"],
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["Fairseq Dense 6.7B", "KoboldAI/fairseq-dense-6.7B", "16GB"],
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["Fairseq Dense 2.7B", "KoboldAI/fairseq-dense-2.7B", "8GB"],
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["Fairseq Dense 1.3B", "KoboldAI/fairseq-dense-1.3B", "6GB"],
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["Fairseq Dense 355M", "KoboldAI/fairseq-dense-355M", ""],
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["Fairseq Dense 125M", "KoboldAI/fairseq-dense-125M", ""],
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["Return to Main Menu", "Return", ""],
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]
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xglmlist = [
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["XGLM 4.5B (Larger Dataset)", "facebook/xglm-4.5B", ""],
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["XGLM 7.5B", "facebook/xglm-7.5B", ""],
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["XGLM 2.9B", "facebook/xglm-2.9B", ""],
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["XGLM 1.7B", "facebook/xglm-1.7B", ""],
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["XGLM 564M", "facebook/xglm-564M", ""],
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["Return to Main Menu", "Return", ""],
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]
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apilist = [
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["GooseAI API (requires API key)", "GooseAI", ""],
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["OpenAI API (requires API key)", "OAI", ""],
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["InferKit API (requires API key)", "InferKit", ""],
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["KoboldAI Server API (Old Google Colab)", "Colab", ""],
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["Return to Main Menu", "Return", ""],
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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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@ -261,6 +259,9 @@ utils.vars = vars
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#==================================================================#
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# Function to get model selection at startup
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#==================================================================#
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def sendModelSelection(menu="mainmenu"):
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emit('from_server', {'cmd': 'show_model_menu', 'data': model_menu[menu], 'menu': menu}, broadcast=True)
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def getModelSelection(modellist):
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print(" # Model\t\t\t\t\t\tVRAM\n ========================================================")
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i = 1
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@ -717,6 +718,22 @@ def spRequest(filename):
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# Startup
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#==================================================================#
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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, Response, request, copy_current_request_context
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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, async_method="eventlet")
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print("{0}OK!{1}".format(colors.GREEN, colors.END))
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def general_startup():
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global args
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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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@ -737,7 +754,7 @@ parser.add_argument("--unblock", action='store_true', default=False, help="Unblo
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parser.add_argument("--quiet", action='store_true', default=False, help="If present will suppress any story related text from showing on the console")
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parser.add_argument("--lowmem", action='store_true', help="Extra Low Memory loading for the GPU, slower but memory does not peak to twice the usage")
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args: argparse.Namespace = None
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if(os.environ.get("KOBOLDAI_ARGS") is not None):
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import shlex
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args = parser.parse_args(shlex.split(os.environ["KOBOLDAI_ARGS"]))
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@ -775,18 +792,15 @@ if args.cpu:
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vars.smandelete = vars.host == args.override_delete
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vars.smanrename = vars.host == args.override_rename
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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 Server!\nListed RAM is the optimal VRAM and CPU ram can be up to twice the amount.\nMost models can run at less VRAM with reduced max tokens or less layers on the GPU.\nSelect an AI model to continue:{1}\n".format(colors.CYAN, colors.END))
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getModelSelection(mainmenu)
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#==================================================================#
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# Load Model
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#==================================================================#
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def load_model(use_gpu=True, key=''):
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global model
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global generator
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vars.noai = False
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set_aibusy(True)
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# If transformers model was selected & GPU available, ask to use CPU or GPU
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if(vars.model not in ["InferKit", "Colab", "OAI", "GooseAI" , "ReadOnly", "TPUMeshTransformerGPTJ"]):
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vars.allowsp = True
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@ -865,19 +879,13 @@ if(not vars.use_colab_tpu and vars.model not in ["InferKit", "Colab", "OAI", "Go
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vars.usegpu = False
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vars.breakmodel = True
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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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else:
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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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if(use_gpu):
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if(vars.bmsupported):
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vars.breakmodel = True
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vars.usegpu = False
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@ -886,19 +894,16 @@ if(not vars.use_colab_tpu and vars.model not in ["InferKit", "Colab", "OAI", "Go
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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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else:
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vars.breakmodel = False
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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("settings/" + getmodelname().replace('/', '_') + ".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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vars.apikey = key
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# Write API key to file
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os.makedirs('settings', exist_ok=True)
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file = open("settings/" + getmodelname().replace('/', '_') + ".settings", "w")
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@ -918,8 +923,7 @@ if(vars.model == "InferKit"):
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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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vars.apikey = key
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js["apikey"] = vars.apikey
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# Write API key to file
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file = open("settings/" + getmodelname().replace('/', '_') + ".settings", "w")
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@ -940,8 +944,7 @@ if(vars.model == "OAI"):
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args.configname = "OAI"
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if(not path.exists("settings/" + getmodelname().replace('/', '_') + ".settings")):
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# If the client settings file doesn't exist, create it
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print("{0}Please enter your API key:{1}\n".format(colors.CYAN, colors.END))
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vars.oaiapikey = input("Key> ")
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vars.oaiapikey = key
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# Write API key to file
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os.makedirs('settings', exist_ok=True)
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file = open("settings/" + getmodelname().replace('/', '_') + ".settings", "w")
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@ -961,8 +964,7 @@ if(vars.model == "OAI"):
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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 API key:{1}\n".format(colors.CYAN, colors.END))
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vars.oaiapikey = input("Key> ")
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vars.oaiapikey = key
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js["oaiapikey"] = vars.oaiapikey
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# Write API key to file
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file = open("settings/" + getmodelname().replace('/', '_') + ".settings", "w")
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@ -1015,20 +1017,6 @@ if(vars.model == "Colab"):
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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, Response, request, copy_current_request_context
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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, async_method="eventlet")
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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.use_colab_tpu and vars.model not in ["InferKit", "Colab", "OAI", "GooseAI" , "ReadOnly", "TPUMeshTransformerGPTJ"]):
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if(not vars.noai):
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@ -1562,6 +1550,13 @@ else:
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else:
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loadsettings()
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lua_startup()
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# Load scripts
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load_lua_scripts()
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final_startup()
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set_aibusy(False)
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# Set up Flask routes
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@app.route('/')
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@app.route('/index')
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@ -1614,6 +1609,12 @@ def download():
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#============================ LUA API =============================#
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_bridged = {}
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F = TypeVar("F", bound=Callable)
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def lua_startup():
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global _bridged
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global F
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global bridged
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if(path.exists("settings/" + getmodelname().replace('/', '_') + ".settings")):
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file = open("settings/" + getmodelname().replace('/', '_') + ".settings", "r")
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js = json.load(file)
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@ -1631,12 +1632,46 @@ if(path.exists("settings/" + getmodelname().replace('/', '_') + ".settings")):
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vars.corescript = "default.lua"
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file.close()
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#==================================================================#
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# Lua runtime startup
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#==================================================================#
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print("", end="", flush=True)
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print(colors.PURPLE + "Initializing Lua Bridge... " + colors.END, end="", flush=True)
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# Set up Lua state
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vars.lua_state = lupa.LuaRuntime(unpack_returned_tuples=True)
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# Load bridge.lua
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bridged = {
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"corescript_path": os.path.join(os.path.dirname(os.path.realpath(__file__)), "cores"),
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"userscript_path": os.path.join(os.path.dirname(os.path.realpath(__file__)), "userscripts"),
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"config_path": os.path.join(os.path.dirname(os.path.realpath(__file__)), "userscripts"),
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"lib_paths": vars.lua_state.table(os.path.join(os.path.dirname(os.path.realpath(__file__)), "lualibs"), os.path.join(os.path.dirname(os.path.realpath(__file__)), "extern", "lualibs")),
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"vars": vars,
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}
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for kwarg in _bridged:
|
||||
bridged[kwarg] = _bridged[kwarg]
|
||||
try:
|
||||
vars.lua_kobold, vars.lua_koboldcore, vars.lua_koboldbridge = vars.lua_state.globals().dofile(os.path.join(os.path.dirname(os.path.realpath(__file__)), "bridge.lua"))(
|
||||
vars.lua_state.globals().python,
|
||||
bridged,
|
||||
)
|
||||
except lupa.LuaError as e:
|
||||
print(colors.RED + "ERROR!" + colors.END)
|
||||
vars.lua_koboldbridge.obliterate_multiverse()
|
||||
print("{0}{1}{2}".format(colors.RED, "***LUA ERROR***: ", colors.END), end="", file=sys.stderr)
|
||||
print("{0}{1}{2}".format(colors.RED, str(e).replace("\033", ""), colors.END), file=sys.stderr)
|
||||
exit(1)
|
||||
print(colors.GREEN + "OK!" + colors.END)
|
||||
|
||||
|
||||
|
||||
def lua_log_format_name(name):
|
||||
return f"[{name}]" if type(name) is str else "CORE"
|
||||
|
||||
_bridged = {}
|
||||
F = TypeVar("F", bound=Callable)
|
||||
def bridged_kwarg(name=None):
|
||||
global F
|
||||
def _bridged_kwarg(f: F):
|
||||
_bridged[name if name is not None else f.__name__[4:] if f.__name__[:4] == "lua_" else f.__name__] = f
|
||||
return f
|
||||
@ -2172,42 +2207,6 @@ def execute_outmod():
|
||||
for k in vars.lua_deleted:
|
||||
inlinedelete(k)
|
||||
|
||||
#==================================================================#
|
||||
# Lua runtime startup
|
||||
#==================================================================#
|
||||
|
||||
print("", end="", flush=True)
|
||||
print(colors.PURPLE + "Initializing Lua Bridge... " + colors.END, end="", flush=True)
|
||||
|
||||
# Set up Lua state
|
||||
vars.lua_state = lupa.LuaRuntime(unpack_returned_tuples=True)
|
||||
|
||||
# Load bridge.lua
|
||||
bridged = {
|
||||
"corescript_path": os.path.join(os.path.dirname(os.path.realpath(__file__)), "cores"),
|
||||
"userscript_path": os.path.join(os.path.dirname(os.path.realpath(__file__)), "userscripts"),
|
||||
"config_path": os.path.join(os.path.dirname(os.path.realpath(__file__)), "userscripts"),
|
||||
"lib_paths": vars.lua_state.table(os.path.join(os.path.dirname(os.path.realpath(__file__)), "lualibs"), os.path.join(os.path.dirname(os.path.realpath(__file__)), "extern", "lualibs")),
|
||||
"vars": vars,
|
||||
}
|
||||
for kwarg in _bridged:
|
||||
bridged[kwarg] = _bridged[kwarg]
|
||||
try:
|
||||
vars.lua_kobold, vars.lua_koboldcore, vars.lua_koboldbridge = vars.lua_state.globals().dofile(os.path.join(os.path.dirname(os.path.realpath(__file__)), "bridge.lua"))(
|
||||
vars.lua_state.globals().python,
|
||||
bridged,
|
||||
)
|
||||
except lupa.LuaError as e:
|
||||
print(colors.RED + "ERROR!" + colors.END)
|
||||
vars.lua_koboldbridge.obliterate_multiverse()
|
||||
print("{0}{1}{2}".format(colors.RED, "***LUA ERROR***: ", colors.END), end="", file=sys.stderr)
|
||||
print("{0}{1}{2}".format(colors.RED, str(e).replace("\033", ""), colors.END), file=sys.stderr)
|
||||
exit(1)
|
||||
print(colors.GREEN + "OK!" + colors.END)
|
||||
|
||||
# Load scripts
|
||||
load_lua_scripts()
|
||||
|
||||
|
||||
#============================ METHODS =============================#
|
||||
|
||||
@ -2528,6 +2527,12 @@ def get_message(msg):
|
||||
load_lua_scripts()
|
||||
unloaded, loaded = getuslist()
|
||||
sendUSStatItems()
|
||||
elif(msg['cmd'] == 'list_model'):
|
||||
sendModelSelection(menu=msg['data'])
|
||||
elif(msg['cmd'] == 'load_model'):
|
||||
load_model(use_gpu=msg['use_gpu'], key=msg['key'])
|
||||
elif(msg['cmd'] == 'selectmodel'):
|
||||
vars.model = msg['data']
|
||||
elif(msg['cmd'] == 'loadselect'):
|
||||
vars.loadselect = msg["data"]
|
||||
elif(msg['cmd'] == 'spselect'):
|
||||
@ -3793,10 +3798,16 @@ def refresh_settings():
|
||||
def set_aibusy(state):
|
||||
if(state):
|
||||
vars.aibusy = True
|
||||
try:
|
||||
emit('from_server', {'cmd': 'setgamestate', 'data': 'wait'}, broadcast=True)
|
||||
except:
|
||||
pass
|
||||
else:
|
||||
vars.aibusy = False
|
||||
try:
|
||||
emit('from_server', {'cmd': 'setgamestate', 'data': 'ready'}, broadcast=True)
|
||||
except:
|
||||
pass
|
||||
|
||||
#==================================================================#
|
||||
#
|
||||
@ -5088,6 +5099,7 @@ def randomGameRequest(topic, memory=""):
|
||||
vars.memory = memory
|
||||
emit('from_server', {'cmd': 'setmemory', 'data': vars.memory}, broadcast=True)
|
||||
|
||||
def final_startup():
|
||||
# Prevent tokenizer from taking extra time the first time it's used
|
||||
def __preempt_tokenizer():
|
||||
if("tokenizer" not in globals()):
|
||||
@ -5175,6 +5187,11 @@ print("", end="", flush=True)
|
||||
if __name__ == "__main__":
|
||||
print("{0}\nStarting webserver...{1}".format(colors.GREEN, colors.END), flush=True)
|
||||
|
||||
general_startup()
|
||||
#show_select_model_list()
|
||||
vars.model = "ReadOnly"
|
||||
load_model()
|
||||
|
||||
# Start Flask/SocketIO (Blocking, so this must be last method!)
|
||||
|
||||
#socketio.run(app, host='0.0.0.0', port=5000)
|
||||
|
||||
@ -7,6 +7,7 @@ var socket;
|
||||
|
||||
// UI references for jQuery
|
||||
var connect_status;
|
||||
var button_loadmodel;
|
||||
var button_newgame;
|
||||
var button_rndgame;
|
||||
var button_save;
|
||||
@ -55,6 +56,7 @@ var savepins;
|
||||
var topic;
|
||||
var saveas_accept;
|
||||
var saveas_close;
|
||||
var loadmodelpopup;
|
||||
var loadpopup;
|
||||
var loadcontent;
|
||||
var load_accept;
|
||||
@ -890,6 +892,17 @@ function sendSaveAsRequest() {
|
||||
socket.send({'cmd': 'saveasrequest', 'data': {"name": saveasinput.val(), "pins": savepins.val()}});
|
||||
}
|
||||
|
||||
function showLoadModelPopup() {
|
||||
loadmodelpopup.removeClass("hidden");
|
||||
loadmodelpopup.addClass("flex");
|
||||
}
|
||||
|
||||
function hideLoadModelPopup() {
|
||||
loadmodelpopup.removeClass("flex");
|
||||
loadmodelpopup.addClass("hidden");
|
||||
loadmodelcontent.html("");
|
||||
}
|
||||
|
||||
function showLoadPopup() {
|
||||
loadpopup.removeClass("hidden");
|
||||
loadpopup.addClass("flex");
|
||||
@ -923,6 +936,46 @@ function hideUSPopup() {
|
||||
spcontent.html("");
|
||||
}
|
||||
|
||||
|
||||
function buildLoadModelList(ar) {
|
||||
disableButtons([load_model_accept]);
|
||||
loadmodelcontent.html("");
|
||||
var i;
|
||||
for(i=0; i<ar.length; i++) {
|
||||
var html
|
||||
html = "<div class=\"flex\">\
|
||||
<div class=\"loadlistpadding\"></div>"
|
||||
if(ar[i][3]) {
|
||||
html = html + "<span class=\"loadlisticon loadmodellisticon-folder oi oi-folder allowed\" aria-hidden=\"true\"></span>"
|
||||
} else {
|
||||
html = html + "<div class=\"loadlistpadding\"></div>"
|
||||
}
|
||||
html = html + "<div class=\"loadlistpadding\"></div>\
|
||||
<div class=\"loadlistitem\" id=\"loadmodel"+i+"\" name=\""+ar[i][1]+"\">\
|
||||
<div>"+ar[i][0]+"</div>\
|
||||
<div class=\"flex-push-right\">"+ar[i][2]+"</div>\
|
||||
</div>\
|
||||
</div>"
|
||||
loadmodelcontent.append(html);
|
||||
if(ar[i][3]) {
|
||||
$("#loadmodel"+i).off("click").on("click", (function () {
|
||||
return function () {
|
||||
socket.send({'cmd': 'list_model', 'data': $(this).attr("name")});
|
||||
disableButtons([load_model_accept]);
|
||||
}
|
||||
})(i));
|
||||
} else {
|
||||
$("#loadmodel"+i).off("click").on("click", (function () {
|
||||
return function () {
|
||||
socket.send({'cmd': 'selectmodel', 'data': $(this).attr("name")});
|
||||
highlightLoadLine($(this));
|
||||
enableButtons([load_model_accept]);
|
||||
}
|
||||
})(i));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
function buildLoadList(ar) {
|
||||
disableButtons([load_accept]);
|
||||
loadcontent.html("");
|
||||
@ -1771,6 +1824,7 @@ $(document).ready(function(){
|
||||
|
||||
// Bind UI references
|
||||
connect_status = $('#connectstatus');
|
||||
button_loadmodel = $('#btn_loadmodel');
|
||||
button_newgame = $('#btn_newgame');
|
||||
button_rndgame = $('#btn_rndgame');
|
||||
button_save = $('#btn_save');
|
||||
@ -1823,9 +1877,13 @@ $(document).ready(function(){
|
||||
saveas_accept = $("#btn_saveasaccept");
|
||||
saveas_close = $("#btn_saveasclose");
|
||||
loadpopup = $("#loadcontainer");
|
||||
loadmodelpopup = $("#loadmodelcontainer");
|
||||
loadcontent = $("#loadlistcontent");
|
||||
loadmodelcontent = $("#loadmodellistcontent");
|
||||
load_accept = $("#btn_loadaccept");
|
||||
load_close = $("#btn_loadclose");
|
||||
load_model_accept = $("#btn_loadmodelaccept");
|
||||
load_model_close = $("#btn_loadmodelclose");
|
||||
sppopup = $("#spcontainer");
|
||||
spcontent = $("#splistcontent");
|
||||
sp_accept = $("#btn_spaccept");
|
||||
@ -2313,6 +2371,18 @@ $(document).ready(function(){
|
||||
} else {
|
||||
debug_area.addClass("hidden");
|
||||
}
|
||||
} else if(msg.cmd == 'show_model_menu') {
|
||||
if(msg.menu == 'gpt2list') {
|
||||
$("#use_gpu_div").removeClass("hidden")
|
||||
} else {
|
||||
$("#use_gpu_div").addClass("hidden")
|
||||
}
|
||||
if(msg.menu == 'apilist') {
|
||||
$("#modelkey").removeClass("hidden")
|
||||
} else {
|
||||
$("#modelkey").addClass("hidden")
|
||||
}
|
||||
buildLoadModelList(msg.data);
|
||||
}
|
||||
});
|
||||
|
||||
@ -2511,6 +2581,10 @@ $(document).ready(function(){
|
||||
hideLoadPopup();
|
||||
});
|
||||
|
||||
load_model_close.on("click", function(ev) {
|
||||
hideLoadModelPopup();
|
||||
});
|
||||
|
||||
load_accept.on("click", function(ev) {
|
||||
hideMessage();
|
||||
newly_loaded = true;
|
||||
@ -2518,6 +2592,13 @@ $(document).ready(function(){
|
||||
hideLoadPopup();
|
||||
});
|
||||
|
||||
load_model_accept.on("click", function(ev) {
|
||||
hideMessage();
|
||||
socket.send({'cmd': 'load_model', 'use_gpu': $('#use_gpu')[0].checked, 'key': $('#modelkey')[0].value});
|
||||
loadmodelcontent.html("");
|
||||
hideLoadModelPopup();
|
||||
});
|
||||
|
||||
sp_close.on("click", function(ev) {
|
||||
hideSPPopup();
|
||||
});
|
||||
@ -2540,6 +2621,11 @@ $(document).ready(function(){
|
||||
hideUSPopup();
|
||||
});
|
||||
|
||||
button_loadmodel.on("click", function(ev) {
|
||||
showLoadModelPopup();
|
||||
socket.send({'cmd': 'list_model', 'data': 'mainmenu'});
|
||||
});
|
||||
|
||||
button_newgame.on("click", function(ev) {
|
||||
if(connected) {
|
||||
showNewStoryPopup();
|
||||
|
||||
@ -33,6 +33,12 @@
|
||||
</button>
|
||||
<div class="collapse navbar-collapse" id="navbarNavDropdown">
|
||||
<ul class="nav navbar-nav">
|
||||
<li class="nav-item dropdown">
|
||||
<a class="nav-link dropdown-toggle" href="#" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false">AI</a>
|
||||
<div class="dropdown-menu">
|
||||
<a class="dropdown-item" href="#" id="btn_loadmodel">Load Model</a>
|
||||
</div>
|
||||
</li>
|
||||
<li class="nav-item dropdown">
|
||||
<a class="nav-link dropdown-toggle" href="#" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false">New Game</a>
|
||||
<div class="dropdown-menu">
|
||||
@ -265,6 +271,29 @@
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="popupcontainer hidden" id="loadmodelcontainer">
|
||||
<div id="loadpopup">
|
||||
<div class="popuptitlebar">
|
||||
<div class="popuptitletext">Select A Model To Load</div>
|
||||
</div>
|
||||
<div class="loadmodellistheader">
|
||||
<div>Model</div>
|
||||
</div>
|
||||
<div id="loadmodellistcontent">
|
||||
</div>
|
||||
<div class="popupfooter">
|
||||
<input class="form-control hidden" type="text" placeholder="key" id="modelkey"><br>
|
||||
</div>
|
||||
<div class="popupfooter">
|
||||
<button type="button" class="btn btn-primary" id="btn_loadmodelaccept">Load</button>
|
||||
<button type="button" class="btn btn-primary" id="btn_loadmodelclose">Cancel</button>
|
||||
<div class="box flex-push-right hidden" id=use_gpu_div>
|
||||
<input type="checkbox" data-toggle="toggle" data-onstyle="success" id="use_gpu" checked>
|
||||
<div class="box-label">Use GPU</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="popupcontainer hidden" id="spcontainer">
|
||||
<div id="sppopup">
|
||||
<div class="popuptitlebar">
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user