diff --git a/.gitattributes b/.gitattributes index d234b5e0..661ee711 100644 --- a/.gitattributes +++ b/.gitattributes @@ -1,2 +1,3 @@ *.min.lua linguist-vendored *documentation.html linguist-vendored +/static/swagger-ui/* linguist-vendored diff --git a/.gitignore b/.gitignore index b97d1d30..90669874 100644 --- a/.gitignore +++ b/.gitignore @@ -25,6 +25,8 @@ softprompts models !models/models go here.txt Uninstall +flask_session +accelerate-disk-cache .ipynb_checkpoints # Ignore PyCharm project files. diff --git a/Uninstall.bat b/Uninstall.bat index ed143996..ae7a4201 100644 --- a/Uninstall.bat +++ b/Uninstall.bat @@ -11,11 +11,15 @@ IF EXIST "Uninstall\unins000.exe" ( start Uninstall\unins000.exe exit ) ELSE ( - echo This will remove all KoboldAI folders that do not contain user data - pause - GOTO UNINSTALL + echo This will remove all KoboldAI folders that do not contain user data. + echo DO NOT CONTINUE IF KOBOLDAI IS NOT IN ITS OWN FOLDER! OTHERWISE YOUR OTHER DATA IN THIS FOLDER WILL BE DELETED AS WELL! + pause + set /P D=Type DELETE if you wish to continue the uninstallation: ) +IF %D%==DELETE GOTO UNINSTALL +exit + :UNINSTALL echo Uninstallation in progress, please wait... set DM=Y diff --git a/aiserver.py b/aiserver.py index a4cf35c1..28a2c00c 100644 --- a/aiserver.py +++ b/aiserver.py @@ -1,4 +1,4 @@ - #!/usr/bin/python3 +#!/usr/bin/python3 #==================================================================# # KoboldAI # Version: 1.18.1 @@ -7,9 +7,7 @@ # External packages import eventlet -from eventlet import tpool eventlet.monkey_patch(all=True, thread=False, os=False) -#eventlet.monkey_patch(os=True, select=True, socket=True, thread=True, time=True, psycopg=True) import os os.system("") __file__ = os.path.dirname(os.path.realpath(__file__)) @@ -37,10 +35,11 @@ import itertools import bisect import functools import traceback +import inspect +import warnings import multiprocessing from collections.abc import Iterable -from collections import OrderedDict -from typing import Any, Callable, Optional, TypeVar, Tuple, Union, Dict, Set, List +from typing import Any, Callable, TypeVar, Tuple, Union, Dict, Set, List, Optional, Type import requests import html @@ -121,17 +120,19 @@ model_menu = { ["Adventure Models", "adventurelist", "", True], ["Novel Models", "novellist", "", True], ["NSFW Models", "nsfwlist", "", True], + ["Untuned OPT", "optlist", "", True], ["Untuned GPT-Neo/J", "gptneolist", "", True], ["Untuned Fairseq Dense", "fsdlist", "", True], - ["Untuned OPT", "optlist", "", True], ["Untuned XGLM", "xglmlist", "", True], ["Untuned GPT2", "gpt2list", "", True], ["Online Services", "apilist", "", True], ["Read Only (No AI)", "ReadOnly", "", False] ], 'adventurelist': [ + ["Nerys FSD 13B V2 (Hybrid)", "KoboldAI/fairseq-dense-13B-Nerys-v2", "32GB", False], ["Nerys FSD 13B (Hybrid)", "KoboldAI/fairseq-dense-13B-Nerys", "32GB", False], ["Skein 6B", "KoboldAI/GPT-J-6B-Skein", "16GB", False], + ["OPT Nerys 6B V2", "KoboldAI/OPT-6B-nerys-v2", "16GB", False], ["Adventure 6B", "KoboldAI/GPT-J-6B-Adventure", "16GB", False], ["Nerys FSD 2.7B (Hybrid)", "KoboldAI/fairseq-dense-2.7B-Nerys", "8GB", False], ["Adventure 2.7B", "KoboldAI/GPT-Neo-2.7B-AID", "8GB", False], @@ -140,8 +141,10 @@ model_menu = { ["Return to Main Menu", "mainmenu", "", True], ], 'novellist': [ - ["Nerys FSD 13B (Hybrid)", "KoboldAI/fairseq-dense-13B-Nerys", "32GB", False], + ["Nerys FSD 13B V2 (Hybrid)", "KoboldAI/fairseq-dense-13B-Nerys-v2", "32GB", False], ["Janeway FSD 13B", "KoboldAI/fairseq-dense-13B-Janeway", "32GB", False], + ["Nerys FSD 13B (Hybrid)", "KoboldAI/fairseq-dense-13B-Nerys", "32GB", False], + ["OPT Nerys 6B V2", "KoboldAI/OPT-6B-nerys-v2", "16GB", False], ["Janeway FSD 6.7B", "KoboldAI/fairseq-dense-6.7B-Janeway", "16GB", False], ["Janeway Neo 6B", "KoboldAI/GPT-J-6B-Janeway", "16GB", False], ["Janeway Neo 2.7B", "KoboldAI/GPT-Neo-2.7B-Janeway", "8GB", False], @@ -181,6 +184,7 @@ model_menu = { ["Return to Main Menu", "mainmenu", "", True], ], 'optlist': [ + ["OPT 66B", "facebook/opt-66b", "128GB", False], ["OPT 30B", "facebook/opt-30b", "64GB", False], ["OPT 13B", "facebook/opt-13b", "32GB", False], ["OPT 6.7B", "facebook/opt-6.7b", "16GB", False], @@ -211,11 +215,15 @@ model_menu = { ["GooseAI API (requires API key)", "GooseAI", "", False], ["OpenAI API (requires API key)", "OAI", "", False], ["InferKit API (requires API key)", "InferKit", "", False], - ["KoboldAI Server API (Old Google Colab)", "Colab", "", False], + # ["KoboldAI Server API (Old Google Colab)", "Colab", "", False], + ["KoboldAI API", "API", "", False], ["Return to Main Menu", "mainmenu", "", True], ] } + +utils.koboldai_vars = koboldai_vars + class Send_to_socketio(object): def write(self, bar): print(bar, end="") @@ -232,10 +240,13 @@ log.setLevel(logging.ERROR) # Start flask & SocketIO print("{0}Initializing Flask... {1}".format(colors.PURPLE, colors.END), end="") -from flask import Flask, render_template, Response, request, copy_current_request_context, send_from_directory, session, has_request_context +from flask import Flask, render_template, Response, request, copy_current_request_context, send_from_directory, session, jsonify, abort, redirect, has_request_context from flask_socketio import SocketIO, emit, join_room, leave_room +from flask_socketio import emit as _emit from flask_session import Session import secrets +from werkzeug.exceptions import HTTPException, NotFound, InternalServerError +import secrets app = Flask(__name__, root_path=os.getcwd()) app.secret_key = secrets.token_hex() app.config['SESSION_TYPE'] = 'filesystem' @@ -249,6 +260,208 @@ utils.koboldai_vars = koboldai_vars print("{0}OK!{1}".format(colors.GREEN, colors.END)) +old_socketio_on = socketio.on +def new_socketio_on(*a, **k): + decorator = old_socketio_on(*a, **k) + def new_decorator(f): + @functools.wraps(f) + def g(*a, **k): + if args.no_ui: + return + return f(*a, **k) + return decorator(g) + return new_decorator +socketio.on = new_socketio_on + +def emit(*args, **kwargs): + try: + return _emit(*args, **kwargs) + except AttributeError: + return socketio.emit(*args, **kwargs) + +# marshmallow/apispec setup +from apispec import APISpec +from apispec.ext.marshmallow import MarshmallowPlugin +from apispec.ext.marshmallow.field_converter import make_min_max_attributes +from apispec_webframeworks.flask import FlaskPlugin +from marshmallow import Schema, fields, validate, EXCLUDE +from marshmallow.exceptions import ValidationError + +class KoboldSchema(Schema): + pass + +def new_make_min_max_attributes(validators, min_attr, max_attr) -> dict: + # Patched apispec function that creates "exclusiveMinimum"/"exclusiveMaximum" OpenAPI attributes insteaed of "minimum"/"maximum" when using validators.Range or validators.Length with min_inclusive=False or max_inclusive=False + attributes = {} + min_list = [validator.min for validator in validators if validator.min is not None] + max_list = [validator.max for validator in validators if validator.max is not None] + min_inclusive_list = [getattr(validator, "min_inclusive", True) for validator in validators if validator.min is not None] + max_inclusive_list = [getattr(validator, "max_inclusive", True) for validator in validators if validator.max is not None] + if min_list: + if min_attr == "minimum" and not min_inclusive_list[max(range(len(min_list)), key=min_list.__getitem__)]: + min_attr = "exclusiveMinimum" + attributes[min_attr] = max(min_list) + if max_list: + if min_attr == "maximum" and not max_inclusive_list[min(range(len(max_list)), key=max_list.__getitem__)]: + min_attr = "exclusiveMaximum" + attributes[max_attr] = min(max_list) + return attributes +make_min_max_attributes.__code__ = new_make_min_max_attributes.__code__ + +def api_format_docstring(f): + f.__doc__ = eval('f"""{}"""'.format(f.__doc__.replace("\\", "\\\\"))) + return f + +def api_catch_out_of_memory_errors(f): + @functools.wraps(f) + def decorated(*args, **kwargs): + try: + return f(*args, **kwargs) + except Exception as e: + if any (s in traceback.format_exc().lower() for s in ("out of memory", "not enough memory")): + for line in reversed(traceback.format_exc().split("\n")): + if any(s in line.lower() for s in ("out of memory", "not enough memory")) and line.count(":"): + line = line.split(":", 1)[1] + line = re.sub(r"\[.+?\] +data\.", "", line).strip() + raise KoboldOutOfMemoryError("KoboldAI ran out of memory: " + line, type="out_of_memory.gpu.cuda" if "cuda out of memory" in line.lower() else "out_of_memory.gpu.hip" if "hip out of memory" in line.lower() else "out_of_memory.tpu.hbm" if "memory space hbm" in line.lower() else "out_of_memory.cpu.default_memory_allocator" if "defaultmemoryallocator" in line.lower() else "out_of_memory.unknown.unknown") + raise KoboldOutOfMemoryError(type="out_of_memory.unknown.unknown") + raise e + return decorated + +def api_schema_wrap(f): + try: + input_schema: Type[Schema] = next(iter(inspect.signature(f).parameters.values())).annotation + except: + HAS_SCHEMA = False + else: + HAS_SCHEMA = inspect.isclass(input_schema) and issubclass(input_schema, Schema) + f = api_format_docstring(f) + f = api_catch_out_of_memory_errors(f) + @functools.wraps(f) + def decorated(*args, **kwargs): + if HAS_SCHEMA: + body = request.get_json() + schema = input_schema.from_dict(input_schema().load(body)) + response = f(schema, *args, **kwargs) + else: + response = f(*args, **kwargs) + if not isinstance(response, Response): + response = jsonify(response) + return response + return decorated + +@app.errorhandler(HTTPException) +def handler(e): + if request.path != "/api" and not request.path.startswith("/api/"): + return e + resp = jsonify(detail={"msg": str(e), "type": "generic.error_" + str(e.code)}) + if e.code == 405 and e.valid_methods is not None: + resp.headers["Allow"] = ", ".join(e.valid_methods) + return resp, e.code + +class KoboldOutOfMemoryError(HTTPException): + code = 507 + description = "KoboldAI ran out of memory." + type = "out_of_memory.unknown.unknown" + def __init__(self, *args, type=None, **kwargs): + super().__init__(*args, **kwargs) + if type is not None: + self.type = type +@app.errorhandler(KoboldOutOfMemoryError) +def handler(e): + if request.path != "/api" and not request.path.startswith("/api/"): + return InternalServerError() + return jsonify(detail={"type": e.type, "msg": e.description}), e.code + +@app.errorhandler(ValidationError) +def handler(e): + if request.path != "/api" and not request.path.startswith("/api/"): + return InternalServerError() + return jsonify(detail=e.messages), 422 + +@app.errorhandler(NotImplementedError) +def handler(e): + if request.path != "/api" and not request.path.startswith("/api/"): + return InternalServerError() + return jsonify(detail={"type": "not_implemented", "msg": str(e).strip()}), 501 + +api_versions: List[str] = [] + +class KoboldAPISpec(APISpec): + class KoboldFlaskPlugin(FlaskPlugin): + def __init__(self, api: "KoboldAPISpec", *args, **kwargs): + self._kobold_api_spec = api + super().__init__(*args, **kwargs) + + def path_helper(self, *args, **kwargs): + return super().path_helper(*args, **kwargs)[len(self._kobold_api_spec._prefixes[0]):] + + def __init__(self, *args, title: str = "KoboldAI API", openapi_version: str = "3.0.3", version: str = "1.0.0", prefixes: List[str] = None, **kwargs): + plugins = [KoboldAPISpec.KoboldFlaskPlugin(self), MarshmallowPlugin()] + self._prefixes = prefixes if prefixes is not None else [""] + self._kobold_api_spec_version = version + api_versions.append(version) + api_versions.sort(key=lambda x: [int(e) for e in x.split(".")]) + super().__init__(*args, title=title, openapi_version=openapi_version, version=version, plugins=plugins, servers=[{"url": self._prefixes[0]}], **kwargs) + for prefix in self._prefixes: + app.route(prefix, endpoint="~KoboldAPISpec~" + prefix)(lambda: redirect(request.path + "/docs/")) + app.route(prefix + "/", endpoint="~KoboldAPISpec~" + prefix + "/")(lambda: redirect("docs/")) + app.route(prefix + "/docs", endpoint="~KoboldAPISpec~" + prefix + "/docs")(lambda: redirect("docs/")) + app.route(prefix + "/docs/", endpoint="~KoboldAPISpec~" + prefix + "/docs/")(lambda: render_template("swagger-ui.html", url=self._prefixes[0] + "/openapi.json")) + app.route(prefix + "/openapi.json", endpoint="~KoboldAPISpec~" + prefix + "/openapi.json")(lambda: jsonify(self.to_dict())) + + def route(self, rule: str, methods=["GET"], **kwargs): + __F = TypeVar("__F", bound=Callable[..., Any]) + if "strict_slashes" not in kwargs: + kwargs["strict_slashes"] = False + def new_decorator(f: __F) -> __F: + @functools.wraps(f) + def g(*args, **kwargs): + global api_version + api_version = self._kobold_api_spec_version + try: + return f(*args, **kwargs) + finally: + api_version = None + for prefix in self._prefixes: + g = app.route(prefix + rule, methods=methods, **kwargs)(g) + with app.test_request_context(): + self.path(view=g, **kwargs) + return g + return new_decorator + + def get(self, rule: str, **kwargs): + return self.route(rule, methods=["GET"], **kwargs) + + def post(self, rule: str, **kwargs): + return self.route(rule, methods=["POST"], **kwargs) + + def put(self, rule: str, **kwargs): + return self.route(rule, methods=["PUT"], **kwargs) + + def patch(self, rule: str, **kwargs): + return self.route(rule, methods=["PATCH"], **kwargs) + + def delete(self, rule: str, **kwargs): + return self.route(rule, methods=["DELETE"], **kwargs) + +tags = [ + {"name": "info", "description": "Metadata about this API"}, + {"name": "generate", "description": "Text generation endpoints"}, + {"name": "model", "description": "Information about the current text generation model"}, + {"name": "story", "description": "Endpoints for managing the story in the KoboldAI GUI"}, + {"name": "world_info", "description": "Endpoints for managing the world info in the KoboldAI GUI"}, + {"name": "config", "description": "Allows you to get/set various setting values"}, +] + +api_version = None # This gets set automatically so don't change this value + +api_v1 = KoboldAPISpec( + version="1.1.4", + prefixes=["/api/v1", "/api/latest"], + tags=tags, +) + #==================================================================# # Function to get model selection at startup #==================================================================# @@ -327,7 +540,7 @@ def getModelSelection(modellist): modpath = fileops.getdirpath(getcwd() + "/models", "Select Model Folder") if(modpath): - # Save directory to vars + # Save directory to koboldai_vars koboldai_vars.custmodpth = modpath else: # Print error and retry model selection @@ -396,7 +609,10 @@ def device_config(config): global breakmodel, generator import breakmodel n_layers = utils.num_layers(config) - if(args.breakmodel_gpulayers is not None or (utils.HAS_ACCELERATE and args.breakmodel_disklayers is not None)): + if args.cpu: + breakmodel.gpu_blocks = [0]*n_layers + return + elif(args.breakmodel_gpulayers is not None or (utils.HAS_ACCELERATE and args.breakmodel_disklayers is not None)): try: if(not args.breakmodel_gpulayers): breakmodel.gpu_blocks = [] @@ -517,6 +733,11 @@ def move_model_to_devices(model): import breakmodel if(utils.HAS_ACCELERATE): + import accelerate.utils + for key, value in model.state_dict().items(): + target_dtype = torch.float32 if breakmodel.primary_device == "cpu" else torch.float16 + if(value.dtype is not target_dtype): + accelerate.utils.set_module_tensor_to_device(model, key, target_dtype) disk_blocks = breakmodel.disk_blocks gpu_blocks = breakmodel.gpu_blocks ram_blocks = len(utils.layers_module_names) - sum(gpu_blocks) @@ -642,7 +863,7 @@ def loadmodelsettings(): koboldai_vars.authornotetemplate = koboldai_vars.setauthornotetemplate #==================================================================# -# Take settings from vars and write them to client settings file +# Take settings from koboldai_vars and write them to client settings file #==================================================================# def savesettings(): # Build json to write @@ -673,10 +894,18 @@ def savesettings(): js["nopromptgen"] = koboldai_vars.nopromptgen js["rngpersist"] = koboldai_vars.rngpersist js["nogenmod"] = koboldai_vars.nogenmod + js["fulldeterminism"] = koboldai_vars.full_determinism js["autosave"] = koboldai_vars.autosave js["welcome"] = koboldai_vars.welcome - js["newlinemode"] = koboldai_vars.newlinemode js["output_streaming"] = koboldai_vars.output_streaming + js["show_probs"] = koboldai_vars.show_probs + + if(koboldai_vars.seed_specified): + js["seed"] = koboldai_vars.seed + else: + js["seed"] = None + + js["newlinemode"] = koboldai_vars.newlinemode js["antemplate"] = koboldai_vars.setauthornotetemplate @@ -702,7 +931,7 @@ def settingschanged(): savesettings() #==================================================================# -# Read settings from client file JSON and send to vars +# Read settings from client file JSON and send to koboldai_vars #==================================================================# def loadsettings(): @@ -722,7 +951,7 @@ def loadsettings(): file.close() def processsettings(js): -# Copy file contents to vars +# Copy file contents to koboldai_vars if("apikey" in js): koboldai_vars.apikey = js["apikey"] if("andepth" in js): @@ -775,6 +1004,8 @@ def processsettings(js): koboldai_vars.rngpersist = js["rngpersist"] if("nogenmod" in js): koboldai_vars.nogenmod = js["nogenmod"] + if("fulldeterminism" in js): + koboldai_vars.full_determinism = js["fulldeterminism"] if("autosave" in js): koboldai_vars.autosave = js["autosave"] if("newlinemode" in js): @@ -782,7 +1013,18 @@ def processsettings(js): if("welcome" in js): koboldai_vars.welcome = js["welcome"] if("output_streaming" in js): - koboldai_vars.autosave = js["output_streaming"] + koboldai_vars.output_streaming = js["output_streaming"] + if("show_probs" in js): + koboldai_vars.show_probs = js["show_probs"] + + if("seed" in js): + koboldai_vars.seed = js["seed"] + if(koboldai_vars.seed is not None): + koboldai_vars.seed_specified = True + else: + koboldai_vars.seed_specified = False + else: + koboldai_vars.seed_specified = False if("antemplate" in js): koboldai_vars.setauthornotetemplate = js["antemplate"] @@ -809,12 +1051,20 @@ def processsettings(js): def check_for_sp_change(): while(True): - time.sleep(0.1) + time.sleep(0.05) + if(koboldai_vars.sp_changed): with app.app_context(): emit('from_server', {'cmd': 'spstatitems', 'data': {koboldai_vars.spfilename: koboldai_vars.spmeta} if koboldai_vars.allowsp and len(koboldai_vars.spfilename) else {}}, namespace=None, broadcast=True, room="UI_1") koboldai_vars.sp_changed = False + if(koboldai_vars.token_stream_queue.queue): + # If emit blocks, waiting for it to complete before clearing could + # introduce a race condition that drops tokens. + queued_tokens = list(koboldai_vars.token_stream_queue.queue) + koboldai_vars.token_stream_queue.queue.clear() + socketio.emit("from_server", {"cmd": "streamtoken", "data": queued_tokens}, namespace=None, broadcast=True) + socketio.start_background_task(check_for_sp_change) def spRequest(filename): @@ -911,6 +1161,8 @@ def general_startup(override_args=None): parser.add_argument("--no_aria2", action='store_true', default=False, help="Prevents KoboldAI from using aria2 to download huggingface models more efficiently, in case aria2 is causing you issues") 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") parser.add_argument("--savemodel", action='store_true', help="Saves the model to the models folder even if --colab is used (Allows you to save models to Google Drive)") + parser.add_argument("--customsettings", help="Preloads arguements from json file. You only need to provide the location of the json file. Use customsettings.json template file. It can be renamed if you wish so that you can store multiple configurations. Leave any settings you want as default as null. Any values you wish to set need to be in double quotation marks") + parser.add_argument("--no_ui", action='store_true', default=False, help="Disables the GUI and Socket.IO server while leaving the API server running.") #args: argparse.Namespace = None if "pytest" in sys.modules and override_args is None: args = parser.parse_args([]) @@ -938,8 +1190,19 @@ def general_startup(override_args=None): setattr(args, arg, False) else: setattr(args, arg, os.environ[arg]) - - + if args.customsettings: + f = open (args.customsettings) + importedsettings = json.load(f) + for items in importedsettings: + if importedsettings[items] is not None: + setattr(args, items, importedsettings[items]) + f.close() + + if args.no_ui: + def new_emit(*args, **kwargs): + return + old_emit = socketio.emit + socketio.emit = new_emit koboldai_vars.model = args.model; koboldai_vars.revision = args.revision @@ -985,7 +1248,7 @@ def general_startup(override_args=None): modpath = fileops.getdirpath(getcwd() + "/models", "Select Model Folder") if(modpath): - # Save directory to vars + # Save directory to koboldai_vars koboldai_vars.model = "NeoCustom" koboldai_vars.custmodpth = modpath elif args.model: @@ -1060,6 +1323,8 @@ def get_model_info(model, directory=""): url = True elif not utils.HAS_ACCELERATE and not torch.cuda.is_available(): pass + elif args.cpu: + pass else: layer_count = get_layer_count(model, directory=directory) if layer_count is None: @@ -1067,7 +1332,7 @@ def get_model_info(model, directory=""): else: breakmodel = True if model in ["NeoCustom", "GPT2Custom"]: - filename = os.path.basename(os.path.normpath(directory)) + filename = "settings/{}.breakmodel".format(os.path.basename(os.path.normpath(directory))) else: filename = "settings/{}.breakmodel".format(model.replace("/", "_")) if path.exists(filename): @@ -1102,14 +1367,13 @@ def get_layer_count(model, directory=""): else: from transformers import AutoConfig if directory == "": - if os.path.isdir("./models/{}".format(model.replace("/", "_"))): - model_config = AutoConfig.from_pretrained("./models/{}".format(model.replace("/", "_")), cache_dir="cache") - else: - model_config = AutoConfig.from_pretrained(model, cache_dir="cache") - elif os.path.isdir(directory): - model_config = AutoConfig.from_pretrained(directory, cache_dir="cache") + model_config = AutoConfig.from_pretrained(koboldai_vars.model, revision=koboldai_vars.revision, cache_dir="cache") + elif(os.path.isdir(koboldai_vars.custmodpth.replace('/', '_'))): + model_config = AutoConfig.from_pretrained(koboldai_vars.custmodpth.replace('/', '_'), revision=koboldai_vars.revision, cache_dir="cache") + elif(os.path.isdir(directory)): + model_config = AutoConfig.from_pretrained(directory, revision=koboldai_vars.revision, cache_dir="cache") else: - assert "Selected Model directory doesn't exist" + model_config = AutoConfig.from_pretrained(koboldai_vars.custmodpth, revision=koboldai_vars.revision, cache_dir="cache") @@ -1235,28 +1499,32 @@ def patch_transformers_download(): total = resume_size + int(content_length) if content_length is not None else None # `tqdm` behavior is determined by `utils.logging.is_progress_bar_enabled()` # and can be set using `utils.logging.enable/disable_progress_bar()` - koboldai_vars.total_download_chunks = total - progress = tqdm.tqdm( - unit="B", - unit_scale=True, - unit_divisor=1024, - total=total, - initial=resume_size, - desc=f"Downloading {file_name}" if file_name is not None else "Downloading", - file=Send_to_socketio(), - ) + if url[-11:] != 'config.json': + progress = tqdm.tqdm( + unit="B", + unit_scale=True, + unit_divisor=1024, + total=total, + initial=resume_size, + desc=f"Downloading {file_name}" if file_name is not None else "Downloading", + file=Send_to_socketio(), + ) for chunk in r.iter_content(chunk_size=1024): if chunk: # filter out keep-alive new chunks - progress.update(len(chunk)) - koboldai_vars.downloaded_chunks += len(chunk) + if url[-11:] != 'config.json': + progress.update(len(chunk)) temp_file.write(chunk) - progress.close() + if url[-11:] != 'config.json': + progress.close() transformers.utils.hub.http_get = http_get + def patch_transformers(): global transformers + patch_transformers_download() + old_from_pretrained = PreTrainedModel.from_pretrained.__func__ @classmethod def new_from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs): @@ -1424,6 +1692,9 @@ def patch_transformers(): self.regeneration_required = False self.halt = False + if(koboldai_vars.standalone): + return scores + scores_shape = scores.shape scores_list = scores.tolist() koboldai_vars.lua_koboldbridge.logits = koboldai_vars.lua_state.table() @@ -1441,11 +1712,37 @@ def patch_transformers(): assert scores.shape == scores_shape return scores + + from torch.nn import functional as F + + class ProbabilityVisualizerLogitsProcessor(LogitsProcessor): + def __init__(self): + pass + + def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor) -> torch.FloatTensor: + assert scores.ndim == 2 + assert input_ids.ndim == 2 + + if koboldai_vars.numseqs > 1 or not koboldai_vars.show_probs: + return scores + + probs = F.softmax(scores, dim = -1).cpu().numpy()[0] + + token_prob_info = [] + for token_id, score in sorted(enumerate(probs), key=lambda x: x[1], reverse=True)[:8]: + token_prob_info.append({ + "tokenId": token_id, + "decoded": utils.decodenewlines(tokenizer.decode(token_id)), + "score": float(score), + }) + + koboldai_vars.token_stream_queue.probability_buffer = token_prob_info + return scores def new_get_logits_processor(*args, **kwargs) -> LogitsProcessorList: processors = new_get_logits_processor.old_get_logits_processor(*args, **kwargs) processors.insert(0, LuaLogitsProcessor()) - processors.insert(0, PhraseBiasLogitsProcessor()) + processors.append(ProbabilityVisualizerLogitsProcessor()) return processors new_get_logits_processor.old_get_logits_processor = transformers.generation_utils.GenerationMixin._get_logits_processor transformers.generation_utils.GenerationMixin._get_logits_processor = new_get_logits_processor @@ -1490,7 +1787,7 @@ def patch_transformers(): class TokenStreamer(StoppingCriteria): # A StoppingCriteria is used here because it seems to run after - # everything has been evaluated score-wise. + # everything has been evaluated score-wise. def __init__(self, tokenizer): self.tokenizer = tokenizer @@ -1534,12 +1831,14 @@ def patch_transformers(): **kwargs, ) -> bool: koboldai_vars.generated_tkns += 1 - if(koboldai_vars.lua_koboldbridge.generated_cols and koboldai_vars.generated_tkns != koboldai_vars.lua_koboldbridge.generated_cols): + if(not koboldai_vars.standalone and koboldai_vars.lua_koboldbridge.generated_cols and koboldai_vars.generated_tkns != koboldai_vars.lua_koboldbridge.generated_cols): raise RuntimeError(f"Inconsistency detected between KoboldAI Python and Lua backends ({koboldai_vars.generated_tkns} != {koboldai_vars.lua_koboldbridge.generated_cols})") if(koboldai_vars.abort or koboldai_vars.generated_tkns >= koboldai_vars.genamt): self.regeneration_required = False self.halt = False return True + if(koboldai_vars.standalone): + return False assert input_ids.ndim == 2 assert len(self.excluded_world_info) == input_ids.shape[0] @@ -1569,12 +1868,38 @@ def patch_transformers(): tokenizer=tokenizer, excluded_world_info=self.kai_scanner_excluded_world_info, ) + token_streamer = TokenStreamer(tokenizer=tokenizer) + stopping_criteria.insert(0, self.kai_scanner) token_streamer = TokenStreamer(tokenizer=tokenizer) stopping_criteria.insert(0, token_streamer) return stopping_criteria transformers.generation_utils.GenerationMixin._get_stopping_criteria = new_get_stopping_criteria +def reset_model_settings(): + koboldai_vars.socketio = socketio + koboldai_vars.max_length = 1024 # Maximum number of tokens to submit per action + koboldai_vars.ikmax = 3000 # Maximum number of characters to submit to InferKit + koboldai_vars.genamt = 80 # Amount of text for each action to generate + koboldai_vars.ikgen = 200 # Number of characters for InferKit to generate + koboldai_vars.rep_pen = 1.1 # Default generator repetition_penalty + koboldai_vars.rep_pen_slope = 0.7 # Default generator repetition penalty slope + koboldai_vars.rep_pen_range = 1024 # Default generator repetition penalty range + koboldai_vars.temp = 0.5 # Default generator temperature + koboldai_vars.top_p = 0.9 # Default generator top_p + koboldai_vars.top_k = 0 # Default generator top_k + koboldai_vars.top_a = 0.0 # Default generator top-a + koboldai_vars.tfs = 1.0 # Default generator tfs (tail-free sampling) + koboldai_vars.typical = 1.0 # Default generator typical sampling threshold + koboldai_vars.numseqs = 1 # Number of sequences to ask the generator to create + koboldai_vars.generated_tkns = 0 # If using a backend that supports Lua generation modifiers, how many tokens have already been generated, otherwise 0 + koboldai_vars.badwordsids = [] + koboldai_vars.fp32_model = False # Whether or not the most recently loaded HF model was in fp32 format + koboldai_vars.modeldim = -1 # Embedding dimension of your model (e.g. it's 4096 for GPT-J-6B and 2560 for GPT-Neo-2.7B) + koboldai_vars.sampler_order = [0, 1, 2, 3, 4, 5] + koboldai_vars.newlinemode = "n" + koboldai_vars.revision = None + def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=False, online_model=""): global model global generator @@ -1582,6 +1907,7 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal global model_config global GPT2TokenizerFast global tokenizer + reset_model_settings() if not utils.HAS_ACCELERATE: disk_layers = None koboldai_vars.reset_model() @@ -1589,25 +1915,31 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal if not initial_load: set_aibusy(True) if koboldai_vars.model != 'ReadOnly': - emit('from_server', {'cmd': 'model_load_status', 'data': "Loading {}".format(koboldai_vars.model)}, broadcast=True, room="UI_1") + emit('from_server', {'cmd': 'model_load_status', 'data': "Loading {}".format(koboldai_vars.model)}, broadcast=True) #Have to add a sleep so the server will send the emit for some reason time.sleep(0.1) if gpu_layers is not None: args.breakmodel_gpulayers = gpu_layers + elif initial_load: + gpu_layers = args.breakmodel_gpulayers if disk_layers is not None: args.breakmodel_disklayers = int(disk_layers) + elif initial_load: + disk_layers = args.breakmodel_disklayers #We need to wipe out the existing model and refresh the cuda cache model = None generator = None model_config = None - for tensor in gc.get_objects(): - try: - if torch.is_tensor(tensor): - with torch.no_grad(): - tensor.set_(torch.tensor((), device=tensor.device, dtype=tensor.dtype)) - except: - pass + with torch.no_grad(): + with warnings.catch_warnings(): + warnings.filterwarnings("ignore", message="torch.distributed.reduce_op is deprecated") + for tensor in gc.get_objects(): + try: + if torch.is_tensor(tensor): + tensor.set_(torch.tensor((), device=tensor.device, dtype=tensor.dtype)) + except: + pass gc.collect() try: with torch.no_grad(): @@ -1646,7 +1978,7 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal # If transformers model was selected & GPU available, ask to use CPU or GPU - if(koboldai_vars.model not in ["InferKit", "Colab", "OAI", "GooseAI" , "ReadOnly", "TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX"]): + if(koboldai_vars.model not in ["InferKit", "Colab", "API", "OAI", "GooseAI" , "ReadOnly", "TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX"]): koboldai_vars.allowsp = True # Test for GPU support @@ -1685,7 +2017,7 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal print("WARNING: No model type detected, assuming Neo (If this is a GPT2 model use the other menu option or --model GPT2Custom)") koboldai_vars.model_type = "gpt_neo" - if(not koboldai_vars.use_colab_tpu and koboldai_vars.model not in ["InferKit", "Colab", "OAI", "GooseAI" , "ReadOnly", "TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX"]): + if(not koboldai_vars.use_colab_tpu and koboldai_vars.model not in ["InferKit", "Colab", "API", "OAI", "GooseAI" , "ReadOnly", "TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX"]): loadmodelsettings() loadsettings() print("{0}Looking for GPU support...{1}".format(colors.PURPLE, colors.END), end="") @@ -1705,41 +2037,19 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal else: print("{0}NOT FOUND!{1}".format(colors.YELLOW, colors.END)) - if args.model: - if(koboldai_vars.hascuda): - genselected = True + if args.cpu: + koboldai_vars.usegpu = False + gpu_layers = None + disk_layers = None + koboldai_vars.breakmodel = False + elif koboldai_vars.hascuda: + if(koboldai_vars.bmsupported): + koboldai_vars.usegpu = False + koboldai_vars.breakmodel = True + else: + koboldai_vars.breakmodel = False koboldai_vars.usegpu = True - koboldai_vars.breakmodel = utils.HAS_ACCELERATE - if(koboldai_vars.bmsupported): - koboldai_vars.usegpu = False - koboldai_vars.breakmodel = True - if(args.cpu): - koboldai_vars.usegpu = False - koboldai_vars.breakmodel = utils.HAS_ACCELERATE - elif(koboldai_vars.hascuda): - if(koboldai_vars.bmsupported): - genselected = True - koboldai_vars.usegpu = False - koboldai_vars.breakmodel = True - else: - genselected = False - else: - genselected = False - if(koboldai_vars.hascuda): - if(use_gpu): - if(koboldai_vars.bmsupported): - koboldai_vars.breakmodel = True - koboldai_vars.usegpu = False - genselected = True - else: - koboldai_vars.breakmodel = False - koboldai_vars.usegpu = True - genselected = True - else: - koboldai_vars.breakmodel = utils.HAS_ACCELERATE - koboldai_vars.usegpu = False - genselected = True # Ask for API key if InferKit was selected if(koboldai_vars.model == "InferKit"): @@ -1760,7 +2070,7 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal koboldai_vars.noai = True # Start transformers and create pipeline - if(not koboldai_vars.use_colab_tpu and koboldai_vars.model not in ["InferKit", "Colab", "OAI", "GooseAI" , "ReadOnly", "TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX"]): + if(not koboldai_vars.use_colab_tpu and koboldai_vars.model not in ["InferKit", "Colab", "API", "OAI", "GooseAI" , "ReadOnly", "TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX"]): if(not koboldai_vars.noai): print("{0}Initializing transformers, please wait...{1}".format(colors.PURPLE, colors.END)) for m in ("GPTJModel", "XGLMModel"): @@ -2079,7 +2389,7 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal shutil.move(transformers.file_utils.get_from_cache(transformers.file_utils.hf_bucket_url(koboldai_vars.model, filename, revision=koboldai_vars.revision), cache_dir="cache", local_files_only=True), os.path.join("models/{}".format(koboldai_vars.model.replace('/', '_')), filename)) shutil.rmtree("cache/") - if(koboldai_vars.badwordsids is koboldai_settings.badwordsids_default and koboldai_vars.model_type not in ("gpt2", "gpt_neo", "gptj")): + if(koboldai_vars.badwordsids is koboldai_vars.badwordsids_default and koboldai_vars.model_type not in ("gpt2", "gpt_neo", "gptj")): koboldai_vars.badwordsids = [[v] for k, v in tokenizer.get_vocab().items() if any(c in str(k) for c in "<>[]") if koboldai_vars.newlinemode != "s" or str(k) != ""] patch_causallm(model) @@ -2114,8 +2424,8 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal # Suppress Author's Note by flagging square brackets (Old implementation) #vocab = tokenizer.get_vocab() #vocab_keys = vocab.keys() - #vars.badwords = gettokenids("[") - #for key in vars.badwords: + #koboldai_vars.badwords = gettokenids("[") + #for key in koboldai_vars.badwords: # koboldai_vars.badwordsids.append([vocab[key]]) print("{0}OK! {1} pipeline created!{2}".format(colors.GREEN, koboldai_vars.model, colors.END)) @@ -2215,7 +2525,7 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal } # If we're running Colab or OAI, we still need a tokenizer. - if(koboldai_vars.model == "Colab"): + if(koboldai_vars.model in ("Colab", "API")): from transformers import GPT2TokenizerFast tokenizer = GPT2TokenizerFast.from_pretrained("EleutherAI/gpt-neo-2.7B", revision=koboldai_vars.revision, cache_dir="cache") loadsettings() @@ -2228,7 +2538,7 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal global tpu_mtj_backend import tpu_mtj_backend if(koboldai_vars.model == "TPUMeshTransformerGPTNeoX"): - koboldai_vars.badwordsids = koboldai_settings.badwordsids_neox + koboldai_vars.badwordsids = koboldai_vars.badwordsids_neox print("{0}Initializing Mesh Transformer JAX, please wait...{1}".format(colors.PURPLE, colors.END)) if koboldai_vars.model in ("TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX") and (not koboldai_vars.custmodpth or not os.path.isdir(koboldai_vars.custmodpth)): raise FileNotFoundError(f"The specified model path {repr(koboldai_vars.custmodpth)} is not the path to a valid folder") @@ -2247,7 +2557,7 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal tpu_mtj_backend.load_model(koboldai_vars.custmodpth, hf_checkpoint=koboldai_vars.model not in ("TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX") and koboldai_vars.use_colab_tpu, **koboldai_vars.modelconfig) koboldai_vars.modeldim = int(tpu_mtj_backend.params.get("d_embed", tpu_mtj_backend.params["d_model"])) tokenizer = tpu_mtj_backend.tokenizer - if(koboldai_vars.badwordsids is koboldai_settings.badwordsids_default and koboldai_vars.model_type not in ("gpt2", "gpt_neo", "gptj")): + if(koboldai_vars.badwordsids is koboldai_vars.badwordsids_default and koboldai_vars.model_type not in ("gpt2", "gpt_neo", "gptj")): koboldai_vars.badwordsids = [[v] for k, v in tokenizer.get_vocab().items() if any(c in str(k) for c in "<>[]") if koboldai_vars.newlinemode != "s" or str(k) != ""] else: loadsettings() @@ -2316,16 +2626,24 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal @app.route('/') @app.route('/index') def index(): - if 'story' in session: - if session['story'] not in koboldai_vars.story_list(): - session['story'] = 'default' - return render_template('index.html', hide_ai_menu=args.noaimenu, flaskwebgui=koboldai_vars.flaskwebgui) + if args.no_ui: + return redirect('/api/latest') + if 'new_ui' in request.args: + return render_template('index_new.html', hide_ai_menu=args.noaimenu) + else: + return render_template('index.html', hide_ai_menu=args.noaimenu, flaskwebgui=koboldai_vars.flaskwebgui) +@app.route('/api', strict_slashes=False) +def api(): + return redirect('/api/latest') @app.route('/favicon.ico') def favicon(): return send_from_directory(app.root_path, 'koboldai.ico', mimetype='image/vnd.microsoft.icon') @app.route('/download') def download(): + if args.no_ui: + raise NotFound() + save_format = request.args.get("format", "json").strip().lower() if(save_format == "plaintext"): @@ -2408,7 +2726,7 @@ def lua_startup(): "userscript_path": "userscripts", "config_path": "userscripts", "lib_paths": koboldai_vars.lua_state.table("lualibs", os.path.join("extern", "lualibs")), - "koboldai_vars": koboldai_vars + "koboldai_vars": koboldai_vars, } for kwarg in _bridged: bridged[kwarg] = _bridged[kwarg] @@ -2725,6 +3043,7 @@ def lua_has_setting(setting): "adsnsp", "singleline", "output_streaming", + "show_probs" ) #==================================================================# @@ -2756,7 +3075,8 @@ def lua_get_setting(setting): if(setting in ("frmtrmspch", "rmspch")): return koboldai_vars.formatoptns["frmttrmspch"] if(setting in ("frmtadsnsp", "adsnsp")): return koboldai_vars.formatoptns["frmtadsnsp"] if(setting in ("frmtsingleline", "singleline")): return koboldai_vars.formatoptns["singleline"] - if(setting == "outputstreaming"): koboldai_vars.output_streaming = v + if(setting == "output_streaming"): return koboldai_vars.output_streaming + if(setting == "show_probs"): return koboldai_vars.show_probs #==================================================================# # Set the setting with the given name if it exists @@ -2793,6 +3113,8 @@ def lua_set_setting(setting, v): if(setting in ("frmtrmspch", "rmspch")): koboldai_vars.formatoptns["frmttrmspch"] = v if(setting in ("frmtadsnsp", "adsnsp")): koboldai_vars.formatoptns["frmtadsnsp"] = v if(setting in ("frmtsingleline", "singleline")): koboldai_vars.formatoptns["singleline"] = v + if(setting == "output_streaming"): koboldai_vars.output_streaming = v + if(setting == "show_probs"): koboldai_vars.show_probs = v #==================================================================# # Get contents of memory @@ -2891,7 +3213,7 @@ def lua_set_chunk(k, v): def lua_get_modeltype(): if(koboldai_vars.noai): return "readonly" - if(koboldai_vars.model in ("Colab", "OAI", "InferKit")): + if(koboldai_vars.model in ("Colab", "API", "OAI", "InferKit")): return "api" if(not koboldai_vars.use_colab_tpu and koboldai_vars.model not in ("TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX") and (koboldai_vars.model in ("GPT2Custom", "NeoCustom") or koboldai_vars.model_type in ("gpt2", "gpt_neo", "gptj"))): hidden_size = get_hidden_size_from_model(model) @@ -2920,7 +3242,7 @@ def lua_get_modeltype(): def lua_get_modelbackend(): if(koboldai_vars.noai): return "readonly" - if(koboldai_vars.model in ("Colab", "OAI", "InferKit")): + if(koboldai_vars.model in ("Colab", "API", "OAI", "InferKit")): return "api" if(koboldai_vars.use_colab_tpu or koboldai_vars.model in ("TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX")): return "mtj" @@ -3373,8 +3695,12 @@ def get_message(msg): if gpu_layers == msg['gpu_layers'] and disk_layers == msg['disk_layers']: changed = False if changed: - f = open("settings/" + koboldai_vars.model.replace('/', '_') + ".breakmodel", "w") - f.write(msg['gpu_layers'] + '\n' + msg['disk_layers']) + if koboldai_vars.model in ["NeoCustom", "GPT2Custom"]: + filename = "settings/{}.breakmodel".format(os.path.basename(os.path.normpath(koboldai_vars.custmodpth))) + else: + filename = "settings/{}.breakmodel".format(koboldai_vars.model.replace('/', '_')) + f = open(filename, "w") + f.write(str(msg['gpu_layers']) + '\n' + str(msg['disk_layers'])) f.close() koboldai_vars.colaburl = msg['url'] + "/request" load_model(use_gpu=msg['use_gpu'], gpu_layers=msg['gpu_layers'], disk_layers=msg['disk_layers'], online_model=msg['online_model']) @@ -3503,10 +3829,18 @@ def get_message(msg): koboldai_vars.nogenmod = msg['data'] settingschanged() refresh_settings() + elif(msg['cmd'] == 'setfulldeterminism'): + koboldai_vars.full_determinism = msg['data'] + settingschanged() + refresh_settings() elif(msg['cmd'] == 'setoutputstreaming'): koboldai_vars.output_streaming = msg['data'] settingschanged() refresh_settings() + elif(msg['cmd'] == 'setshowprobs'): + koboldai_vars.show_probs = msg['data'] + settingschanged() + refresh_settings() elif(not koboldai_vars.host and msg['cmd'] == 'importwi'): wiimportrequest() elif(msg['cmd'] == 'debug'): @@ -3514,6 +3848,40 @@ def get_message(msg): emit('from_server', {'cmd': 'set_debug', 'data': msg['data']}, broadcast=True, room="UI_1") if koboldai_vars.debug: send_debug() + elif(msg['cmd'] == 'getfieldbudget'): + unencoded = msg["data"]["unencoded"] + field = msg["data"]["field"] + + # Tokenizer may be undefined here when a model has not been chosen. + if "tokenizer" not in globals(): + # We don't have a tokenizer, just return nulls. + emit( + 'from_server', + {'cmd': 'showfieldbudget', 'data': {"length": None, "max": None, "field": field}}, + broadcast=True + ) + return + + header_length = len(tokenizer._koboldai_header) + max_tokens = koboldai_vars.max_length - header_length - koboldai_vars.sp_length - koboldai_vars.genamt + + if not unencoded: + # Unencoded is empty, just return 0 + emit( + 'from_server', + {'cmd': 'showfieldbudget', 'data': {"length": 0, "max": max_tokens, "field": field}}, + broadcast=True + ) + else: + if field == "anoteinput": + unencoded = buildauthorsnote(unencoded, msg["data"]["anotetemplate"]) + tokens_length = len(tokenizer.encode(unencoded)) + + emit( + 'from_server', + {'cmd': 'showfieldbudget', 'data': {"length": tokens_length, "max": max_tokens, "field": field}}, + broadcast=True + ) #==================================================================# # Send userscripts list to client @@ -3592,7 +3960,7 @@ def check_for_backend_compilation(): break koboldai_vars.checking = False -def actionsubmit(data, actionmode=0, force_submit=False, force_prompt_gen=False, disable_recentrng=False): +def actionsubmit(data, actionmode=0, force_submit=False, force_prompt_gen=False, disable_recentrng=False, no_generate=False): # Ignore new submissions if the AI is currently busy if(koboldai_vars.aibusy): return @@ -3600,6 +3968,32 @@ def actionsubmit(data, actionmode=0, force_submit=False, force_prompt_gen=False, while(True): set_aibusy(1) + if(koboldai_vars.model == "API"): + global tokenizer + tokenizer_id = requests.get( + koboldai_vars.colaburl[:-8] + "/api/v1/model", + ).json()["result"] + if tokenizer_id != koboldai_vars.api_tokenizer_id: + try: + if(os.path.isdir(tokenizer_id)): + try: + tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, revision=koboldai_vars.revision, cache_dir="cache") + except: + tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, revision=koboldai_vars.revision, cache_dir="cache", use_fast=False) + elif(os.path.isdir("models/{}".format(tokenizer_id.replace('/', '_')))): + try: + tokenizer = AutoTokenizer.from_pretrained("models/{}".format(tokenizer_id.replace('/', '_')), revision=koboldai_vars.revision, cache_dir="cache") + except: + tokenizer = AutoTokenizer.from_pretrained("models/{}".format(tokenizer_id.replace('/', '_')), revision=koboldai_vars.revision, cache_dir="cache", use_fast=False) + else: + try: + tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, revision=koboldai_vars.revision, cache_dir="cache") + except: + tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, revision=koboldai_vars.revision, cache_dir="cache", use_fast=False) + except: + print(f"WARNING: Unknown tokenizer {repr(tokenizer_id)}") + koboldai_vars.api_tokenizer_id = tokenizer_id + if(disable_recentrng): koboldai_vars.recentrng = koboldai_vars.recentrngm = None @@ -3626,7 +4020,9 @@ def actionsubmit(data, actionmode=0, force_submit=False, force_prompt_gen=False, if(not koboldai_vars.gamestarted): koboldai_vars.submission = data - execute_inmod() + if(not no_generate): + execute_inmod() + koboldai_vars.submission = re.sub(r"[^\S\r\n]*([\r\n]*)$", r"\1", koboldai_vars.submission) # Remove trailing whitespace, excluding newlines data = koboldai_vars.submission if(not force_submit and len(data.strip()) == 0): assert False @@ -3650,7 +4046,8 @@ def actionsubmit(data, actionmode=0, force_submit=False, force_prompt_gen=False, koboldai_vars.prompt = data if len(data) > 0 else '"' for i in range(koboldai_vars.numseqs): koboldai_vars.lua_koboldbridge.outputs[i+1] = "" - execute_outmod() + if(not no_generate): + execute_outmod() koboldai_vars.lua_koboldbridge.regeneration_required = False genout = [] for i in range(koboldai_vars.numseqs): @@ -3687,7 +4084,9 @@ def actionsubmit(data, actionmode=0, force_submit=False, force_prompt_gen=False, if(koboldai_vars.actionmode == 0): data = applyinputformatting(data) koboldai_vars.submission = data - execute_inmod() + if(not no_generate): + execute_inmod() + koboldai_vars.submission = re.sub(r"[^\S\r\n]*([\r\n]*)$", r"\1", koboldai_vars.submission) # Remove trailing whitespace, excluding newlines data = koboldai_vars.submission # Dont append submission if it's a blank/continue action if(data != ""): @@ -3699,7 +4098,7 @@ def actionsubmit(data, actionmode=0, force_submit=False, force_prompt_gen=False, update_story_chunk('last') send_debug() - if(not koboldai_vars.noai and koboldai_vars.lua_koboldbridge.generating): + if(not no_generate and not koboldai_vars.noai and koboldai_vars.lua_koboldbridge.generating): # Off to the tokenizer! calcsubmit(data) if(not koboldai_vars.abort and koboldai_vars.lua_koboldbridge.restart_sequence is not None and len(koboldai_vars.genseqs) == 0): @@ -3710,26 +4109,27 @@ def actionsubmit(data, actionmode=0, force_submit=False, force_prompt_gen=False, emit('from_server', {'cmd': 'scrolldown', 'data': ''}, broadcast=True, room="UI_1") break else: - for i in range(koboldai_vars.numseqs): - koboldai_vars.lua_koboldbridge.outputs[i+1] = "" - execute_outmod() - koboldai_vars.lua_koboldbridge.regeneration_required = False + if(not no_generate): + for i in range(koboldai_vars.numseqs): + koboldai_vars.lua_koboldbridge.outputs[i+1] = "" + execute_outmod() + koboldai_vars.lua_koboldbridge.regeneration_required = False genout = [] for i in range(koboldai_vars.numseqs): - genout.append({"generated_text": koboldai_vars.lua_koboldbridge.outputs[i+1]}) + genout.append({"generated_text": koboldai_vars.lua_koboldbridge.outputs[i+1] if not no_generate else ""}) assert type(genout[-1]["generated_text"]) is str koboldai_vars.actions.clear_unused_options() koboldai_vars.actions.append_options([x["generated_text"] for x in genout]) genout = [{"generated_text": x['text']} for x in koboldai_vars.actions.get_current_options()] if(len(genout) == 1): genresult(genout[0]["generated_text"]) - if(not koboldai_vars.abort and koboldai_vars.lua_koboldbridge.restart_sequence is not None): + if(not no_generate and not koboldai_vars.abort and koboldai_vars.lua_koboldbridge.restart_sequence is not None): data = "" force_submit = True disable_recentrng = True continue else: - if(not koboldai_vars.abort and koboldai_vars.lua_koboldbridge.restart_sequence is not None and koboldai_vars.lua_koboldbridge.restart_sequence > 0): + if(not no_generate and not koboldai_vars.abort and koboldai_vars.lua_koboldbridge.restart_sequence is not None and koboldai_vars.lua_koboldbridge.restart_sequence > 0): genresult(genout[koboldai_vars.lua_koboldbridge.restart_sequence-1]["generated_text"]) data = "" force_submit = True @@ -3740,6 +4140,130 @@ def actionsubmit(data, actionmode=0, force_submit=False, force_prompt_gen=False, emit('from_server', {'cmd': 'scrolldown', 'data': ''}, broadcast=True, room="UI_1") break +def apiactionsubmit_generate(txt, minimum, maximum): + koboldai_vars.generated_tkns = 0 + + if not koboldai_vars.quiet: + print("{0}Min:{1}, Max:{2}, Txt:{3}{4}".format(colors.YELLOW, minimum, maximum, utils.decodenewlines(tokenizer.decode(txt)), colors.END)) + + # Clear CUDA cache if using GPU + if(koboldai_vars.hascuda and (koboldai_vars.usegpu or koboldai_vars.breakmodel)): + gc.collect() + torch.cuda.empty_cache() + + # Submit input text to generator + _genout, already_generated = tpool.execute(_generate, txt, minimum, maximum, set()) + + genout = [applyoutputformatting(utils.decodenewlines(tokenizer.decode(tokens[-already_generated:]))) for tokens in _genout] + + # Clear CUDA cache again if using GPU + if(koboldai_vars.hascuda and (koboldai_vars.usegpu or koboldai_vars.breakmodel)): + del _genout + gc.collect() + torch.cuda.empty_cache() + + return genout + +def apiactionsubmit_tpumtjgenerate(txt, minimum, maximum): + koboldai_vars.generated_tkns = 0 + + if(koboldai_vars.full_determinism): + tpu_mtj_backend.set_rng_seed(koboldai_vars.seed) + + if not koboldai_vars.quiet: + print("{0}Min:{1}, Max:{2}, Txt:{3}{4}".format(colors.YELLOW, minimum, maximum, utils.decodenewlines(tokenizer.decode(txt)), colors.END)) + + koboldai_vars._actions = koboldai_vars.actions + koboldai_vars._prompt = koboldai_vars.prompt + if(koboldai_vars.dynamicscan): + koboldai_vars._actions = koboldai_vars._actions.copy() + + # Submit input text to generator + soft_tokens = tpumtjgetsofttokens() + genout = tpool.execute( + tpu_mtj_backend.infer_static, + np.uint32(txt), + gen_len = maximum-minimum+1, + temp=koboldai_vars.temp, + top_p=koboldai_vars.top_p, + top_k=koboldai_vars.top_k, + tfs=koboldai_vars.tfs, + typical=koboldai_vars.typical, + top_a=koboldai_vars.top_a, + numseqs=koboldai_vars.numseqs, + repetition_penalty=koboldai_vars.rep_pen, + rpslope=koboldai_vars.rep_pen_slope, + rprange=koboldai_vars.rep_pen_range, + soft_embeddings=koboldai_vars.sp, + soft_tokens=soft_tokens, + sampler_order=koboldai_vars.sampler_order, + ) + genout = [applyoutputformatting(utils.decodenewlines(tokenizer.decode(txt))) for txt in genout] + + return genout + +def apiactionsubmit(data, use_memory=False, use_world_info=False, use_story=False, use_authors_note=False): + if(koboldai_vars.model == "Colab"): + raise NotImplementedError("API generation is not supported in old Colab API mode.") + elif(koboldai_vars.model == "API"): + raise NotImplementedError("API generation is not supported in API mode.") + elif(koboldai_vars.model == "OAI"): + raise NotImplementedError("API generation is not supported in OpenAI/GooseAI mode.") + elif(koboldai_vars.model == "ReadOnly"): + raise NotImplementedError("API generation is not supported in read-only mode; please load a model and then try again.") + + data = applyinputformatting(data) + + if(koboldai_vars.memory != "" and koboldai_vars.memory[-1] != "\n"): + mem = koboldai_vars.memory + "\n" + else: + mem = koboldai_vars.memory + if(use_authors_note and koboldai_vars.authornote != ""): + anotetxt = ("\n" + koboldai_vars.authornotetemplate + "\n").replace("<|>", koboldai_vars.authornote) + else: + anotetxt = "" + MIN_STORY_TOKENS = 8 + story_tokens = [] + mem_tokens = [] + wi_tokens = [] + story_budget = lambda: koboldai_vars.max_length - koboldai_vars.sp_length - koboldai_vars.genamt - len(tokenizer._koboldai_header) - len(story_tokens) - len(mem_tokens) - len(wi_tokens) + budget = lambda: story_budget() + MIN_STORY_TOKENS + if budget() < 0: + abort(Response(json.dumps({"detail": { + "msg": f"Your Max Tokens setting is too low for your current soft prompt and tokenizer to handle. It needs to be at least {koboldai_vars.max_length - budget()}.", + "type": "token_overflow", + }}), mimetype="application/json", status=500)) + if use_memory: + mem_tokens = tokenizer.encode(utils.encodenewlines(mem))[-budget():] + if use_world_info: + world_info, _ = checkworldinfo(data, force_use_txt=True, scan_story=use_story) + wi_tokens = tokenizer.encode(utils.encodenewlines(world_info))[-budget():] + if use_story: + if koboldai_vars.useprompt: + story_tokens = tokenizer.encode(utils.encodenewlines(koboldai_vars.prompt))[-budget():] + story_tokens = tokenizer.encode(utils.encodenewlines(data))[-story_budget():] + story_tokens + if use_story: + for i, action in enumerate(reversed(koboldai_vars.actions.values())): + if story_budget() <= 0: + assert story_budget() == 0 + break + story_tokens = tokenizer.encode(utils.encodenewlines(action))[-story_budget():] + story_tokens + if i == koboldai_vars.andepth - 1: + story_tokens = tokenizer.encode(utils.encodenewlines(anotetxt))[-story_budget():] + story_tokens + if not koboldai_vars.useprompt: + story_tokens = tokenizer.encode(utils.encodenewlines(koboldai_vars.prompt))[-budget():] + story_tokens + tokens = tokenizer._koboldai_header + mem_tokens + wi_tokens + story_tokens + assert story_budget() >= 0 + minimum = len(tokens) + 1 + maximum = len(tokens) + koboldai_vars.genamt + + if(not koboldai_vars.use_colab_tpu and koboldai_vars.model not in ["Colab", "API", "OAI", "TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX"]): + genout = apiactionsubmit_generate(tokens, minimum, maximum) + elif(koboldai_vars.use_colab_tpu or koboldai_vars.model in ("TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX")): + genout = apiactionsubmit_tpumtjgenerate(tokens, minimum, maximum) + + return genout + #==================================================================# # #==================================================================# @@ -3793,6 +4317,12 @@ def actionredo(): #==================================================================# # #==================================================================# +def buildauthorsnote(authorsnote, template): + # Build Author's Note if set + if authorsnote == "": + return "" + return ("\n" + template + "\n").replace("<|>", authorsnote) + def calcsubmitbudgetheader(txt, **kwargs): # Scan for WorldInfo matches winfo, found_entries = checkworldinfo(txt, **kwargs) @@ -3803,11 +4333,7 @@ def calcsubmitbudgetheader(txt, **kwargs): else: mem = koboldai_vars.memory - # Build Author's Note if set - if(koboldai_vars.authornote != ""): - anotetxt = ("\n" + koboldai_vars.authornotetemplate + "\n").replace("<|>", koboldai_vars.authornote) - else: - anotetxt = "" + anotetxt = buildauthorsnote(koboldai_vars.authornote, koboldai_vars.authornotetemplate) return winfo, mem, anotetxt, found_entries @@ -3849,7 +4375,7 @@ def calcsubmitbudget(actionlen, winfo, mem, anotetxt, actions, submission=None, if(koboldai_vars.useprompt): budget = koboldai_vars.max_length - lnsp - lnprompt - lnmem - lnanote - lnwi - koboldai_vars.genamt - budget_deduction else: - budget = koboldai_vars.max_length - lnsp - lnmem - lnanote - lnwi - koboldai_vars.genamt - budget_deduction + budget = koboldai_vars.max_length - lnheader - lnsp - lnmem - lnanote - lnwi - koboldai_vars.genamt - budget_deduction lnsubmission = len(tokenizer.encode(utils.encodenewlines(koboldai_vars.comregex_ai.sub('', submission)), max_length=int(2e9), truncation=True)) if submission is not None else 0 maybe_lnprompt = lnprompt if koboldai_vars.useprompt and actionlen > 0 else 0 @@ -3861,7 +4387,7 @@ def calcsubmitbudget(actionlen, winfo, mem, anotetxt, actions, submission=None, if(actionlen == 0): # First/Prompt action - tokens = tokenizer._koboldai_header + memtokens + witokens + anotetkns + prompttkns + tokens = (tokenizer._koboldai_header if koboldai_vars.model not in ("Colab", "API", "OAI") else []) + memtokens + witokens + anotetkns + prompttkns assert len(tokens) <= koboldai_vars.max_length - lnsp - koboldai_vars.genamt - budget_deduction ln = len(tokens) + lnsp return tokens, ln+1, ln+koboldai_vars.genamt @@ -3909,12 +4435,12 @@ def calcsubmitbudget(actionlen, winfo, mem, anotetxt, actions, submission=None, # Did we get to add the A.N.? If not, do it here if(anotetxt != ""): if((not anoteadded) or forceanote): - tokens = tokenizer._koboldai_header + memtokens + witokens + anotetkns + prompttkns + tokens + tokens = (tokenizer._koboldai_header if koboldai_vars.model not in ("Colab", "API", "OAI") else []) + memtokens + witokens + anotetkns + prompttkns + tokens else: - tokens = tokenizer._koboldai_header + memtokens + witokens + prompttkns + tokens + tokens = (tokenizer._koboldai_header if koboldai_vars.model not in ("Colab", "API", "OAI") else []) + memtokens + witokens + prompttkns + tokens else: # Prepend Memory, WI, and Prompt before action tokens - tokens = tokenizer._koboldai_header + memtokens + witokens + prompttkns + tokens + tokens = (tokenizer._koboldai_header if koboldai_vars.model not in ("Colab", "API", "OAI") else []) + memtokens + witokens + prompttkns + tokens # Send completed bundle to generator assert len(tokens) <= koboldai_vars.max_length - lnsp - koboldai_vars.genamt - budget_deduction @@ -3936,19 +4462,23 @@ def calcsubmit(txt): if(koboldai_vars.model != "InferKit"): subtxt, min, max = calcsubmitbudget(actionlen, winfo, mem, anotetxt, koboldai_vars.actions, submission=txt) if(actionlen == 0): - if(not koboldai_vars.use_colab_tpu and koboldai_vars.model not in ["Colab", "OAI", "TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX"]): + if(not koboldai_vars.use_colab_tpu and koboldai_vars.model not in ["Colab", "API", "OAI", "TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX"]): generate(subtxt, min, max, found_entries=found_entries) elif(koboldai_vars.model == "Colab"): sendtocolab(utils.decodenewlines(tokenizer.decode(subtxt)), min, max) + elif(koboldai_vars.model == "API"): + sendtoapi(utils.decodenewlines(tokenizer.decode(subtxt)), min, max) elif(koboldai_vars.model == "OAI"): oairequest(utils.decodenewlines(tokenizer.decode(subtxt)), min, max) elif(koboldai_vars.use_colab_tpu or koboldai_vars.model in ("TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX")): tpumtjgenerate(subtxt, min, max, found_entries=found_entries) else: - if(not koboldai_vars.use_colab_tpu and koboldai_vars.model not in ["Colab", "OAI", "TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX"]): + if(not koboldai_vars.use_colab_tpu and koboldai_vars.model not in ["Colab", "API", "OAI", "TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX"]): generate(subtxt, min, max, found_entries=found_entries) elif(koboldai_vars.model == "Colab"): sendtocolab(utils.decodenewlines(tokenizer.decode(subtxt)), min, max) + elif(koboldai_vars.model == "API"): + sendtoapi(utils.decodenewlines(tokenizer.decode(subtxt)), min, max) elif(koboldai_vars.model == "OAI"): oairequest(utils.decodenewlines(tokenizer.decode(subtxt)), min, max) elif(koboldai_vars.use_colab_tpu or koboldai_vars.model in ("TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX")): @@ -4015,6 +4545,9 @@ def calcsubmit(txt): #==================================================================# def _generate(txt, minimum, maximum, found_entries): + if(koboldai_vars.full_determinism): + torch.manual_seed(koboldai_vars.seed) + gen_in = torch.tensor(txt, dtype=torch.long)[None] if(koboldai_vars.sp is not None): soft_tokens = torch.arange( @@ -4333,10 +4866,88 @@ def sendtocolab(txt, min, max): emit('from_server', {'cmd': 'errmsg', 'data': errmsg}, broadcast=True, room="UI_1") set_aibusy(0) + +#==================================================================# +# Send transformers-style request to KoboldAI API +#==================================================================# +def sendtoapi(txt, min, max): + # Log request to console + if not koboldai_vars.quiet: + 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 + koboldai_vars.lastctx = txt + + # Build request JSON data + reqdata = { + 'prompt': txt, + 'max_length': max - min + 1, + 'max_context_length': koboldai_vars.max_length, + 'rep_pen': koboldai_vars.rep_pen, + 'rep_pen_slope': koboldai_vars.rep_pen_slope, + 'rep_pen_range': koboldai_vars.rep_pen_range, + 'temperature': koboldai_vars.temp, + 'top_p': koboldai_vars.top_p, + 'top_k': koboldai_vars.top_k, + 'top_a': koboldai_vars.top_a, + 'tfs': koboldai_vars.tfs, + 'typical': koboldai_vars.typical, + 'n': koboldai_vars.numseqs, + } + + # Create request + while True: + req = requests.post( + koboldai_vars.colaburl[:-8] + "/api/v1/generate", + json=reqdata, + ) + if(req.status_code == 503): # Server is currently generating something else so poll until it's our turn + time.sleep(1) + continue + js = req.json() + if(req.status_code != 200): + errmsg = "KoboldAI API Error: Failed to get a reply from the server. Please check the console." + print("{0}{1}{2}".format(colors.RED, json.dumps(js, indent=2), colors.END)) + emit('from_server', {'cmd': 'errmsg', 'data': errmsg}, broadcast=True) + set_aibusy(0) + return + + genout = [obj["text"] for obj in js["results"]] + + for i in range(koboldai_vars.numseqs): + koboldai_vars.lua_koboldbridge.outputs[i+1] = genout[i] + + execute_outmod() + if(koboldai_vars.lua_koboldbridge.regeneration_required): + koboldai_vars.lua_koboldbridge.regeneration_required = False + genout = [] + for i in range(koboldai_vars.numseqs): + genout.append(koboldai_vars.lua_koboldbridge.outputs[i+1]) + assert type(genout[-1]) is str + + if(len(genout) == 1): + genresult(genout[0]) + else: + # Convert torch output format to transformers + seqs = [] + for seq in genout: + seqs.append({"generated_text": seq}) + if(koboldai_vars.lua_koboldbridge.restart_sequence is not None and koboldai_vars.lua_koboldbridge.restart_sequence > 0): + genresult(genout[koboldai_vars.lua_koboldbridge.restart_sequence-1]["generated_text"]) + else: + genselect(genout) + + set_aibusy(0) + return + + #==================================================================# # Send text to TPU mesh transformer backend #==================================================================# def tpumtjgenerate(txt, minimum, maximum, found_entries=None): + if(koboldai_vars.full_determinism): + tpu_mtj_backend.set_rng_seed(koboldai_vars.seed) + koboldai_vars.generated_tkns = 0 if(found_entries is None): @@ -4627,6 +5238,7 @@ def refresh_settings(): emit('from_server', {'cmd': 'updatenopromptgen', 'data': koboldai_vars.nopromptgen}, broadcast=True, room="UI_1") emit('from_server', {'cmd': 'updaterngpersist', 'data': koboldai_vars.rngpersist}, broadcast=True, room="UI_1") emit('from_server', {'cmd': 'updatenogenmod', 'data': koboldai_vars.nogenmod}, broadcast=True, room="UI_1") + emit('from_server', {'cmd': 'updatefulldeterminism', 'data': koboldai_vars.full_determinism}, broadcast=True, room="UI_1") emit('from_server', {'cmd': 'updatefrmttriminc', 'data': koboldai_vars.formatoptns["frmttriminc"]}, broadcast=True, room="UI_1") emit('from_server', {'cmd': 'updatefrmtrmblln', 'data': koboldai_vars.formatoptns["frmtrmblln"]}, broadcast=True, room="UI_1") @@ -4634,6 +5246,7 @@ def refresh_settings(): emit('from_server', {'cmd': 'updatefrmtadsnsp', 'data': koboldai_vars.formatoptns["frmtadsnsp"]}, broadcast=True, room="UI_1") emit('from_server', {'cmd': 'updatesingleline', 'data': koboldai_vars.formatoptns["singleline"]}, broadcast=True, room="UI_1") emit('from_server', {'cmd': 'updateoutputstreaming', 'data': koboldai_vars.output_streaming}, broadcast=True, room="UI_1") + emit('from_server', {'cmd': 'updateshowprobs', 'data': koboldai_vars.show_probs}, broadcast=True, room="UI_1") # Allow toggle events again emit('from_server', {'cmd': 'allowtoggle', 'data': True}, broadcast=True, room="UI_1") @@ -4642,6 +5255,8 @@ def refresh_settings(): # Sets the logical and display states for the AI Busy condition #==================================================================# def set_aibusy(state): + if(koboldai_vars.disable_set_aibusy): + return if(state): koboldai_vars.aibusy = True emit('from_server', {'cmd': 'setgamestate', 'data': 'wait'}, broadcast=True, room="UI_1") @@ -5599,7 +6214,7 @@ def importRequest(): # Clear Popup Contents emit('from_server', {'cmd': 'clearpopup', 'data': ''}, broadcast=True, room="UI_1") - # Initialize vars + # Initialize koboldai_vars num = 0 koboldai_vars.importnum = -1 @@ -5633,7 +6248,7 @@ def importgame(): # Cache reference to selected game ref = koboldai_vars.importjs[koboldai_vars.importnum] - # Copy game contents to vars + # Copy game contents to koboldai_vars koboldai_vars.gamestarted = True # Support for different versions of export script @@ -5950,9 +6565,27 @@ def final_startup(): }, ).start() + # Set the initial RNG seed + if(koboldai_vars.seed is not None): + if(koboldai_vars.use_colab_tpu): + if(koboldai_vars.seed_specified): + __import__("tpu_mtj_backend").set_rng_seed(koboldai_vars.seed) + else: + __import__("tpu_mtj_backend").randomize_rng_seed() + else: + if(koboldai_vars.seed_specified): + __import__("torch").manual_seed(koboldai_vars.seed) + else: + __import__("torch").seed() + koboldai_vars.seed = __import__("tpu_mtj_backend").get_rng_seed() if koboldai_vars.use_colab_tpu else __import__("torch").initial_seed() + def send_debug(): if koboldai_vars.debug: debug_info = "" + try: + debug_info = "{}Seed: {} ({})\n".format(debug_info, repr(__import__("tpu_mtj_backend").get_rng_seed() if koboldai_vars.use_colab_tpu else __import__("torch").initial_seed()), "specified by user in settings file" if koboldai_vars.seed_specified else "randomly generated") + except: + pass try: debug_info = "{}Newline Mode: {}\n".format(debug_info, koboldai_vars.newlinemode) except: @@ -5986,6 +6619,18 @@ def send_debug(): #==================================================================# +# Load file browser for soft prompts +#==================================================================# +@socketio.on('show_folder_soft_prompt') +def show_folder_soft_prompt(data): + file_popup("Load Softprompt", "./softprompts", "", renameable=True, folder_only=False, editable=False, deleteable=True, jailed=True, item_check=None) + +#==================================================================# +# Load file browser for user scripts +#==================================================================# +@socketio.on('show_folder_usersripts') +def show_folder_usersripts(data): + file_popup("Load Softprompt", "./userscripts", "", renameable=True, folder_only=False, editable=True, deleteable=True, jailed=True, item_check=None) # UI V2 CODE #==================================================================# @app.route('/ai_text') @@ -6697,6 +7342,2663 @@ def show_vars(): +#==================================================================# +class EmptySchema(KoboldSchema): + pass + +class BasicTextResultInnerSchema(KoboldSchema): + text: str = fields.String(required=True) + +class BasicTextResultSchema(KoboldSchema): + result: BasicTextResultInnerSchema = fields.Nested(BasicTextResultInnerSchema) + +class BasicResultInnerSchema(KoboldSchema): + result: str = fields.String(required=True) + +class BasicResultSchema(KoboldSchema): + result: BasicResultInnerSchema = fields.Nested(BasicResultInnerSchema, required=True) + +class BasicResultsSchema(KoboldSchema): + results: BasicResultInnerSchema = fields.List(fields.Nested(BasicResultInnerSchema), required=True) + +class BasicStringSchema(KoboldSchema): + value: str = fields.String(required=True) + +class BasicBooleanSchema(KoboldSchema): + value: bool = fields.Boolean(required=True) + +class BasicUIDSchema(KoboldSchema): + uid: str = fields.Integer(required=True, validate=validate.Range(min=-2147483648, max=2147483647), metadata={"description": "32-bit signed integer unique to this world info entry/folder."}) + +class BasicErrorSchema(KoboldSchema): + msg: str = fields.String(required=True) + type: str = fields.String(required=True) + +class StoryEmptyErrorSchema(KoboldSchema): + detail: BasicErrorSchema = fields.Nested(BasicErrorSchema, required=True) + +class StoryTooShortErrorSchema(KoboldSchema): + detail: BasicErrorSchema = fields.Nested(BasicErrorSchema, required=True) + +class OutOfMemoryErrorSchema(KoboldSchema): + detail: BasicErrorSchema = fields.Nested(BasicErrorSchema, required=True) + +class NotFoundErrorSchema(KoboldSchema): + detail: BasicErrorSchema = fields.Nested(BasicErrorSchema, required=True) + +api_out_of_memory_response = """507: + description: Out of memory + content: + application/json: + schema: OutOfMemoryErrorSchema + examples: + gpu.cuda: + value: + detail: + msg: "KoboldAI ran out of memory: CUDA out of memory. Tried to allocate 20.00 MiB (GPU 0; 4.00 GiB total capacity; 2.97 GiB already allocated; 0 bytes free; 2.99 GiB reserved in total by PyTorch)" + type: out_of_memory.gpu.cuda + gpu.hip: + value: + detail: + msg: "KoboldAI ran out of memory: HIP out of memory. Tried to allocate 20.00 MiB (GPU 0; 4.00 GiB total capacity; 2.97 GiB already allocated; 0 bytes free; 2.99 GiB reserved in total by PyTorch)" + type: out_of_memory.gpu.hip + tpu.hbm: + value: + detail: + msg: "KoboldAI ran out of memory: Compilation failed: Compilation failure: Ran out of memory in memory space hbm. Used 8.83G of 8.00G hbm. Exceeded hbm capacity by 848.88M." + type: out_of_memory.tpu.hbm + cpu.default_cpu_allocator: + value: + detail: + msg: "KoboldAI ran out of memory: DefaultCPUAllocator: not enough memory: you tried to allocate 209715200 bytes." + type: out_of_memory.cpu.default_cpu_allocator + unknown.unknown: + value: + detail: + msg: "KoboldAI ran out of memory." + type: out_of_memory.unknown.unknown""" + +class ValidationErrorSchema(KoboldSchema): + detail: Dict[str, List[str]] = fields.Dict(keys=fields.String(), values=fields.List(fields.String(), validate=validate.Length(min=1)), required=True) + +api_validation_error_response = """422: + description: Validation error + content: + application/json: + schema: ValidationErrorSchema""" + +class ServerBusyErrorSchema(KoboldSchema): + detail: BasicErrorSchema = fields.Nested(BasicErrorSchema, required=True) + +api_server_busy_response = """503: + description: Server is busy + content: + application/json: + schema: ServerBusyErrorSchema + example: + detail: + msg: Server is busy; please try again later. + type: service_unavailable""" + +class NotImplementedErrorSchema(KoboldSchema): + detail: BasicErrorSchema = fields.Nested(BasicErrorSchema, required=True) + +api_not_implemented_response = """501: + description: Not implemented + content: + application/json: + schema: NotImplementedErrorSchema + example: + detail: + msg: API generation is not supported in read-only mode; please load a model and then try again. + type: not_implemented""" + +class SamplerSettingsSchema(KoboldSchema): + rep_pen: Optional[float] = fields.Float(validate=validate.Range(min=1), metadata={"description": "Base repetition penalty value."}) + rep_pen_range: Optional[int] = fields.Integer(validate=validate.Range(min=0), metadata={"description": "Repetition penalty range."}) + rep_pen_slope: Optional[float] = fields.Float(validate=validate.Range(min=0), metadata={"description": "Repetition penalty slope."}) + top_k: Optional[int] = fields.Integer(validate=validate.Range(min=0), metadata={"description": "Top-k sampling value."}) + top_a: Optional[float] = fields.Float(validate=validate.Range(min=0), metadata={"description": "Top-a sampling value."}) + top_p: Optional[float] = fields.Float(validate=validate.Range(min=0, max=1), metadata={"description": "Top-p sampling value."}) + tfs: Optional[float] = fields.Float(validate=validate.Range(min=0, max=1), metadata={"description": "Tail free sampling value."}) + typical: Optional[float] = fields.Float(validate=validate.Range(min=0, max=1), metadata={"description": "Typical sampling value."}) + temperature: Optional[float] = fields.Float(validate=validate.Range(min=0, min_inclusive=False), metadata={"description": "Temperature value."}) + +def soft_prompt_validator(soft_prompt: str): + if len(soft_prompt.strip()) == 0: + return + if not koboldai_vars.allowsp: + raise ValidationError("Cannot use soft prompts with current backend.") + if any(q in soft_prompt for q in ("/", "\\")): + return + z, _, _, _, _ = fileops.checksp(soft_prompt.strip(), koboldai_vars.modeldim) + if isinstance(z, int): + raise ValidationError("Must be a valid soft prompt name.") + z.close() + return True + +def story_load_validator(name: str): + if any(q in name for q in ("/", "\\")): + return + if len(name.strip()) == 0 or not os.path.isfile(fileops.storypath(name)): + raise ValidationError("Must be a valid story name.") + return True + +class GenerationInputSchema(SamplerSettingsSchema): + prompt: str = fields.String(required=True, metadata={"description": "This is the submission."}) + use_memory: bool = fields.Boolean(load_default=False, metadata={"description": "Whether or not to use the memory from the KoboldAI GUI when generating text."}) + use_story: bool = fields.Boolean(load_default=False, metadata={"description": "Whether or not to use the story from the KoboldAI GUI when generating text."}) + use_authors_note: bool = fields.Boolean(load_default=False, metadata={"description": "Whether or not to use the author's note from the KoboldAI GUI when generating text. This has no effect unless `use_story` is also enabled."}) + use_world_info: bool = fields.Boolean(load_default=False, metadata={"description": "Whether or not to use the world info from the KoboldAI GUI when generating text."}) + use_userscripts: bool = fields.Boolean(load_default=False, metadata={"description": "Whether or not to use the userscripts from the KoboldAI GUI when generating text."}) + soft_prompt: Optional[str] = fields.String(metadata={"description": "Soft prompt to use when generating. If set to the empty string or any other string containing no non-whitespace characters, uses no soft prompt."}, validate=[soft_prompt_validator, validate.Regexp(r"^[^/\\]*$")]) + max_length: int = fields.Integer(validate=validate.Range(min=1, max=512), metadata={"description": "Number of tokens to generate."}) + max_context_length: int = fields.Integer(validate=validate.Range(min=512, max=2048), metadata={"description": "Maximum number of tokens to send to the model."}) + n: int = fields.Integer(validate=validate.Range(min=1, max=5), metadata={"description": "Number of outputs to generate."}) + disable_output_formatting: bool = fields.Boolean(load_default=True, metadata={"description": "When enabled, all output formatting options default to `false` instead of the value in the KoboldAI GUI."}) + frmttriminc: Optional[bool] = fields.Boolean(metadata={"description": "Output formatting option. When enabled, removes some characters from the end of the output such that the output doesn't end in the middle of a sentence. If the output is less than one sentence long, does nothing.\n\nIf `disable_output_formatting` is `true`, this defaults to `false` instead of the value in the KoboldAI GUI."}) + frmtrmblln: Optional[bool] = fields.Boolean(metadata={"description": "Output formatting option. When enabled, replaces all occurrences of two or more consecutive newlines in the output with one newline.\n\nIf `disable_output_formatting` is `true`, this defaults to `false` instead of the value in the KoboldAI GUI."}) + frmtrmspch: Optional[bool] = fields.Boolean(metadata={"description": "Output formatting option. When enabled, removes `#/@%{}+=~|\^<>` from the output.\n\nIf `disable_output_formatting` is `true`, this defaults to `false` instead of the value in the KoboldAI GUI."}) + singleline: Optional[bool] = fields.Boolean(metadata={"description": "Output formatting option. When enabled, removes everything after the first line of the output, including the newline.\n\nIf `disable_output_formatting` is `true`, this defaults to `false` instead of the value in the KoboldAI GUI."}) + disable_input_formatting: bool = fields.Boolean(load_default=True, metadata={"description": "When enabled, all input formatting options default to `false` instead of the value in the KoboldAI GUI"}) + frmtadsnsp: Optional[bool] = fields.Boolean(metadata={"description": "Input formatting option. When enabled, adds a leading space to your input if there is no trailing whitespace at the end of the previous action.\n\nIf `disable_input_formatting` is `true`, this defaults to `false` instead of the value in the KoboldAI GUI."}) + +class GenerationResultSchema(KoboldSchema): + text: str = fields.String(required=True, metadata={"description": "Generated output as plain text."}) + +class GenerationOutputSchema(KoboldSchema): + results: List[GenerationResultSchema] = fields.List(fields.Nested(GenerationResultSchema), required=True, metadata={"description": "Array of generated outputs."}) + +class StoryNumsChunkSchema(KoboldSchema): + num: int = fields.Integer(required=True, metadata={"description": "Guaranteed to not equal the `num` of any other active story chunk. Equals 0 iff this is the first action of the story (the prompt)."}) + +class StoryChunkSchema(StoryNumsChunkSchema, KoboldSchema): + text: str = fields.String(required=True, metadata={"description": "The text inside this story chunk."}) + +class StorySchema(KoboldSchema): + results: List[StoryChunkSchema] = fields.List(fields.Nested(StoryChunkSchema), required=True, metadata={"description": "Array of story actions. The array is sorted such that actions closer to the end of this array are closer to the end of the story."}) + +class BasicBooleanSchema(KoboldSchema): + result: bool = fields.Boolean(required=True) + +class StoryNumsSchema(KoboldSchema): + results: List[int] = fields.List(fields.Integer(), required=True, metadata={"description": "Array of story action nums. The array is sorted such that actions closer to the end of this array are closer to the end of the story."}) + +class StoryChunkResultSchema(KoboldSchema): + result: StoryChunkSchema = fields.Nested(StoryChunkSchema, required=True) + +class StoryChunkNumSchema(KoboldSchema): + value: int = fields.Integer(required=True) + +class StoryChunkTextSchema(KoboldSchema): + value: str = fields.String(required=True) + +class StoryChunkSetTextSchema(KoboldSchema): + value: str = fields.String(required=True, validate=validate.Regexp(r"^(.|\n)*\S$")) + +class StoryLoadSchema(KoboldSchema): + name: str = fields.String(required=True, validate=[story_load_validator, validate.Regexp(r"^[^/\\]*$")]) + +class StorySaveSchema(KoboldSchema): + name: str = fields.String(required=True, validate=validate.Regexp(r"^(?=.*\S)(?!.*[/\\]).*$")) + +class WorldInfoEntrySchema(KoboldSchema): + uid: int = fields.Integer(required=True, validate=validate.Range(min=-2147483648, max=2147483647), metadata={"description": "32-bit signed integer unique to this world info entry."}) + content: str = fields.String(required=True, metadata={"description": "The \"What To Remember\" for this entry."}) + key: str = fields.String(required=True, metadata={"description": "Comma-separated list of keys, or of primary keys if selective mode is enabled."}) + keysecondary: str = fields.String(metadata={"description": "Comma-separated list of secondary keys if selective mode is enabled."}) + selective: bool = fields.Boolean(required=True, metadata={"description": "Whether or not selective mode is enabled for this world info entry."}) + constant: bool = fields.Boolean(required=True, metadata={"description": "Whether or not constant mode is enabled for this world info entry."}) + comment: bool = fields.String(required=True, metadata={"description": "The comment/description/title for this world info entry."}) + +class WorldInfoEntryResultSchema(KoboldSchema): + result: WorldInfoEntrySchema = fields.Nested(WorldInfoEntrySchema, required=True) + +class WorldInfoFolderBasicSchema(KoboldSchema): + uid: int = fields.Integer(required=True, validate=validate.Range(min=-2147483648, max=2147483647), metadata={"description": "32-bit signed integer unique to this world info folder."}) + name: str = fields.String(required=True, metadata={"description": "Name of this world info folder."}) + +class WorldInfoFolderSchema(WorldInfoFolderBasicSchema): + entries: List[WorldInfoEntrySchema] = fields.List(fields.Nested(WorldInfoEntrySchema), required=True) + +class WorldInfoFolderUIDsSchema(KoboldSchema): + uid: int = fields.Integer(required=True, validate=validate.Range(min=-2147483648, max=2147483647), metadata={"description": "32-bit signed integer unique to this world info folder."}) + entries: List[int] = fields.List(fields.Integer(required=True, validate=validate.Range(min=-2147483648, max=2147483647), metadata={"description": "32-bit signed integer unique to this world info entry."}), required=True) + +class WorldInfoEntriesSchema(KoboldSchema): + entries: List[WorldInfoEntrySchema] = fields.List(fields.Nested(WorldInfoEntrySchema), required=True) + +class WorldInfoFoldersSchema(KoboldSchema): + folders: List[WorldInfoFolderBasicSchema] = fields.List(fields.Nested(WorldInfoFolderBasicSchema), required=True) + +class WorldInfoSchema(WorldInfoEntriesSchema): + folders: List[WorldInfoFolderSchema] = fields.List(fields.Nested(WorldInfoFolderSchema), required=True) + +class WorldInfoEntriesUIDsSchema(KoboldSchema): + entries: List[int] = fields.List(fields.Integer(required=True, validate=validate.Range(min=-2147483648, max=2147483647), metadata={"description": "32-bit signed integer unique to this world info entry."}), required=True) + +class WorldInfoFoldersUIDsSchema(KoboldSchema): + folders: List[int] = fields.List(fields.Integer(required=True, validate=validate.Range(min=-2147483648, max=2147483647), metadata={"description": "32-bit signed integer unique to this world info folder."}), required=True) + +class WorldInfoUIDsSchema(WorldInfoEntriesUIDsSchema): + folders: List[WorldInfoFolderSchema] = fields.List(fields.Nested(WorldInfoFolderUIDsSchema), required=True) + +def _generate_text(body: GenerationInputSchema): + if koboldai_vars.aibusy or koboldai_vars.genseqs: + abort(Response(json.dumps({"detail": { + "msg": "Server is busy; please try again later.", + "type": "service_unavailable", + }}), mimetype="application/json", status=503)) + mapping = { + "disable_input_formatting": ("koboldai_vars", "disable_input_formatting", None), + "disable_output_formatting": ("koboldai_vars", "disable_output_formatting", None), + "rep_pen": ("koboldai_vars", "rep_pen", None), + "rep_pen_range": ("koboldai_vars", "rep_pen_range", None), + "rep_pen_slope": ("koboldai_vars", "rep_pen_slope", None), + "top_k": ("koboldai_vars", "top_k", None), + "top_a": ("koboldai_vars", "top_a", None), + "top_p": ("koboldai_vars", "top_p", None), + "tfs": ("koboldai_vars", "tfs", None), + "typical": ("koboldai_vars", "typical", None), + "temperature": ("koboldai_vars", "temp", None), + "frmtadsnsp": ("koboldai_vars.formatoptns", "@frmtadsnsp", "input"), + "frmttriminc": ("koboldai_vars.formatoptns", "@frmttriminc", "output"), + "frmtrmblln": ("koboldai_vars.formatoptns", "@frmtrmblln", "output"), + "frmtrmspch": ("koboldai_vars.formatoptns", "@frmtrmspch", "output"), + "singleline": ("koboldai_vars.formatoptns", "@singleline", "output"), + "max_length": ("koboldai_vars", "genamt", None), + "max_context_length": ("koboldai_vars", "max_length", None), + "n": ("koboldai_vars", "numseqs", None), + } + saved_settings = {} + set_aibusy(1) + disable_set_aibusy = koboldai_vars.disable_set_aibusy + koboldai_vars.disable_set_aibusy = True + _standalone = koboldai_vars.standalone + koboldai_vars.standalone = True + show_probs = koboldai_vars.show_probs + koboldai_vars.show_probs = False + output_streaming = koboldai_vars.output_streaming + koboldai_vars.output_streaming = False + for key, entry in mapping.items(): + obj = {"koboldai_vars": koboldai_vars, "koboldai_vars.formatoptns": koboldai_vars.formatoptns}[entry[0]] + if entry[2] == "input" and koboldai_vars.disable_input_formatting and not hasattr(body, key): + setattr(body, key, False) + if entry[2] == "output" and koboldai_vars.disable_output_formatting and not hasattr(body, key): + setattr(body, key, False) + if getattr(body, key, None) is not None: + if entry[1].startswith("@"): + saved_settings[key] = obj[entry[1][1:]] + obj[entry[1][1:]] = getattr(body, key) + else: + saved_settings[key] = getattr(obj, entry[1]) + setattr(obj, entry[1], getattr(body, key)) + try: + if koboldai_vars.allowsp and getattr(body, "soft_prompt", None) is not None: + if any(q in body.soft_prompt for q in ("/", "\\")): + raise RuntimeError + old_spfilename = koboldai_vars.spfilename + spRequest(body.soft_prompt.strip()) + genout = apiactionsubmit(body.prompt, use_memory=body.use_memory, use_story=body.use_story, use_world_info=body.use_world_info, use_authors_note=body.use_authors_note) + output = {"results": [{"text": txt} for txt in genout]} + finally: + for key in saved_settings: + entry = mapping[key] + obj = {"koboldai_vars": koboldai_vars, "koboldai_vars.formatoptns": koboldai_vars.formatoptns}[entry[0]] + if getattr(body, key, None) is not None: + if entry[1].startswith("@"): + if obj[entry[1][1:]] == getattr(body, key): + obj[entry[1][1:]] = saved_settings[key] + else: + if getattr(obj, entry[1]) == getattr(body, key): + setattr(obj, entry[1], saved_settings[key]) + koboldai_vars.disable_set_aibusy = disable_set_aibusy + koboldai_vars.standalone = _standalone + koboldai_vars.show_probs = show_probs + koboldai_vars.output_streaming = output_streaming + if koboldai_vars.allowsp and getattr(body, "soft_prompt", None) is not None: + spRequest(old_spfilename) + set_aibusy(0) + return output + + +@api_v1.get("/info/version") +@api_schema_wrap +def get_version(): + """--- + get: + summary: Current API version + tags: + - info + description: |-2 + Returns the version of the API that you are currently using. + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicResultSchema + example: + result: 1.0.0 + """ + return {"result": api_version} + + +@api_v1.get("/info/version/latest") +@api_schema_wrap +def get_version_latest(): + """--- + get: + summary: Latest API version + tags: + - info + description: |-2 + Returns the latest API version available. + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicResultSchema + example: + result: 1.0.0 + """ + return {"result": api_versions[-1]} + + +@api_v1.get("/info/version/list") +@api_schema_wrap +def get_version_list(): + """--- + get: + summary: List API versions + tags: + - info + description: |-2 + Returns a list of available API versions sorted in ascending order. + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicResultsSchema + example: + results: + - 1.0.0 + """ + return {"results": api_versions} + + +@api_v1.post("/generate") +@api_schema_wrap +def post_generate(body: GenerationInputSchema): + """--- + post: + summary: Generate text + tags: + - generate + description: |-2 + Generates text given a submission, sampler settings, soft prompt and number of return sequences. + + By default, the story, userscripts, memory, author's note and world info are disabled. + + Unless otherwise specified, optional values default to the values in the KoboldAI GUI. + requestBody: + required: true + content: + application/json: + schema: GenerationInputSchema + example: + prompt: |-2 + Explosions of suspicious origin occur at AMNAT satellite-receiver stations from Turkey to Labrador as three high-level Canadian defense ministers vanish and then a couple of days later are photographed at a Volgograd bistro hoisting shots of Stolichnaya with Slavic bimbos on their knee. + top_p: 0.9 + temperature: 0.5 + responses: + 200: + description: Successful request + content: + application/json: + schema: GenerationOutputSchema + example: + results: + - text: |-2 + It is later established that all of the cabinet members have died of old age. + MEGAMATRIX becomes involved in the growing number of mass abductions and kidnappings. Many disappearances occur along highways in western Canada, usually when traffic has come to a standstill because of a stalled truck or snowstorm. One or two abducted individuals will be released within a day or so but never + {api_validation_error_response} + {api_not_implemented_response} + {api_server_busy_response} + {api_out_of_memory_response} + """ + return _generate_text(body) + + +@api_v1.get("/model") +@api_schema_wrap +def get_model(): + """--- + get: + summary: Retrieve the current model string + description: |-2 + Gets the current model string, which is shown in the title of the KoboldAI GUI in parentheses, e.g. "KoboldAI Client (KoboldAI/fairseq-dense-13B-Nerys-v2)". + tags: + - model + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicResultSchema + example: + result: KoboldAI/fairseq-dense-13B-Nerys-v2 + """ + return {"result": koboldai_vars.model} + + +def prompt_validator(prompt: str): + if len(prompt.strip()) == 0: + raise ValidationError("String does not match expected pattern.") + +class SubmissionInputSchema(KoboldSchema): + prompt: str = fields.String(required=True, validate=prompt_validator, metadata={"pattern": r"^.*\S.*$", "description": "This is the submission."}) + disable_input_formatting: bool = fields.Boolean(load_default=True, metadata={"description": "When enabled, disables all input formatting options, overriding their individual enabled/disabled states."}) + frmtadsnsp: Optional[bool] = fields.Boolean(metadata={"description": "Input formatting option. When enabled, adds a leading space to your input if there is no trailing whitespace at the end of the previous action."}) + +@api_v1.post("/story/end") +@api_schema_wrap +def post_story_end(body: SubmissionInputSchema): + """--- + post: + summary: Add an action to the end of the story + tags: + - story + description: |-2 + Inserts a single action at the end of the story in the KoboldAI GUI without generating text. + requestBody: + required: true + content: + application/json: + schema: SubmissionInputSchema + example: + prompt: |-2 + This is some text to put at the end of the story. + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + {api_validation_error_response} + {api_server_busy_response} + """ + if koboldai_vars.aibusy or koboldai_vars.genseqs: + abort(Response(json.dumps({"detail": { + "msg": "Server is busy; please try again later.", + "type": "service_unavailable", + }}), mimetype="application/json", status=503)) + set_aibusy(1) + disable_set_aibusy = koboldai_vars.disable_set_aibusy + koboldai_vars.disable_set_aibusy = True + _standalone = koboldai_vars.standalone + koboldai_vars.standalone = True + numseqs = koboldai_vars.numseqs + koboldai_vars.numseqs = 1 + try: + actionsubmit(body.prompt, force_submit=True, no_generate=True) + finally: + koboldai_vars.disable_set_aibusy = disable_set_aibusy + koboldai_vars.standalone = _standalone + koboldai_vars.numseqs = numseqs + set_aibusy(0) + return {} + + +@api_v1.get("/story/end") +@api_schema_wrap +def get_story_end(): + """--- + get: + summary: Retrieve the last action of the story + tags: + - story + description: |-2 + Returns the last action of the story in the KoboldAI GUI. + responses: + 200: + description: Successful request + content: + application/json: + schema: StoryChunkResultSchema + 510: + description: Story is empty + content: + application/json: + schema: StoryEmptyErrorSchema + example: + detail: + msg: Could not retrieve the last action of the story because the story is empty. + type: story_empty + """ + if not koboldai_vars.gamestarted: + abort(Response(json.dumps({"detail": { + "msg": "Could not retrieve the last action of the story because the story is empty.", + "type": "story_empty", + }}), mimetype="application/json", status=510)) + if len(koboldai_vars.actions) == 0: + return {"result": {"text": koboldai_vars.prompt, "num": 0}} + return {"result": {"text": koboldai_vars.actions[koboldai_vars.actions.get_last_key()], "num": koboldai_vars.actions.get_last_key() + 1}} + + +@api_v1.get("/story/end/num") +@api_schema_wrap +def get_story_end_num(): + """--- + get: + summary: Retrieve the num of the last action of the story + tags: + - story + description: |-2 + Returns the `num` of the last action of the story in the KoboldAI GUI. + responses: + 200: + description: Successful request + content: + application/json: + schema: StoryChunkNumSchema + 510: + description: Story is empty + content: + application/json: + schema: StoryEmptyErrorSchema + example: + detail: + msg: Could not retrieve the last action of the story because the story is empty. + type: story_empty + """ + if not koboldai_vars.gamestarted: + abort(Response(json.dumps({"detail": { + "msg": "Could not retrieve the last action of the story because the story is empty.", + "type": "story_empty", + }}), mimetype="application/json", status=510)) + if len(koboldai_vars.actions) == 0: + return {"result": {"text": 0}} + return {"result": {"text": koboldai_vars.actions.get_last_key() + 1}} + + +@api_v1.get("/story/end/text") +@api_schema_wrap +def get_story_end_text(): + """--- + get: + summary: Retrieve the text of the last action of the story + tags: + - story + description: |-2 + Returns the text of the last action of the story in the KoboldAI GUI. + responses: + 200: + description: Successful request + content: + application/json: + schema: StoryChunkTextSchema + 510: + description: Story is empty + content: + application/json: + schema: StoryEmptyErrorSchema + example: + detail: + msg: Could not retrieve the last action of the story because the story is empty. + type: story_empty + """ + if not koboldai_vars.gamestarted: + abort(Response(json.dumps({"detail": { + "msg": "Could not retrieve the last action of the story because the story is empty.", + "type": "story_empty", + }}), mimetype="application/json", status=510)) + if len(koboldai_vars.actions) == 0: + return {"result": {"text": koboldai_vars.prompt}} + return {"result": {"text": koboldai_vars.actions[koboldai_vars.actions.get_last_key()]}} + + +@api_v1.put("/story/end/text") +@api_schema_wrap +def put_story_end_text(body: StoryChunkSetTextSchema): + """--- + put: + summary: Set the text of the last action of the story + tags: + - story + description: |-2 + Sets the text of the last action of the story in the KoboldAI GUI to the desired value. + requestBody: + required: true + content: + application/json: + schema: StoryChunkSetTextSchema + example: + value: string + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + 510: + description: Story is empty + content: + application/json: + schema: StoryEmptyErrorSchema + example: + detail: + msg: Could not retrieve the last action of the story because the story is empty. + type: story_empty + {api_validation_error_response} + """ + if not koboldai_vars.gamestarted: + abort(Response(json.dumps({"detail": { + "msg": "Could not retrieve the last action of the story because the story is empty.", + "type": "story_empty", + }}), mimetype="application/json", status=510)) + value = body.value.rstrip() + if len(koboldai_vars.actions) == 0: + inlineedit(0, value) + else: + inlineedit(koboldai_vars.actions.get_last_key() + 1, value) + return {} + + +@api_v1.post("/story/end/delete") +@api_schema_wrap +def post_story_end_delete(body: EmptySchema): + """--- + post: + summary: Remove the last action of the story + tags: + - story + description: |-2 + Removes the last action of the story in the KoboldAI GUI. + requestBody: + required: true + content: + application/json: + schema: EmptySchema + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + 510: + description: Story too short + content: + application/json: + schema: StoryTooShortErrorSchema + example: + detail: + msg: Could not delete the last action of the story because the number of actions in the story is less than or equal to 1. + type: story_too_short + {api_validation_error_response} + {api_server_busy_response} + """ + if koboldai_vars.aibusy or koboldai_vars.genseqs: + abort(Response(json.dumps({"detail": { + "msg": "Server is busy; please try again later.", + "type": "service_unavailable", + }}), mimetype="application/json", status=503)) + if not koboldai_vars.gamestarted or not len(koboldai_vars.actions): + abort(Response(json.dumps({"detail": { + "msg": "Could not delete the last action of the story because the number of actions in the story is less than or equal to 1.", + "type": "story_too_short", + }}), mimetype="application/json", status=510)) + actionback() + return {} + + +@api_v1.get("/story") +@api_schema_wrap +def get_story(): + """--- + get: + summary: Retrieve the entire story + tags: + - story + description: |-2 + Returns the entire story currently shown in the KoboldAI GUI. + responses: + 200: + description: Successful request + content: + application/json: + schema: StorySchema + """ + chunks = [] + if koboldai_vars.gamestarted: + chunks.append({"num": 0, "text": koboldai_vars.prompt}) + for num, action in koboldai_vars.actions.items(): + chunks.append({"num": num + 1, "text": action}) + return {"results": chunks} + + +@api_v1.get("/story/nums") +@api_schema_wrap +def get_story_nums(): + """--- + get: + summary: Retrieve a list of the nums of the chunks in the current story + tags: + - story + description: |-2 + Returns the `num`s of the story chunks currently shown in the KoboldAI GUI. + responses: + 200: + description: Successful request + content: + application/json: + schema: StorySchema + """ + chunks = [] + if koboldai_vars.gamestarted: + chunks.append(0) + for num in koboldai_vars.actions.keys(): + chunks.append(num + 1) + return {"results": chunks} + + +@api_v1.get("/story/nums/") +@api_schema_wrap +def get_story_nums_num(num: int): + """--- + get: + summary: Determine whether or not there is a story chunk with the given num + tags: + - story + parameters: + - name: num + in: path + description: |-2 + `num` of the desired story chunk. + schema: + type: integer + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicBooleanSchema + """ + if num == 0: + return {"result": koboldai_vars.gamestarted} + return {"result": num - 1 in koboldai_vars.actions} + + +@api_v1.get("/story/") +@api_schema_wrap +def get_story_num(num: int): + """--- + get: + summary: Retrieve a story chunk + tags: + - story + description: |-2 + Returns information about a story chunk given its `num`. + parameters: + - name: num + in: path + description: |-2 + `num` of the desired story chunk. + schema: + type: integer + responses: + 200: + description: Successful request + content: + application/json: + schema: StoryChunkResultSchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No chunk with the given num exists. + type: key_error + """ + if num == 0: + if not koboldai_vars.gamestarted: + abort(Response(json.dumps({"detail": { + "msg": "No chunk with the given num exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + return {"result": {"text": koboldai_vars.prompt, "num": num}} + if num - 1 not in koboldai_vars.actions: + abort(Response(json.dumps({"detail": { + "msg": "No chunk with the given num exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + return {"result": {"text": koboldai_vars.actions[num - 1], "num": num}} + + +@api_v1.get("/story//text") +@api_schema_wrap +def get_story_num_text(num: int): + """--- + get: + summary: Retrieve the text of a story chunk + tags: + - story + description: |-2 + Returns the text inside a story chunk given its `num`. + parameters: + - name: num + in: path + description: |-2 + `num` of the desired story chunk. + schema: + type: integer + responses: + 200: + description: Successful request + content: + application/json: + schema: StoryChunkTextSchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No chunk with the given num exists. + type: key_error + """ + if num == 0: + if not koboldai_vars.gamestarted: + abort(Response(json.dumps({"detail": { + "msg": "No chunk with the given num exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + return {"value": koboldai_vars.prompt} + if num - 1 not in koboldai_vars.actions: + abort(Response(json.dumps({"detail": { + "msg": "No chunk with the given num exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + return {"value": koboldai_vars.actions[num - 1]} + + +@api_v1.put("/story//text") +@api_schema_wrap +def put_story_num_text(body: StoryChunkSetTextSchema, num: int): + """--- + put: + summary: Set the text of a story chunk + tags: + - story + description: |-2 + Sets the text inside a story chunk given its `num`. + parameters: + - name: num + in: path + description: |-2 + `num` of the desired story chunk. + schema: + type: integer + requestBody: + required: true + content: + application/json: + schema: StoryChunkSetTextSchema + example: + value: string + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No chunk with the given num exists. + type: key_error + {api_validation_error_response} + """ + if num == 0: + if not koboldai_vars.gamestarted: + abort(Response(json.dumps({"detail": { + "msg": "No chunk with the given num exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + inlineedit(0, body.value.rstrip()) + return {} + if num - 1 not in koboldai_vars.actions: + abort(Response(json.dumps({"detail": { + "msg": "No chunk with the given num exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + inlineedit(num, body.value.rstrip()) + return {} + + +@api_v1.delete("/story/") +@api_schema_wrap +def post_story_num_delete(num: int): + """--- + delete: + summary: Remove a story chunk + tags: + - story + description: |-2 + Removes a story chunk from the story in the KoboldAI GUI given its `num`. Cannot be used to delete the first action (the prompt). + parameters: + - name: num + in: path + description: |-2 + `num` of the desired story chunk. Must be larger than or equal to 1. + schema: + type: integer + minimum: 1 + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No chunk with the given num exists. + type: key_error + {api_server_busy_response} + """ + if num < 1: + abort(Response(json.dumps({"detail": { + "num": ["Must be greater than or equal to 1."], + }}), mimetype="application/json", status=422)) + if num - 1 not in koboldai_vars.actions: + abort(Response(json.dumps({"detail": { + "msg": "No chunk with the given num exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + if koboldai_vars.aibusy or koboldai_vars.genseqs: + abort(Response(json.dumps({"detail": { + "msg": "Server is busy; please try again later.", + "type": "service_unavailable", + }}), mimetype="application/json", status=503)) + inlinedelete(num) + return {} + + +@api_v1.delete("/story") +@api_schema_wrap +def delete_story(): + """--- + delete: + summary: Clear the story + tags: + - story + description: |-2 + Starts a new blank story. + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + {api_server_busy_response} + """ + if koboldai_vars.aibusy or koboldai_vars.genseqs: + abort(Response(json.dumps({"detail": { + "msg": "Server is busy; please try again later.", + "type": "service_unavailable", + }}), mimetype="application/json", status=503)) + newGameRequest() + return {} + + +@api_v1.put("/story/load") +@api_schema_wrap +def put_story_load(body: StoryLoadSchema): + """--- + put: + summary: Load a story + tags: + - story + description: |-2 + Loads a story given its filename (without the .json). + requestBody: + required: true + content: + application/json: + schema: StoryLoadSchema + example: + name: string + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + {api_validation_error_response} + {api_server_busy_response} + """ + if koboldai_vars.aibusy or koboldai_vars.genseqs: + abort(Response(json.dumps({"detail": { + "msg": "Server is busy; please try again later.", + "type": "service_unavailable", + }}), mimetype="application/json", status=503)) + loadRequest(fileops.storypath(body.name.strip())) + return {} + + +@api_v1.put("/story/save") +@api_schema_wrap +def put_story_save(body: StorySaveSchema): + """--- + put: + summary: Save the current story + tags: + - story + description: |-2 + Saves the current story given its destination filename (without the .json). + requestBody: + required: true + content: + application/json: + schema: StorySaveSchema + example: + name: string + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + {api_validation_error_response} + """ + saveRequest(fileops.storypath(body.name.strip())) + return {} + + +@api_v1.get("/world_info") +@api_schema_wrap +def get_world_info(): + """--- + get: + summary: Retrieve all world info entries + tags: + - world_info + description: |-2 + Returns all world info entries currently shown in the KoboldAI GUI. + + The `folders` are sorted in the same order as they are in the GUI and the `entries` within the folders and within the parent `result` object are all sorted in the same order as they are in their respective parts of the GUI. + responses: + 200: + description: Successful request + content: + application/json: + schema: WorldInfoSchema + """ + folders = [] + entries = [] + ln = len(koboldai_vars.worldinfo) + stablesortwi() + koboldai_vars.worldinfo_i = [wi for wi in koboldai_vars.worldinfo if wi["init"]] + folder: Optional[list] = None + if ln: + last_folder = ... + for wi in koboldai_vars.worldinfo_i: + if wi["folder"] != last_folder: + folder = [] + if wi["folder"] is not None: + folders.append({"uid": wi["folder"], "name": koboldai_vars.wifolders_d[wi["folder"]]["name"], "entries": folder}) + last_folder = wi["folder"] + (folder if wi["folder"] is not None else entries).append({k: v for k, v in wi.items() if k not in ("init", "folder", "num") and (wi["selective"] or k != "keysecondary")}) + return {"folders": folders, "entries": entries} + +@api_v1.get("/world_info/uids") +@api_schema_wrap +def get_world_info_uids(): + """--- + get: + summary: Retrieve the UIDs of all world info entries + tags: + - world_info + description: |-2 + Returns in a similar format as GET /world_info except only the `uid`s are returned. + responses: + 200: + description: Successful request + content: + application/json: + schema: WorldInfoUIDsSchema + """ + folders = [] + entries = [] + ln = len(koboldai_vars.worldinfo) + stablesortwi() + koboldai_vars.worldinfo_i = [wi for wi in koboldai_vars.worldinfo if wi["init"]] + folder: Optional[list] = None + if ln: + last_folder = ... + for wi in koboldai_vars.worldinfo_i: + if wi["folder"] != last_folder: + folder = [] + if wi["folder"] is not None: + folders.append({"uid": wi["folder"], "entries": folder}) + last_folder = wi["folder"] + (folder if wi["folder"] is not None else entries).append(wi["uid"]) + return {"folders": folders, "entries": entries} + + +@api_v1.get("/world_info/uids/") +@api_schema_wrap +def get_world_info_uids_uid(uid: int): + """--- + get: + summary: Determine whether or not there is a world info entry with the given UID + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicBooleanSchema + """ + return {"result": uid in koboldai_vars.worldinfo_u and koboldai_vars.worldinfo_u[uid]["init"]} + + +@api_v1.get("/world_info/folders") +@api_schema_wrap +def get_world_info_folders(): + """--- + get: + summary: Retrieve all world info folders + tags: + - world_info + description: |-2 + Returns details about all world info folders currently shown in the KoboldAI GUI. + + The `folders` are sorted in the same order as they are in the GUI. + responses: + 200: + description: Successful request + content: + application/json: + schema: WorldInfoFoldersSchema + """ + stablesortwi() + koboldai_vars.worldinfo_i = [wi for wi in koboldai_vars.worldinfo if wi["init"]] + return {"folders": [{"uid": folder, **{k: v for k, v in koboldai_vars.wifolders_d[folder].items() if k != "collapsed"}} for folder in koboldai_vars.wifolders_l]} + + +@api_v1.get("/world_info/folders/uids") +@api_schema_wrap +def get_world_info_folders_uids(): + """--- + get: + summary: Retrieve the UIDs all world info folders + tags: + - world_info + description: |-2 + Returns the `uid`s of all world info folders currently shown in the KoboldAI GUI. + + The `folders` are sorted in the same order as they are in the GUI. + responses: + 200: + description: Successful request + content: + application/json: + schema: WorldInfoFoldersUIDsSchema + """ + stablesortwi() + koboldai_vars.worldinfo_i = [wi for wi in koboldai_vars.worldinfo if wi["init"]] + return {"folders": koboldai_vars.wifolders_l} + + +@api_v1.get("/world_info/folders/none") +@api_schema_wrap +def get_world_info_folders_none(): + """--- + get: + summary: Retrieve all world info entries not in a folder + tags: + - world_info + description: |-2 + Returns all world info entries that are not in a world info folder. + + The `entries` are sorted in the same order as they are in the KoboldAI GUI. + responses: + 200: + description: Successful request + content: + application/json: + schema: WorldInfoEntriesSchema + """ + entries = [] + stablesortwi() + koboldai_vars.worldinfo_i = [wi for wi in koboldai_vars.worldinfo if wi["init"]] + for wi in reversed(koboldai_vars.worldinfo_i): + if wi["folder"] is not None: + break + entries.append({k: v for k, v in wi.items() if k not in ("init", "folder", "num") and (wi["selective"] or k != "keysecondary")}) + return {"entries": list(reversed(entries))} + + +@api_v1.get("/world_info/folders/none/uids") +@api_schema_wrap +def get_world_info_folders_none_uids(): + """--- + get: + summary: Retrieve the UIDs of all world info entries not in a folder + tags: + - world_info + description: |-2 + Returns the `uid`s of all world info entries that are not in a world info folder. + + The `entries` are sorted in the same order as they are in the KoboldAI GUI. + responses: + 200: + description: Successful request + content: + application/json: + schema: WorldInfoEntriesUIDsSchema + """ + entries = [] + stablesortwi() + koboldai_vars.worldinfo_i = [wi for wi in koboldai_vars.worldinfo if wi["init"]] + for wi in reversed(koboldai_vars.worldinfo_i): + if wi["folder"] is not None: + break + entries.append(wi["uid"]) + return {"entries": list(reversed(entries))} + + +@api_v1.get("/world_info/folders/none/uids/") +@api_schema_wrap +def get_world_info_folders_none_uids_uid(uid: int): + """--- + get: + summary: Determine whether or not there is a world info entry with the given UID that is not in a world info folder + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicBooleanSchema + """ + return {"result": uid in koboldai_vars.worldinfo_u and koboldai_vars.worldinfo_u[uid]["folder"] is None and koboldai_vars.worldinfo_u[uid]["init"]} + + +@api_v1.get("/world_info/folders/") +@api_schema_wrap +def get_world_info_folders_uid(uid: int): + """--- + get: + summary: Retrieve all world info entries in the given folder + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info folder. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + description: |-2 + Returns all world info entries that are in the world info folder with the given `uid`. + + The `entries` are sorted in the same order as they are in the KoboldAI GUI. + responses: + 200: + description: Successful request + content: + application/json: + schema: WorldInfoEntriesSchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info folder with the given uid exists. + type: key_error + """ + if uid not in koboldai_vars.wifolders_d: + abort(Response(json.dumps({"detail": { + "msg": "No world info folder with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + entries = [] + stablesortwi() + koboldai_vars.worldinfo_i = [wi for wi in koboldai_vars.worldinfo if wi["init"]] + for wi in koboldai_vars.wifolders_u[uid]: + if wi["init"]: + entries.append({k: v for k, v in wi.items() if k not in ("init", "folder", "num") and (wi["selective"] or k != "keysecondary")}) + return {"entries": entries} + + +@api_v1.get("/world_info/folders//uids") +@api_schema_wrap +def get_world_info_folders_uid_uids(uid: int): + """--- + get: + summary: Retrieve the UIDs of all world info entries in the given folder + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info folder. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + description: |-2 + Returns the `uid`s of all world info entries that are in the world info folder with the given `uid`. + + The `entries` are sorted in the same order as they are in the KoboldAI GUI. + responses: + 200: + description: Successful request + content: + application/json: + schema: WorldInfoEntriesUIDsSchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info folder with the given uid exists. + type: key_error + """ + if uid not in koboldai_vars.wifolders_d: + abort(Response(json.dumps({"detail": { + "msg": "No world info folder with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + entries = [] + stablesortwi() + koboldai_vars.worldinfo_i = [wi for wi in koboldai_vars.worldinfo if wi["init"]] + for wi in koboldai_vars.wifolders_u[uid]: + if wi["init"]: + entries.append(wi["uid"]) + return {"entries": entries} + + +@api_v1.get("/world_info/folders//uids/") +@api_schema_wrap +def get_world_info_folders_folder_uid_uids_entry_uid(folder_uid: int, entry_uid: int): + """--- + get: + summary: Determine whether or not there is a world info entry with the given UID in the world info folder with the given UID + tags: + - world_info + parameters: + - name: folder_uid + in: path + description: |-2 + `uid` of the desired world info folder. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + - name: entry_uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicBooleanSchema + """ + return {"result": entry_uid in koboldai_vars.worldinfo_u and koboldai_vars.worldinfo_u[entry_uid]["folder"] == folder_uid and koboldai_vars.worldinfo_u[entry_uid]["init"]} + + +@api_v1.get("/world_info/folders//name") +@api_schema_wrap +def get_world_info_folders_uid_name(uid: int): + """--- + get: + summary: Retrieve the name of the world info folder with the given UID + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info folder. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicStringSchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info folder with the given uid exists. + type: key_error + """ + if uid not in koboldai_vars.wifolders_d: + abort(Response(json.dumps({"detail": { + "msg": "No world info folder with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + return {"value": koboldai_vars.wifolders_d[uid]["name"]} + + +@api_v1.put("/world_info/folders//name") +@api_schema_wrap +def put_world_info_folders_uid_name(body: BasicStringSchema, uid: int): + """--- + put: + summary: Set the name of the world info folder with the given UID to the specified value + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info folder. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + requestBody: + required: true + content: + application/json: + schema: BasicStringSchema + example: + value: string + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info folder with the given uid exists. + type: key_error + {api_validation_error_response} + """ + if uid not in koboldai_vars.wifolders_d: + abort(Response(json.dumps({"detail": { + "msg": "No world info folder with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + koboldai_vars.wifolders_d[uid]["name"] = body.value + setgamesaved(False) + return {} + + +@api_v1.get("/world_info/") +@api_schema_wrap +def get_world_info_uid(uid: int): + """--- + get: + summary: Retrieve information about the world info entry with the given UID + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + responses: + 200: + description: Successful request + content: + application/json: + schema: WorldInfoEntrySchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info entry with the given uid exists. + type: key_error + """ + if uid not in koboldai_vars.worldinfo_u: + abort(Response(json.dumps({"detail": { + "msg": "No world info entry with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + wi = koboldai_vars.worldinfo_u[uid] + return {k: v for k, v in wi.items() if k not in ("init", "folder", "num") and (wi["selective"] or k != "keysecondary")} + + +@api_v1.get("/world_info//comment") +@api_schema_wrap +def get_world_info_uid_comment(uid: int): + """--- + get: + summary: Retrieve the comment of the world info entry with the given UID + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicStringSchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info entry with the given uid exists. + type: key_error + """ + if uid not in koboldai_vars.worldinfo_u: + abort(Response(json.dumps({"detail": { + "msg": "No world info entry with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + return {"value": koboldai_vars.worldinfo_u[uid]["comment"]} + + +@api_v1.put("/world_info//comment") +@api_schema_wrap +def put_world_info_uid_comment(body: BasicStringSchema, uid: int): + """--- + put: + summary: Set the comment of the world info entry with the given UID to the specified value + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + requestBody: + required: true + content: + application/json: + schema: BasicStringSchema + example: + value: string + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info entry with the given uid exists. + type: key_error + {api_validation_error_response} + """ + if uid not in koboldai_vars.worldinfo_u: + abort(Response(json.dumps({"detail": { + "msg": "No world info entry with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + koboldai_vars.worldinfo_u[uid]["comment"] = body.value + setgamesaved(False) + return {} + + +@api_v1.get("/world_info//content") +@api_schema_wrap +def get_world_info_uid_content(uid: int): + """--- + get: + summary: Retrieve the content of the world info entry with the given UID + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicStringSchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info entry with the given uid exists. + type: key_error + """ + if uid not in koboldai_vars.worldinfo_u: + abort(Response(json.dumps({"detail": { + "msg": "No world info entry with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + return {"value": koboldai_vars.worldinfo_u[uid]["content"]} + + +@api_v1.put("/world_info//content") +@api_schema_wrap +def put_world_info_uid_content(body: BasicStringSchema, uid: int): + """--- + put: + summary: Set the content of the world info entry with the given UID to the specified value + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + requestBody: + required: true + content: + application/json: + schema: BasicStringSchema + example: + value: string + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info entry with the given uid exists. + type: key_error + {api_validation_error_response} + """ + if uid not in koboldai_vars.worldinfo_u: + abort(Response(json.dumps({"detail": { + "msg": "No world info entry with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + koboldai_vars.worldinfo_u[uid]["content"] = body.value + setgamesaved(False) + return {} + + +@api_v1.get("/world_info//key") +@api_schema_wrap +def get_world_info_uid_key(uid: int): + """--- + get: + summary: Retrieve the keys or primary keys of the world info entry with the given UID + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicStringSchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info entry with the given uid exists. + type: key_error + """ + if uid not in koboldai_vars.worldinfo_u: + abort(Response(json.dumps({"detail": { + "msg": "No world info entry with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + return {"value": koboldai_vars.worldinfo_u[uid]["key"]} + + +@api_v1.put("/world_info//key") +@api_schema_wrap +def put_world_info_uid_key(body: BasicStringSchema, uid: int): + """--- + put: + summary: Set the keys or primary keys of the world info entry with the given UID to the specified value + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + requestBody: + required: true + content: + application/json: + schema: BasicStringSchema + example: + value: string + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info entry with the given uid exists. + type: key_error + {api_validation_error_response} + """ + if uid not in koboldai_vars.worldinfo_u: + abort(Response(json.dumps({"detail": { + "msg": "No world info entry with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + koboldai_vars.worldinfo_u[uid]["key"] = body.value + setgamesaved(False) + return {} + + +@api_v1.get("/world_info//keysecondary") +@api_schema_wrap +def get_world_info_uid_keysecondary(uid: int): + """--- + get: + summary: Retrieve the secondary keys of the world info entry with the given UID + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicStringSchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info entry with the given uid exists. + type: key_error + """ + if uid not in koboldai_vars.worldinfo_u: + abort(Response(json.dumps({"detail": { + "msg": "No world info entry with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + return {"value": koboldai_vars.worldinfo_u[uid]["keysecondary"]} + + +@api_v1.put("/world_info//keysecondary") +@api_schema_wrap +def put_world_info_uid_keysecondary(body: BasicStringSchema, uid: int): + """--- + put: + summary: Set the secondary keys of the world info entry with the given UID to the specified value + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + requestBody: + required: true + content: + application/json: + schema: BasicStringSchema + example: + value: string + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info entry with the given uid exists. + type: key_error + {api_validation_error_response} + """ + if uid not in koboldai_vars.worldinfo_u: + abort(Response(json.dumps({"detail": { + "msg": "No world info entry with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + koboldai_vars.worldinfo_u[uid]["keysecondary"] = body.value + setgamesaved(False) + return {} + + +@api_v1.get("/world_info//selective") +@api_schema_wrap +def get_world_info_uid_selective(uid: int): + """--- + get: + summary: Retrieve the selective mode state of the world info entry with the given UID + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicBooleanSchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info entry with the given uid exists. + type: key_error + """ + if uid not in koboldai_vars.worldinfo_u: + abort(Response(json.dumps({"detail": { + "msg": "No world info entry with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + return {"value": koboldai_vars.worldinfo_u[uid]["selective"]} + + +@api_v1.put("/world_info//selective") +@api_schema_wrap +def put_world_info_uid_selective(body: BasicBooleanSchema, uid: int): + """--- + put: + summary: Set the selective mode state of the world info entry with the given UID to the specified value + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + requestBody: + required: true + content: + application/json: + schema: BasicBooleanSchema + example: + value: true + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info entry with the given uid exists. + type: key_error + {api_validation_error_response} + """ + if uid not in koboldai_vars.worldinfo_u: + abort(Response(json.dumps({"detail": { + "msg": "No world info entry with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + koboldai_vars.worldinfo_u[uid]["selective"] = body.value + setgamesaved(False) + return {} + + +@api_v1.get("/world_info//constant") +@api_schema_wrap +def get_world_info_uid_constant(uid: int): + """--- + get: + summary: Retrieve the constant mode state of the world info entry with the given UID + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicBooleanSchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info entry with the given uid exists. + type: key_error + """ + if uid not in koboldai_vars.worldinfo_u: + abort(Response(json.dumps({"detail": { + "msg": "No world info entry with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + return {"value": koboldai_vars.worldinfo_u[uid]["constant"]} + + +@api_v1.put("/world_info//constant") +@api_schema_wrap +def put_world_info_uid_constant(body: BasicBooleanSchema, uid: int): + """--- + put: + summary: Set the constant mode state of the world info entry with the given UID to the specified value + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + requestBody: + required: true + content: + application/json: + schema: BasicBooleanSchema + example: + value: true + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info entry with the given uid exists. + type: key_error + {api_validation_error_response} + """ + if uid not in koboldai_vars.worldinfo_u: + abort(Response(json.dumps({"detail": { + "msg": "No world info entry with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + koboldai_vars.worldinfo_u[uid]["constant"] = body.value + setgamesaved(False) + return {} + + +@api_v1.post("/world_info/folders/none") +@api_schema_wrap +def post_world_info_folders_none(body: EmptySchema): + """--- + post: + summary: Create a new world info entry outside of a world info folder, at the end of the world info + tags: + - world_info + requestBody: + required: true + content: + application/json: + schema: EmptySchema + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicUIDSchema + {api_validation_error_response} + """ + stablesortwi() + koboldai_vars.worldinfo_i = [wi for wi in koboldai_vars.worldinfo if wi["init"]] + setgamesaved(False) + emit('from_server', {'cmd': 'wiexpand', 'data': koboldai_vars.worldinfo[-1]["num"]}, broadcast=True) + koboldai_vars.worldinfo[-1]["init"] = True + addwiitem(folder_uid=None) + return {"uid": koboldai_vars.worldinfo[-2]["uid"]} + + +@api_v1.post("/world_info/folders/") +@api_schema_wrap +def post_world_info_folders_uid(body: EmptySchema, uid: int): + """--- + post: + summary: Create a new world info entry at the end of the world info folder with the given UID + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info folder. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + requestBody: + required: true + content: + application/json: + schema: EmptySchema + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicUIDSchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info folder with the given uid exists. + type: key_error + {api_validation_error_response} + """ + if uid not in koboldai_vars.wifolders_d: + abort(Response(json.dumps({"detail": { + "msg": "No world info folder with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + stablesortwi() + koboldai_vars.worldinfo_i = [wi for wi in koboldai_vars.worldinfo if wi["init"]] + setgamesaved(False) + emit('from_server', {'cmd': 'wiexpand', 'data': koboldai_vars.wifolders_u[uid][-1]["num"]}, broadcast=True) + koboldai_vars.wifolders_u[uid][-1]["init"] = True + addwiitem(folder_uid=uid) + return {"uid": koboldai_vars.wifolders_u[uid][-2]["uid"]} + + +@api_v1.delete("/world_info/") +@api_schema_wrap +def delete_world_info_uid(uid: int): + """--- + delete: + summary: Delete the world info entry with the given UID + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info entry. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info entry with the given uid exists. + type: key_error + """ + if uid not in koboldai_vars.worldinfo_u: + abort(Response(json.dumps({"detail": { + "msg": "No world info entry with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + deletewi(uid) + return {} + + +@api_v1.post("/world_info/folders") +@api_schema_wrap +def post_world_info_folders(body: EmptySchema): + """--- + post: + summary: Create a new world info folder at the end of the world info + tags: + - world_info + requestBody: + required: true + content: + application/json: + schema: EmptySchema + responses: + 200: + description: Successful request + content: + application/json: + schema: BasicUIDSchema + {api_validation_error_response} + """ + addwifolder() + return {"uid": koboldai_vars.wifolders_l[-1]} + + +@api_v1.delete("/world_info/folders/") +@api_schema_wrap +def delete_world_info_folders_uid(uid: int): + """--- + delete: + summary: Delete the world info folder with the given UID + tags: + - world_info + parameters: + - name: uid + in: path + description: |-2 + `uid` of the desired world info folder. + schema: + type: integer + minimum: -2147483648 + maximum: 2147483647 + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + 404: + description: Not found + content: + application/json: + schema: NotFoundErrorSchema + example: + detail: + msg: No world info folders with the given uid exists. + type: key_error + """ + if uid not in koboldai_vars.wifolders_d: + abort(Response(json.dumps({"detail": { + "msg": "No world info folder with the given uid exists.", + "type": "key_error", + }}), mimetype="application/json", status=404)) + deletewifolder(uid) + return {} + + +def _make_f_get(obj, _var_name, _name, _schema, _example_yaml_value): + def f_get(): + """--- + get: + summary: Retrieve the current {} setting value + tags: + - config + responses: + 200: + description: Successful request + content: + application/json: + schema: {} + example: + value: {} + """ + _obj = {"koboldai_vars": koboldai_vars, "koboldai_vars.formatoptns": koboldai_vars.formatoptns}[obj] + if _var_name.startswith("@"): + return {"value": _obj[_var_name[1:]]} + else: + return {"value": getattr(_obj, _var_name)} + f_get.__doc__ = f_get.__doc__.format(_name, _schema, _example_yaml_value) + return f_get + +def _make_f_put(schema_class: Type[KoboldSchema], obj, _var_name, _name, _schema, _example_yaml_value): + def f_put(body: schema_class): + """--- + put: + summary: Set {} setting to specified value + tags: + - config + requestBody: + required: true + content: + application/json: + schema: {} + example: + value: {} + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + {api_validation_error_response} + """ + _obj = {"koboldai_vars": koboldai_vars, "koboldai_vars.formatoptns": koboldai_vars.formatoptns}[obj] + if _var_name.startswith("@"): + _obj[_var_name[1:]] = body.value + else: + setattr(_obj, _var_name, body.value) + settingschanged() + refresh_settings() + return {} + f_put.__doc__ = f_put.__doc__.format(_name, _schema, _example_yaml_value, api_validation_error_response=api_validation_error_response) + return f_put + +def create_config_endpoint(method="GET", schema="MemorySchema"): + _name = globals()[schema].KoboldMeta.name + _var_name = globals()[schema].KoboldMeta.var_name + _route_name = globals()[schema].KoboldMeta.route_name + _obj = globals()[schema].KoboldMeta.obj + _example_yaml_value = globals()[schema].KoboldMeta.example_yaml_value + _schema = schema + f = _make_f_get(_obj, _var_name, _name, _schema, _example_yaml_value) if method == "GET" else _make_f_put(globals()[schema], _obj, _var_name, _name, _schema, _example_yaml_value) + f.__name__ = f"{method.lower()}_config_{_name}" + f = api_schema_wrap(f) + for api in (api_v1,): + f = api.route(f"/config/{_route_name}", methods=[method])(f) + +class SoftPromptSettingSchema(KoboldSchema): + value: str = fields.String(required=True, validate=[soft_prompt_validator, validate.Regexp(r"^[^/\\]*$")], metadata={"description": "Soft prompt name, or a string containing only whitespace for no soft prompt. If using the GET method and no soft prompt is loaded, this will always be the empty string."}) + +@api_v1.get("/config/soft_prompt") +@api_schema_wrap +def get_config_soft_prompt(): + """--- + get: + summary: Retrieve the current soft prompt name + tags: + - config + responses: + 200: + description: Successful request + content: + application/json: + schema: SoftPromptSettingSchema + example: + value: "" + """ + return {"value": koboldai_vars.spfilename.strip()} + +@api_v1.put("/config/soft_prompt") +@api_schema_wrap +def put_config_soft_prompt(body: SoftPromptSettingSchema): + """--- + put: + summary: Set soft prompt by name + tags: + - config + requestBody: + required: true + content: + application/json: + schema: SoftPromptSettingSchema + example: + value: "" + responses: + 200: + description: Successful request + content: + application/json: + schema: EmptySchema + {api_validation_error_response} + """ + if koboldai_vars.allowsp: + spRequest(body.value) + settingschanged() + return {} + +config_endpoint_schemas: List[Type[KoboldSchema]] = [] + +def config_endpoint_schema(c: Type[KoboldSchema]): + config_endpoint_schemas.append(c) + return c + + +@config_endpoint_schema +class MemorySettingSchema(KoboldSchema): + value = fields.String(required=True) + class KoboldMeta: + route_name = "memory" + obj = "koboldai_vars" + var_name = "memory" + name = "memory" + example_yaml_value = "Memory" + +@config_endpoint_schema +class AuthorsNoteSettingSchema(KoboldSchema): + value = fields.String(required=True) + class KoboldMeta: + route_name = "authors_note" + obj = "koboldai_vars" + var_name = "authornote" + name = "author's note" + example_yaml_value = "''" + +@config_endpoint_schema +class AuthorsNoteTemplateSettingSchema(KoboldSchema): + value = fields.String(required=True) + class KoboldMeta: + route_name = "authors_note_template" + obj = "koboldai_vars" + var_name = "authornotetemplate" + name = "author's note template" + example_yaml_value = "\"[Author's note: <|>]\"" + +@config_endpoint_schema +class TopKSamplingSettingSchema(KoboldSchema): + value = fields.Integer(validate=validate.Range(min=0), required=True) + class KoboldMeta: + route_name = "top_k" + obj = "koboldai_vars" + var_name = "top_k" + name = "top-k sampling" + example_yaml_value = "0" + +@config_endpoint_schema +class TopASamplingSettingSchema(KoboldSchema): + value = fields.Float(validate=validate.Range(min=0), required=True) + class KoboldMeta: + route_name = "top_a" + obj = "koboldai_vars" + var_name = "top_a" + name = "top-a sampling" + example_yaml_value = "0.0" + +@config_endpoint_schema +class TopPSamplingSettingSchema(KoboldSchema): + value = fields.Float(validate=validate.Range(min=0, max=1), required=True) + class KoboldMeta: + route_name = "top_p" + obj = "koboldai_vars" + var_name = "top_p" + name = "top-p sampling" + example_yaml_value = "0.9" + +@config_endpoint_schema +class TailFreeSamplingSettingSchema(KoboldSchema): + value = fields.Float(validate=validate.Range(min=0, max=1), required=True) + class KoboldMeta: + route_name = "tfs" + obj = "koboldai_vars" + var_name = "tfs" + name = "tail free sampling" + example_yaml_value = "1.0" + +@config_endpoint_schema +class TypicalSamplingSettingSchema(KoboldSchema): + value = fields.Float(validate=validate.Range(min=0, max=1), required=True) + class KoboldMeta: + route_name = "typical" + obj = "koboldai_vars" + var_name = "typical" + name = "typical sampling" + example_yaml_value = "1.0" + +@config_endpoint_schema +class TemperatureSamplingSettingSchema(KoboldSchema): + value = fields.Float(validate=validate.Range(min=0, min_inclusive=False), required=True) + class KoboldMeta: + route_name = "temperature" + obj = "koboldai_vars" + var_name = "temp" + name = "temperature" + example_yaml_value = "0.5" + +@config_endpoint_schema +class GensPerActionSettingSchema(KoboldSchema): + value = fields.Integer(validate=validate.Range(min=0, max=5), required=True) + class KoboldMeta: + route_name = "n" + obj = "koboldai_vars" + var_name = "numseqs" + name = "Gens Per Action" + example_yaml_value = "1" + +@config_endpoint_schema +class MaxLengthSettingSchema(KoboldSchema): + value = fields.Integer(validate=validate.Range(min=1, max=512), required=True) + class KoboldMeta: + route_name = "max_length" + obj = "koboldai_vars" + var_name = "genamt" + name = "max length" + example_yaml_value = "80" + +@config_endpoint_schema +class WorldInfoDepthSettingSchema(KoboldSchema): + value = fields.Integer(validate=validate.Range(min=1, max=5), required=True) + class KoboldMeta: + route_name = "world_info_depth" + obj = "koboldai_vars" + var_name = "widepth" + name = "world info depth" + example_yaml_value = "3" + +@config_endpoint_schema +class AuthorsNoteDepthSettingSchema(KoboldSchema): + value = fields.Integer(validate=validate.Range(min=1, max=5), required=True) + class KoboldMeta: + route_name = "authors_note_depth" + obj = "koboldai_vars" + var_name = "andepth" + name = "author's note depth" + example_yaml_value = "3" + +@config_endpoint_schema +class MaxContextLengthSettingSchema(KoboldSchema): + value = fields.Integer(validate=validate.Range(min=512, max=2048), required=True) + class KoboldMeta: + route_name = "max_context_length" + obj = "koboldai_vars" + var_name = "max_length" + name = "max context length" + example_yaml_value = "2048" + +@config_endpoint_schema +class TrimIncompleteSentencesSettingsSchema(KoboldSchema): + value = fields.Boolean(required=True) + class KoboldMeta: + route_name = "frmttriminc" + obj = "koboldai_vars.formatoptns" + var_name = "@frmttriminc" + name = "trim incomplete sentences (output formatting)" + example_yaml_value = "false" + +@config_endpoint_schema +class RemoveBlankLinesSettingsSchema(KoboldSchema): + value = fields.Boolean(required=True) + class KoboldMeta: + route_name = "frmtrmblln" + obj = "koboldai_vars.formatoptns" + var_name = "@frmtrmblln" + name = "remove blank lines (output formatting)" + example_yaml_value = "false" + +@config_endpoint_schema +class RemoveSpecialCharactersSettingsSchema(KoboldSchema): + value = fields.Boolean(required=True) + class KoboldMeta: + route_name = "frmtrmspch" + obj = "koboldai_vars.formatoptns" + var_name = "@frmtrmspch" + name = "remove special characters (output formatting)" + example_yaml_value = "false" + +@config_endpoint_schema +class SingleLineSettingsSchema(KoboldSchema): + value = fields.Boolean(required=True) + class KoboldMeta: + route_name = "singleline" + obj = "koboldai_vars.formatoptns" + var_name = "@singleline" + name = "single line (output formatting)" + example_yaml_value = "false" + +@config_endpoint_schema +class AddSentenceSpacingSettingsSchema(KoboldSchema): + value = fields.Boolean(required=True) + class KoboldMeta: + route_name = "frmtadsnsp" + obj = "koboldai_vars.formatoptns" + var_name = "@frmtadsnsp" + name = "add sentence spacing (input formatting)" + example_yaml_value = "false" + + + +for schema in config_endpoint_schemas: + create_config_endpoint(schema=schema.__name__, method="GET") + create_config_endpoint(schema=schema.__name__, method="PUT") + + #==================================================================# # Final startup commands to launch Flask app #==================================================================# @@ -6750,8 +10052,9 @@ if __name__ == "__main__": socketio.run(app, host='0.0.0.0', port=port) else: if args.unblock: - import webbrowser - webbrowser.open_new('http://localhost:{0}'.format(port)) + if not args.no_ui: + import webbrowser + webbrowser.open_new('http://localhost:{0}'.format(port)) print("{0}Server started!\nYou may now connect with a browser at http://127.0.0.1:{1}/{2}" .format(colors.GREEN, port, colors.END)) koboldai_vars.serverstarted = True @@ -6763,8 +10066,9 @@ if __name__ == "__main__": koboldai_vars.flaskwebgui = True FlaskUI(app, socketio=socketio, start_server="flask-socketio", maximized=True, close_server_on_exit=True).run() except: - import webbrowser - webbrowser.open_new('http://localhost:{0}'.format(port)) + if not args.no_ui: + import webbrowser + webbrowser.open_new('http://localhost:{0}'.format(port)) print("{0}Server started!\nYou may now connect with a browser at http://127.0.0.1:{1}/{2}" .format(colors.GREEN, port, colors.END)) koboldai_vars.serverstarted = True diff --git a/bridge.lua b/bridge.lua index 66bedaa0..014426a8 100644 --- a/bridge.lua +++ b/bridge.lua @@ -165,7 +165,7 @@ return function(_python, _bridged) ---@field num_outputs integer ---@field feedback string ---@field is_config_file_open boolean - local kobold = setmetatable({API_VERSION = 1.1}, metawrapper) + local kobold = setmetatable({API_VERSION = 1.2}, metawrapper) local KoboldLib_mt = setmetatable({}, metawrapper) local KoboldLib_getters = setmetatable({}, metawrapper) local KoboldLib_setters = setmetatable({}, metawrapper) @@ -505,6 +505,7 @@ return function(_python, _bridged) elseif entries.name == "KoboldWorldInfoEntry" then _entries = {entries} else + _entries = {} for k, v in pairs(entries) do if type(v) == "table" and v.name == "KoboldWorldInfoEntry" and v:is_valid() then _entries[k] = v.uid @@ -725,11 +726,11 @@ return function(_python, _bridged) if k == "content" then if rawget(t, "_num") == 0 then if bridged.koboldai_vars.gamestarted then - local prompt = koboldbridge.userstate == "genmod" and bridged.vars._prompt or bridged.koboldai_vars.prompt + local prompt = koboldbridge.userstate == "genmod" and bridged.koboldai_vars._prompt or bridged.koboldai_vars.prompt return prompt end end - local actions = koboldbridge.userstate == "genmod" and bridged.vars._actions or bridged.koboldai_vars.actions + local actions = koboldbridge.userstate == "genmod" and bridged.koboldai_vars._actions or bridged.koboldai_vars.actions return _python.as_attrgetter(actions).get(math.tointeger(rawget(t, "_num")) - 1) end end @@ -751,7 +752,7 @@ return function(_python, _bridged) error("Attempted to set the prompt chunk's content to the empty string; this is not allowed") return end - local actions = koboldbridge.userstate == "genmod" and bridged.vars._actions or bridged.koboldai_vars.actions + local actions = koboldbridge.userstate == "genmod" and bridged.koboldai_vars._actions or bridged.koboldai_vars.actions if _k ~= 0 and _python.as_attrgetter(actions).get(_k-1) == nil then return end @@ -776,7 +777,7 @@ return function(_python, _bridged) ---@return fun(): KoboldStoryChunk, table, nil function KoboldStory:forward_iter() - local actions = koboldbridge.userstate == "genmod" and bridged.vars._actions or bridged.koboldai_vars.actions + local actions = koboldbridge.userstate == "genmod" and bridged.koboldai_vars._actions or bridged.koboldai_vars.actions local nxt, iterator = _python.iter(actions) local run_once = false local function f() @@ -804,7 +805,7 @@ return function(_python, _bridged) ---@return fun(): KoboldStoryChunk, table, nil function KoboldStory:reverse_iter() - local actions = koboldbridge.userstate == "genmod" and bridged.vars._actions or bridged.koboldai_vars.actions + local actions = koboldbridge.userstate == "genmod" and bridged.koboldai_vars._actions or bridged.koboldai_vars.actions local nxt, iterator = _python.iter(_python.builtins.reversed(actions)) local last_run = false local function f() diff --git a/colab/GPU.ipynb b/colab/GPU.ipynb index 0e86c4a5..f652d3bb 100644 --- a/colab/GPU.ipynb +++ b/colab/GPU.ipynb @@ -41,7 +41,7 @@ "\n", "For more information about KoboldAI check our our Github readme : https://github.com/KoboldAI/KoboldAI-Client/blob/main/readme.md\n", "\n", - "For the larger AI models (That are typically more coherent) check out our [TPU edition](https://colab.research.google.com/github/KoboldAI/KoboldAI-Client/blob/main/colab/TPU.ipynb)" + "For the larger AI models (That are typically more coherent) check out our **[TPU edition](https://colab.research.google.com/github/KoboldAI/KoboldAI-Client/blob/main/colab/TPU.ipynb)**!" ] }, { @@ -65,23 +65,56 @@ "cellView": "form" }, "source": [ - "#@title <-- Click this to start KoboldAI\n", + "#@title <-- Select your model below and then click this to start KoboldAI\n", "#@markdown You can find a description of the models below along with instructions on how to start KoboldAI.\n", "\n", - "Model = \"KoboldAI/fairseq-dense-2.7B-Nerys\" #@param [\"KoboldAI/fairseq-dense-2.7B-Nerys\", \"KoboldAI/GPT-Neo-2.7B-Janeway\", \"KoboldAI/GPT-Neo-2.7B-AID\", \"KoboldAI/GPT-Neo-2.7B-Picard\", \"KoboldAI/GPT-Neo-2.7B-Horni-LN\", \"KoboldAI/GPT-Neo-2.7B-Horni\", \"KoboldAI/GPT-Neo-2.7B-Shinen\", \"EleutherAI/gpt-neo-2.7B\"] {allow-input: true}\n", + "Model = \"Nerys 2.7B\" #@param [\"Nerys 2.7B\", \"Janeway 2.7B\", \"Picard 2.7B\", \"AID 2.7B\", \"Horni LN 2.7B\", \"Horni 2.7B\", \"Shinen 2.7B\", \"Neo 2.7B\"] {allow-input: true}\n", "Version = \"Official\" #@param [\"Official\", \"United\"] {allow-input: true}\n", - "Provider = \"Localtunnel\" #@param [\"Localtunnel\", \"Cloudflare\"]\n", + "Provider = \"Cloudflare\" #@param [\"Localtunnel\", \"Cloudflare\"]\n", "\n", "!nvidia-smi\n", "from google.colab import drive\n", "drive.mount('/content/drive/')\n", "\n", + "if Model == \"Nerys 2.7B\":\n", + " Model = \"KoboldAI/fairseq-dense-2.7B-Nerys\"\n", + " path = \"\"\n", + " download = \"\"\n", + "elif Model == \"Janeway 2.7B\":\n", + " Model = \"KoboldAI/GPT-Neo-2.7B-Janeway\"\n", + " path = \"\"\n", + " download = \"\"\n", + "elif Model == \"Picard 2.7B\":\n", + " Model = \"KoboldAI/GPT-Neo-2.7B-Picard\"\n", + " path = \"\"\n", + " download = \"\"\n", + "elif Model == \"AID 2.7B\":\n", + " Model = \"KoboldAI/GPT-Neo-2.7B-AID\"\n", + " path = \"\"\n", + " download = \"\"\n", + "elif Model == \"Horni LN 2.7B\":\n", + " Model = \"KoboldAI/GPT-Neo-2.7B-Horni-LN\"\n", + " path = \"\"\n", + " download = \"\"\n", + "elif Model == \"Horni 2.7B\":\n", + " Model = \"KoboldAI/GPT-Neo-2.7B-Horni\"\n", + " path = \"\"\n", + " download = \"\"\n", + "elif Model == \"Shinen 2.7B\":\n", + " Model = \"KoboldAI/GPT-Neo-2.7B-Shinen\"\n", + " path = \"\"\n", + " download = \"\"\n", + "elif Model == \"Neo 2.7B\":\n", + " Model = \"EleutherAI/gpt-neo-2.7B\"\n", + " path = \"\"\n", + " download = \"\"\n", + "\n", "if Provider == \"Localtunnel\":\n", " tunnel = \"--localtunnel yes\"\n", "else:\n", " tunnel = \"\"\n", "\n", - "!wget https://henk.tech/ckds -O - | bash /dev/stdin -m $Model -g $Version $tunnel" + "!wget https://koboldai.org/ckds -O - | bash /dev/stdin -m $Model -g $Version $tunnel" ], "execution_count": null, "outputs": [] @@ -92,27 +125,25 @@ "# GPU Edition Model Descriptions\n", "| Model | Size | Style | Description |\n", "| --- | --- | --- | --- |\n", - "| [Fairseq-Dense-2.7B-Nerys](https://huggingface.co/KoboldAI/fairseq-dense-2.7B-Nerys) by Mr Seeker | 2.7B | Novel/Adventure | Nerys is a hybrid model based on Pike (A newer Janeway), on top of the Pike dataset you also get some Light Novels, Adventure mode support and a little bit of shinen thrown in the mix. The end result is a very diverse model that is heavily biased towards SFW novel writing, but one that can go beyond its novel training and make for an excellent adventure model to. Adventure mode is best played from a second person perspective, but can be played in first or third person as well. Novel writing can be done best from the first or third person. |\n", - "| [GPT-Neo-2.7B-Janeway](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Janeway) by Mr Seeker | 2.7B | Novel | Janeway is a model created from Picard's dataset combined with a brand new collection of ebooks. This model is trained on 20% more content than Picard and has been trained on literature from various genres. Although the model is mainly focussed on SFW, romantic scenes might involve a degree of nudity. |\n", - "| [GPT-Neo-2.7B-Picard](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Picard) by Mr Seeker | 2.7B | Novel | Picard is a model trained for SFW Novels based on GPT-Neo-2.7B. It is focused on Novel style writing without the NSFW bias. While the name suggests a sci-fi model this model is designed for Novels of a variety of genre's. It is meant to be used in KoboldAI's regular mode. |\n", - "| [GPT-Neo-2.7B-AID](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-AID) by melastacho | 2.7B | Adventure | Also know as Adventure 2.7B this is a clone of the AI Dungeon Classic model and is best known for the epic wackey adventures that AI Dungeon Classic players love. |\n", - "| [GPT-Neo-2.7B-Horni-LN](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Horni-LN) by finetune | 2.7B | Novel | This model is based on GPT-Neo-2.7B-Horni and retains its NSFW knowledge, but was then further biased towards SFW novel stories. If you seek a balance between a SFW Novel model and a NSFW model this model should be a good choice. |\n", - "| [GPT-Neo-2.7B-Horni](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Horni) by finetune | 2.7B | NSFW | This model is tuned on Literotica to produce a Novel style model biased towards NSFW content. Can still be used for SFW stories but will have a bias towards NSFW content. It is meant to be used in KoboldAI's regular mode. |\n", - "| [GPT-Neo-2.7B-Shinen](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Shinen) by Mr Seeker | 2.7B | NSFW | Shinen is an alternative to the Horni model designed to be more explicit. If Horni is to tame for you shinen might produce better results. While it is a Novel model it is unsuitable for SFW stories due to its heavy NSFW bias. Shinen will not hold back. It is meant to be used in KoboldAI's regular mode. |\n", - "| [GPT-Neo-2.7B](https://huggingface.co/EleutherAI/gpt-neo-2.7B) by EleutherAI | 2.7B | Generic | This is the base model for all the other 2.7B models, it is best used when you have a use case that we have no other models available for, such as writing blog articles or programming. It can also be a good basis for the experience of some of the softprompts if your softprompt is not about a subject the other models cover. |\n", + "| [Nerys 2.7B](https://huggingface.co/KoboldAI/fairseq-dense-2.7B-Nerys) by Mr Seeker | 2.7B | Novel/Adventure | Nerys is a hybrid model based on Pike (A newer Janeway), on top of the Pike dataset you also get some Light Novels, Adventure mode support and a little bit of Shinen thrown in the mix. The end result is a very diverse model that is heavily biased towards SFW novel writing, but one that can go beyond its novel training and make for an excellent adventure model to. Adventure mode is best played from a second person perspective, but can be played in first or third person as well. Novel writing can be done best from the first or third person. |\n", + "| [Janeway 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Janeway) by Mr Seeker | 2.7B | Novel | Janeway is a model created from Picard's dataset combined with a brand new collection of ebooks. This model is trained on 20% more content than Picard and has been trained on literature from various genres. Although the model is mainly focussed on SFW, romantic scenes might involve a degree of nudity. |\n", + "| [Picard 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Picard) by Mr Seeker | 2.7B | Novel | Picard is a model trained for SFW Novels based on Neo 2.7B. It is focused on Novel style writing without the NSFW bias. While the name suggests a sci-fi model this model is designed for Novels of a variety of genre's. It is meant to be used in KoboldAI's regular mode. |\n", + "| [AID 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-AID) by melastacho | 2.7B | Adventure | Also know as Adventure 2.7B this is a clone of the AI Dungeon Classic model and is best known for the epic wackey adventures that AI Dungeon Classic players love. |\n", + "| [Horni LN 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Horni-LN) by finetune | 2.7B | Novel | This model is based on Horni 2.7B and retains its NSFW knowledge, but was then further biased towards SFW novel stories. If you seek a balance between a SFW Novel model and a NSFW model this model should be a good choice. |\n", + "| [Horni 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Horni) by finetune | 2.7B | NSFW | This model is tuned on Literotica to produce a Novel style model biased towards NSFW content. Can still be used for SFW stories but will have a bias towards NSFW content. It is meant to be used in KoboldAI's regular mode. |\n", + "| [Shinen 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Shinen) by Mr Seeker | 2.7B | NSFW | Shinen is an alternative to the Horni model designed to be more explicit. If Horni is to tame for you Shinen might produce better results. While it is a Novel model it is unsuitable for SFW stories due to its heavy NSFW bias. Shinen will not hold back. It is meant to be used in KoboldAI's regular mode. |\n", + "| [Neo 2.7B](https://huggingface.co/EleutherAI/gpt-neo-2.7B) by EleutherAI | 2.7B | Generic | This is the base model for all the other 2.7B models, it is best used when you have a use case that we have no other models available for, such as writing blog articles or programming. It can also be a good basis for the experience of some of the softprompts if your softprompt is not about a subject the other models cover. |\n", "\n", "# [TPU Edition Model Descriptions](https://colab.research.google.com/github/KoboldAI/KoboldAI-Client/blob/main/colab/TPU.ipynb)\n", "\n", "| Model | Size | Style | Description |\n", "| --- | --- | --- | --- |\n", - "| [Nerys](https://huggingface.co/KoboldAI/fairseq-dense-13B-Nerys) by Mr Seeker | 13B | Novel/Adventure | Nerys is a hybrid model based on Pike (A newer Janeway), on top of the Pike dataset you also get some Light Novels, Adventure mode support and a little bit of shinen thrown in the mix. The end result is a very diverse model that is heavily biased towards SFW novel writing, but one that can go beyond its novel training and make for an excellent adventure model to. Adventure mode is best played from a second person perspective, but can be played in first or third person as well. Novel writing can be done best from the first or third person. |\n", + "| [Nerys](https://huggingface.co/KoboldAI/fairseq-dense-13B-Nerys) by Mr Seeker | 13B | Novel/Adventure | Nerys is a hybrid model based on Pike (A newer Janeway), on top of the Pike dataset you also get some Light Novels, Adventure mode support and a little bit of Shinen thrown in the mix. The end result is a very diverse model that is heavily biased towards SFW novel writing, but one that can go beyond its novel training and make for an excellent adventure model to. Adventure mode is best played from a second person perspective, but can be played in first or third person as well. Novel writing can be done best from the first or third person. |\n", "| [Janeway](https://huggingface.co/KoboldAI/fairseq-dense-13B-Janeway) by Mr Seeker | 13B | Novel | Janeway is a model created from Picard's dataset combined with a brand new collection of ebooks. This model is trained on 20% more content than Picard and has been trained on literature from various genres. Although the model is mainly focussed on SFW, romantic scenes might involve a degree of nudity. |\n", "| [Shinen](https://huggingface.co/KoboldAI/fairseq-dense-13B-Shinen) by Mr Seeker | 13B | NSFW | Shinen is an NSFW model designed to be more explicit. Trained on a variety of stories from the website Sexstories it contains many different kinks. |\n", "| [Skein](https://huggingface.co/KoboldAI/GPT-J-6B-Skein) by VE\\_FORBRYDERNE | 6B | Adventure | Skein is best used with Adventure mode enabled, it consists of a 4 times larger adventure dataset than the Adventure model making it excellent for text adventure gaming. On top of that it also consists of light novel training further expanding its knowledge and writing capabilities. It can be used with the You filter bias if you wish to write Novels with it, but dedicated Novel models can perform better for this task. |\n", "| [Adventure](https://huggingface.co/KoboldAI/GPT-J-6B-Adventure) by VE\\_FORBRYDERNE | 6B | Adventure | Adventure is a 6B model designed to mimick the behavior of AI Dungeon. It is exclusively for Adventure Mode and can take you on the epic and wackey adventures that AI Dungeon players love. It also features the many tropes of AI Dungeon as it has been trained on very similar data. It must be used in second person (You). |\n", "| [Lit](https://huggingface.co/hakurei/lit-6B) by Haru | 6B | NSFW | Lit is a great NSFW model trained by Haru on both a large set of Literotica stories and high quality novels along with tagging support. Creating a high quality model for your NSFW stories. This model is exclusively a novel model and is best used in third person. |\n", - "| [Convo](https://huggingface.co/hitomi-team/convo-6B) by Hitomi Team | 6B | Chatbot | Convo-6B is a GPT-J 6B model fine-tuned on a collection of high quality open source datasets which amount to 6 million messages. The primary goal of the model is to provide improved performance and generalization when generating multi-turn dialogue for characters that were not present from within the fine tuning data. The prompted performance has especially improved over the predecessor model [C1-6B](https://huggingface.co/hakurei/c1-6B). |\n", - "| [C1](https://huggingface.co/hakurei/c1-6B) by Haru | 6B | Chatbot | C1 has been trained on various internet chatrooms, it makes the basis for an interesting chatbot model and has been optimized to be used in the Chatmode. |\n", "| Neo(X) by EleutherAI | 20B | Generic | NeoX is the largest EleutherAI model currently available, being a generic model it is not particularly trained towards anything and can do a variety of writing, Q&A and coding tasks. 20B's performance is closely compared to the 13B models and it is worth trying both especially if you have a task that does not involve english writing. Its behavior will be similar to the GPT-J-6B model since they are trained on the same dataset but with more sensitivity towards repetition penalty and with more knowledge. |\n", "| [Fairseq Dense](https://huggingface.co/KoboldAI/fairseq-dense-13B) | 13B | Generic | Trained by Facebook Researchers this model stems from the MOE research project within Fairseq. This particular version has been converted by us for use in KoboldAI. It is known to be on par with the larger 20B model from EleutherAI and considered as better for pop culture and language tasks. Because the model has never seen a new line (enter) it may perform worse on formatting and paragraphing. |\n", "| [GPT-J-6B](https://huggingface.co/EleutherAI/gpt-j-6B) by EleutherAI | 6B | Generic | This model serves as the basis for most other 6B models (Some being based on Fairseq Dense instead). Being trained on the Pile and not biased towards anything in particular it is suitable for a variety of tasks such as writing, Q&A and coding tasks. You will likely get better result with larger generic models or finetuned models. |\n", @@ -123,9 +154,9 @@ "| Novel | For regular story writing, not compatible with Adventure mode or other specialty modes. |\n", "| NSFW | Indicates that the model is strongly biased towards NSFW content and is not suitable for children, work environments or livestreaming. Most NSFW models are also Novel models in nature. |\n", "| Adventure | These models are excellent for people willing to play KoboldAI like a Text Adventure game and are meant to be used with Adventure mode enabled. Even if you wish to use it as a Novel style model you should always have Adventure mode on and set it to story. These models typically have a strong bias towards the use of the word You and without Adventure mode enabled break the story flow and write actions on your behalf. |\n", - "| Chatbot | These models are specifically trained for chatting and are best used with the Chatmode enabled. Typically trained on either public chatrooms or private chats. |\n", "| Generic | Generic models are not trained towards anything specific, typically used as a basis for other tasks and models. They can do everything the other models can do, but require much more handholding to work properly. Generic models are an ideal basis for tasks that we have no specific model for, or for experiencing a softprompt in its raw form. |\n", "\n", + "---\n", "# How to start KoboldAI in 7 simple steps\n", "Using KoboldAI on Google Colab is easy! Simply follow these steps to get started:\n", "1. Mobile phone? Tap the play button below next to \"<--- Tap this if you play on mobile\" to reveal an audio player, play the silent audio to keep the tab alive so Google will not shut you down when your using KoboldAI. If no audio player is revealed your phone browser does not support Google Colab in the mobile view, go to your browser menu and enable Desktop mode before you continue.\n", @@ -143,4 +174,4 @@ } } ] -} \ No newline at end of file +} diff --git a/colab/TPU.ipynb b/colab/TPU.ipynb index 89f53af2..448880e7 100644 --- a/colab/TPU.ipynb +++ b/colab/TPU.ipynb @@ -32,7 +32,9 @@ "\n", "Further down the page you can find descriptions of the models, and tips to get the most out of your Google Colab experience.\n", "\n", - "Make sure to keep this page open while you are using KoboldAI, and check back regularly to see if you got a Captcha. Failure to complete the captcha's in time can result in termination of your session or a lower priority towards the TPUs." + "Make sure to keep this page open while you are using KoboldAI, and check back regularly to see if you got a Captcha. Failure to complete the captcha's in time can result in termination of your session or a lower priority towards the TPUs.\n", + "\n", + "Firefox users need to disable the enhanced tracking protection or use a different browser in order to be able to use Google Colab without errors (This is not something we can do anything about, the cookie blocker breaks the Google Drive integration because it uses different domains)." ], "metadata": { "id": "zrLGxVCEaqZx" @@ -64,10 +66,9 @@ "#@title <-- Select your model below and then click this to start KoboldAI\n", "#@markdown You can find a description of the models below along with instructions on how to start KoboldAI.\n", "\n", - "#@title <-- Click this to start KoboldAI\n", - "Model = \"Nerys 13B\" #@param [\"Nerys 13B\", \"Janeway 13B\", \"Shinen 13B\", \"Skein 6B\", \"Janeway 6B\", \"Adventure 6B\", \"Shinen 6B\", \"Lit 6B\", \"NeoX 20B\", \"facebook/opt-13b\", \"KoboldAI/fairseq-dense-13B\", \"EleutherAI/gpt-j-6B\"] {allow-input: true}\n", + "Model = \"Nerys 13B V2\" #@param [\"Nerys 13B V2\", \"Janeway 13B\", \"Shinen 13B\", \"Skein 6B\", \"Janeway 6B\", \"Adventure 6B\", \"Shinen 6B\", \"Lit 6B\", \"NeoX 20B\", \"OPT 13B\", \"Fairseq Dense 13B\", \"GPT-J-6B\"] {allow-input: true}\n", "Version = \"Official\" #@param [\"Official\", \"United\"] {allow-input: true}\n", - "Provider = \"Localtunnel\" #@param [\"Localtunnel\", \"Cloudflare\"]\n", + "Provider = \"Cloudflare\" #@param [\"Localtunnel\", \"Cloudflare\"]\n", "\n", "import os\n", "try:\n", @@ -84,8 +85,8 @@ " Model = \"KoboldAI/fairseq-dense-13B-Janeway\"\n", " path = \"\"\n", " download = \"\"\n", - "elif Model == \"Nerys 13B\":\n", - " Model = \"KoboldAI/fairseq-dense-13B-Nerys\"\n", + "elif Model == \"Nerys 13B V2\":\n", + " Model = \"KoboldAI/fairseq-dense-13B-Nerys-v2\"\n", " path = \"\"\n", " download = \"\"\n", "elif Model == \"Shinen 13B\":\n", @@ -93,13 +94,9 @@ " path = \"\"\n", " download = \"\"\n", "elif Model == \"NeoX 20B\":\n", - " Model = \"TPUMeshTransformerGPTNeoX\"\n", - " path = \" -p gpt-neox-20b-jax\"\n", - " location = \"colab\"\n", - " download = \" -a https://storage.henk.tech/KoboldAI/neox-20b.txt\"\n", - " extract = \"\"\n", - " Drive = \"Unextracted (Less Space)\"\n", - " ![[ -f /content/drive/MyDrive/KoboldAI/settings/gpt-neox-20b-jax.settings ]] || echo -e \"{\\n \\\"apikey\\\": \\\"\\\",\\n \\\"andepth\\\": 3,\\n \\\"temp\\\": 0.5,\\n \\\"top_p\\\": 0.9,\\n \\\"top_k\\\": 0,\\n \\\"tfs\\\": 1.0,\\n \\\"rep_pen\\\": 1.03,\\n \\\"genamt\\\": 80,\\n \\\"max_length\\\": 2048,\\n \\\"ikgen\\\": 200,\\n \\\"formatoptns\\\": {\\n \\\"frmttriminc\\\": true,\\n \\\"frmtrmblln\\\": false,\\n \\\"frmtrmspch\\\": false,\\n \\\"frmtadsnsp\\\": false\\n },\\n \\\"numseqs\\\": 1,\\n \\\"widepth\\\": 3,\\n \\\"useprompt\\\": true,\\n \\\"adventure\\\": false\\n}\" > /content/drive/MyDrive/KoboldAI/settings/gpt-neox-20b-jax.settings\n", + " Model = \"EleutherAI/gpt-neox-20b\"\n", + " path = \"\"\n", + " download = \"\"\n", "elif Model == \"Skein 6B\":\n", " Model = \"KoboldAI/GPT-J-6B-Skein\"\n", " path = \"\"\n", @@ -120,14 +117,18 @@ " Model = \"KoboldAI/GPT-J-6B-Shinen\"\n", " path = \"\"\n", " download = \"\"\n", - "elif Model == \"Convo 6B\":\n", - " Model = \"hitomi-team/convo-6B\"\n", + "elif Model == \"OPT 13B\":\n", + " Model = \"facebook/opt-13b\"\n", " path = \"\"\n", " download = \"\"\n", - "elif Model == \"C1 6B\":\n", - " Model = \"hakurei/c1-6B\"\n", + "elif Model == \"Fairseq Dense 13B\":\n", + " Model = \"KoboldAI/fairseq-dense-13B\"\n", " path = \"\"\n", " download = \"\"\n", + "elif Model == \"GPT-J-6B\":\n", + " Model = \"EleutherAI/gpt-j-6B\"\n", + " path = \"\"\n", + " download = \"\"\n", "else:\n", " path = \"\"\n", " download = \"\"\n", @@ -137,17 +138,17 @@ "else:\n", " tunnel = \"\"\n", "\n", - "!wget https://henk.tech/ckds -O - | bash /dev/stdin $path$download -m $Model -g $Version $tunnel" + "!wget https://koboldai.org/ckds -O - | bash /dev/stdin $path$download -m $Model -g $Version $tunnel" ] }, { "cell_type": "markdown", "source": [ - "## TPU Edition Model Descriptions\n", + "# TPU Edition Model Descriptions\n", "\n", "| Model | Size | Style | Description |\n", "| --- | --- | --- | --- |\n", - "| [Nerys](https://huggingface.co/KoboldAI/fairseq-dense-13B-Nerys) by Mr Seeker | 13B | Novel/Adventure | Nerys is a hybrid model based on Pike (A newer Janeway), on top of the Pike dataset you also get some Light Novels, Adventure mode support and a little bit of shinen thrown in the mix. The end result is a very diverse model that is heavily biased towards SFW novel writing, but one that can go beyond its novel training and make for an excellent adventure model to. Adventure mode is best played from a second person perspective, but can be played in first or third person as well. Novel writing can be done best from the first or third person. |\n", + "| [Nerys](https://huggingface.co/KoboldAI/fairseq-dense-13B-Nerys) by Mr Seeker | 13B | Novel/Adventure | Nerys is a hybrid model based on Pike (A newer Janeway), on top of the Pike dataset you also get some Light Novels, Adventure mode support and a little bit of Shinen thrown in the mix. The end result is a very diverse model that is heavily biased towards SFW novel writing, but one that can go beyond its novel training and make for an excellent adventure model to. Adventure mode is best played from a second person perspective, but can be played in first or third person as well. Novel writing can be done best from the first or third person. |\n", "| [Janeway](https://huggingface.co/KoboldAI/fairseq-dense-13B-Janeway) by Mr Seeker | 13B | Novel | Janeway is a model created from Picard's dataset combined with a brand new collection of ebooks. This model is trained on 20% more content than Picard and has been trained on literature from various genres. Although the model is mainly focussed on SFW, romantic scenes might involve a degree of nudity. |\n", "| [Shinen](https://huggingface.co/KoboldAI/fairseq-dense-13B-Shinen) by Mr Seeker | 13B | NSFW | Shinen is an NSFW model designed to be more explicit. Trained on a variety of stories from the website Sexstories it contains many different kinks. |\n", "| [Skein](https://huggingface.co/KoboldAI/GPT-J-6B-Skein) by VE\\_FORBRYDERNE | 6B | Adventure | Skein is best used with Adventure mode enabled, it consists of a 4 times larger adventure dataset than the Adventure model making it excellent for text adventure gaming. On top of that it also consists of light novel training further expanding its knowledge and writing capabilities. It can be used with the You filter bias if you wish to write Novels with it, but dedicated Novel models can perform better for this task. |\n", @@ -162,35 +163,47 @@ "\n", "| Model | Size | Style | Description |\n", "| --- | --- | --- | --- |\n", - "| [Fairseq-Dense-2.7B-Nerys](https://huggingface.co/KoboldAI/fairseq-dense-2.7B-Nerys) by Mr Seeker | 2.7B | Novel/Adventure | Nerys is a hybrid model based on Pike (A newer Janeway), on top of the Pike dataset you also get some Light Novels, Adventure mode support and a little bit of shinen thrown in the mix. The end result is a very diverse model that is heavily biased towards SFW novel writing, but one that can go beyond its novel training and make for an excellent adventure model to. Adventure mode is best played from a second person perspective, but can be played in first or third person as well. Novel writing can be done best from the first or third person. |\n", - "| [GPT-Neo-2.7B-Janeway](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Janeway) by Mr Seeker | 2.7B | Novel | Janeway is a model created from Picard's dataset combined with a brand new collection of ebooks. This model is trained on 20% more content than Picard and has been trained on literature from various genres. Although the model is mainly focussed on SFW, romantic scenes might involve a degree of nudity. |\n", - "| [GPT-Neo-2.7B-Picard](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Picard) by Mr Seeker | 2.7B | Novel | Picard is a model trained for SFW Novels based on GPT-Neo-2.7B. It is focused on Novel style writing without the NSFW bias. While the name suggests a sci-fi model this model is designed for Novels of a variety of genre's. It is meant to be used in KoboldAI's regular mode. |\n", - "| [GPT-Neo-2.7B-AID](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-AID) by melastacho | 2.7B | Adventure | Also know as Adventure 2.7B this is a clone of the AI Dungeon Classic model and is best known for the epic wackey adventures that AI Dungeon Classic players love. |\n", - "| [GPT-Neo-2.7B-Horni-LN](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Horni-LN) by finetune | 2.7B | Novel | This model is based on GPT-Neo-2.7B-Horni and retains its NSFW knowledge, but was then further biased towards SFW novel stories. If you seek a balance between a SFW Novel model and a NSFW model this model should be a good choice. |\n", - "| [GPT-Neo-2.7B-Horni](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Horni) by finetune | 2.7B | NSFW | This model is tuned on Literotica to produce a Novel style model biased towards NSFW content. Can still be used for SFW stories but will have a bias towards NSFW content. It is meant to be used in KoboldAI's regular mode. |\n", - "| [GPT-Neo-2.7B-Shinen](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Shinen) by Mr Seeker | 2.7B | NSFW | Shinen is an alternative to the Horni model designed to be more explicit. If Horni is to tame for you shinen might produce better results. While it is a Novel model it is unsuitable for SFW stories due to its heavy NSFW bias. Shinen will not hold back. It is meant to be used in KoboldAI's regular mode. |\n", - "| [GPT-Neo-2.7B](https://huggingface.co/EleutherAI/gpt-neo-2.7B) by EleutherAI | 2.7B | Generic | This is the base model for all the other 2.7B models, it is best used when you have a use case that we have no other models available for, such as writing blog articles or programming. It can also be a good basis for the experience of some of the softprompts if your softprompt is not about a subject the other models cover. |\n", + "| [Nerys 2.7B](https://huggingface.co/KoboldAI/fairseq-dense-2.7B-Nerys) by Mr Seeker | 2.7B | Novel/Adventure | Nerys is a hybrid model based on Pike (A newer Janeway), on top of the Pike dataset you also get some Light Novels, Adventure mode support and a little bit of Shinen thrown in the mix. The end result is a very diverse model that is heavily biased towards SFW novel writing, but one that can go beyond its novel training and make for an excellent adventure model to. Adventure mode is best played from a second person perspective, but can be played in first or third person as well. Novel writing can be done best from the first or third person. |\n", + "| [Janeway 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Janeway) by Mr Seeker | 2.7B | Novel | Janeway is a model created from Picard's dataset combined with a brand new collection of ebooks. This model is trained on 20% more content than Picard and has been trained on literature from various genres. Although the model is mainly focussed on SFW, romantic scenes might involve a degree of nudity. |\n", + "| [Picard 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Picard) by Mr Seeker | 2.7B | Novel | Picard is a model trained for SFW Novels based on Neo 2.7B. It is focused on Novel style writing without the NSFW bias. While the name suggests a sci-fi model this model is designed for Novels of a variety of genre's. It is meant to be used in KoboldAI's regular mode. |\n", + "| [AID 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-AID) by melastacho | 2.7B | Adventure | Also know as Adventure 2.7B this is a clone of the AI Dungeon Classic model and is best known for the epic wackey adventures that AI Dungeon Classic players love. |\n", + "| [Horni LN 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Horni-LN) by finetune | 2.7B | Novel | This model is based on Horni 2.7B and retains its NSFW knowledge, but was then further biased towards SFW novel stories. If you seek a balance between a SFW Novel model and a NSFW model this model should be a good choice. |\n", + "| [Horni 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Horni) by finetune | 2.7B | NSFW | This model is tuned on Literotica to produce a Novel style model biased towards NSFW content. Can still be used for SFW stories but will have a bias towards NSFW content. It is meant to be used in KoboldAI's regular mode. |\n", + "| [Shinen 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Shinen) by Mr Seeker | 2.7B | NSFW | Shinen is an alternative to the Horni model designed to be more explicit. If Horni is to tame for you Shinen might produce better results. While it is a Novel model it is unsuitable for SFW stories due to its heavy NSFW bias. Shinen will not hold back. It is meant to be used in KoboldAI's regular mode. |\n", + "| [Neo 2.7B](https://huggingface.co/EleutherAI/gpt-neo-2.7B) by EleutherAI | 2.7B | Generic | This is the base model for all the other 2.7B models, it is best used when you have a use case that we have no other models available for, such as writing blog articles or programming. It can also be a good basis for the experience of some of the softprompts if your softprompt is not about a subject the other models cover. |\n", "\n", "| Style | Description |\n", "| --- | --- |\n", "| Novel | For regular story writing, not compatible with Adventure mode or other specialty modes. |\n", "| NSFW | Indicates that the model is strongly biased towards NSFW content and is not suitable for children, work environments or livestreaming. Most NSFW models are also Novel models in nature. |\n", "| Adventure | These models are excellent for people willing to play KoboldAI like a Text Adventure game and are meant to be used with Adventure mode enabled. Even if you wish to use it as a Novel style model you should always have Adventure mode on and set it to story. These models typically have a strong bias towards the use of the word You and without Adventure mode enabled break the story flow and write actions on your behalf. |\n", - "| Chatbot | These models are specifically trained for chatting and are best used with the Chatmode enabled. Typically trained on either public chatrooms or private chats. |\n", "| Generic | Generic models are not trained towards anything specific, typically used as a basis for other tasks and models. They can do everything the other models can do, but require much more handholding to work properly. Generic models are an ideal basis for tasks that we have no specific model for, or for experiencing a softprompt in its raw form. |\n", "\n", "---\n", - "## Tips to get the most out of Google Colab\n", + "# Tips to get the most out of Google Colab\n", "- Google will occationally show a Captcha, typically after it has been open for 30 minutes but it can be more frequent if you often use Colab. Make sure to do these properly, or you risk getting your instance shut down and getting a lower priority towards the TPU's.\n", "- KoboldAI uses Google Drive to store your files and settings, if you wish to upload a softprompt or userscript this can be done directly on the Google Drive website. You can also use this to download backups of your KoboldAI related files or upload models of your own.\n", "- Don't want to save your stories on Google Drive for privacy reasons? Do not use KoboldAI's save function and instead click Download as .json, this will automatically download the story to your own computer without ever touching Google's harddrives. You can load this back trough the Load from file option.\n", "- Google shut your instance down unexpectedly? You can still make use of the Download as .json button to recover your story as long as you did not close the KoboldAI window. You can then load this back up in your next session.\n", - "- Done with KoboldAI? Go to the Runtime menu, click on Manage Sessions and terminate your open sessions that you no longer need. This trick can help you maintain higher priority towards getting a TPU.\n", - "- Models stored on Google Drive typically load faster than models we need to download from the internet." + "- Done with KoboldAI? Go to the Runtime menu, click on Manage Sessions and terminate your open sessions that you no longer need. This trick can help you maintain higher priority towards getting a TPU." ], "metadata": { "id": "i0-9ARA3c4Fx" } + }, + { + "cell_type": "code", + "source": [ + "#@title Model Cleaner\n", + "#@markdown Out of space? Run this to remove all cached models (Google Drive models are not effected).\n", + "!rm /content/KoboldAI-Client/cache/*\n" + ], + "metadata": { + "cellView": "form", + "id": "QQZSmoNol04V" + }, + "execution_count": null, + "outputs": [] } ], "metadata": { @@ -212,4 +225,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/colab/vscode.ipynb b/colab/vscode.ipynb deleted file mode 100644 index 6a8fe84c..00000000 --- a/colab/vscode.ipynb +++ /dev/null @@ -1,76 +0,0 @@ -{ - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { - "colab": { - "name": "ColabKobold Code", - "provenance": [], - "authorship_tag": "ABX9TyOuIHmyxj4U9dipAib4hfIi", - "include_colab_link": true - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - }, - "language_info": { - "name": "python" - }, - "accelerator": "TPU" - }, - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "view-in-github", - "colab_type": "text" - }, - "source": [ - "\"Open" - ] - }, - { - "cell_type": "markdown", - "source": [ - "# ColabKobold VSCode Edition\n", - "This is a special edition of ColabKobold aimed at developers, it will not start a KoboldAI instance for you to play KoboldAI and instead will launch a fully functional copy of VSCode for easy development.\n", - "\n", - "Few things of note:\n", - "1. Make sure the desired (or no) accelertor is selected on Colab, you do not want a TPU ban for not using it.\n", - "1. The Version can be replaced with your github URL and appended with -b for the branch for example \"https://github.com/henk717/koboldai -b united\" dependencies will automatically be installed from requirements.txt or requirements_mtj.txt.\n", - "1. With the args you can specify launch options for the KoboldAI Deployment Script, this way you can easily preinstall models to your development instance so you have a model to test with. To install TPU requirements specify the -m TPUMeshTransformerGPTJ argument.\n", - "1. You will need an Ngrok auth token which you can obtain here : https://dashboard.ngrok.com/get-started/your-authtoken\n", - "1. KoboldAI is installed in /content/koboldai-client opening this folder is enough to automatically get full git history and revision support. Also keep in mind that it mounts your Google Drive, be careful comitting directly from this instance.\n", - "1. With Ctrl + Shift + ` you can get a terminal to launch KoboldAI with your own parameters, launching with --colab is recommended.\n", - "\n", - "# [If you are not a developer and are looking to use KoboldAI click here](https://henk.tech/colabkobold)" - ], - "metadata": { - "id": "hMRnGz42Xsy3" - } - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "40B1QvI3Xv02" - }, - "outputs": [], - "source": [ - "#@title VSCode Server\n", - "Version = \"United\" #@param [\"Official\", \"United\"] {allow-input: true}\n", - "Args = \"-m TPUMeshTransformerGPTJ -a https://api.wandb.ai/files/ve-forbryderne/skein/files/gpt-j-6b-skein-jax/aria2.txt\" #@param {type:\"string\"}\n", - "Authtoken = \"\" #@param {type:\"string\"}\n", - "\n", - "from google.colab import drive\n", - "drive.mount('/content/drive/')\n", - "\n", - "!wget https://henk.tech/ckds -O - | bash /dev/stdin -g $Version -i only $Args\n", - "\n", - "!pip install colabcode\n", - "!pip install 'flask>=2.1.0'\n", - "from colabcode import ColabCode\n", - "ColabCode(authtoken=Authtoken)" - ] - } - ] -} \ No newline at end of file diff --git a/customsettings_template.json b/customsettings_template.json new file mode 100644 index 00000000..361ca4e6 --- /dev/null +++ b/customsettings_template.json @@ -0,0 +1 @@ +{"aria2_port":null, "breakmodel":null, "breakmodel_disklayers":null, "breakmodel_gpulayers":null, "breakmodel_layers":null, "colab":null, "configname":null, "cpu":null, "host":null, "localtunnel":null, "lowmem":null, "model":null, "ngrok":null, "no_aria2":null, "noaimenu":null, "nobreakmodel":null, "override_delete":null, "override_rename":null, "path":null, "port":null, "quiet":null, "remote":null, "revision":null, "savemodel":null, "unblock":null} diff --git a/docker-standalone/Dockerfile b/docker-standalone/Dockerfile new file mode 100644 index 00000000..6e13ce0e --- /dev/null +++ b/docker-standalone/Dockerfile @@ -0,0 +1,8 @@ +FROM debian +RUN apt update && apt install wget aria2 git bzip2 -y +RUN git clone https://github.com/henk717/koboldai /opt/koboldai +WORKDIR /opt/koboldai +RUN ./install_requirements.sh cuda +COPY docker-helper.sh /opt/koboldai/docker-helper.sh +EXPOSE 5000/tcp +CMD /opt/koboldai/docker-helper.sh diff --git a/docker-standalone/Readme.txt b/docker-standalone/Readme.txt new file mode 100644 index 00000000..9b698f90 --- /dev/null +++ b/docker-standalone/Readme.txt @@ -0,0 +1,17 @@ +These are the source files for the official versions of the standalone docker and are provided for completeness. +Using these files you will not use any of the local modifications you make, instead it will use the latest github version of KoboldAI as the basis. + +If you wish to run KoboldAI containerised with access to the local directory you can do so using docker-cuda.sh or docker-rocm.sh instead. + +We do not support ROCm in the standalone docker as it is intended for cloud deployment on CUDA systems. +If you wish to build a ROCm version instead, you can do so by modifying the Dockerfile and changing the install_requirements.sh from cuda to rocm. + +Similarly you need to modify the Dockerfile to specify which branch of KoboldAI the docker is being built for. + +Usage: +This docker will automatically assume the persistent volume is mounted to /content and will by default not store models there. +The following environment variables exist to adjust the behavior if desired. + +KOBOLDAI_DATADIR=/content , this can be used to specify a different default location for your stories, settings, userscripts, etc in case your provider does not let you change the mounted folder path. +KOBOLDAI_MODELDIR= , This variable can be used to make model storage persistent, it can be the same location as your datadir but this is not required. +KOBOLDAI_ARGS= , This variable is built in KoboldAI and can be used to override the default launch options. Right now the docker by default will launch in remote mode, with output hidden from the logs and file management enabled. \ No newline at end of file diff --git a/docker-standalone/docker-helper.sh b/docker-standalone/docker-helper.sh new file mode 100644 index 00000000..30107e8a --- /dev/null +++ b/docker-standalone/docker-helper.sh @@ -0,0 +1,47 @@ +#!/bin/bash +cd /opt/koboldai +git pull +#./install_requirements.sh cuda + +if [[ ! -v KOBOLDAI_DATADIR ]];then + mkdir /content + KOBOLDAI_DATADIR=/content +fi + +mkdir $KOBOLDAI_DATADIR/stories +if [[ ! -v KOBOLDAI_MODELDIR ]];then + mkdir $KOBOLDAI_MODELDIR/models +fi +mkdir $KOBOLDAI_DATADIR/settings +mkdir $KOBOLDAI_DATADIR/softprompts +mkdir $KOBOLDAI_DATADIR/userscripts +#mkdir $KOBOLDAI_MODELDIR/cache + +cp -rn stories/* $KOBOLDAI_DATADIR/stories/ +cp -rn userscripts/* $KOBOLDAI_DATADIR/userscripts/ +cp -rn softprompts/* $KOBOLDAI_DATADIR/softprompts/ + +rm stories +rm -rf stories/ +rm userscripts +rm -rf userscripts/ +rm softprompts +rm -rf softprompts/ + +if [[ ! -v KOBOLDAI_MODELDIR ]];then + rm models + rm -rf models/ + #rm cache + #rm -rf cache/ +fi + +ln -s $KOBOLDAI_DATADIR/stories/ stories +ln -s $KOBOLDAI_DATADIR/settings/ settings +ln -s $KOBOLDAI_DATADIR/softprompts/ softprompts +ln -s $KOBOLDAI_DATADIR/userscripts/ userscripts +if [[ ! -v KOBOLDAI_MODELDIR ]];then + ln -s $KOBOLDAI_MODELDIR/models/ models + #ln -s $KOBOLDAI_MODELDIR/cache/ cache +fi + +PYTHONUNBUFFERED=1 ./play.sh --remote --quiet --override_delete --override_rename diff --git a/environments/finetuneanon.yml b/environments/finetuneanon.yml index b49f0bd7..995bd8fa 100644 --- a/environments/finetuneanon.yml +++ b/environments/finetuneanon.yml @@ -6,6 +6,7 @@ channels: dependencies: - colorama - flask-socketio + - flask-session - pytorch - cudatoolkit=11.1 - tensorflow-gpu @@ -15,6 +16,8 @@ dependencies: - bleach=4.1.0 - pip - git=2.35.1 + - marshmallow>=3.13 + - apispec-webframeworks - pip: - git+https://github.com/finetuneanon/transformers@gpt-neo-localattention3-rp-b - flask-cloudflared diff --git a/environments/huggingface.yml b/environments/huggingface.yml index afa37301..7261cada 100644 --- a/environments/huggingface.yml +++ b/environments/huggingface.yml @@ -6,6 +6,7 @@ channels: dependencies: - colorama - flask-socketio + - flask-session - pytorch=1.11.* - python=3.8.* - cudatoolkit=11.1 @@ -16,6 +17,8 @@ dependencies: - git=2.35.1 - sentencepiece - protobuf + - marshmallow>=3.13 + - apispec-webframeworks - pip: - flask-cloudflared - flask-ngrok diff --git a/environments/rocm-finetune.yml b/environments/rocm-finetune.yml index 5672ed21..05d7a2c1 100644 --- a/environments/rocm-finetune.yml +++ b/environments/rocm-finetune.yml @@ -5,12 +5,15 @@ channels: dependencies: - colorama - flask-socketio + - flask-session - python=3.8.* - eventlet - markdown - bleach=4.1.0 - pip - git=2.35.1 + - marshmallow>=3.13 + - apispec-webframeworks - pip: - --find-links https://download.pytorch.org/whl/rocm4.2/torch_stable.html - torch diff --git a/environments/rocm.yml b/environments/rocm.yml index 8ade341f..142d4230 100644 --- a/environments/rocm.yml +++ b/environments/rocm.yml @@ -5,6 +5,7 @@ channels: dependencies: - colorama - flask-socketio + - flask-session - python=3.8.* - eventlet - markdown @@ -13,6 +14,8 @@ dependencies: - git=2.35.1 - sentencepiece - protobuf + - marshmallow>=3.13 + - apispec-webframeworks - pip: - --find-links https://download.pytorch.org/whl/rocm4.2/torch_stable.html - torch==1.10.* diff --git a/gensettings.py b/gensettings.py index 4152e907..64802f3d 100644 --- a/gensettings.py +++ b/gensettings.py @@ -21,7 +21,7 @@ gensettingstf = [ "id": "settemp", "min": 0.1, "max": 2.0, - "step": 0.05, + "step": 0.01, "default": 0.5, "tooltip": "Randomness of sampling. High values can increase creativity but may make text less sensible. Lower values will make text more predictable but can become repetitious.", "menu_path": "Settings", @@ -36,7 +36,7 @@ gensettingstf = [ "id": "settopp", "min": 0.0, "max": 1.0, - "step": 0.05, + "step": 0.01, "default": 0.9, "tooltip": "Used to discard unlikely text in the sampling process. Lower values will make text more predictable but can become repetitious. (Put this value on 1 to disable its effect)", "menu_path": "Settings", @@ -67,7 +67,7 @@ gensettingstf = [ "id": "settfs", "min": 0.0, "max": 1.0, - "step": 0.05, + "step": 0.01, "default": 1.0, "tooltip": "Alternative sampling method; it is recommended to disable top_p and top_k (set top_p to 1 and top_k to 0) if using this. 0.95 is thought to be a good value. (Put this value on 1 to disable its effect)", "menu_path": "Settings", @@ -82,7 +82,7 @@ gensettingstf = [ "id": "settypical", "min": 0.0, "max": 1.0, - "step": 0.05, + "step": 0.01, "default": 1.0, "tooltip": "Alternative sampling method described in the paper \"Typical Decoding for Natural Language Generation\" (10.48550/ARXIV.2202.00666). The paper suggests 0.2 as a good value for this setting. Set this setting to 1 to disable its effect.", "menu_path": "Settings", @@ -315,6 +315,17 @@ gensettingstf = [ "classname": "user", "name": "nogenmod" }, + { + "uitype": "toggle", + "unit": "bool", + "label": "Full Determinism", + "id": "setfulldeterminism", + "min": 0, + "max": 1, + "step": 1, + "default": 0, + "tooltip": "Causes generation to be fully deterministic -- the model will always output the same thing as long as your story, settings and RNG seed are the same. If this is off, only the sequence of outputs that the model makes will be deterministic." + }, { "uitype": "toggle", "unit": "bool", @@ -579,9 +590,9 @@ formatcontrols = [{ "tooltip": "Remove special characters (@,#,%,^, etc)" }, { - "label": "Add sentence spacing", + "label": "Automatic spacing", "id": "frmtadsnsp", - "tooltip": "If the last action ended with punctuation, add a space to the beginning of the next action." + "tooltip": "Add spaces automatically if needed" }, { "label": "Single Line", diff --git a/install_requirements.bat b/install_requirements.bat index cd7b0aef..c82132ed 100644 --- a/install_requirements.bat +++ b/install_requirements.bat @@ -1,16 +1,11 @@ @echo off title KoboldAI Runtime Installer (MicroMamba) -echo Please choose one of the following transformers options -echo 1. Official Transformers (Recommended) -echo 2. Finetune Transformers (For old 6B models) -echo. + echo Errors? Rerun this as admin so it can add the needed LongPathsEnabled registery tweak. echo Installer failed or crashed? Run it again so it can continue. echo Only Windows 10 and higher officially supported, older Windows installations can't handle the paths. echo. -SET /P B=Type the number of the desired option and then press ENTER: - Reg add "HKLM\SYSTEM\CurrentControlSet\Control\FileSystem" /v "LongPathsEnabled" /t REG_DWORD /d "1" /f 2>nul cd /D %~dp0 @@ -19,7 +14,7 @@ if exist miniconda3\ ( echo This is required if you are switching modes, or if you get dependency errors in the game. echo 1. Yes echo 2. No - SET /P D=Type the number of the desired option and then press ENTER: + SET /P D=Type the number of the desired option and then press ENTER: ) ELSE ( SET D=Workaround ) @@ -30,7 +25,7 @@ echo Which installation mode would you like? echo 1. Temporary Drive Letter (Mounts the folder as drive B:, more stable and portable) echo 2. Subfolder (Traditional method, can't run in folder paths that contain spaces) echo. -SET /P M=Type the number of the desired option and then press ENTER: +SET /P M=Type the number of the desired option and then press ENTER: IF %M%==1 GOTO drivemap IF %M%==2 GOTO subfolder ECHO Incorrect choice @@ -40,7 +35,7 @@ GOTO MODE :drivemap echo 3 > loader.settings subst B: /D >nul -mkdir miniconda3 +mkdir miniconda3 subst B: miniconda3 SET TEMP=B:\ SET TMP=B:\ @@ -49,8 +44,7 @@ copy loader.settings B:\loader.settings copy disconnect-kobold-drive.bat B:\disconnect-kobold-drive.bat B: umamba.exe create -r B:\python\ -n base -IF %B%==1 umamba.exe install --no-shortcuts -r B:\python\ -n base -f "%~dp0\environments\huggingface.yml" -y --always-copy -IF %B%==2 umamba.exe install --no-shortcuts -r B:\python\ -n base -f "%~dp0\environments\finetuneanon.yml" -y --always-copy +umamba.exe install --no-shortcuts -r B:\python\ -n base -f "%~dp0\environments\huggingface.yml" -y --always-copy umamba.exe -r B:\ clean -a -y rd B:\Python\pkgs /S /Q subst B: /d @@ -62,8 +56,7 @@ echo 2 > loader.settings SET TEMP=%~DP0MINICONDA3 SET TMP=%~DP0MINICONDA3 umamba.exe create -r miniconda3\ -n base -IF %B%==1 umamba.exe install --no-shortcuts -r miniconda3 -n base -f environments\huggingface.yml -y --always-copy -IF %B%==2 umamba.exe install --no-shortcuts -r miniconda3 -n base -f environments\finetuneanon.yml -y --always-copy +umamba.exe install --no-shortcuts -r miniconda3 -n base -f environments\huggingface.yml -y --always-copy umamba.exe clean -a -y rd miniconda3\Python\pkgs /S /Q pause diff --git a/maps/bloom.json b/maps/bloom.json new file mode 100644 index 00000000..e3f5feb9 --- /dev/null +++ b/maps/bloom.json @@ -0,0 +1,30 @@ +{ + "mtj_compat": "bloom", + "mtj_pe": "alibi", + "mtj_config_map": { + "d_model": "n_embed", + "n_heads": "num_attention_heads", + "layers": "n_layer" + }, + "static_weights": { + "word_embeddings.weight": {"mtj": {"module": "embedding_shard/~/linear", "param": "w", "transforms": ["no_transpose", "vocab_pad"]}}, + "word_embeddings_layernorm.weight": {"mtj": {"module": "embedding_shard/~/replicated_layer_norm", "param": "scale"}}, + "word_embeddings_layernorm.bias": {"mtj": {"module": "embedding_shard/~/replicated_layer_norm", "param": "offset"}}, + "ln_f.weight": {"mtj": {"module": "projection_shard/~/replicated_layer_norm", "param": "scale"}}, + "ln_f.bias": {"mtj": {"module": "projection_shard/~/replicated_layer_norm", "param": "offset"}} + }, + "layer_weights": { + "h.{layer}.self_attention.query_key_value.weight": {"mtj": {"module": "layer_{layer}/~/combined_qkv", "param": "w"}}, + "h.{layer}.self_attention.query_key_value.bias": {"mtj": {"module": "layer_{layer}/~/combined_qkv", "param": "b"}}, + "h.{layer}.self_attention.dense.weight": {"mtj": {"module": "layer_{layer}/~/linear_3", "param": "w"}}, + "h.{layer}.self_attention.dense.bias": {"mtj": {"module": "layer_{layer}/~/linear_3", "param": "b", "transforms": ["divide_by_shards"]}}, + "h.{layer}.mlp.dense_h_to_4h.weight": {"mtj": {"module": "layer_{layer}/~/linear_4", "param": "w"}}, + "h.{layer}.mlp.dense_h_to_4h.bias": {"mtj": {"module": "layer_{layer}/~/linear_4", "param": "b"}}, + "h.{layer}.mlp.dense_4h_to_h.weight": {"mtj": {"module": "layer_{layer}/~/linear_5", "param": "w"}}, + "h.{layer}.mlp.dense_4h_to_h.bias": {"mtj": {"module": "layer_{layer}/~/linear_5", "param": "b", "transforms": ["divide_by_shards"]}}, + "h.{layer}.input_layernorm.weight": {"mtj": {"module": "layer_{layer}/~/replicated_layer_norm", "param": "scale"}}, + "h.{layer}.input_layernorm.bias": {"mtj": {"module": "layer_{layer}/~/replicated_layer_norm", "param": "offset"}}, + "h.{layer}.post_attention_layernorm.weight": {"mtj": {"module": "layer_{layer}/~/replicated_layer_norm_1", "param": "scale"}}, + "h.{layer}.post_attention_layernorm.bias": {"mtj": {"module": "layer_{layer}/~/replicated_layer_norm_1", "param": "offset"}} + } +} diff --git a/readme.md b/readme.md index ee0d601b..43b43046 100644 --- a/readme.md +++ b/readme.md @@ -8,7 +8,7 @@ Stories can be played like a Novel, a text adventure game or used as a chatbot w ### Adventure mode -By default KoboldAI will run in a generic mode optimized for writing, but with the right model you can play this like AI Dungeon without any issues. You can enable this in the settings and bring your own prompt, try generating a random prompt or download one of the prompts available at [prompts.aidg.club](https://prompts.aidg.club) . +By default KoboldAI will run in a generic mode optimized for writing, but with the right model you can play this like AI Dungeon without any issues. You can enable this in the settings and bring your own prompt, try generating a random prompt or download one of the prompts available at [/aids/ Prompts](https://aetherroom.club/). The gameplay will be slightly different than the gameplay in AI Dungeon because we adopted the Type of the Unleashed fork, giving you full control over all the characters because we do not automatically adapt your sentences behind the scenes. This means you can more reliably control characters that are not you. @@ -21,7 +21,7 @@ If you want to do this with your friends we advise using the main character as Y ### Writing assistant -If you want to use KoboldAI as a writing assistant this is best done in the regular mode with a model optimized for Novels. These models do not make the assumption that there is a You character and focus on Novel like writing. For writing these will often give you better results than Adventure or Generic models. That said, if you give it a good introduction to the story large generic models like 6B can be used if a more specific model is not available for what you wish to write. You can also try to use models that are not specific to what you wish to do, for example a NSFW Novel model for a SFW story if a SFW model is unavailable. This will mean you will have to correct the model more often because of its bias, but can still produce good enough results if it is familiar enough with your topic. +If you want to use KoboldAI as a writing assistant this is best done in the regular mode with a model optimized for Novels. These models do not make the assumption that there is a You character and focus on Novel like writing. For writing these will often give you better results than Adventure or Generic models. That said, if you give it a good introduction to the story large generic models like 13B can be used if a more specific model is not available for what you wish to write. You can also try to use models that are not specific to what you wish to do, for example a NSFW Novel model for a SFW story if a SFW model is unavailable. This will mean you will have to correct the model more often because of its bias, but can still produce good enough results if it is familiar enough with your topic. ### Chatbot Mode @@ -48,18 +48,16 @@ If you would like to play KoboldAI online for free on a powerful computer you ca Each edition features different models and requires different hardware to run, this means that if you are unable to obtain a TPU or a GPU you might still be able to use the other version. The models you can use are listed underneath the edition. To open a Colab click the big link featuring the editions name. -### [Click here for the TPU Edition Colab](https://colab.research.google.com/github/KoboldAI/KoboldAI-Client/blob/main/colab/TPU.ipynb) +## [TPU Edition Model Descriptions](https://colab.research.google.com/github/KoboldAI/KoboldAI-Client/blob/main/colab/TPU.ipynb) | Model | Size | Style | Description | | --- | --- | --- | --- | -| [Nerys](https://huggingface.co/KoboldAI/fairseq-dense-13B-Nerys) by Mr Seeker | 13B | Novel/Adventure | Nerys is a hybrid model based on Pike (A newer Janeway), on top of the Pike dataset you also get some Light Novels, Adventure mode support and a little bit of shinen thrown in the mix. The end result is a very diverse model that is heavily biased towards SFW novel writing, but one that can go beyond its novel training and make for an excellent adventure model to. Adventure mode is best played from a second person perspective, but can be played in first or third person as well. Novel writing can be done best from the first or third person. | +| [Nerys](https://huggingface.co/KoboldAI/fairseq-dense-13B-Nerys) by Mr Seeker | 13B | Novel/Adventure | Nerys is a hybrid model based on Pike (A newer Janeway), on top of the Pike dataset you also get some Light Novels, Adventure mode support and a little bit of Shinen thrown in the mix. The end result is a very diverse model that is heavily biased towards SFW novel writing, but one that can go beyond its novel training and make for an excellent adventure model to. Adventure mode is best played from a second person perspective, but can be played in first or third person as well. Novel writing can be done best from the first or third person. | | [Janeway](https://huggingface.co/KoboldAI/fairseq-dense-13B-Janeway) by Mr Seeker | 13B | Novel | Janeway is a model created from Picard's dataset combined with a brand new collection of ebooks. This model is trained on 20% more content than Picard and has been trained on literature from various genres. Although the model is mainly focussed on SFW, romantic scenes might involve a degree of nudity. | | [Shinen](https://huggingface.co/KoboldAI/fairseq-dense-13B-Shinen) by Mr Seeker | 13B | NSFW | Shinen is an NSFW model designed to be more explicit. Trained on a variety of stories from the website Sexstories it contains many different kinks. | | [Skein](https://huggingface.co/KoboldAI/GPT-J-6B-Skein) by VE\_FORBRYDERNE | 6B | Adventure | Skein is best used with Adventure mode enabled, it consists of a 4 times larger adventure dataset than the Adventure model making it excellent for text adventure gaming. On top of that it also consists of light novel training further expanding its knowledge and writing capabilities. It can be used with the You filter bias if you wish to write Novels with it, but dedicated Novel models can perform better for this task. | | [Adventure](https://huggingface.co/KoboldAI/GPT-J-6B-Adventure) by VE\_FORBRYDERNE | 6B | Adventure | Adventure is a 6B model designed to mimick the behavior of AI Dungeon. It is exclusively for Adventure Mode and can take you on the epic and wackey adventures that AI Dungeon players love. It also features the many tropes of AI Dungeon as it has been trained on very similar data. It must be used in second person (You). | | [Lit](https://huggingface.co/hakurei/lit-6B) by Haru | 6B | NSFW | Lit is a great NSFW model trained by Haru on both a large set of Literotica stories and high quality novels along with tagging support. Creating a high quality model for your NSFW stories. This model is exclusively a novel model and is best used in third person. | -| [Convo](https://huggingface.co/hitomi-team/convo-6B) by Hitomi Team | 6B | Chatbot | Convo-6B is a GPT-J 6B model fine-tuned on a collection of high quality open source datasets which amount to 6 million messages. The primary goal of the model is to provide improved performance and generalization when generating multi-turn dialogue for characters that were not present from within the fine tuning data. The prompted performance has especially improved over the predecessor model [C1-6B](https://huggingface.co/hakurei/c1-6B). | -| [C1](https://huggingface.co/hakurei/c1-6B) by Haru | 6B | Chatbot | C1 has been trained on various internet chatrooms, it makes the basis for an interesting chatbot model and has been optimized to be used in the Chatmode. | | Neo(X) by EleutherAI | 20B | Generic | NeoX is the largest EleutherAI model currently available, being a generic model it is not particularly trained towards anything and can do a variety of writing, Q&A and coding tasks. 20B's performance is closely compared to the 13B models and it is worth trying both especially if you have a task that does not involve english writing. Its behavior will be similar to the GPT-J-6B model since they are trained on the same dataset but with more sensitivity towards repetition penalty and with more knowledge. | | [Fairseq Dense](https://huggingface.co/KoboldAI/fairseq-dense-13B) | 13B | Generic | Trained by Facebook Researchers this model stems from the MOE research project within Fairseq. This particular version has been converted by us for use in KoboldAI. It is known to be on par with the larger 20B model from EleutherAI and considered as better for pop culture and language tasks. Because the model has never seen a new line (enter) it may perform worse on formatting and paragraphing. | | [GPT-J-6B](https://huggingface.co/EleutherAI/gpt-j-6B) by EleutherAI | 6B | Generic | This model serves as the basis for most other 6B models (Some being based on Fairseq Dense instead). Being trained on the Pile and not biased towards anything in particular it is suitable for a variety of tasks such as writing, Q&A and coding tasks. You will likely get better result with larger generic models or finetuned models. | @@ -68,21 +66,23 @@ Each edition features different models and requires different hardware to run, t | Model | Size | Style | Description | | --- | --- | --- | --- | -| [Fairseq-Dense-2.7B-Nerys](https://huggingface.co/KoboldAI/fairseq-dense-2.7B-Nerys) by Mr Seeker | 2.7B | Novel/Adventure | Nerys is a hybrid model based on Pike (A newer Janeway), on top of the Pike dataset you also get some Light Novels, Adventure mode support and a little bit of shinen thrown in the mix. The end result is a very diverse model that is heavily biased towards SFW novel writing, but one that can go beyond its novel training and make for an excellent adventure model to. Adventure mode is best played from a second person perspective, but can be played in first or third person as well. Novel writing can be done best from the first or third person. | -| [GPT-Neo-2.7B-Janeway](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Janeway) by Mr Seeker | 2.7B | Novel | Janeway is a model created from Picard's dataset combined with a brand new collection of ebooks. This model is trained on 20% more content than Picard and has been trained on literature from various genres. Although the model is mainly focussed on SFW, romantic scenes might involve a degree of nudity. | -| [GPT-Neo-2.7B-Picard](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Picard) by Mr Seeker | 2.7B | Novel | Picard is a model trained for SFW Novels based on GPT-Neo-2.7B. It is focused on Novel style writing without the NSFW bias. While the name suggests a sci-fi model this model is designed for Novels of a variety of genre's. It is meant to be used in KoboldAI's regular mode. | -| [GPT-Neo-2.7B-AID](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-AID) by melastacho | 2.7B | Adventure | Also know as Adventure 2.7B this is a clone of the AI Dungeon Classic model and is best known for the epic wackey adventures that AI Dungeon Classic players love. | -| [GPT-Neo-2.7B-Horni-LN](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Horni-LN) by finetune | 2.7B | Novel | This model is based on GPT-Neo-2.7B-Horni and retains its NSFW knowledge, but was then further biased towards SFW novel stories. If you seek a balance between a SFW Novel model and a NSFW model this model should be a good choice. | -| [GPT-Neo-2.7B-Horni](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Horni) by finetune | 2.7B | NSFW | This model is tuned on Literotica to produce a Novel style model biased towards NSFW content. Can still be used for SFW stories but will have a bias towards NSFW content. It is meant to be used in KoboldAI's regular mode. | -| [GPT-Neo-2.7B-Shinen](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Shinen) by Mr Seeker | 2.7B | NSFW | Shinen is an alternative to the Horni model designed to be more explicit. If Horni is to tame for you shinen might produce better results. While it is a Novel model it is unsuitable for SFW stories due to its heavy NSFW bias. Shinen will not hold back. It is meant to be used in KoboldAI's regular mode. | -| [GPT-Neo-2.7B](https://huggingface.co/EleutherAI/gpt-neo-2.7B) by EleutherAI | 2.7B | Generic | This is the base model for all the other 2.7B models, it is best used when you have a use case that we have no other models available for, such as writing blog articles or programming. It can also be a good basis for the experience of some of the softprompts if your softprompt is not about a subject the other models cover. | +| [Nerys 2.7B](https://huggingface.co/KoboldAI/fairseq-dense-2.7B-Nerys) by Mr Seeker | 2.7B | Novel/Adventure | Nerys is a hybrid model based on Pike (A newer Janeway), on top of the Pike dataset you also get some Light Novels, Adventure mode support and a little bit of Shinen thrown in the mix. The end result is a very diverse model that is heavily biased towards SFW novel writing, but one that can go beyond its novel training and make for an excellent adventure model to. Adventure mode is best played from a second person perspective, but can be played in first or third person as well. Novel writing can be done best from the first or third person. | +| [Janeway 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Janeway) by Mr Seeker | 2.7B | Novel | Janeway is a model created from Picard's dataset combined with a brand new collection of ebooks. This model is trained on 20% more content than Picard and has been trained on literature from various genres. Although the model is mainly focussed on SFW, romantic scenes might involve a degree of nudity. | +| [Picard 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Picard) by Mr Seeker | 2.7B | Novel | Picard is a model trained for SFW Novels based on Neo 2.7B. It is focused on Novel style writing without the NSFW bias. While the name suggests a sci-fi model this model is designed for Novels of a variety of genre's. It is meant to be used in KoboldAI's regular mode. | +| [AID 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-AID) by melastacho | 2.7B | Adventure | Also know as Adventure 2.7B this is a clone of the AI Dungeon Classic model and is best known for the epic wackey adventures that AI Dungeon Classic players love. | +| [Horni LN 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Horni-LN) by finetune | 2.7B | Novel | This model is based on Horni 2.7B and retains its NSFW knowledge, but was then further biased towards SFW novel stories. If you seek a balance between a SFW Novel model and a NSFW model this model should be a good choice. | +| [Horni 2.7B](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Horni) by finetune | 2.7B | NSFW | This model is tuned on Literotica to produce a Novel style model biased towards NSFW content. Can still be used for SFW stories but will have a bias towards NSFW content. It is meant to be used in KoboldAI's regular mode. | +| [Shinen 2.7B ](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Shinen) by Mr Seeker | 2.7B | NSFW | Shinen is an alternative to the Horni model designed to be more explicit. If Horni is to tame for you Shinen might produce better results. While it is a Novel model it is unsuitable for SFW stories due to its heavy NSFW bias. Shinen will not hold back. It is meant to be used in KoboldAI's regular mode. | +| [Neo 2.7B](https://huggingface.co/EleutherAI/gpt-neo-2.7B) by EleutherAI | 2.7B | Generic | This is the base model for all the other 2.7B models, it is best used when you have a use case that we have no other models available for, such as writing blog articles or programming. It can also be a good basis for the experience of some of the softprompts if your softprompt is not about a subject the other models cover. | -| Style | Description | +### Styles + +| Type | Description | | --- | --- | | Novel | For regular story writing, not compatible with Adventure mode or other specialty modes. | | NSFW | Indicates that the model is strongly biased towards NSFW content and is not suitable for children, work environments or livestreaming. Most NSFW models are also Novel models in nature. | -| Adventure | These models are excellent for people willing to play KoboldAI like a Text Adventure game and are meant to be used with Adventure mode enabled. Even if you wish to use it as a Novel style model you should always have Adventure mode on and set it to story. These models typically have a strong bias towards the use of the word You and without Adventure mode enabled break the story flow and write actions on your behalf. | -| Chatbot | These models are specifically trained for chatting and are best used with the Chatmode enabled. Typically trained on either public chatrooms or private chats. | +| Adventure | These models are excellent for people willing to play KoboldAI like a Text Adventure game and are meant to be used with Adventure mode enabled. Even if you wish to use it as a Novel Type model you should always have Adventure mode on and set it to story. These models typically have a strong bias towards the use of the word You and without Adventure mode enabled break the story flow and write actions on your behalf. | +| Hybrid | Hybrid models are a blend between different Types, for example they are trained on both Novel stories and Adventure stories. These models are great variety models that you can use for multiple different playTypes and modes, but depending on your usage you may need to enable Adventure Mode or the You bias (in userscripts). | | Generic | Generic models are not trained towards anything specific, typically used as a basis for other tasks and models. They can do everything the other models can do, but require much more handholding to work properly. Generic models are an ideal basis for tasks that we have no specific model for, or for experiencing a softprompt in its raw form. | ## Tips to get the most out of Google Colab @@ -94,28 +94,6 @@ Each edition features different models and requires different hardware to run, t * Done with KoboldAI? Go to the Runtime menu, click on Manage Sessions and terminate your open sessions that you no longer need. This trick can help you maintain higher priority towards getting a TPU. * Models stored on Google Drive typically load faster than models we need to download from the internet. -### [Click here for the GPU Edition Colab](https://colab.research.google.com/github/KoboldAI/KoboldAI-Client/blob/main/colab/GPU.ipynb) - -| Model | Size | Type | Description | -| --- | --- | --- | --- | -| [GPT-Neo-2.7B-Picard](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Picard) by Mr Seeker | 2.7B GPU | Novel | Picard is a model trained for SFW Novels based on GPT-Neo-2.7B. It is focused on Novel Type writing without the NSFW bias. While the name suggests a sci-fi model this model is designed for Novels of a variety of genre's. It is meant to be used in KoboldAI's regular mode. | -| [GPT-Neo-2.7B-AID](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-AID) by melastacho | 2.7B GPU | Adventure | Also know as Adventure 2.7B this is a clone of the AI Dungeon Classic model and is best known for the epic wackey adventures that AI Dungeon Classic players love. | -| [GPT-Neo-2.7B-Horni-LN](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Horni-LN) by finetune | 2.7B GPU | Novel | This model is based on GPT-Neo-2.7B-Horni and retains its NSFW knowledge, but was then further biased towards SFW novel stories. If you seek a balance between a SFW Novel model and a NSFW model this model should be a good choice. | -| [GPT-Neo-2.7B-Horni](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Horni) by finetune | 2.7B GPU | NSFW | This model is tuned on Literotica to produce a Novel Type model biased towards NSFW content. Can still be used for SFW stories but will have a bias towards NSFW content. It is meant to be used in KoboldAI's regular mode. | -| [GPT-Neo-2.7B-Shinen](https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Shinen) by Mr Seeker | 2.7B GPU | NSFW | Shinen is an alternative to the Horni model designed to be more explicit. If Horni is to tame for you shinen might produce better results. While it is a Novel model it is unsuitable for SFW stories due to its heavy NSFW bias. Shinen will not hold back. It is meant to be used in KoboldAI's regular mode. | -| [GPT-Neo-2.7B](https://huggingface.co/EleutherAI/gpt-neo-2.7B) by EleutherAI | 2.7B GPU | Generic | This is the base model for all the other 2.7B models, it is best used when you have a use case that we have no other models available for, such as writing blog articles or programming. It can also be a good basis for the experience of some of the softprompts if your softprompt is not about a subject the other models cover. | - -### Model Types - -| Type | Description | -| --- | --- | -| Novel | For regular story writing, not compatible with Adventure mode or other specialty modes. | -| NSFW | Indicates that the model is strongly biased towards NSFW content and is not suitable for children, work environments or livestreaming. Most NSFW models are also Novel models in nature. | -| Adventure | These models are excellent for people willing to play KoboldAI like a Text Adventure game and are meant to be used with Adventure mode enabled. Even if you wish to use it as a Novel Type model you should always have Adventure mode on and set it to story. These models typically have a strong bias towards the use of the word You and without Adventure mode enabled break the story flow and write actions on your behalf. | -| Chatbot | These models are specifically trained for chatting and are best used with the Chatmode enabled. Typically trained on either public chatrooms or private chats. | -| Hybrid | Hybrid models are a blend between different Types, for example they are trained on both Novel stories and Adventure stories. These models are great variety models that you can use for multiple different playTypes and modes, but depending on your usage you may need to enable Adventure Mode or the You bias (in userscripts). | -| Generic | Generic models are not trained towards anything specific, typically used as a basis for other tasks and models. They can do everything the other models can do, but require much more handholding to work properly. Generic models are an ideal basis for tasks that we have no specific model for, or for experiencing a softprompt in its raw form. | - ## Install KoboldAI on your own computer KoboldAI has a large number of dependencies you will need to install on your computer, unfortunately Python does not make it easy for us to provide instructions that work for everyone. The instructions below will work on most computers, but if you have multiple versions of Python installed conflicts can occur. @@ -195,11 +173,11 @@ If you get these errors you either did not select the correct folder for your cu Softprompts (also known as Modules in other products) are addons that can change the output of existing models. For example you may load a softprompt that biases the AI towards a certain subject and style like transcripts from your favorite TV show. -Since these softprompts are often based on existing franchises we currently do not bundle any of them with KoboldAI due to copyright concerns (We do not want to put the entire project at risk). Instead look at community resources like #softprompts on the [KoboldAI Discord](https://discord.gg/XuQWadgU9k) or the [community hosted mirror](https://storage.henk.tech/KoboldAI/softprompts/) . +Since these softprompts are often based on existing franchises we currently do not bundle any of them with KoboldAI due to copyright concerns (We do not want to put the entire project at risk). Instead look at community resources like #softprompts on the [KoboldAI Discord](https://discord.gg/XuQWadgU9k) or the [community hosted mirror](https://storage.henk.tech/KoboldAI/softprompts/). That way we are better protected from any DMCA claims as things can be taken down easier than directly on Github. If you have a copyright free softprompt that you made from scratch and is not based on existing IP that you would like to see officially bundled with KoboldAI issue a pull request with your softprompt. -Training softprompts can be done for free with the [mtj-softtuner colab](https://colab.research.google.com/github/VE-FORBRYDERNE/mtj-softtuner/blob/main/mtj-softtuner.ipynb) , in that case you can leave most of the settings default. Your source data needs to be a folder with text files that are UTF-8 formatted and contain Unix line endings. +Training softprompts can be done for free with the [Easy Softprompt Tuner](https://colab.research.google.com/gist/henk717/281fd57ebd2e88d852ef9dcc3f29bebf/easy-softprompt-tuner.ipynb#sandboxMode=true), in that case you can leave most of the settings default. Your source data needs to be a folder with text files that are UTF-8 formatted and contain Unix line endings. ## Userscripts diff --git a/requirements.txt b/requirements.txt index b55dbaf2..f087a16b 100644 --- a/requirements.txt +++ b/requirements.txt @@ -13,4 +13,6 @@ sentencepiece protobuf accelerate python-socketio[client] -flask_session \ No newline at end of file +flask_session +marshmallow>=3.13 +apispec-webframeworks diff --git a/requirements_mtj.txt b/requirements_mtj.txt index 32836175..e681e2e3 100644 --- a/requirements_mtj.txt +++ b/requirements_mtj.txt @@ -18,4 +18,6 @@ lupa==1.10 markdown bleach==4.1.0 python-socketio[client] -flask_session +flask-session +marshmallow>=3.13 +apispec-webframeworks diff --git a/static/application.js b/static/application.js index b256e3ef..c4149a29 100644 --- a/static/application.js +++ b/static/application.js @@ -78,6 +78,8 @@ var rs_accept; var rs_close; var seqselmenu; var seqselcontents; +var stream_preview; +var token_prob_container; var storyname = null; var memorymode = false; @@ -87,6 +89,7 @@ var wiscroll = 0; var editmode = false; var connected = false; var newly_loaded = true; +var all_modified_chunks = new Set(); var modified_chunks = new Set(); var empty_chunks = new Set(); var gametext_bound = false; @@ -102,6 +105,7 @@ var gamestate = ""; var gamesaved = true; var modelname = null; var model = ""; +var ignore_stream = false; // This is true iff [we're in macOS and the browser is Safari] or [we're in iOS] var using_webkit_patch = true; @@ -129,6 +133,7 @@ var adventure = false; var chatmode = false; var sliders_throttle = getThrottle(200); +var submit_throttle = null; //=================================================================// // METHODS @@ -507,6 +512,16 @@ function addWiLine(ob) { $(".wisortable-excluded-dynamic").removeClass("wisortable-excluded-dynamic"); $(this).parent().css("max-height", "").find(".wicomment").find(".form-control").css("max-height", ""); }); + + for (const wientry of document.getElementsByClassName("wientry")) { + // If we are uninitialized, skip. + if ($(wientry).closest(".wilistitem-uninitialized").length) continue; + + // add() will not add if the class is already present + wientry.classList.add("tokens-counted"); + } + + registerTokenCounters(); } function addWiFolder(uid, ob) { @@ -830,6 +845,7 @@ function exitMemoryMode() { button_actmem.html("Memory"); show([button_actback, button_actfwd, button_actretry, button_actwi]); input_text.val(""); + updateInputBudget(input_text[0]); // Hide Author's Note field anote_menu.slideUp("fast"); } @@ -886,11 +902,25 @@ function formatChunkInnerText(chunk) { } function dosubmit(disallow_abort) { + beginStream(); submit_start = Date.now(); var txt = input_text.val().replace(/\u00a0/g, " "); if((disallow_abort || gamestate !== "wait") && !memorymode && !gamestarted && ((!adventure || !action_mode) && txt.trim().length == 0)) { return; } + chunkOnFocusOut("override"); + // Wait for editor changes to be applied before submitting + submit_throttle = getThrottle(70); + submit_throttle.txt = txt; + submit_throttle.disallow_abort = disallow_abort; + submit_throttle(0, _dosubmit); +} + +function _dosubmit() { + beginStream(); + var txt = submit_throttle.txt; + var disallow_abort = submit_throttle.disallow_abort; + submit_throttle = null; input_text.val(""); hideMessage(); hidegenseqs(); @@ -1030,6 +1060,18 @@ function buildLoadModelList(ar, menu, breadcrumbs, showdelete) { if (breadcrumbs.length > 0) { $("#loadmodellistbreadcrumbs").append("
") } + //If we're in the custom load menu (we need to send the path data back in that case) + if(['NeoCustom', 'GPT2Custom'].includes(menu)) { + $("#loadmodel"+i).off("click").on("click", (function () { + return function () { + socket.send({'cmd': 'selectmodel', 'data': $(this).attr("name"), 'path': $(this).attr("pretty_name")}); + highlightLoadLine($(this)); + } + })(i)); + $("#custommodelname").removeClass("hidden"); + $("#custommodelname")[0].setAttribute("menu", menu); + } + for(i=0; i\
" //if the menu item is a link to another menu - if(ar[i][3]) { + console.log(ar[i]); + if((ar[i][3]) || (['Load a model from its directory', 'Load an old GPT-2 model (eg CloverEdition)'].includes(ar[i][0]))) { html = html + "" } else { //this is a model - html = html + "
" + html = html + "
   " } //now let's do the delete icon if applicable @@ -1065,6 +1108,7 @@ function buildLoadModelList(ar, menu, breadcrumbs, showdelete) { " loadmodelcontent.append(html); //If this is a menu + console.log(ar[i]); if(ar[i][3]) { $("#loadmodel"+i).off("click").on("click", (function () { return function () { @@ -1072,27 +1116,29 @@ function buildLoadModelList(ar, menu, breadcrumbs, showdelete) { disableButtons([load_model_accept]); } })(i)); - //If we're in the custom load menu (we need to send the path data back in that case) - } else if(['NeoCustom', 'GPT2Custom'].includes(menu)) { - $("#loadmodel"+i).off("click").on("click", (function () { - return function () { - socket.send({'cmd': 'selectmodel', 'data': $(this).attr("name"), 'path': $(this).attr("pretty_name")}); - highlightLoadLine($(this)); - } - })(i)); - $("#custommodelname").removeClass("hidden"); - $("#custommodelname")[0].setAttribute("menu", menu); //Normal load } else { - $("#loadmodel"+i).off("click").on("click", (function () { - return function () { - $("#use_gpu_div").addClass("hidden"); - $("#modelkey").addClass("hidden"); - $("#modellayers").addClass("hidden"); - socket.send({'cmd': 'selectmodel', 'data': $(this).attr("name")}); - highlightLoadLine($(this)); - } - })(i)); + if (['NeoCustom', 'GPT2Custom'].includes(menu)) { + $("#loadmodel"+i).off("click").on("click", (function () { + return function () { + $("#use_gpu_div").addClass("hidden"); + $("#modelkey").addClass("hidden"); + $("#modellayers").addClass("hidden"); + socket.send({'cmd': 'selectmodel', 'data': $(this).attr("name"), 'path': $(this).attr("pretty_name")}); + highlightLoadLine($(this)); + } + })(i)); + } else { + $("#loadmodel"+i).off("click").on("click", (function () { + return function () { + $("#use_gpu_div").addClass("hidden"); + $("#modelkey").addClass("hidden"); + $("#modellayers").addClass("hidden"); + socket.send({'cmd': 'selectmodel', 'data': $(this).attr("name")}); + highlightLoadLine($(this)); + } + })(i)); + } } } } @@ -1522,14 +1568,30 @@ function chunkOnTextInput(event) { r.deleteContents(); } - // In Chrome the added
will go outside of the chunks if we press + // In Chrome and Safari the added
will go outside of the chunks if we press // enter at the end of the story in the editor, so this is here // to put the
back in the right place var br = $("#_EDITOR_LINEBREAK_")[0]; if(br.parentNode === game_text[0]) { + var parent = br.previousSibling; if(br.previousSibling.nodeType !== 1) { + parent = br.previousSibling.previousSibling; br.previousSibling.previousSibling.appendChild(br.previousSibling); } + if(parent.lastChild.tagName === "BR") { + parent.lastChild.remove(); // Chrome and Safari also insert an extra
in this case for some reason so we need to remove it + if(using_webkit_patch) { + // Safari on iOS has a bug where it selects all text in the last chunk of the story when this happens so we collapse the selection to the end of the chunk in that case + setTimeout(function() { + var s = getSelection(); + var r = s.getRangeAt(0); + r.selectNodeContents(parent); + r.collapse(false); + s.removeAllRanges(); + s.addRange(r); + }, 2); + } + } br.previousSibling.appendChild(br); r.selectNodeContents(br.parentNode); s.removeAllRanges(); @@ -1711,22 +1773,29 @@ function applyChunkDeltas(nodes) { var chunks = Array.from(buildChunkSetFromNodeArray(nodes)); for(var i = 0; i < chunks.length; i++) { modified_chunks.add(chunks[i]); + all_modified_chunks.add(chunks[i]); } setTimeout(function() { var chunks = Array.from(modified_chunks); var selected_chunks = buildChunkSetFromNodeArray(getSelectedNodes()); for(var i = 0; i < chunks.length; i++) { var chunk = document.getElementById("n" + chunks[i]); - if(chunk && formatChunkInnerText(chunk).length != 0 && chunks[i] != '0') { + if(chunk && formatChunkInnerText(chunk).trim().length != 0 && chunks[i] != '0') { if(!selected_chunks.has(chunks[i])) { modified_chunks.delete(chunks[i]); socket.send({'cmd': 'inlineedit', 'chunk': chunks[i], 'data': formatChunkInnerText(chunk)}); + if(submit_throttle !== null) { + submit_throttle(0, _dosubmit); + } } empty_chunks.delete(chunks[i]); } else { if(!selected_chunks.has(chunks[i])) { modified_chunks.delete(chunks[i]); - socket.send({'cmd': 'inlineedit', 'chunk': chunks[i], 'data': ''}); + socket.send({'cmd': 'inlineedit', 'chunk': chunks[i], 'data': formatChunkInnerText(chunk)}); + if(submit_throttle !== null) { + submit_throttle(0, _dosubmit); + } } empty_chunks.add(chunks[i]); } @@ -1748,6 +1817,9 @@ function syncAllModifiedChunks(including_selected_chunks=false) { empty_chunks.delete(chunks[i]); } socket.send({'cmd': 'inlineedit', 'chunk': chunks[i], 'data': data}); + if(submit_throttle !== null) { + submit_throttle(0, _dosubmit); + } } } } @@ -1800,10 +1872,16 @@ function restorePrompt() { if(this.innerText.trim().length) { saved_prompt = this.innerText.trim(); socket.send({'cmd': 'inlinedelete', 'data': this.getAttribute("n")}); + if(submit_throttle !== null) { + submit_throttle(0, _dosubmit); + } this.parentNode.removeChild(this); return false; } socket.send({'cmd': 'inlinedelete', 'data': this.getAttribute("n")}); + if(submit_throttle !== null) { + submit_throttle(0, _dosubmit); + } this.parentNode.removeChild(this); }); } @@ -1818,6 +1896,9 @@ function restorePrompt() { modified_chunks.delete('0'); empty_chunks.delete('0'); socket.send({'cmd': 'inlineedit', 'chunk': '0', 'data': saved_prompt}); + if(submit_throttle !== null) { + submit_throttle(0, _dosubmit); + } } function deleteEmptyChunks() { @@ -1829,13 +1910,21 @@ function deleteEmptyChunks() { restorePrompt(); } else { socket.send({'cmd': 'inlinedelete', 'data': chunks[i]}); + if(submit_throttle !== null) { + submit_throttle(0, _dosubmit); + } } } if(modified_chunks.has('0')) { modified_chunks.delete(chunks[i]); socket.send({'cmd': 'inlineedit', 'chunk': chunks[i], 'data': formatChunkInnerText(document.getElementById("n0"))}); + if(submit_throttle !== null) { + submit_throttle(0, _dosubmit); + } + } + if(gamestarted) { + saved_prompt = formatChunkInnerText($("#n0")[0]); } - saved_prompt = formatChunkInnerText($("#n0")[0]); } function highlightEditingChunks() { @@ -1858,6 +1947,70 @@ function highlightEditingChunks() { } } +function cleanupChunkWhitespace() { + unbindGametext(); + + var chunks = Array.from(all_modified_chunks); + for(var i = 0; i < chunks.length; i++) { + var original_chunk = document.getElementById("n" + chunks[i]); + if(original_chunk === null || original_chunk.innerText.trim().length === 0) { + all_modified_chunks.delete(chunks[i]); + modified_chunks.delete(chunks[i]); + empty_chunks.add(chunks[i]); + } + } + + // Merge empty chunks with the next chunk + var chunks = Array.from(empty_chunks); + chunks.sort(function(e) {parseInt(e)}); + for(var i = 0; i < chunks.length; i++) { + if(chunks[i] == "0") { + continue; + } + var original_chunk = document.getElementById("n" + chunks[i]); + if(original_chunk === null) { + continue; + } + var chunk = original_chunk.nextSibling; + while(chunk) { + if(chunk.tagName === "CHUNK") { + break; + } + chunk = chunk.nextSibling; + } + if(chunk) { + chunk.innerText = original_chunk.innerText + chunk.innerText; + if(original_chunk.innerText.length != 0 && !modified_chunks.has(chunk.getAttribute("n"))) { + modified_chunks.add(chunk.getAttribute("n")); + } + } + original_chunk.innerText = ""; + } + // Move whitespace at the end of non-empty chunks into the beginning of the next non-empty chunk + var chunks = Array.from(all_modified_chunks); + chunks.sort(function(e) {parseInt(e)}); + for(var i = 0; i < chunks.length; i++) { + var original_chunk = document.getElementById("n" + chunks[i]); + var chunk = original_chunk.nextSibling; + while(chunk) { + if(chunk.tagName === "CHUNK" && !empty_chunks.has(chunk.getAttribute("n"))) { + break; + } + chunk = chunk.nextSibling; + } + var ln = original_chunk.innerText.trimEnd().length; + if (chunk) { + chunk.innerText = original_chunk.innerText.substring(ln) + chunk.innerText; + if(ln != original_chunk.innerText.length && !modified_chunks.has(chunk.getAttribute("n"))) { + modified_chunks.add(chunk.getAttribute("n")); + } + } + original_chunk.innerText = original_chunk.innerText.substring(0, ln); + } + + bindGametext(); +} + // This gets run every time the text in a chunk is edited // or a chunk is deleted function chunkOnDOMMutate(mutations, observer) { @@ -1929,13 +2082,15 @@ function chunkOnKeyDownSelectionChange(event) { // This gets run when you defocus the editor by clicking // outside of the editor or by pressing escape or tab function chunkOnFocusOut(event) { - if(!gametext_bound || !allowedit || event.target !== game_text[0]) { + if(event !== "override" && (!gametext_bound || !allowedit || event.target !== game_text[0])) { return; } setTimeout(function() { if(document.activeElement === game_text[0] || game_text[0].contains(document.activeElement)) { return; } + cleanupChunkWhitespace(); + all_modified_chunks = new Set(); syncAllModifiedChunks(true); setTimeout(function() { var blurred = game_text[0] !== document.activeElement; @@ -1959,6 +2114,20 @@ function unbindGametext() { gametext_bound = false; } +function beginStream() { + ignore_stream = false; + token_prob_container[0].innerHTML = ""; +} + +function endStream() { + // Clear stream, the real text is about to be displayed. + ignore_stream = true; + if (stream_preview) { + stream_preview.remove(); + stream_preview = null; + } +} + function update_gpu_layers() { var gpu_layers gpu_layers = 0; @@ -1987,6 +2156,45 @@ function RemoveAllButFirstOption(selectElement) { } } +function interpolateRGB(color0, color1, t) { + return [ + color0[0] + ((color1[0] - color0[0]) * t), + color0[1] + ((color1[1] - color0[1]) * t), + color0[2] + ((color1[2] - color0[2]) * t), + ] +} + +function updateInputBudget(inputElement) { + let data = {"unencoded": inputElement.value, "field": inputElement.id}; + + if (inputElement.id === "anoteinput") { + data["anotetemplate"] = $("#anotetemplate").val(); + } + + socket.send({"cmd": "getfieldbudget", "data": data}); +} + +function registerTokenCounters() { + // Add token counters to all input containers with the class of "tokens-counted", + // if a token counter is not already a child of said container. + for (const el of document.getElementsByClassName("tokens-counted")) { + if (el.getElementsByClassName("input-token-usage").length) continue; + + let span = document.createElement("span"); + span.classList.add("input-token-usage"); + span.innerText = "?/? Tokens"; + el.appendChild(span); + + let inputElement = el.querySelector("input, textarea"); + + inputElement.addEventListener("input", function() { + updateInputBudget(this); + }); + + updateInputBudget(inputElement); + } +} + //=================================================================// // READY/RUNTIME //=================================================================// @@ -2078,9 +2286,16 @@ $(document).ready(function(){ rs_close = $("#btn_rsclose"); seqselmenu = $("#seqselmenu"); seqselcontents = $("#seqselcontents"); + token_prob_container = $("#token_prob_container"); + token_prob_menu = $("#token_prob_menu"); // Connect to SocketIO server socket = io.connect(window.document.origin, {transports: ['polling', 'websocket'], closeOnBeforeunload: false, query:{"ui": "1"}}); + socket.on('load_popup', function(data){load_popup(data);}); + socket.on('popup_items', function(data){popup_items(data);}); + socket.on('popup_breadcrumbs', function(data){popup_breadcrumbs(data);}); + socket.on('popup_edit_file', function(data){popup_edit_file(data);}); + socket.on('error_popup', function(data){error_popup(data);}); socket.on('from_server', function(msg) { //console.log(msg); @@ -2130,6 +2345,75 @@ $(document).ready(function(){ active_element.focus(); })(); $("body").addClass("connected"); + } else if (msg.cmd == "streamtoken") { + // Sometimes the stream_token messages will come in too late, after + // we have recieved the full text. This leads to some stray tokens + // appearing after the output. To combat this, we only allow tokens + // to be displayed after requesting and before recieving text. + if (ignore_stream) return; + + let streamingEnabled = $("#setoutputstreaming")[0].checked; + let probabilitiesEnabled = $("#setshowprobs")[0].checked; + + if (!streamingEnabled && !probabilitiesEnabled) return; + + if (!stream_preview && streamingEnabled) { + stream_preview = document.createElement("span"); + game_text.append(stream_preview); + } + + for (const token of msg.data) { + if (streamingEnabled) stream_preview.innerText += token.decoded; + + if (probabilitiesEnabled) { + // Probability display + let probDiv = document.createElement("div"); + probDiv.classList.add("token-probs"); + + let probTokenSpan = document.createElement("span"); + probTokenSpan.classList.add("token-probs-header"); + probTokenSpan.innerText = token.decoded.replaceAll("\n", "\\n"); + probDiv.appendChild(probTokenSpan); + + let probTable = document.createElement("table"); + let probTBody = document.createElement("tbody"); + probTable.appendChild(probTBody); + + for (const probToken of token.probabilities) { + let tr = document.createElement("tr"); + let rgb = interpolateRGB( + [255, 255, 255], + [0, 255, 0], + probToken.score + ).map(Math.round); + let color = `rgb(${rgb.join(", ")})`; + + if (probToken.decoded === token.decoded) { + tr.classList.add("token-probs-final-token"); + } + + let tds = {}; + + for (const property of ["tokenId", "decoded", "score"]) { + let td = document.createElement("td"); + td.style.color = color; + tds[property] = td; + tr.appendChild(td); + } + + tds.tokenId.innerText = probToken.tokenId; + tds.decoded.innerText = probToken.decoded.toString().replaceAll("\n", "\\n"); + tds.score.innerText = (probToken.score * 100).toFixed(2) + "%"; + + probTBody.appendChild(tr); + } + + probDiv.appendChild(probTable); + token_prob_container.append(probDiv); + } + } + + scrollToBottom(); } else if(msg.cmd == "updatescreen") { var _gamestarted = gamestarted; gamestarted = msg.gamestarted; @@ -2140,6 +2424,7 @@ $(document).ready(function(){ unbindGametext(); allowedit = gamestarted && $("#allowediting").prop('checked'); game_text.attr('contenteditable', allowedit); + all_modified_chunks = new Set(); modified_chunks = new Set(); empty_chunks = new Set(); game_text.html(msg.data); @@ -2159,6 +2444,7 @@ $(document).ready(function(){ scrollToBottom(); } else if(msg.cmd == "updatechunk") { hideMessage(); + game_text.attr('contenteditable', allowedit); if (typeof submit_start !== 'undefined') { $("#runtime")[0].innerHTML = `Generation time: ${Math.round((Date.now() - submit_start)/1000)} sec`; delete submit_start; @@ -2178,7 +2464,11 @@ $(document).ready(function(){ } else if (!empty_chunks.has(index.toString())) { // Append at the end unbindGametext(); - var lc = game_text[0].lastChild; + + // game_text can contain things other than chunks (stream + // preview), so we use querySelector to get the last chunk. + var lc = game_text[0].querySelector("chunk:last-of-type"); + if(lc.tagName === "CHUNK" && lc.lastChild !== null && lc.lastChild.tagName === "BR") { lc.removeChild(lc.lastChild); } @@ -2194,7 +2484,11 @@ $(document).ready(function(){ var element = game_text.children('#n' + index); if(element.length) { unbindGametext(); - if((element[0].nextSibling === null || element[0].nextSibling.nodeType !== 1 || element[0].nextSibling.tagName !== "CHUNK") && element[0].previousSibling !== null && element[0].previousSibling.tagName === "CHUNK") { + if( + (element[0].nextSibling === null || element[0].nextSibling.nodeType !== 1 || element[0].nextSibling.tagName !== "CHUNK") + && element[0].previousSibling !== null + && element[0].previousSibling.tagName === "CHUNK" + ) { element[0].previousSibling.appendChild(document.createElement("br")); } element.remove(); // Remove the chunk @@ -2204,6 +2498,7 @@ $(document).ready(function(){ } else if(msg.cmd == "setgamestate") { // Enable or Disable buttons if(msg.data == "ready") { + endStream(); enableSendBtn(); enableButtons([button_actmem, button_actwi, button_actback, button_actfwd, button_actretry]); hideWaitAnimation(); @@ -2243,6 +2538,7 @@ $(document).ready(function(){ memorytext = msg.data; input_text.val(msg.data); } + updateInputBudget(input_text[0]); } else if(msg.cmd == "setmemory") { memorytext = msg.data; if(memorymode) { @@ -2364,6 +2660,7 @@ $(document).ready(function(){ } else if(msg.cmd == "setanote") { // Set contents of Author's Note field anote_input.val(msg.data); + updateInputBudget(anote_input[0]); } else if(msg.cmd == "setanotetemplate") { // Set contents of Author's Note Template field $("#anotetemplate").val(msg.data); @@ -2390,6 +2687,17 @@ $(document).ready(function(){ } else if(msg.cmd == "updatesingleline") { // Update toggle state $("#singleline").prop('checked', msg.data).change(); + } else if(msg.cmd == "updateoutputstreaming") { + // Update toggle state + $("#setoutputstreaming").prop('checked', msg.data).change(); + } else if(msg.cmd == "updateshowprobs") { + $("#setshowprobs").prop('checked', msg.data).change(); + + if(msg.data) { + token_prob_menu.removeClass("hidden"); + } else { + token_prob_menu.addClass("hidden"); + } } else if(msg.cmd == "allowtoggle") { // Allow toggle change states to propagate allowtoggle = msg.data; @@ -2564,6 +2872,9 @@ $(document).ready(function(){ } else if(msg.cmd == "updatenogenmod") { // Update toggle state $("#setnogenmod").prop('checked', msg.data).change(); + } else if(msg.cmd == "updatefulldeterminism") { + // Update toggle state + $("#setfulldeterminism").prop('checked', msg.data).change(); } else if(msg.cmd == "runs_remotely") { remote = true; hide([button_savetofile, button_import, button_importwi]); @@ -2589,6 +2900,8 @@ $(document).ready(function(){ if (msg.key) { $("#modelkey").removeClass("hidden"); $("#modelkey")[0].value = msg.key_value; + //if we're in the API list, disable to load button until the model is selected (after the API Key is entered) + disableButtons([load_model_accept]); } else { $("#modelkey").addClass("hidden"); @@ -2626,6 +2939,7 @@ $(document).ready(function(){ } } else if(msg.cmd == 'oai_engines') { $("#oaimodel").removeClass("hidden") + enableButtons([load_model_accept]); selected_item = 0; length = $("#oaimodel")[0].options.length; for (let i = 0; i < length; i++) { @@ -2648,6 +2962,7 @@ $(document).ready(function(){ $("#showmodelnamecontainer").removeClass("hidden"); } else if(msg.cmd == 'hide_model_name') { $("#showmodelnamecontainer").addClass("hidden"); + location.reload(); //console.log("Closing window"); } else if(msg.cmd == 'model_load_status') { $("#showmodelnamecontent").html("
" + msg.data + "
"); @@ -2661,7 +2976,18 @@ $(document).ready(function(){ opt.innerHTML = engine[1]; $("#oaimodel")[0].appendChild(opt); } + } else if(msg.cmd == 'showfieldbudget') { + let inputElement = document.getElementById(msg.data.field); + let tokenBudgetElement = inputElement.parentNode.getElementsByClassName("input-token-usage")[0]; + if (msg.data.max === null) { + tokenBudgetElement.innerText = ""; + } else { + let tokenLength = msg.data.length ?? "?"; + let tokenMax = msg.data.max ?? "?"; + tokenBudgetElement.innerText = `${tokenLength}/${tokenMax} Tokens`; + } } + enableButtons([load_model_accept]); }); socket.on('disconnect', function() { @@ -2691,6 +3017,12 @@ $(document).ready(function(){ chunkOnFocusOut ); mutation_observer = new MutationObserver(chunkOnDOMMutate); + $("#gamescreen").on('click', function(e) { + if(this !== e.target) { + return; + } + document.activeElement.blur(); + }); // This is required for the editor to work correctly in Firefox on desktop // because the gods of HTML and JavaScript say so @@ -2776,6 +3108,7 @@ $(document).ready(function(){ }); button_actretry.on("click", function(ev) { + beginStream(); hideMessage(); socket.send({'cmd': 'retry', 'chatname': chatmode ? chat_name.val() : undefined, 'data': ''}); hidegenseqs(); @@ -3022,6 +3355,7 @@ $(document).ready(function(){ }); rs_accept.on("click", function(ev) { + beginStream(); hideMessage(); socket.send({'cmd': 'rndgame', 'memory': $("#rngmemory").val(), 'data': topic.val()}); hideRandomStoryPopup(); @@ -3095,4 +3429,287 @@ $(document).ready(function(){ return true; } }); + + // Shortcuts + $(window).keydown(function (ev) { + // Only ctrl prefixed (for now) + if (!ev.ctrlKey) return; + + let handled = true; + switch (ev.key) { + // Ctrl+Z - Back + case "z": + button_actback.click(); + break; + // Ctrl+Y - Forward + case "y": + button_actfwd.click(); + break; + // Ctrl+E - Retry + case "e": + button_actretry.click(); + break; + default: + handled = false; + } + + if (handled) ev.preventDefault(); + }); + + $("#anotetemplate").on("input", function() { + updateInputBudget(anote_input[0]); + }) + + registerTokenCounters(); + + updateInputBudget(input_text[0]); + }); + + + +var popup_deleteable = false; +var popup_editable = false; +var popup_renameable = false; + +function load_popup(data) { + document.getElementById('spcontainer').classList.add('hidden'); + document.getElementById('uscontainer').classList.add('hidden'); + popup_deleteable = data.deleteable; + popup_editable = data.editable; + popup_renameable = data.renameable; + var popup = document.getElementById("popup"); + var popup_title = document.getElementById("popup_title"); + popup_title.textContent = data.popup_title; + var popup_list = document.getElementById("popup_list"); + //first, let's clear out our existing data + while (popup_list.firstChild) { + popup_list.removeChild(popup_list.firstChild); + } + var breadcrumbs = document.getElementById('popup_breadcrumbs'); + while (breadcrumbs.firstChild) { + breadcrumbs.removeChild(breadcrumbs.firstChild); + } + + if (data.upload) { + const dropArea = document.getElementById('popup_list'); + dropArea.addEventListener('dragover', (event) => { + event.stopPropagation(); + event.preventDefault(); + // Style the drag-and-drop as a "copy file" operation. + event.dataTransfer.dropEffect = 'copy'; + }); + + dropArea.addEventListener('drop', (event) => { + event.stopPropagation(); + event.preventDefault(); + const fileList = event.dataTransfer.files; + for (file of fileList) { + reader = new FileReader(); + reader.onload = function (event) { + socket.emit("upload_file", {'filename': file.name, "data": event.target.result}); + }; + reader.readAsArrayBuffer(file); + } + }); + } else { + + } + + popup.classList.remove("hidden"); + + //adjust accept button + if (data.call_back == "") { + document.getElementById("popup_accept").classList.add("hidden"); + } else { + document.getElementById("popup_accept").classList.remove("hidden"); + var accept = document.getElementById("popup_accept"); + accept.classList.add("disabled"); + accept.setAttribute("emit", data.call_back); + accept.setAttribute("selected_value", ""); + accept.onclick = function () { + socket.emit(this.emit, this.getAttribute("selected_value")); + document.getElementById("popup").classList.add("hidden"); + }; + } + +} + +function popup_items(data) { + var popup_list = document.getElementById('popup_list'); + //first, let's clear out our existing data + while (popup_list.firstChild) { + popup_list.removeChild(popup_list.firstChild); + } + document.getElementById('popup_upload_input').value = ""; + + for (item of data) { + var list_item = document.createElement("span"); + list_item.classList.add("item"); + + //create the folder icon + var folder_icon = document.createElement("span"); + folder_icon.classList.add("folder_icon"); + if (item[0]) { + folder_icon.classList.add("oi"); + folder_icon.setAttribute('data-glyph', "folder"); + } + list_item.append(folder_icon); + + //create the edit icon + var edit_icon = document.createElement("span"); + edit_icon.classList.add("edit_icon"); + if ((popup_editable) && !(item[0])) { + edit_icon.classList.add("oi"); + edit_icon.setAttribute('data-glyph', "spreadsheet"); + edit_icon.title = "Edit" + edit_icon.id = item[1]; + edit_icon.onclick = function () { + socket.emit("popup_edit", this.id); + }; + } + list_item.append(edit_icon); + + //create the rename icon + var rename_icon = document.createElement("span"); + rename_icon.classList.add("rename_icon"); + if ((popup_renameable) && !(item[0])) { + rename_icon.classList.add("oi"); + rename_icon.setAttribute('data-glyph', "pencil"); + rename_icon.title = "Rename" + rename_icon.id = item[1]; + rename_icon.setAttribute("filename", item[2]); + rename_icon.onclick = function () { + var new_name = prompt("Please enter new filename for \n"+ this.getAttribute("filename")); + if (new_name != null) { + socket.emit("popup_rename", {"file": this.id, "new_name": new_name}); + } + }; + } + list_item.append(rename_icon); + + //create the delete icon + var delete_icon = document.createElement("span"); + delete_icon.classList.add("delete_icon"); + if (popup_deleteable) { + delete_icon.classList.add("oi"); + delete_icon.setAttribute('data-glyph', "x"); + delete_icon.title = "Delete" + delete_icon.id = item[1]; + delete_icon.setAttribute("folder", item[0]); + delete_icon.onclick = function () { + if (this.getAttribute("folder") == "true") { + if (window.confirm("Do you really want to delete this folder and ALL files under it?")) { + socket.emit("popup_delete", this.id); + } + } else { + if (window.confirm("Do you really want to delete this file?")) { + socket.emit("popup_delete", this.id); + } + } + }; + } + list_item.append(delete_icon); + + //create the actual item + var popup_item = document.createElement("span"); + popup_item.classList.add("file"); + popup_item.id = item[1]; + popup_item.setAttribute("folder", item[0]); + popup_item.setAttribute("valid", item[3]); + popup_item.textContent = item[2]; + popup_item.onclick = function () { + var accept = document.getElementById("popup_accept"); + if (this.getAttribute("valid") == "true") { + accept.classList.remove("disabled"); + accept.setAttribute("selected_value", this.id); + } else { + console.log("not valid"); + accept.setAttribute("selected_value", ""); + accept.classList.add("disabled"); + if (this.getAttribute("folder") == "true") { + console.log("folder"); + socket.emit("popup_change_folder", this.id); + } + } + }; + list_item.append(popup_item); + + + popup_list.append(list_item); + + + } +} + +function popup_breadcrumbs(data) { + var breadcrumbs = document.getElementById('popup_breadcrumbs') + while (breadcrumbs.firstChild) { + breadcrumbs.removeChild(breadcrumbs.firstChild); + } + + for (item of data) { + var button = document.createElement("button"); + button.id = item[0]; + button.textContent = item[1]; + button.classList.add("breadcrumbitem"); + button.onclick = function () { + socket.emit("popup_change_folder", this.id); + }; + breadcrumbs.append(button); + var span = document.createElement("span"); + span.textContent = "\\"; + breadcrumbs.append(span); + } +} + +function popup_edit_file(data) { + var popup_list = document.getElementById('popup_list'); + var accept = document.getElementById("popup_accept"); + accept.classList.add("btn-secondary"); + accept.classList.remove("btn-primary"); + accept.textContent = "Save"; + //first, let's clear out our existing data + while (popup_list.firstChild) { + popup_list.removeChild(popup_list.firstChild); + } + var accept = document.getElementById("popup_accept"); + accept.setAttribute("selected_value", ""); + accept.onclick = function () { + var textarea = document.getElementById("filecontents"); + socket.emit("popup_change_file", {"file": textarea.getAttribute("filename"), "data": textarea.value}); + document.getElementById("popup").classList.add("hidden"); + this.classList.add("hidden"); + }; + + var textarea = document.createElement("textarea"); + textarea.classList.add("fullwidth"); + textarea.rows = 25; + textarea.id = "filecontents" + textarea.setAttribute("filename", data.file); + textarea.value = data.text; + textarea.onblur = function () { + var accept = document.getElementById("popup_accept"); + accept.classList.remove("hidden"); + accept.classList.remove("btn-secondary"); + accept.classList.add("btn-primary"); + }; + popup_list.append(textarea); + +} + +function error_popup(data) { + alert(data); +} + +function upload_file(file_box) { + var fileList = file_box.files; + for (file of fileList) { + reader = new FileReader(); + reader.onload = function (event) { + socket.emit("upload_file", {'filename': file.name, "data": event.target.result}); + }; + reader.readAsArrayBuffer(file); + } +} + diff --git a/static/custom.css b/static/custom.css index 6d88f1af..af238dc7 100644 --- a/static/custom.css +++ b/static/custom.css @@ -4,6 +4,7 @@ body { chunk { color: #ffffff; + white-space: pre-wrap; } #gametext.adventure action { @@ -290,7 +291,7 @@ body.connected #formatmenu, #formatmenu.always-available { align-items: center; } -#popup { +#popup_old { width: 75%; min-width: 500px; max-width: 1000px; @@ -1545,4 +1546,179 @@ body.connected .popupfooter, .popupfooter.always-available { .change .menubar3 { transform: translate(0px, -6px) rotate(45deg); +} + + +/*---------------------------------- Popup -------------------------------------------------*/ +.new_popup { + position: absolute; + top: 10vh; + left: 10%; + z-index: 999; + width: 80%; + height: 80vh; + background-color: black; + display: flex; + flex-direction: column; + background-color: #474B4F; + color: white; +} + +.new_popup .title { + width: 100%; + background-color: #337AB7; + text-align: center; + font-size: 1.3em; +} + +.new_popup .popup_list_area { + height: 70vh; + overflow-x: hidden; +} +.new_popup .item { + width: 100%; + background-color: #262626; + padding: 2px; + display: grid; + grid-template-areas: "folder_icon delete_icon edit_icon rename_icon file"; + grid-template-columns: 20px 20px 20px 20px auto; + +} + +.new_popup .item .folder_icon { + grid-area: folder_icon; +} + +.new_popup .item .edit_icon { + grid-area: edit_icon; +} + +.new_popup .item .rename_icon { + grid-area: rename_icon; +} + +.new_popup .item .delete_icon { + grid-area: delete_icon; +} + +.new_popup .item .file { + grid-area: file; +} + +.new_popup .item .file:hover { + background-color: #688f1f; +} + +.new_popup textarea { + grid-area: textarea; + background-color: #404040; + color: white; + resize: none; + width: 100%; +} + +.new_popup .popup_load_cancel { + text-align: center; + background-color: #285070; +} + +.popup_load_cancel_button { + vertical-align: bottom; + display: inline; +} + +.popup_load_cancel_button.btn-secondary { + color: rgb(51, 51, 51); + background-color: #686c68; +} + +.breadcrumbitem { + padding: 5px 10px 5px 10px; + color: #ffffff; + background-color: transparent; + border: none; + + -moz-transition: background-color 0.25s ease-in; + -o-transition: background-color 0.25s ease-in; + -webkit-transition: background-color 0.25s ease-in; + transition: background-color 0.25s ease-in; +} + +.breadcrumbitem:hover { + cursor: pointer; + background-color: #688f1f; +} + +#token_prob_menu { + color: white; + background-color: #262626; +} + +.token-probs { + display: inline-block; + text-align: center; + margin-right: 5px; +} + +.token-probs > table { + width: 100%; +} + +.token-probs > table > tbody > tr > td { + border: 1px solid #262626; + border-collapse: collapse; + padding: 2px 15px; +} + +.token-probs > table > tbody > tr { + background-color: #3e3e3e; +} + +.token-probs > table > tbody > tr:nth-child(2n) { + background-color: #575757; +} + +.token-probs-final-token { + font-weight: bold; + text-decoration: underline; +} + +.token-probs-final-token > td { + background: #5c8a5a; +} + +.token-probs-header { + display: block; +} + +#token_prob_container { + overflow-x: auto; + white-space: nowrap; +} + +.tokens-counted { + position: relative; +} + +.input-token-usage { + color: white; + position: absolute; + font-size: 10px; + bottom: 2px; + right: 5px; + + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; +} + +/* Override needed here due to the 10px right padding on inputrowleft; add 10 px. */ +#inputrowleft > .input-token-usage { + right: 15px; + bottom: 1px; +} + +.wientry > .input-token-usage { + bottom: 8px; } \ No newline at end of file diff --git a/static/swagger-ui/LICENSE b/static/swagger-ui/LICENSE new file mode 100644 index 00000000..d6456956 --- /dev/null +++ b/static/swagger-ui/LICENSE @@ -0,0 +1,202 @@ + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ + +a { color: #8c8cfa; } + +::-webkit-scrollbar-track-piece { background-color: rgba(255, 255, 255, .2) !important; } + +::-webkit-scrollbar-track { background-color: rgba(255, 255, 255, .3) !important; } + +::-webkit-scrollbar-thumb { background-color: rgba(255, 255, 255, .5) !important; } + +embed[type="application/pdf"] { filter: invert(90%); } + +html { + background: #1f1f1f !important; + box-sizing: border-box; + filter: contrast(100%) brightness(100%) saturate(100%); + overflow-y: scroll; +} + +body { + background: #1f1f1f; + background-color: #1f1f1f; + background-image: none !important; +} + +button, input, select, textarea { + background-color: #1f1f1f; + color: #bfbfbf; +} + +font, html { color: #bfbfbf; } + +.swagger-ui, .swagger-ui section h3 { color: #b5bac9; } + +.swagger-ui a { background-color: transparent; } + +.swagger-ui mark { + background-color: #664b00; + color: #bfbfbf; +} + +.swagger-ui legend { color: inherit; } + +.swagger-ui .debug * { outline: #e6da99 solid 1px; } + +.swagger-ui .debug-white * { outline: #fff solid 1px; } + +.swagger-ui .debug-black * { outline: #bfbfbf solid 1px; } + +.swagger-ui .debug-grid { background: url(data:image/png;base64,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) 0 0; } + +.swagger-ui .debug-grid-16 { background: url(data:image/png;base64,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) 0 0; } + +.swagger-ui .debug-grid-8-solid { background: url(data:image/jpeg;base64,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) 0 0 #1c1c21; } + +.swagger-ui .debug-grid-16-solid { background: url(data:image/png;base64,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) 0 0 #1c1c21; } + +.swagger-ui .b--black { border-color: #000; } + +.swagger-ui .b--near-black { border-color: #121212; } + +.swagger-ui .b--dark-gray { border-color: #333; } + +.swagger-ui .b--mid-gray { border-color: #545454; } + +.swagger-ui .b--gray { border-color: #787878; } + +.swagger-ui .b--silver { border-color: #999; } + +.swagger-ui .b--light-silver { border-color: #6e6e6e; } + +.swagger-ui .b--moon-gray { border-color: #4d4d4d; } + +.swagger-ui .b--light-gray { border-color: #2b2b2b; } + +.swagger-ui .b--near-white { border-color: #242424; } + +.swagger-ui .b--white { border-color: #1c1c21; } + +.swagger-ui .b--white-90 { border-color: rgba(28, 28, 33, .9); } + +.swagger-ui .b--white-80 { border-color: rgba(28, 28, 33, .8); } + +.swagger-ui .b--white-70 { border-color: rgba(28, 28, 33, .7); } + +.swagger-ui .b--white-60 { border-color: rgba(28, 28, 33, .6); } + +.swagger-ui .b--white-50 { border-color: rgba(28, 28, 33, .5); } + +.swagger-ui .b--white-40 { border-color: rgba(28, 28, 33, .4); } + +.swagger-ui .b--white-30 { border-color: rgba(28, 28, 33, .3); } + +.swagger-ui .b--white-20 { border-color: rgba(28, 28, 33, .2); } + +.swagger-ui .b--white-10 { border-color: rgba(28, 28, 33, .1); } + +.swagger-ui .b--white-05 { border-color: rgba(28, 28, 33, .05); } + +.swagger-ui .b--white-025 { border-color: rgba(28, 28, 33, .024); } + +.swagger-ui .b--white-0125 { border-color: rgba(28, 28, 33, .01); } + +.swagger-ui .b--black-90 { border-color: rgba(0, 0, 0, .9); } + +.swagger-ui .b--black-80 { border-color: rgba(0, 0, 0, .8); } + +.swagger-ui .b--black-70 { border-color: rgba(0, 0, 0, .7); } + +.swagger-ui .b--black-60 { border-color: rgba(0, 0, 0, .6); } + +.swagger-ui .b--black-50 { border-color: rgba(0, 0, 0, .5); } + +.swagger-ui .b--black-40 { border-color: rgba(0, 0, 0, .4); } + +.swagger-ui .b--black-30 { border-color: rgba(0, 0, 0, .3); } + +.swagger-ui .b--black-20 { border-color: rgba(0, 0, 0, .2); } + +.swagger-ui .b--black-10 { border-color: rgba(0, 0, 0, .1); } + +.swagger-ui .b--black-05 { border-color: rgba(0, 0, 0, .05); } + +.swagger-ui .b--black-025 { border-color: rgba(0, 0, 0, .024); } + +.swagger-ui .b--black-0125 { border-color: rgba(0, 0, 0, .01); } + +.swagger-ui .b--dark-red { border-color: #bc2f36; } + +.swagger-ui .b--red { border-color: #c83932; } + +.swagger-ui .b--light-red { border-color: #ab3c2b; } + +.swagger-ui .b--orange { border-color: #cc6e33; } + +.swagger-ui .b--purple { border-color: #5e2ca5; } + +.swagger-ui .b--light-purple { border-color: #672caf; } + +.swagger-ui .b--dark-pink { border-color: #ab2b81; } + +.swagger-ui .b--hot-pink { border-color: #c03086; } + +.swagger-ui .b--pink { border-color: #8f2464; } + +.swagger-ui .b--light-pink { border-color: #721d4d; } + +.swagger-ui .b--dark-green { border-color: #1c6e50; } + +.swagger-ui .b--green { border-color: #279b70; } + +.swagger-ui .b--light-green { border-color: #228762; } + +.swagger-ui .b--navy { border-color: #0d1d35; } + +.swagger-ui .b--dark-blue { border-color: #20497e; } + +.swagger-ui .b--blue { border-color: #4380d0; } + +.swagger-ui .b--light-blue { border-color: #20517e; } + +.swagger-ui .b--lightest-blue { border-color: #143a52; } + +.swagger-ui .b--washed-blue { border-color: #0c312d; } + +.swagger-ui .b--washed-green { border-color: #0f3d2c; } + +.swagger-ui .b--washed-red { border-color: #411010; } + +.swagger-ui .b--transparent { border-color: transparent; } + +.swagger-ui .b--gold, .swagger-ui .b--light-yellow, .swagger-ui .b--washed-yellow, .swagger-ui .b--yellow { border-color: #664b00; } + +.swagger-ui .shadow-1 { box-shadow: rgba(0, 0, 0, .2) 0 0 4px 2px; } + +.swagger-ui .shadow-2 { box-shadow: rgba(0, 0, 0, .2) 0 0 8px 2px; } + +.swagger-ui .shadow-3 { box-shadow: rgba(0, 0, 0, .2) 2px 2px 4px 2px; } + +.swagger-ui .shadow-4 { box-shadow: rgba(0, 0, 0, .2) 2px 2px 8px 0; } + +.swagger-ui .shadow-5 { box-shadow: rgba(0, 0, 0, .2) 4px 4px 8px 0; } + +@media screen and (min-width: 30em) { + .swagger-ui .shadow-1-ns { box-shadow: rgba(0, 0, 0, .2) 0 0 4px 2px; } + + .swagger-ui .shadow-2-ns { box-shadow: rgba(0, 0, 0, .2) 0 0 8px 2px; } + + .swagger-ui .shadow-3-ns { box-shadow: rgba(0, 0, 0, .2) 2px 2px 4px 2px; } + + .swagger-ui .shadow-4-ns { box-shadow: rgba(0, 0, 0, .2) 2px 2px 8px 0; } + + .swagger-ui .shadow-5-ns { box-shadow: rgba(0, 0, 0, .2) 4px 4px 8px 0; } +} + +@media screen and (max-width: 60em) and (min-width: 30em) { + .swagger-ui .shadow-1-m { box-shadow: rgba(0, 0, 0, .2) 0 0 4px 2px; } + + .swagger-ui .shadow-2-m { box-shadow: rgba(0, 0, 0, .2) 0 0 8px 2px; } + + .swagger-ui .shadow-3-m { box-shadow: rgba(0, 0, 0, .2) 2px 2px 4px 2px; } + + .swagger-ui .shadow-4-m { box-shadow: rgba(0, 0, 0, .2) 2px 2px 8px 0; } + + .swagger-ui .shadow-5-m { box-shadow: rgba(0, 0, 0, .2) 4px 4px 8px 0; } +} + +@media screen and (min-width: 60em) { + .swagger-ui .shadow-1-l { box-shadow: rgba(0, 0, 0, .2) 0 0 4px 2px; } + + .swagger-ui .shadow-2-l { box-shadow: rgba(0, 0, 0, .2) 0 0 8px 2px; } + + .swagger-ui .shadow-3-l { box-shadow: rgba(0, 0, 0, .2) 2px 2px 4px 2px; } + + .swagger-ui .shadow-4-l { box-shadow: rgba(0, 0, 0, .2) 2px 2px 8px 0; } + + .swagger-ui .shadow-5-l { box-shadow: rgba(0, 0, 0, .2) 4px 4px 8px 0; } +} + +.swagger-ui .black-05 { color: rgba(191, 191, 191, .05); } + +.swagger-ui .bg-black-05 { background-color: rgba(0, 0, 0, .05); } + +.swagger-ui .black-90, .swagger-ui .hover-black-90:focus, .swagger-ui .hover-black-90:hover { color: rgba(191, 191, 191, .9); } + +.swagger-ui .black-80, .swagger-ui .hover-black-80:focus, .swagger-ui .hover-black-80:hover { color: rgba(191, 191, 191, .8); } + +.swagger-ui .black-70, .swagger-ui .hover-black-70:focus, .swagger-ui .hover-black-70:hover { color: rgba(191, 191, 191, .7); } + +.swagger-ui .black-60, .swagger-ui .hover-black-60:focus, .swagger-ui .hover-black-60:hover { color: rgba(191, 191, 191, .6); } + +.swagger-ui .black-50, .swagger-ui .hover-black-50:focus, .swagger-ui .hover-black-50:hover { color: rgba(191, 191, 191, .5); } + +.swagger-ui .black-40, .swagger-ui .hover-black-40:focus, .swagger-ui .hover-black-40:hover { color: rgba(191, 191, 191, .4); } + +.swagger-ui .black-30, .swagger-ui .hover-black-30:focus, .swagger-ui .hover-black-30:hover { color: rgba(191, 191, 191, .3); } + +.swagger-ui .black-20, .swagger-ui .hover-black-20:focus, .swagger-ui .hover-black-20:hover { color: rgba(191, 191, 191, .2); } + +.swagger-ui .black-10, .swagger-ui .hover-black-10:focus, .swagger-ui .hover-black-10:hover { color: rgba(191, 191, 191, .1); } + +.swagger-ui .hover-white-90:focus, .swagger-ui .hover-white-90:hover, .swagger-ui .white-90 { color: rgba(255, 255, 255, .9); } + +.swagger-ui .hover-white-80:focus, .swagger-ui .hover-white-80:hover, .swagger-ui .white-80 { color: rgba(255, 255, 255, .8); } + +.swagger-ui .hover-white-70:focus, .swagger-ui .hover-white-70:hover, .swagger-ui .white-70 { color: rgba(255, 255, 255, .7); } + +.swagger-ui .hover-white-60:focus, .swagger-ui .hover-white-60:hover, .swagger-ui .white-60 { color: rgba(255, 255, 255, .6); } + +.swagger-ui .hover-white-50:focus, .swagger-ui .hover-white-50:hover, .swagger-ui .white-50 { color: rgba(255, 255, 255, .5); } + +.swagger-ui .hover-white-40:focus, .swagger-ui .hover-white-40:hover, .swagger-ui .white-40 { color: rgba(255, 255, 255, .4); } + +.swagger-ui .hover-white-30:focus, .swagger-ui .hover-white-30:hover, .swagger-ui .white-30 { color: rgba(255, 255, 255, .3); } + +.swagger-ui .hover-white-20:focus, .swagger-ui .hover-white-20:hover, .swagger-ui .white-20 { color: rgba(255, 255, 255, .2); } + +.swagger-ui .hover-white-10:focus, .swagger-ui .hover-white-10:hover, .swagger-ui .white-10 { color: rgba(255, 255, 255, .1); } + +.swagger-ui .hover-moon-gray:focus, .swagger-ui .hover-moon-gray:hover, .swagger-ui .moon-gray { color: #ccc; } + +.swagger-ui .hover-light-gray:focus, .swagger-ui .hover-light-gray:hover, .swagger-ui .light-gray { color: #ededed; } + +.swagger-ui .hover-near-white:focus, .swagger-ui .hover-near-white:hover, .swagger-ui .near-white { color: #f5f5f5; } + +.swagger-ui .dark-red, .swagger-ui .hover-dark-red:focus, .swagger-ui .hover-dark-red:hover { color: #e6999d; } + +.swagger-ui .hover-red:focus, .swagger-ui .hover-red:hover, .swagger-ui .red { color: #e69d99; } + +.swagger-ui .hover-light-red:focus, .swagger-ui .hover-light-red:hover, .swagger-ui .light-red { color: #e6a399; } + +.swagger-ui .hover-orange:focus, .swagger-ui .hover-orange:hover, .swagger-ui .orange { color: #e6b699; } + +.swagger-ui .gold, .swagger-ui .hover-gold:focus, .swagger-ui .hover-gold:hover { color: #e6d099; } + +.swagger-ui .hover-yellow:focus, .swagger-ui .hover-yellow:hover, .swagger-ui .yellow { color: #e6da99; } + +.swagger-ui .hover-light-yellow:focus, .swagger-ui .hover-light-yellow:hover, .swagger-ui .light-yellow { color: #ede6b6; } + +.swagger-ui .hover-purple:focus, .swagger-ui .hover-purple:hover, .swagger-ui .purple { color: #b99ae4; } + +.swagger-ui .hover-light-purple:focus, .swagger-ui .hover-light-purple:hover, .swagger-ui .light-purple { color: #bb99e6; } + +.swagger-ui .dark-pink, .swagger-ui .hover-dark-pink:focus, .swagger-ui .hover-dark-pink:hover { color: #e699cc; } + +.swagger-ui .hot-pink, .swagger-ui .hover-hot-pink:focus, .swagger-ui .hover-hot-pink:hover, .swagger-ui .hover-pink:focus, .swagger-ui .hover-pink:hover, .swagger-ui .pink { color: #e699c7; } + +.swagger-ui .hover-light-pink:focus, .swagger-ui .hover-light-pink:hover, .swagger-ui .light-pink { color: #edb6d5; } + +.swagger-ui .dark-green, .swagger-ui .green, .swagger-ui .hover-dark-green:focus, .swagger-ui .hover-dark-green:hover, .swagger-ui .hover-green:focus, .swagger-ui .hover-green:hover { color: #99e6c9; } + +.swagger-ui .hover-light-green:focus, .swagger-ui .hover-light-green:hover, .swagger-ui .light-green { color: #a1e8ce; } + +.swagger-ui .hover-navy:focus, .swagger-ui .hover-navy:hover, .swagger-ui .navy { color: #99b8e6; } + +.swagger-ui .blue, .swagger-ui .dark-blue, .swagger-ui .hover-blue:focus, .swagger-ui .hover-blue:hover, .swagger-ui .hover-dark-blue:focus, .swagger-ui .hover-dark-blue:hover { color: #99bae6; } + +.swagger-ui .hover-light-blue:focus, .swagger-ui .hover-light-blue:hover, .swagger-ui .light-blue { color: #a9cbea; } + +.swagger-ui .hover-lightest-blue:focus, .swagger-ui .hover-lightest-blue:hover, .swagger-ui .lightest-blue { color: #d6e9f5; } + +.swagger-ui .hover-washed-blue:focus, .swagger-ui .hover-washed-blue:hover, .swagger-ui .washed-blue { color: #f7fdfc; } + +.swagger-ui .hover-washed-green:focus, .swagger-ui .hover-washed-green:hover, .swagger-ui .washed-green { color: #ebfaf4; } + +.swagger-ui .hover-washed-yellow:focus, .swagger-ui .hover-washed-yellow:hover, .swagger-ui .washed-yellow { color: #fbf9ef; } + +.swagger-ui .hover-washed-red:focus, .swagger-ui .hover-washed-red:hover, .swagger-ui .washed-red { color: #f9e7e7; } + +.swagger-ui .color-inherit, .swagger-ui .hover-inherit:focus, .swagger-ui .hover-inherit:hover { color: inherit; } + +.swagger-ui .bg-black-90, .swagger-ui .hover-bg-black-90:focus, .swagger-ui .hover-bg-black-90:hover { background-color: rgba(0, 0, 0, .9); } + +.swagger-ui .bg-black-80, .swagger-ui .hover-bg-black-80:focus, .swagger-ui .hover-bg-black-80:hover { background-color: rgba(0, 0, 0, .8); } + +.swagger-ui .bg-black-70, .swagger-ui .hover-bg-black-70:focus, .swagger-ui .hover-bg-black-70:hover { background-color: rgba(0, 0, 0, .7); } + +.swagger-ui .bg-black-60, .swagger-ui .hover-bg-black-60:focus, .swagger-ui .hover-bg-black-60:hover { background-color: rgba(0, 0, 0, .6); } + +.swagger-ui .bg-black-50, .swagger-ui .hover-bg-black-50:focus, .swagger-ui .hover-bg-black-50:hover { background-color: rgba(0, 0, 0, .5); } + +.swagger-ui .bg-black-40, .swagger-ui .hover-bg-black-40:focus, .swagger-ui .hover-bg-black-40:hover { background-color: rgba(0, 0, 0, .4); } + +.swagger-ui .bg-black-30, .swagger-ui .hover-bg-black-30:focus, .swagger-ui .hover-bg-black-30:hover { background-color: rgba(0, 0, 0, .3); } + +.swagger-ui .bg-black-20, .swagger-ui .hover-bg-black-20:focus, .swagger-ui .hover-bg-black-20:hover { background-color: rgba(0, 0, 0, .2); } + +.swagger-ui .bg-white-90, .swagger-ui .hover-bg-white-90:focus, .swagger-ui .hover-bg-white-90:hover { background-color: rgba(28, 28, 33, .9); } + +.swagger-ui .bg-white-80, .swagger-ui .hover-bg-white-80:focus, .swagger-ui .hover-bg-white-80:hover { background-color: rgba(28, 28, 33, .8); } + +.swagger-ui .bg-white-70, .swagger-ui .hover-bg-white-70:focus, .swagger-ui .hover-bg-white-70:hover { background-color: rgba(28, 28, 33, .7); } + +.swagger-ui .bg-white-60, .swagger-ui .hover-bg-white-60:focus, .swagger-ui .hover-bg-white-60:hover { background-color: rgba(28, 28, 33, .6); } + +.swagger-ui .bg-white-50, .swagger-ui .hover-bg-white-50:focus, .swagger-ui .hover-bg-white-50:hover { background-color: rgba(28, 28, 33, .5); } + +.swagger-ui .bg-white-40, .swagger-ui .hover-bg-white-40:focus, .swagger-ui .hover-bg-white-40:hover { background-color: rgba(28, 28, 33, .4); } + +.swagger-ui .bg-white-30, .swagger-ui .hover-bg-white-30:focus, .swagger-ui .hover-bg-white-30:hover { background-color: rgba(28, 28, 33, .3); } + +.swagger-ui .bg-white-20, .swagger-ui .hover-bg-white-20:focus, .swagger-ui .hover-bg-white-20:hover { background-color: rgba(28, 28, 33, .2); } + +.swagger-ui .bg-black, .swagger-ui .hover-bg-black:focus, .swagger-ui .hover-bg-black:hover { background-color: #000; } + +.swagger-ui .bg-near-black, .swagger-ui .hover-bg-near-black:focus, .swagger-ui .hover-bg-near-black:hover { background-color: #121212; } + +.swagger-ui .bg-dark-gray, .swagger-ui .hover-bg-dark-gray:focus, .swagger-ui .hover-bg-dark-gray:hover { background-color: #333; } + +.swagger-ui .bg-mid-gray, .swagger-ui .hover-bg-mid-gray:focus, .swagger-ui .hover-bg-mid-gray:hover { background-color: #545454; } + +.swagger-ui .bg-gray, .swagger-ui .hover-bg-gray:focus, .swagger-ui .hover-bg-gray:hover { background-color: #787878; } + +.swagger-ui .bg-silver, .swagger-ui .hover-bg-silver:focus, .swagger-ui .hover-bg-silver:hover { background-color: #999; } + +.swagger-ui .bg-white, .swagger-ui .hover-bg-white:focus, .swagger-ui .hover-bg-white:hover { background-color: #1c1c21; } + +.swagger-ui .bg-transparent, .swagger-ui .hover-bg-transparent:focus, .swagger-ui .hover-bg-transparent:hover { background-color: transparent; } + +.swagger-ui .bg-dark-red, .swagger-ui .hover-bg-dark-red:focus, .swagger-ui .hover-bg-dark-red:hover { background-color: #bc2f36; } + +.swagger-ui .bg-red, .swagger-ui .hover-bg-red:focus, .swagger-ui .hover-bg-red:hover { background-color: #c83932; } + +.swagger-ui .bg-light-red, .swagger-ui .hover-bg-light-red:focus, .swagger-ui .hover-bg-light-red:hover { background-color: #ab3c2b; } + +.swagger-ui .bg-orange, .swagger-ui .hover-bg-orange:focus, .swagger-ui .hover-bg-orange:hover { background-color: #cc6e33; } + +.swagger-ui .bg-gold, .swagger-ui .bg-light-yellow, .swagger-ui .bg-washed-yellow, .swagger-ui .bg-yellow, .swagger-ui .hover-bg-gold:focus, .swagger-ui .hover-bg-gold:hover, .swagger-ui .hover-bg-light-yellow:focus, .swagger-ui .hover-bg-light-yellow:hover, .swagger-ui .hover-bg-washed-yellow:focus, .swagger-ui .hover-bg-washed-yellow:hover, .swagger-ui .hover-bg-yellow:focus, .swagger-ui .hover-bg-yellow:hover { background-color: #664b00; } + +.swagger-ui .bg-purple, .swagger-ui .hover-bg-purple:focus, .swagger-ui .hover-bg-purple:hover { background-color: #5e2ca5; } + +.swagger-ui .bg-light-purple, .swagger-ui .hover-bg-light-purple:focus, .swagger-ui .hover-bg-light-purple:hover { background-color: #672caf; } + +.swagger-ui .bg-dark-pink, .swagger-ui .hover-bg-dark-pink:focus, .swagger-ui .hover-bg-dark-pink:hover { background-color: #ab2b81; } + +.swagger-ui .bg-hot-pink, .swagger-ui .hover-bg-hot-pink:focus, .swagger-ui .hover-bg-hot-pink:hover { background-color: #c03086; } + +.swagger-ui .bg-pink, .swagger-ui .hover-bg-pink:focus, .swagger-ui .hover-bg-pink:hover { background-color: #8f2464; } + +.swagger-ui .bg-light-pink, .swagger-ui .hover-bg-light-pink:focus, .swagger-ui .hover-bg-light-pink:hover { background-color: #721d4d; } + +.swagger-ui .bg-dark-green, .swagger-ui .hover-bg-dark-green:focus, .swagger-ui .hover-bg-dark-green:hover { background-color: #1c6e50; } + +.swagger-ui .bg-green, .swagger-ui .hover-bg-green:focus, .swagger-ui .hover-bg-green:hover { background-color: #279b70; } + +.swagger-ui .bg-light-green, .swagger-ui .hover-bg-light-green:focus, .swagger-ui .hover-bg-light-green:hover { background-color: #228762; } + +.swagger-ui .bg-navy, .swagger-ui .hover-bg-navy:focus, .swagger-ui .hover-bg-navy:hover { background-color: #0d1d35; } + +.swagger-ui .bg-dark-blue, .swagger-ui .hover-bg-dark-blue:focus, .swagger-ui .hover-bg-dark-blue:hover { background-color: #20497e; } + +.swagger-ui .bg-blue, .swagger-ui .hover-bg-blue:focus, .swagger-ui .hover-bg-blue:hover { background-color: #4380d0; } + +.swagger-ui .bg-light-blue, .swagger-ui .hover-bg-light-blue:focus, .swagger-ui .hover-bg-light-blue:hover { background-color: #20517e; } + +.swagger-ui .bg-lightest-blue, .swagger-ui .hover-bg-lightest-blue:focus, .swagger-ui .hover-bg-lightest-blue:hover { background-color: #143a52; } + +.swagger-ui .bg-washed-blue, .swagger-ui .hover-bg-washed-blue:focus, .swagger-ui .hover-bg-washed-blue:hover { background-color: #0c312d; } + +.swagger-ui .bg-washed-green, .swagger-ui .hover-bg-washed-green:focus, .swagger-ui .hover-bg-washed-green:hover { background-color: #0f3d2c; } + +.swagger-ui .bg-washed-red, .swagger-ui .hover-bg-washed-red:focus, .swagger-ui .hover-bg-washed-red:hover { background-color: #411010; } + +.swagger-ui .bg-inherit, .swagger-ui .hover-bg-inherit:focus, .swagger-ui .hover-bg-inherit:hover { background-color: inherit; } + +.swagger-ui .shadow-hover { transition: all .5s cubic-bezier(.165, .84, .44, 1) 0s; } + +.swagger-ui .shadow-hover::after { + border-radius: inherit; + box-shadow: rgba(0, 0, 0, .2) 0 0 16px 2px; + content: ""; + height: 100%; + left: 0; + opacity: 0; + position: absolute; + top: 0; + transition: opacity .5s cubic-bezier(.165, .84, .44, 1) 0s; + width: 100%; + z-index: -1; +} + +.swagger-ui .bg-animate, .swagger-ui .bg-animate:focus, .swagger-ui .bg-animate:hover { transition: background-color .15s ease-in-out 0s; } + +.swagger-ui .nested-links a { + color: #99bae6; + transition: color .15s ease-in 0s; +} + +.swagger-ui .nested-links a:focus, .swagger-ui .nested-links a:hover { + color: #a9cbea; + transition: color .15s ease-in 0s; +} + +.swagger-ui .opblock-tag { + border-bottom: 1px solid rgba(58, 64, 80, .3); + color: #b5bac9; + transition: all .2s ease 0s; +} + +.swagger-ui .opblock-tag svg, .swagger-ui section.models h4 svg { transition: all .4s ease 0s; } + +.swagger-ui .opblock { + border: 1px solid #000; + border-radius: 4px; + box-shadow: rgba(0, 0, 0, .19) 0 0 3px; + margin: 0 0 15px; +} + +.swagger-ui .opblock .tab-header .tab-item.active h4 span::after { background: gray; } + +.swagger-ui .opblock.is-open .opblock-summary { border-bottom: 1px solid #000; } + +.swagger-ui .opblock .opblock-section-header { + background: rgba(28, 28, 33, .8); + box-shadow: rgba(0, 0, 0, .1) 0 1px 2px; +} + +.swagger-ui .opblock .opblock-section-header > label > span { padding: 0 10px 0 0; } + +.swagger-ui .opblock .opblock-summary-method { + background: #000; + color: #fff; + text-shadow: rgba(0, 0, 0, .1) 0 1px 0; +} + +.swagger-ui .opblock.opblock-post { + background: rgba(72, 203, 144, .1); + border-color: #48cb90; +} + +.swagger-ui .opblock.opblock-post .opblock-summary-method, .swagger-ui .opblock.opblock-post .tab-header .tab-item.active h4 span::after { background: #48cb90; } + +.swagger-ui .opblock.opblock-post .opblock-summary { border-color: #48cb90; } + +.swagger-ui .opblock.opblock-put { + background: rgba(213, 157, 88, .1); + border-color: #d59d58; +} + +.swagger-ui .opblock.opblock-put .opblock-summary-method, .swagger-ui .opblock.opblock-put .tab-header .tab-item.active h4 span::after { background: #d59d58; } + +.swagger-ui .opblock.opblock-put .opblock-summary { border-color: #d59d58; } + +.swagger-ui .opblock.opblock-delete { + background: rgba(200, 50, 50, .1); + border-color: #c83232; +} + +.swagger-ui .opblock.opblock-delete .opblock-summary-method, .swagger-ui .opblock.opblock-delete .tab-header .tab-item.active h4 span::after { background: #c83232; } + +.swagger-ui .opblock.opblock-delete .opblock-summary { border-color: #c83232; } + +.swagger-ui .opblock.opblock-get { + background: rgba(42, 105, 167, .1); + border-color: #2a69a7; +} + +.swagger-ui .opblock.opblock-get .opblock-summary-method, .swagger-ui .opblock.opblock-get .tab-header .tab-item.active h4 span::after { background: #2a69a7; } + +.swagger-ui .opblock.opblock-get .opblock-summary { border-color: #2a69a7; } + +.swagger-ui .opblock.opblock-patch { + background: rgba(92, 214, 188, .1); + border-color: #5cd6bc; +} + +.swagger-ui .opblock.opblock-patch .opblock-summary-method, .swagger-ui .opblock.opblock-patch .tab-header .tab-item.active h4 span::after { background: #5cd6bc; } + +.swagger-ui .opblock.opblock-patch .opblock-summary { border-color: #5cd6bc; } + +.swagger-ui .opblock.opblock-head { + background: rgba(140, 63, 207, .1); + border-color: #8c3fcf; +} + +.swagger-ui .opblock.opblock-head .opblock-summary-method, .swagger-ui .opblock.opblock-head .tab-header .tab-item.active h4 span::after { background: #8c3fcf; } + +.swagger-ui .opblock.opblock-head .opblock-summary { border-color: #8c3fcf; } + +.swagger-ui .opblock.opblock-options { + background: rgba(36, 89, 143, .1); + border-color: #24598f; +} + +.swagger-ui .opblock.opblock-options .opblock-summary-method, .swagger-ui .opblock.opblock-options .tab-header .tab-item.active h4 span::after { background: #24598f; } + +.swagger-ui .opblock.opblock-options .opblock-summary { border-color: #24598f; } + +.swagger-ui .opblock.opblock-deprecated { + background: rgba(46, 46, 46, .1); + border-color: #2e2e2e; + opacity: .6; +} + +.swagger-ui .opblock.opblock-deprecated .opblock-summary-method, .swagger-ui .opblock.opblock-deprecated .tab-header .tab-item.active h4 span::after { background: #2e2e2e; } + +.swagger-ui .opblock.opblock-deprecated .opblock-summary { border-color: #2e2e2e; } + +.swagger-ui .filter .operation-filter-input { border: 2px solid #2b3446; } + +.swagger-ui .tab li:first-of-type::after { background: rgba(0, 0, 0, .2); } + +.swagger-ui .download-contents { + background: #7c8192; + color: #fff; +} + +.swagger-ui .scheme-container { + background: #1c1c21; + box-shadow: rgba(0, 0, 0, .15) 0 1px 2px 0; +} + +.swagger-ui .loading-container .loading::before { + animation: 1s linear 0s infinite normal none running rotation, .5s ease 0s 1 normal none running opacity; + border-color: rgba(0, 0, 0, .6) rgba(84, 84, 84, .1) rgba(84, 84, 84, .1); +} + +.swagger-ui .response-control-media-type--accept-controller select { border-color: #196619; } + +.swagger-ui .response-control-media-type__accept-message { color: #99e699; } + +.swagger-ui .version-pragma__message code { background-color: #3b3b3b; } + +.swagger-ui .btn { + background: 0 0; + border: 2px solid gray; + box-shadow: rgba(0, 0, 0, .1) 0 1px 2px; + color: #b5bac9; +} + +.swagger-ui .btn:hover { box-shadow: rgba(0, 0, 0, .3) 0 0 5px; } + +.swagger-ui .btn.authorize, .swagger-ui .btn.cancel { + background-color: transparent; + border-color: #a72a2a; + color: #e69999; +} + +.swagger-ui .btn.authorize { + border-color: #48cb90; + color: #9ce3c3; +} + +.swagger-ui .btn.authorize svg { fill: #9ce3c3; } + +.swagger-ui .btn.execute { + background-color: #5892d5; + border-color: #5892d5; + color: #fff; +} + +.swagger-ui .copy-to-clipboard { background: #7c8192; } + +.swagger-ui .copy-to-clipboard button { background: url("data:image/svg+xml;charset=utf-8,") 50% center no-repeat; } + +.swagger-ui select { + background: url("data:image/svg+xml;charset=utf-8,") right 10px center/20px no-repeat #212121; + background: url(data:image/svg+xml;base64,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) right 10px center/20px no-repeat #1c1c21; + border: 2px solid #41444e; +} + +.swagger-ui select[multiple] { background: #212121; } + +.swagger-ui button.invalid, .swagger-ui input[type=email].invalid, .swagger-ui input[type=file].invalid, .swagger-ui input[type=password].invalid, .swagger-ui input[type=search].invalid, .swagger-ui input[type=text].invalid, .swagger-ui select.invalid, .swagger-ui textarea.invalid { + background: #390e0e; + border-color: #c83232; +} + +.swagger-ui input[type=email], .swagger-ui input[type=file], .swagger-ui input[type=password], .swagger-ui input[type=search], .swagger-ui input[type=text], .swagger-ui textarea { + background: #1c1c21; + border: 1px solid #404040; +} + +.swagger-ui textarea { + background: rgba(28, 28, 33, .8); + color: #b5bac9; +} + +.swagger-ui input[disabled], .swagger-ui select[disabled] { + background-color: #1f1f1f; + color: #bfbfbf; +} + +.swagger-ui textarea[disabled] { + background-color: #41444e; + color: #fff; +} + +.swagger-ui select[disabled] { border-color: #878787; } + +.swagger-ui textarea:focus { border: 2px solid #2a69a7; } + +.swagger-ui .checkbox input[type=checkbox] + label > .item { + background: #303030; + box-shadow: #303030 0 0 0 2px; +} + +.swagger-ui .checkbox input[type=checkbox]:checked + label > .item { background: url("data:image/svg+xml;charset=utf-8,") 50% center no-repeat #303030; } + +.swagger-ui .dialog-ux .backdrop-ux { background: rgba(0, 0, 0, .8); } + +.swagger-ui .dialog-ux .modal-ux { + background: #1c1c21; + border: 1px solid #2e2e2e; + box-shadow: rgba(0, 0, 0, .2) 0 10px 30px 0; +} + +.swagger-ui .dialog-ux .modal-ux-header .close-modal { background: 0 0; } + +.swagger-ui .model .deprecated span, .swagger-ui .model .deprecated td { color: #bfbfbf !important; } + +.swagger-ui .model-toggle::after { background: url("data:image/svg+xml;charset=utf-8,") 50% center/100% no-repeat; } + +.swagger-ui .model-hint { + background: rgba(0, 0, 0, .7); + color: #ebebeb; +} + +.swagger-ui section.models { border: 1px solid rgba(58, 64, 80, .3); } + +.swagger-ui section.models.is-open h4 { border-bottom: 1px solid rgba(58, 64, 80, .3); } + +.swagger-ui section.models .model-container { background: rgba(0, 0, 0, .05); } + +.swagger-ui section.models .model-container:hover { background: rgba(0, 0, 0, .07); } + +.swagger-ui .model-box { background: rgba(0, 0, 0, .1); } + +.swagger-ui .prop-type { color: #aaaad4; } + +.swagger-ui table thead tr td, .swagger-ui table thead tr th { + border-bottom: 1px solid rgba(58, 64, 80, .2); + color: #b5bac9; +} + +.swagger-ui .parameter__name.required::after { color: rgba(230, 153, 153, .6); } + +.swagger-ui .topbar .download-url-wrapper .select-label { color: #f0f0f0; } + +.swagger-ui .topbar .download-url-wrapper .download-url-button { + background: #63a040; + color: #fff; +} + +.swagger-ui .info .title small { background: #7c8492; } + +.swagger-ui .info .title small.version-stamp { background-color: #7a9b27; } + +.swagger-ui .auth-container .errors { + background-color: #350d0d; + color: #b5bac9; +} + +.swagger-ui .errors-wrapper { + background: rgba(200, 50, 50, .1); + border: 2px solid #c83232; +} + +.swagger-ui .markdown code, .swagger-ui .renderedmarkdown code { + background: rgba(0, 0, 0, .05); + color: #c299e6; +} + +.swagger-ui .model-toggle:after { background: url(data:image/svg+xml;base64,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) 50% no-repeat; } + +.swagger-ui .expand-operation svg, .swagger-ui section.models h4 svg { fill: #fff; } + +::-webkit-scrollbar-track { background-color: #646464 !important; } + +::-webkit-scrollbar-thumb { + background-color: #242424 !important; + border: 2px solid #3e4346 !important; +} + +::-webkit-scrollbar-button:vertical:start:decrement { + background: linear-gradient(130deg, #696969 40%, rgba(255, 0, 0, 0) 41%), linear-gradient(230deg, #696969 40%, transparent 41%), linear-gradient(0deg, #696969 40%, transparent 31%); + background-color: #b6b6b6; +} + +::-webkit-scrollbar-button:vertical:end:increment { + background: linear-gradient(310deg, #696969 40%, transparent 41%), linear-gradient(50deg, #696969 40%, transparent 41%), linear-gradient(180deg, #696969 40%, transparent 31%); + background-color: #b6b6b6; +} + +::-webkit-scrollbar-button:horizontal:end:increment { + background: linear-gradient(210deg, #696969 40%, transparent 41%), linear-gradient(330deg, #696969 40%, transparent 41%), linear-gradient(90deg, #696969 30%, transparent 31%); + background-color: #b6b6b6; +} + +::-webkit-scrollbar-button:horizontal:start:decrement { + background: linear-gradient(30deg, #696969 40%, transparent 41%), linear-gradient(150deg, #696969 40%, transparent 41%), linear-gradient(270deg, #696969 30%, transparent 31%); + background-color: #b6b6b6; +} + +::-webkit-scrollbar-button, ::-webkit-scrollbar-track-piece { background-color: #3e4346 !important; } + +.swagger-ui .black, .swagger-ui .checkbox, .swagger-ui .dark-gray, .swagger-ui .download-url-wrapper .loading, .swagger-ui .errors-wrapper .errors small, .swagger-ui .fallback, .swagger-ui .filter .loading, .swagger-ui .gray, .swagger-ui .hover-black:focus, .swagger-ui .hover-black:hover, .swagger-ui .hover-dark-gray:focus, .swagger-ui .hover-dark-gray:hover, .swagger-ui .hover-gray:focus, .swagger-ui .hover-gray:hover, .swagger-ui .hover-light-silver:focus, .swagger-ui .hover-light-silver:hover, .swagger-ui .hover-mid-gray:focus, .swagger-ui .hover-mid-gray:hover, .swagger-ui .hover-near-black:focus, .swagger-ui .hover-near-black:hover, .swagger-ui .hover-silver:focus, .swagger-ui .hover-silver:hover, .swagger-ui .light-silver, .swagger-ui .markdown pre, .swagger-ui .mid-gray, .swagger-ui .model .property, .swagger-ui .model .property.primitive, .swagger-ui .model-title, .swagger-ui .near-black, .swagger-ui .parameter__extension, .swagger-ui .parameter__in, .swagger-ui .prop-format, .swagger-ui .renderedmarkdown pre, .swagger-ui .response-col_links .response-undocumented, .swagger-ui .response-col_status .response-undocumented, .swagger-ui .silver, .swagger-ui section.models h4, .swagger-ui section.models h5, .swagger-ui span.token-not-formatted, .swagger-ui span.token-string, .swagger-ui table.headers .header-example, .swagger-ui table.model tr.description, .swagger-ui table.model tr.extension { color: #bfbfbf; } + +.swagger-ui .hover-white:focus, .swagger-ui .hover-white:hover, .swagger-ui .info .title small pre, .swagger-ui .topbar a, .swagger-ui .white { color: #fff; } + +.swagger-ui .bg-black-10, .swagger-ui .hover-bg-black-10:focus, .swagger-ui .hover-bg-black-10:hover, .swagger-ui .stripe-dark:nth-child(2n + 1) { background-color: rgba(0, 0, 0, .1); } + +.swagger-ui .bg-white-10, .swagger-ui .hover-bg-white-10:focus, .swagger-ui .hover-bg-white-10:hover, .swagger-ui .stripe-light:nth-child(2n + 1) { background-color: rgba(28, 28, 33, .1); } + +.swagger-ui .bg-light-silver, .swagger-ui .hover-bg-light-silver:focus, .swagger-ui .hover-bg-light-silver:hover, .swagger-ui .striped--light-silver:nth-child(2n + 1) { background-color: #6e6e6e; } + +.swagger-ui .bg-moon-gray, .swagger-ui .hover-bg-moon-gray:focus, .swagger-ui .hover-bg-moon-gray:hover, .swagger-ui .striped--moon-gray:nth-child(2n + 1) { background-color: #4d4d4d; } + +.swagger-ui .bg-light-gray, .swagger-ui .hover-bg-light-gray:focus, .swagger-ui .hover-bg-light-gray:hover, .swagger-ui .striped--light-gray:nth-child(2n + 1) { background-color: #2b2b2b; } + +.swagger-ui .bg-near-white, .swagger-ui .hover-bg-near-white:focus, .swagger-ui .hover-bg-near-white:hover, .swagger-ui .striped--near-white:nth-child(2n + 1) { background-color: #242424; } + +.swagger-ui .opblock-tag:hover, .swagger-ui section.models h4:hover { background: rgba(0, 0, 0, .02); } + +.swagger-ui .checkbox p, .swagger-ui .dialog-ux .modal-ux-content h4, .swagger-ui .dialog-ux .modal-ux-content p, .swagger-ui .dialog-ux .modal-ux-header h3, .swagger-ui .errors-wrapper .errors h4, .swagger-ui .errors-wrapper hgroup h4, .swagger-ui .info .base-url, .swagger-ui .info .title, .swagger-ui .info h1, .swagger-ui .info h2, .swagger-ui .info h3, .swagger-ui .info h4, .swagger-ui .info h5, .swagger-ui .info li, .swagger-ui .info p, .swagger-ui .info table, .swagger-ui .loading-container .loading::after, .swagger-ui .model, .swagger-ui .opblock .opblock-section-header h4, .swagger-ui .opblock .opblock-section-header > label, .swagger-ui .opblock .opblock-summary-description, .swagger-ui .opblock .opblock-summary-operation-id, .swagger-ui .opblock .opblock-summary-path, .swagger-ui .opblock .opblock-summary-path__deprecated, .swagger-ui .opblock-description-wrapper, .swagger-ui .opblock-description-wrapper h4, .swagger-ui .opblock-description-wrapper p, .swagger-ui .opblock-external-docs-wrapper, .swagger-ui .opblock-external-docs-wrapper h4, .swagger-ui .opblock-external-docs-wrapper p, .swagger-ui .opblock-tag small, .swagger-ui .opblock-title_normal, .swagger-ui .opblock-title_normal h4, .swagger-ui .opblock-title_normal p, .swagger-ui .parameter__name, .swagger-ui .parameter__type, .swagger-ui .response-col_links, .swagger-ui .response-col_status, .swagger-ui .responses-inner h4, .swagger-ui .responses-inner h5, .swagger-ui .scheme-container .schemes > label, .swagger-ui .scopes h2, .swagger-ui .servers > label, .swagger-ui .tab li, .swagger-ui label, .swagger-ui select, .swagger-ui table.headers td { color: #b5bac9; } + +.swagger-ui .download-url-wrapper .failed, .swagger-ui .filter .failed, .swagger-ui .model-deprecated-warning, .swagger-ui .parameter__deprecated, .swagger-ui .parameter__name.required span, .swagger-ui table.model tr.property-row .star { color: #e69999; } + +.swagger-ui .opblock-body pre.microlight, .swagger-ui textarea.curl { + background: #41444e; + border-radius: 4px; + color: #fff; +} + +.swagger-ui .expand-methods svg, .swagger-ui .expand-methods:hover svg { fill: #bfbfbf; } + +.swagger-ui .auth-container, .swagger-ui .dialog-ux .modal-ux-header { border-bottom: 1px solid #2e2e2e; } + +.swagger-ui .topbar .download-url-wrapper .select-label select, .swagger-ui .topbar .download-url-wrapper input[type=text] { border: 2px solid #63a040; } + +.swagger-ui .info a, .swagger-ui .info a:hover, .swagger-ui .scopes h2 a { color: #99bde6; } + +/* Dark Scrollbar */ +::-webkit-scrollbar { + width: 14px; + height: 14px; +} + +::-webkit-scrollbar-button { + background-color: #3e4346 !important; +} + +::-webkit-scrollbar-track { + background-color: #646464 !important; +} + +::-webkit-scrollbar-track-piece { + background-color: #3e4346 !important; +} + +::-webkit-scrollbar-thumb { + height: 50px; + background-color: #242424 !important; + border: 2px solid #3e4346 !important; +} + +::-webkit-scrollbar-corner {} + +::-webkit-resizer {} + +::-webkit-scrollbar-button:vertical:start:decrement { + background: + linear-gradient(130deg, #696969 40%, rgba(255, 0, 0, 0) 41%), + linear-gradient(230deg, #696969 40%, rgba(0, 0, 0, 0) 41%), + linear-gradient(0deg, #696969 40%, rgba(0, 0, 0, 0) 31%); + background-color: #b6b6b6; +} + +::-webkit-scrollbar-button:vertical:end:increment { + background: + linear-gradient(310deg, #696969 40%, rgba(0, 0, 0, 0) 41%), + linear-gradient(50deg, #696969 40%, rgba(0, 0, 0, 0) 41%), + linear-gradient(180deg, #696969 40%, rgba(0, 0, 0, 0) 31%); + background-color: #b6b6b6; +} + +::-webkit-scrollbar-button:horizontal:end:increment { + background: + linear-gradient(210deg, #696969 40%, rgba(0, 0, 0, 0) 41%), + linear-gradient(330deg, #696969 40%, rgba(0, 0, 0, 0) 41%), + linear-gradient(90deg, #696969 30%, rgba(0, 0, 0, 0) 31%); + background-color: #b6b6b6; +} + +::-webkit-scrollbar-button:horizontal:start:decrement { + background: + linear-gradient(30deg, #696969 40%, rgba(0, 0, 0, 0) 41%), + linear-gradient(150deg, #696969 40%, rgba(0, 0, 0, 0) 41%), + linear-gradient(270deg, #696969 30%, rgba(0, 0, 0, 0) 31%); + background-color: #b6b6b6; +} diff --git a/static/swagger-ui/index.css b/static/swagger-ui/index.css new file mode 100644 index 00000000..0aa7e9be --- /dev/null +++ b/static/swagger-ui/index.css @@ -0,0 +1,17 @@ +/*! Swagger UI 4.13.2 | https://swagger.io/tools/swagger-ui/ | Apache License 2.0 (license file can be found at ./LICENSE) */ +html { + box-sizing: border-box; + overflow: -moz-scrollbars-vertical; + overflow-y: scroll; +} + +*, +*:before, +*:after { + box-sizing: inherit; +} + +body { + margin: 0; + background: #fafafa; +} diff --git a/static/swagger-ui/oauth2-redirect.html b/static/swagger-ui/oauth2-redirect.html new file mode 100644 index 00000000..9a25c9e8 --- /dev/null +++ b/static/swagger-ui/oauth2-redirect.html @@ -0,0 +1,79 @@ + + + + Swagger UI: OAuth2 Redirect + + + + + diff --git a/static/swagger-ui/swagger-ui-bundle.js b/static/swagger-ui/swagger-ui-bundle.js new file mode 100644 index 00000000..0f5ced83 --- /dev/null +++ b/static/swagger-ui/swagger-ui-bundle.js @@ -0,0 +1,2 @@ +/*! 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+ + +

...

 @@ -156,7 +158,7 @@
-
+
@@ -169,7 +171,7 @@
Author's Note
-
+
@@ -210,7 +212,7 @@