diff --git a/aiserver.py b/aiserver.py index 4805736b..48c94976 100644 --- a/aiserver.py +++ b/aiserver.py @@ -38,6 +38,7 @@ import bisect import functools import traceback from collections.abc import Iterable +from collections import OrderedDict from typing import Any, Callable, TypeVar, Tuple, Union, Dict, Set, List import requests @@ -2167,21 +2168,44 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal #Let's load the presets with open('settings/preset/official.presets') as f: presets = json.load(f) - to_use = {"Recommended": {"Default": koboldai_vars.default_preset}} - #Check for 6B in title - if '6B' in koboldai_vars.model or '6.7B' in koboldai_vars.model or '1.3B' in koboldai_vars.model: - to_use['Recommended'].update(presets['6B']) - for key in presets: - if key != '6B': - to_use[key] = presets[key] - elif '13B' in koboldai_vars.model: - to_use['Recommended'].update(presets['13B']) - for key in presets: - if key != '13B': - to_use[key] = presets[key] - else: - for key in presets: - to_use[key] = presets[key] + koboldai_vars.uid_presets = {x['uid']: x for x in presets} + #We want our data to be a 2 deep dict. Top level is "Recommended", "Same Class", "Model 1", "Model 2", etc + #Next layer is "Official", "Custom" + #Then the preset name + + to_use = OrderedDict() + + to_use["Recommended"] = {"Official": [], "Custom": []} + to_use["Same Class"] = {"Official": [], "Custom": []} + used_ids = [] + #Build recommended first: + for preset in presets: + if preset['Model Type'] == koboldai_vars.model and preset['uid'] not in used_ids: + if preset['Model Category'] == 'Custom': + to_use['Recommended']['Custom'].append(preset) + else: + to_use['Recommended']['Official'].append(preset) + used_ids.append(preset['uid']) + #Build Same Class + for preset in presets: + if preset['Model Size'] == koboldai_vars.model and preset['uid'] not in used_ids: + if preset['Model Category'] == 'Custom': + to_use['Recommended']['Custom'].append(preset) + else: + to_use['Recommended']['Official'].append(preset) + used_ids.append(preset['uid']) + #Build the rest of the stuff + for preset in presets: + if preset['uid'] not in used_ids: + used_ids.append(preset['uid']) + if preset['Model Type'] not in to_use: + to_use[preset['Model Type']] = {"Official": [], "Custom": []} + + if preset['Model Category'] == 'Custom': + to_use[preset['Model Type']]['Custom'].append(preset) + else: + to_use[preset['Model Type']]['Official'].append(preset) + koboldai_vars.presets = to_use # Set up Flask routes @@ -6150,6 +6174,8 @@ def get_files_folders(starting_folder): #==================================================================# @socketio.on('var_change') def UI_2_var_change(data): + if 'value' not in data: + return classname = data['ID'].split("_")[0] name = data['ID'][len(classname)+1:] classname += "_settings" diff --git a/convert_xls_to_json_presets.py b/convert_xls_to_json_presets.py new file mode 100644 index 00000000..cd322873 --- /dev/null +++ b/convert_xls_to_json_presets.py @@ -0,0 +1,60 @@ +import pandas as pd +import sys + +output = [] +sheet_mapper = {"KAI-ADAPTED 13B": "13B", "KAI-ADAPTED 6B": "6B", 'KAI-CUSTOM': 'Custom'} + +for file in ['KoboldAI Settings (6B).xlsx', 'KoboldAI Settings (13B).xlsx', 'KoboldAI Settings (Custom).xlsx', 'KoboldAI Settings (Original).xlsx']: + presets = pd.read_excel("preset Files/{}".format(file), None) + for sheet in presets: + df = presets[sheet] + if sheet in sheet_mapper: + sheet = sheet_mapper[sheet] + df = df.dropna(axis=1, how='all') + df = df.rename(columns={"Unnamed: 0": "setting"}) + df = pd.melt(df, id_vars=['setting']) + df = df.rename(columns={"variable": "preset"}) + df['fix'] = df['value'].str.replace(" (KAI)", "", regex=False) + df.loc[~df['fix'].isnull(), 'value'] = df['fix'] + df = df.drop(columns=['fix']) + df.loc[df['setting']=='Samplers Order', 'value'] = df['value'].str.replace("Temp", "5", regex=False) + df.loc[df['setting']=='Samplers Order', 'value'] = df['value'].str.replace("K", "0", regex=False) + df.loc[df['setting']=='Samplers Order', 'value'] = df['value'].str.replace("TFS", "3", regex=False) + df.loc[df['setting']=='Samplers Order', 'value'] = df['value'].str.replace("A", "1", regex=False) + df.loc[df['setting']=='Samplers Order', 'value'] = df['value'].str.replace("Typ", "4", regex=False) + df.loc[df['setting']=='Samplers Order', 'value'] = df['value'].str.replace("P", "2", regex=False) + + + settings_mapper = {'Temperature': 'temp', 'Output Length': 'genamt', 'Repetition Penalty': 'rep_pen', + 'Top P': 'top_p', 'Top K': 'top_k', 'Tail-Free': 'tfs', 'Repetition Penalty Range': 'rep_pen_range', + 'Repetition Penalty Slope': 'rep_pen_slope', 'Typical': 'typical', 'Top A': 'top_a', + 'Samplers Order': 'sampler_order', 'Description of settings from the author': 'description', + 'Author': 'Author', 'Model Type': 'Model Type', + 'Description of settings from NovelAI': 'description', 'Model Size': "Model Size" + } + df['setting'] = df['setting'].map(settings_mapper) + + try: + df = df.pivot(index='preset', columns='setting', values='value') + except: + print(file) + display(df) + raise + + df['Model Type'] = df['Model Type'].str.replace(", ", ",").str.split(",") + + df.loc[:, 'Model Category'] = sheet + + output.append(df) + + #output[sheet] = df.to_json(orient="index") + +df = pd.concat(output) +df = df.reset_index(drop=False) +df['uid'] = df.index +df = df.explode("Model Type") +df['description'] = df['description'].str.strip() + + +with open("official.presets", "w") as f: + f.write(df.reset_index(drop=True).to_json(orient='records')) \ No newline at end of file diff --git a/koboldai_settings.py b/koboldai_settings.py index a74bbf05..4df7d038 100644 --- a/koboldai_settings.py +++ b/koboldai_settings.py @@ -109,6 +109,7 @@ class koboldai_vars(object): if name[0] == "_": super().__setattr__(name, value) if name[0] != "_": + #Send it to the corrent _setting class if name in self._model_settings.__dict__: setattr(self._model_settings, name, value) elif name in self._user_settings.__dict__: @@ -241,6 +242,7 @@ class model_settings(settings): self.revision = None self.presets = [] # Holder for presets self.selected_preset = "" + self.uid_presets = [] self.default_preset = {} #dummy class to eat the tqdm output @@ -254,8 +256,22 @@ class model_settings(settings): super().__setattr__(name, value) #Put variable change actions here + #set preset values + if name == 'selected_preset' and value != "": + if int(value) in self.uid_presets: + for preset_key, preset_value in self.uid_presets[int(value)].items(): + if preset_key in self.__dict__: + if type(getattr(self, preset_key)) == int: + preset_value = int(preset_value) + elif type(getattr(self, preset_key)) == float: + preset_value = float(preset_value) + elif type(getattr(self, preset_key)) == bool: + preset_value = bool(preset_value) + elif type(getattr(self, preset_key)) == str: + preset_value = str(preset_value) + setattr(self, preset_key, preset_value) #Setup TQDP for token generation - if name == "generated_tkns" and 'tqdm' in self.__dict__: + elif name == "generated_tkns" and 'tqdm' in self.__dict__: if value == 0: self.tqdm.reset(total=self.genamt) self.tqdm_progress = 0 diff --git a/settings/preset/official.presets b/settings/preset/official.presets index 482ef581..4de04d8b 100644 --- a/settings/preset/official.presets +++ b/settings/preset/official.presets @@ -1,8 +1 @@ -{ -"6B": - {"Best Guess":{"description":"\nA subtle change with alternative context settings.","genamt":40,"rep_pen":"1.2","rep_pen_range":512,"rep_pen_slope":"3.33","sampler_order":["5","0","2","3","1","4"],"temp":"0.8","tfs":1,"top_a":0,"top_k":"100","top_p":"0.9","typical":1},"Coherent Creativity":{"description":"A good balance between coherence, creativity, and quality of prose.","genamt":40,"rep_pen":"1.2","rep_pen_range":2048,"rep_pen_slope":0,"sampler_order":["5","0","2","3","1","4"],"temp":"0.51","tfs":"0.9","top_a":0,"top_k":0,"top_p":1,"typical":1},"Emperor Moth":{"description":"\nMedium randomness with a decent bit of creative writing.","genamt":40,"rep_pen":"1.15","rep_pen_range":2048,"rep_pen_slope":0,"sampler_order":["5","0","2","3","1","4"],"temp":"1.25","tfs":1,"top_a":0,"top_k":0,"top_p":"0.235","typical":1},"Luna Moth":{"description":"\nA great degree of creativity without losing coherency.","genamt":40,"rep_pen":"1.15","rep_pen_range":2048,"rep_pen_slope":0,"sampler_order":["5","0","2","3","1","4"],"temp":2,"tfs":1,"top_a":0,"top_k":85,"top_p":"0.235","typical":1},"Pleasing Results":{"description":"Expectable output with alternative context settings.","genamt":40,"rep_pen":"1.2","rep_pen_range":1024,"rep_pen_slope":"6.75","sampler_order":["5","0","2","3","1","4"],"temp":"0.44","tfs":"0.9","top_a":0,"top_k":0,"top_p":1,"typical":1},"Sphinx Moth":{"description":"Maximum randomness while still being plot relevant. 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b/static/koboldai.css index 94f162c3..b8628049 100644 --- a/static/koboldai.css +++ b/static/koboldai.css @@ -325,6 +325,10 @@ margin-right: 25px; } +.preset_item { + color: white; /*#2b2a33;*/ +} + .menubar1, .menubar2, .menubar3 { width: 21px; height: 3px; diff --git a/static/koboldai.js b/static/koboldai.js index 1a8c29a9..a83f004d 100644 --- a/static/koboldai.js +++ b/static/koboldai.js @@ -291,45 +291,29 @@ function do_presets(data) { option.text="presets"; select.append(option); presets = data.value; + + for (const [key, value] of Object.entries(data.value)) { var option_group = document.createElement("optgroup"); option_group.label = key; - for (const [preset, preset_value] of Object.entries(value)) { + for (const [group, group_value] of Object.entries(value)) { var option = document.createElement("option"); - option.value=key+"|"+preset; - option.text=preset; - option.title = preset_value.description; + option.text=group; + option.disabled = true; + option.classList.add("preset_group"); option_group.append(option); + for (const [preset, preset_value] of Object.entries(group_value)) { + var option = document.createElement("option"); + option.value=preset; + option.text=preset_value.preset; + option.title = preset_value.description; + option_group.append(option); + } } select.append(option_group); } } -function selected_preset(data) { - - preset_key = data.value.split("|")[0]; - preset = data.value.split("|")[1]; - if ((data.value == undefined) || (presets[preset_key] == undefined)) { - return; - } - if (presets[preset_key][preset] == undefined) { - return; - } - for (const [key, value] of Object.entries(presets[preset_key][preset])) { - if (key.charAt(0) != '_') { - var elements_to_change = document.getElementsByClassName("var_sync_model_"+key); - for (item of elements_to_change) { - if (item.tagName.toLowerCase() === 'input') { - item.value = value; - } else { - item.textContent = fix_text(value); - } - } - } - } - socket.emit("var_change", {"ID": "model_selected_preset", "value": data.value}); -} - function update_status_bar(data) { var percent_complete = data.value; var percent_bar = document.getElementsByClassName("statusbar_inner"); @@ -378,8 +362,6 @@ function var_changed(data) { //Special Case for Presets } else if ((data.classname == 'model') && (data.name == 'presets')) { do_presets(data); - } else if ((data.classname == "model") && (data.name == "selected_preset")) { - selected_preset(data); } else if ((data.classname == 'story') && (data.name == 'prompt')) { do_prompt(data); //Basic Data Syncing @@ -1259,7 +1241,7 @@ function sync_to_server(item) { //get value value = null; name = null; - if ((item.tagName.toLowerCase() === 'input') || (item.tagName.toLowerCase() === 'select') || (item.tagName.toLowerCase() == 'textarea')) { + if ((item.tagName.toLowerCase() === 'checkbox') || (item.tagName.toLowerCase() === 'input') || (item.tagName.toLowerCase() === 'select') || (item.tagName.toLowerCase() == 'textarea')) { if (item.getAttribute("type") == "checkbox") { value = item.checked; } else { diff --git a/templates/settings flyout.html b/templates/settings flyout.html index f747805d..d2b7247e 100644 --- a/templates/settings flyout.html +++ b/templates/settings flyout.html @@ -37,7 +37,7 @@
Running Model: ReadOnly - +