SillyTavern/public/scripts/tokenizers.js

1127 lines
36 KiB
JavaScript

import { characters, main_api, api_server, nai_settings, online_status, this_chid } from '../script.js';
import { power_user, registerDebugFunction } from './power-user.js';
import { chat_completion_sources, model_list, oai_settings } from './openai.js';
import { groups, selected_group } from './group-chats.js';
import { getStringHash } from './utils.js';
import { kai_flags } from './kai-settings.js';
import { textgen_types, textgenerationwebui_settings as textgen_settings, getTextGenServer, getTextGenModel } from './textgen-settings.js';
import { getCurrentDreamGenModelTokenizer, getCurrentOpenRouterModelTokenizer, openRouterModels } from './textgen-models.js';
const { OOBA, TABBY, KOBOLDCPP, VLLM, APHRODITE, LLAMACPP, OPENROUTER, DREAMGEN } = textgen_types;
export const CHARACTERS_PER_TOKEN_RATIO = 3.35;
export const TOKENIZER_WARNING_KEY = 'tokenizationWarningShown';
export const TOKENIZER_SUPPORTED_KEY = 'tokenizationSupported';
export const tokenizers = {
NONE: 0,
GPT2: 1,
OPENAI: 2,
LLAMA: 3,
NERD: 4,
NERD2: 5,
API_CURRENT: 6,
MISTRAL: 7,
YI: 8,
API_TEXTGENERATIONWEBUI: 9,
API_KOBOLD: 10,
CLAUDE: 11,
LLAMA3: 12,
GEMMA: 13,
JAMBA: 14,
QWEN2: 15,
COMMAND_R: 16,
NEMO: 17,
BEST_MATCH: 99,
};
// A list of local tokenizers that support encoding and decoding token ids.
export const ENCODE_TOKENIZERS = [
tokenizers.LLAMA,
tokenizers.MISTRAL,
tokenizers.YI,
tokenizers.LLAMA3,
tokenizers.GEMMA,
tokenizers.JAMBA,
tokenizers.QWEN2,
tokenizers.COMMAND_R,
tokenizers.NEMO,
// uncomment when NovelAI releases Kayra and Clio weights, lol
//tokenizers.NERD,
//tokenizers.NERD2,
];
// A list of Text Completion sources that support remote tokenization.
export const TEXTGEN_TOKENIZERS = [OOBA, TABBY, KOBOLDCPP, LLAMACPP, VLLM, APHRODITE];
const TOKENIZER_URLS = {
[tokenizers.GPT2]: {
encode: '/api/tokenizers/gpt2/encode',
decode: '/api/tokenizers/gpt2/decode',
count: '/api/tokenizers/gpt2/encode',
},
[tokenizers.OPENAI]: {
encode: '/api/tokenizers/openai/encode',
decode: '/api/tokenizers/openai/decode',
count: '/api/tokenizers/openai/encode',
},
[tokenizers.LLAMA]: {
encode: '/api/tokenizers/llama/encode',
decode: '/api/tokenizers/llama/decode',
count: '/api/tokenizers/llama/encode',
},
[tokenizers.NERD]: {
encode: '/api/tokenizers/nerdstash/encode',
decode: '/api/tokenizers/nerdstash/decode',
count: '/api/tokenizers/nerdstash/encode',
},
[tokenizers.NERD2]: {
encode: '/api/tokenizers/nerdstash_v2/encode',
decode: '/api/tokenizers/nerdstash_v2/decode',
count: '/api/tokenizers/nerdstash_v2/encode',
},
[tokenizers.API_KOBOLD]: {
count: '/api/tokenizers/remote/kobold/count',
encode: '/api/tokenizers/remote/kobold/count',
},
[tokenizers.MISTRAL]: {
encode: '/api/tokenizers/mistral/encode',
decode: '/api/tokenizers/mistral/decode',
count: '/api/tokenizers/mistral/encode',
},
[tokenizers.YI]: {
encode: '/api/tokenizers/yi/encode',
decode: '/api/tokenizers/yi/decode',
count: '/api/tokenizers/yi/encode',
},
[tokenizers.CLAUDE]: {
encode: '/api/tokenizers/claude/encode',
decode: '/api/tokenizers/claude/decode',
count: '/api/tokenizers/claude/encode',
},
[tokenizers.LLAMA3]: {
encode: '/api/tokenizers/llama3/encode',
decode: '/api/tokenizers/llama3/decode',
count: '/api/tokenizers/llama3/encode',
},
[tokenizers.GEMMA]: {
encode: '/api/tokenizers/gemma/encode',
decode: '/api/tokenizers/gemma/decode',
count: '/api/tokenizers/gemma/encode',
},
[tokenizers.JAMBA]: {
encode: '/api/tokenizers/jamba/encode',
decode: '/api/tokenizers/jamba/decode',
count: '/api/tokenizers/jamba/encode',
},
[tokenizers.QWEN2]: {
encode: '/api/tokenizers/qwen2/encode',
decode: '/api/tokenizers/qwen2/decode',
count: '/api/tokenizers/qwen2/encode',
},
[tokenizers.COMMAND_R]: {
encode: '/api/tokenizers/command-r/encode',
decode: '/api/tokenizers/command-r/decode',
count: '/api/tokenizers/command-r/encode',
},
[tokenizers.NEMO]: {
encode: '/api/tokenizers/nemo/encode',
decode: '/api/tokenizers/nemo/decode',
count: '/api/tokenizers/nemo/encode',
},
[tokenizers.API_TEXTGENERATIONWEBUI]: {
encode: '/api/tokenizers/remote/textgenerationwebui/encode',
count: '/api/tokenizers/remote/textgenerationwebui/encode',
},
};
const objectStore = new localforage.createInstance({ name: 'SillyTavern_ChatCompletions' });
let tokenCache = {};
/**
* Guesstimates the token count for a string.
* @param {string} str String to tokenize.
* @returns {number} Token count.
*/
export function guesstimate(str) {
return Math.ceil(str.length / CHARACTERS_PER_TOKEN_RATIO);
}
async function loadTokenCache() {
try {
console.debug('Chat Completions: loading token cache');
tokenCache = await objectStore.getItem('tokenCache') || {};
} catch (e) {
console.log('Chat Completions: unable to load token cache, using default value', e);
tokenCache = {};
}
}
export async function saveTokenCache() {
try {
console.debug('Chat Completions: saving token cache');
await objectStore.setItem('tokenCache', tokenCache);
} catch (e) {
console.log('Chat Completions: unable to save token cache', e);
}
}
async function resetTokenCache() {
try {
console.debug('Chat Completions: resetting token cache');
Object.keys(tokenCache).forEach(key => delete tokenCache[key]);
await objectStore.removeItem('tokenCache');
toastr.success('Token cache cleared. Please reload the chat to re-tokenize it.');
} catch (e) {
console.log('Chat Completions: unable to reset token cache', e);
}
}
/**
* @typedef {object} Tokenizer
* @property {number} tokenizerId - The id of the tokenizer option
* @property {string} tokenizerKey - Internal name/key of the tokenizer
* @property {string} tokenizerName - Human-readable detailed name of the tokenizer (as displayed in the UI)
*/
/**
* Gets all tokenizers available to the user.
* @returns {Tokenizer[]} Tokenizer info.
*/
export function getAvailableTokenizers() {
const tokenizerOptions = $('#tokenizer').find('option').toArray();
return tokenizerOptions.map(tokenizerOption => ({
tokenizerId: Number(tokenizerOption.value),
tokenizerKey: Object.entries(tokenizers).find(([_, value]) => value === Number(tokenizerOption.value))[0].toLocaleLowerCase(),
tokenizerName: tokenizerOption.text,
}));
}
/**
* Selects tokenizer if not already selected.
* @param {number} tokenizerId Tokenizer ID.
*/
export function selectTokenizer(tokenizerId) {
if (tokenizerId !== power_user.tokenizer) {
const tokenizer = getAvailableTokenizers().find(tokenizer => tokenizer.tokenizerId === tokenizerId);
if (!tokenizer) {
console.warn('Failed to find tokenizer with id', tokenizerId);
return;
}
$('#tokenizer').val(tokenizer.tokenizerId).trigger('change');
toastr.info(`Tokenizer: "${tokenizer.tokenizerName}" selected`);
}
}
/**
* Gets the friendly name of the current tokenizer.
* @param {string} forApi API to get the tokenizer for. Defaults to the main API.
* @returns {Tokenizer} Tokenizer info
*/
export function getFriendlyTokenizerName(forApi) {
if (!forApi) {
forApi = main_api;
}
const tokenizerOption = $('#tokenizer').find(':selected');
let tokenizerId = Number(tokenizerOption.val());
let tokenizerName = tokenizerOption.text();
if (forApi !== 'openai' && tokenizerId === tokenizers.BEST_MATCH) {
tokenizerId = getTokenizerBestMatch(forApi);
switch (tokenizerId) {
case tokenizers.API_KOBOLD:
tokenizerName = 'API (KoboldAI Classic)';
break;
case tokenizers.API_TEXTGENERATIONWEBUI:
tokenizerName = 'API (Text Completion)';
break;
default:
tokenizerName = $(`#tokenizer option[value="${tokenizerId}"]`).text();
break;
}
}
tokenizerName = forApi == 'openai'
? getTokenizerModel()
: tokenizerName;
tokenizerId = forApi == 'openai'
? tokenizers.OPENAI
: tokenizerId;
const tokenizerKey = Object.entries(tokenizers).find(([_, value]) => value === tokenizerId)[0].toLocaleLowerCase();
return { tokenizerName, tokenizerKey, tokenizerId };
}
/**
* Gets the best tokenizer for the current API.
* @param {string} forApi API to get the tokenizer for. Defaults to the main API.
* @returns {number} Tokenizer type.
*/
export function getTokenizerBestMatch(forApi) {
if (!forApi) {
forApi = main_api;
}
if (forApi === 'novel') {
if (nai_settings.model_novel.includes('clio')) {
return tokenizers.NERD;
}
if (nai_settings.model_novel.includes('kayra')) {
return tokenizers.NERD2;
}
if (nai_settings.model_novel.includes('erato')) {
return tokenizers.LLAMA3;
}
}
if (forApi === 'kobold' || forApi === 'textgenerationwebui' || forApi === 'koboldhorde') {
// Try to use the API tokenizer if possible:
// - API must be connected
// - Kobold must pass a version check
// - Tokenizer haven't reported an error previously
const hasTokenizerError = sessionStorage.getItem(TOKENIZER_WARNING_KEY);
const hasValidEndpoint = sessionStorage.getItem(TOKENIZER_SUPPORTED_KEY);
const isConnected = online_status !== 'no_connection';
const isTokenizerSupported = TEXTGEN_TOKENIZERS.includes(textgen_settings.type) && (textgen_settings.type !== OOBA || hasValidEndpoint);
if (!hasTokenizerError && isConnected) {
if (forApi === 'kobold' && kai_flags.can_use_tokenization) {
return tokenizers.API_KOBOLD;
}
if (forApi === 'textgenerationwebui' && isTokenizerSupported) {
return tokenizers.API_TEXTGENERATIONWEBUI;
}
if (forApi === 'textgenerationwebui' && textgen_settings.type === OPENROUTER) {
return getCurrentOpenRouterModelTokenizer();
}
if (forApi === 'textgenerationwebui' && textgen_settings.type === DREAMGEN) {
return getCurrentDreamGenModelTokenizer();
}
}
if (forApi === 'textgenerationwebui') {
const model = String(getTextGenModel() || online_status).toLowerCase();
if (model.includes('llama3') || model.includes('llama-3')) {
return tokenizers.LLAMA3;
}
if (model.includes('mistral') || model.includes('mixtral')) {
return tokenizers.MISTRAL;
}
if (model.includes('gemma')) {
return tokenizers.GEMMA;
}
if (model.includes('yi')) {
return tokenizers.YI;
}
if (model.includes('jamba')) {
return tokenizers.JAMBA;
}
if (model.includes('command-r')) {
return tokenizers.COMMAND_R;
}
if (model.includes('qwen2')) {
return tokenizers.QWEN2;
}
}
return tokenizers.LLAMA;
}
return tokenizers.NONE;
}
// Get the current remote tokenizer API based on the current text generation API.
function currentRemoteTokenizerAPI() {
switch (main_api) {
case 'kobold':
return tokenizers.API_KOBOLD;
case 'textgenerationwebui':
return tokenizers.API_TEXTGENERATIONWEBUI;
default:
return tokenizers.NONE;
}
}
/**
* Calls the underlying tokenizer model to the token count for a string.
* @param {number} type Tokenizer type.
* @param {string} str String to tokenize.
* @returns {number} Token count.
*/
function callTokenizer(type, str) {
if (type === tokenizers.NONE) return guesstimate(str);
switch (type) {
case tokenizers.API_CURRENT:
return callTokenizer(currentRemoteTokenizerAPI(), str);
case tokenizers.API_KOBOLD:
return countTokensFromKoboldAPI(str);
case tokenizers.API_TEXTGENERATIONWEBUI:
return countTokensFromTextgenAPI(str);
default: {
const endpointUrl = TOKENIZER_URLS[type]?.count;
if (!endpointUrl) {
console.warn('Unknown tokenizer type', type);
return apiFailureTokenCount(str);
}
return countTokensFromServer(endpointUrl, str);
}
}
}
/**
* Calls the underlying tokenizer model to the token count for a string.
* @param {number} type Tokenizer type.
* @param {string} str String to tokenize.
* @returns {Promise<number>} Token count.
*/
function callTokenizerAsync(type, str) {
return new Promise(resolve => {
if (type === tokenizers.NONE) {
return resolve(guesstimate(str));
}
switch (type) {
case tokenizers.API_CURRENT:
return callTokenizerAsync(currentRemoteTokenizerAPI(), str).then(resolve);
case tokenizers.API_KOBOLD:
return countTokensFromKoboldAPI(str, resolve);
case tokenizers.API_TEXTGENERATIONWEBUI:
return countTokensFromTextgenAPI(str, resolve);
default: {
const endpointUrl = TOKENIZER_URLS[type]?.count;
if (!endpointUrl) {
console.warn('Unknown tokenizer type', type);
return resolve(apiFailureTokenCount(str));
}
return countTokensFromServer(endpointUrl, str, resolve);
}
}
});
}
/**
* Gets the token count for a string using the current model tokenizer.
* @param {string} str String to tokenize
* @param {number | undefined} padding Optional padding tokens. Defaults to 0.
* @returns {Promise<number>} Token count.
*/
export async function getTokenCountAsync(str, padding = undefined) {
if (typeof str !== 'string' || !str?.length) {
return 0;
}
let tokenizerType = power_user.tokenizer;
if (main_api === 'openai') {
if (padding === power_user.token_padding) {
// For main "shadow" prompt building
tokenizerType = tokenizers.NONE;
} else {
// For extensions and WI
return counterWrapperOpenAIAsync(str);
}
}
if (tokenizerType === tokenizers.BEST_MATCH) {
tokenizerType = getTokenizerBestMatch(main_api);
}
if (padding === undefined) {
padding = 0;
}
const cacheObject = getTokenCacheObject();
const hash = getStringHash(str);
const cacheKey = `${tokenizerType}-${hash}+${padding}`;
if (typeof cacheObject[cacheKey] === 'number') {
return cacheObject[cacheKey];
}
const result = (await callTokenizerAsync(tokenizerType, str)) + padding;
if (isNaN(result)) {
console.warn('Token count calculation returned NaN');
return 0;
}
cacheObject[cacheKey] = result;
return result;
}
/**
* Gets the token count for a string using the current model tokenizer.
* @param {string} str String to tokenize
* @param {number | undefined} padding Optional padding tokens. Defaults to 0.
* @returns {number} Token count.
* @deprecated Use getTokenCountAsync instead.
*/
export function getTokenCount(str, padding = undefined) {
if (typeof str !== 'string' || !str?.length) {
return 0;
}
let tokenizerType = power_user.tokenizer;
if (main_api === 'openai') {
if (padding === power_user.token_padding) {
// For main "shadow" prompt building
tokenizerType = tokenizers.NONE;
} else {
// For extensions and WI
return counterWrapperOpenAI(str);
}
}
if (tokenizerType === tokenizers.BEST_MATCH) {
tokenizerType = getTokenizerBestMatch(main_api);
}
if (padding === undefined) {
padding = 0;
}
const cacheObject = getTokenCacheObject();
const hash = getStringHash(str);
const cacheKey = `${tokenizerType}-${hash}+${padding}`;
if (typeof cacheObject[cacheKey] === 'number') {
return cacheObject[cacheKey];
}
const result = callTokenizer(tokenizerType, str) + padding;
if (isNaN(result)) {
console.warn('Token count calculation returned NaN');
return 0;
}
cacheObject[cacheKey] = result;
return result;
}
/**
* Gets the token count for a string using the OpenAI tokenizer.
* @param {string} text Text to tokenize.
* @returns {number} Token count.
* @deprecated Use counterWrapperOpenAIAsync instead.
*/
function counterWrapperOpenAI(text) {
const message = { role: 'system', content: text };
return countTokensOpenAI(message, true);
}
/**
* Gets the token count for a string using the OpenAI tokenizer.
* @param {string} text Text to tokenize.
* @returns {Promise<number>} Token count.
*/
function counterWrapperOpenAIAsync(text) {
const message = { role: 'system', content: text };
return countTokensOpenAIAsync(message, true);
}
export function getTokenizerModel() {
// OpenAI models always provide their own tokenizer
if (oai_settings.chat_completion_source == chat_completion_sources.OPENAI) {
return oai_settings.openai_model;
}
const turbo0301Tokenizer = 'gpt-3.5-turbo-0301';
const turboTokenizer = 'gpt-3.5-turbo';
const gpt4Tokenizer = 'gpt-4';
const gpt4oTokenizer = 'gpt-4o';
const gpt2Tokenizer = 'gpt2';
const claudeTokenizer = 'claude';
const llamaTokenizer = 'llama';
const llama3Tokenizer = 'llama3';
const mistralTokenizer = 'mistral';
const yiTokenizer = 'yi';
const gemmaTokenizer = 'gemma';
const jambaTokenizer = 'jamba';
const qwen2Tokenizer = 'qwen2';
const commandRTokenizer = 'command-r';
const nemoTokenizer = 'nemo';
// Assuming no one would use it for different models.. right?
if (oai_settings.chat_completion_source == chat_completion_sources.SCALE) {
return gpt4Tokenizer;
}
// Select correct tokenizer for WindowAI proxies
if (oai_settings.chat_completion_source == chat_completion_sources.WINDOWAI && oai_settings.windowai_model) {
if (oai_settings.windowai_model.includes('gpt-4')) {
return gpt4Tokenizer;
}
else if (oai_settings.windowai_model.includes('gpt-3.5-turbo-0301')) {
return turbo0301Tokenizer;
}
else if (oai_settings.windowai_model.includes('gpt-3.5-turbo')) {
return turboTokenizer;
}
else if (oai_settings.windowai_model.includes('claude')) {
return claudeTokenizer;
}
else if (oai_settings.windowai_model.includes('GPT-NeoXT')) {
return gpt2Tokenizer;
}
}
// And for OpenRouter (if not a site model, then it's impossible to determine the tokenizer)
if (main_api == 'openai' && oai_settings.chat_completion_source == chat_completion_sources.OPENROUTER && oai_settings.openrouter_model ||
main_api == 'textgenerationwebui' && textgen_settings.type === OPENROUTER && textgen_settings.openrouter_model) {
const model = main_api == 'openai'
? model_list.find(x => x.id === oai_settings.openrouter_model)
: openRouterModels.find(x => x.id === textgen_settings.openrouter_model);
if (model?.architecture?.tokenizer === 'Llama2') {
return llamaTokenizer;
}
else if (model?.architecture?.tokenizer === 'Llama3') {
return llama3Tokenizer;
}
else if (model?.architecture?.tokenizer === 'Mistral') {
return mistralTokenizer;
}
else if (model?.architecture?.tokenizer === 'Yi') {
return yiTokenizer;
}
else if (model?.architecture?.tokenizer === 'Gemini') {
return gemmaTokenizer;
}
else if (model?.architecture?.tokenizer === 'Qwen') {
return qwen2Tokenizer;
}
else if (model?.architecture?.tokenizer === 'Cohere') {
return commandRTokenizer;
}
else if (oai_settings.openrouter_model.includes('gpt-4o')) {
return gpt4oTokenizer;
}
else if (oai_settings.openrouter_model.includes('gpt-4')) {
return gpt4Tokenizer;
}
else if (oai_settings.openrouter_model.includes('gpt-3.5-turbo-0301')) {
return turbo0301Tokenizer;
}
else if (oai_settings.openrouter_model.includes('gpt-3.5-turbo')) {
return turboTokenizer;
}
else if (oai_settings.openrouter_model.includes('claude')) {
return claudeTokenizer;
}
else if (oai_settings.openrouter_model.includes('GPT-NeoXT')) {
return gpt2Tokenizer;
}
else if (oai_settings.openrouter_model.includes('jamba')) {
return jambaTokenizer;
}
}
if (oai_settings.chat_completion_source == chat_completion_sources.COHERE) {
return commandRTokenizer;
}
if (oai_settings.chat_completion_source == chat_completion_sources.MAKERSUITE) {
return gemmaTokenizer;
}
if (oai_settings.chat_completion_source == chat_completion_sources.AI21) {
return jambaTokenizer;
}
if (oai_settings.chat_completion_source == chat_completion_sources.CLAUDE) {
return claudeTokenizer;
}
if (oai_settings.chat_completion_source == chat_completion_sources.MISTRALAI) {
if (oai_settings.mistralai_model.includes('nemo') || oai_settings.mistralai_model.includes('pixtral')) {
return nemoTokenizer;
}
return mistralTokenizer;
}
if (oai_settings.chat_completion_source == chat_completion_sources.CUSTOM) {
return oai_settings.custom_model;
}
if (oai_settings.chat_completion_source === chat_completion_sources.PERPLEXITY) {
if (oai_settings.perplexity_model.includes('llama-3') || oai_settings.perplexity_model.includes('llama3')) {
return llama3Tokenizer;
}
if (oai_settings.perplexity_model.includes('llama')) {
return llamaTokenizer;
}
if (oai_settings.perplexity_model.includes('mistral') || oai_settings.perplexity_model.includes('mixtral')) {
return mistralTokenizer;
}
}
if (oai_settings.chat_completion_source === chat_completion_sources.GROQ) {
if (oai_settings.groq_model.includes('llama-3') || oai_settings.groq_model.includes('llama3')) {
return llama3Tokenizer;
}
if (oai_settings.groq_model.includes('mistral') || oai_settings.groq_model.includes('mixtral')) {
return mistralTokenizer;
}
if (oai_settings.groq_model.includes('gemma')) {
return gemmaTokenizer;
}
}
if (oai_settings.chat_completion_source === chat_completion_sources.ZEROONEAI) {
return yiTokenizer;
}
if (oai_settings.chat_completion_source === chat_completion_sources.BLOCKENTROPY) {
if (oai_settings.blockentropy_model.includes('llama3')) {
return llama3Tokenizer;
}
if (oai_settings.blockentropy_model.includes('miqu') || oai_settings.blockentropy_model.includes('mixtral')) {
return mistralTokenizer;
}
}
// Default to Turbo 3.5
return turboTokenizer;
}
/**
* @param {any[] | Object} messages
* @deprecated Use countTokensOpenAIAsync instead.
*/
export function countTokensOpenAI(messages, full = false) {
const tokenizerEndpoint = `/api/tokenizers/openai/count?model=${getTokenizerModel()}`;
const cacheObject = getTokenCacheObject();
if (!Array.isArray(messages)) {
messages = [messages];
}
let token_count = -1;
for (const message of messages) {
const model = getTokenizerModel();
if (model === 'claude') {
full = true;
}
const hash = getStringHash(JSON.stringify(message));
const cacheKey = `${model}-${hash}`;
const cachedCount = cacheObject[cacheKey];
if (typeof cachedCount === 'number') {
token_count += cachedCount;
}
else {
jQuery.ajax({
async: false,
type: 'POST', //
url: tokenizerEndpoint,
data: JSON.stringify([message]),
dataType: 'json',
contentType: 'application/json',
success: function (data) {
token_count += Number(data.token_count);
cacheObject[cacheKey] = Number(data.token_count);
},
});
}
}
if (!full) token_count -= 2;
return token_count;
}
/**
* Returns the token count for a message using the OpenAI tokenizer.
* @param {object[]|object} messages
* @param {boolean} full
* @returns {Promise<number>} Token count.
*/
export async function countTokensOpenAIAsync(messages, full = false) {
const tokenizerEndpoint = `/api/tokenizers/openai/count?model=${getTokenizerModel()}`;
const cacheObject = getTokenCacheObject();
if (!Array.isArray(messages)) {
messages = [messages];
}
let token_count = -1;
for (const message of messages) {
const model = getTokenizerModel();
if (model === 'claude') {
full = true;
}
const hash = getStringHash(JSON.stringify(message));
const cacheKey = `${model}-${hash}`;
const cachedCount = cacheObject[cacheKey];
if (typeof cachedCount === 'number') {
token_count += cachedCount;
}
else {
const data = await jQuery.ajax({
async: true,
type: 'POST', //
url: tokenizerEndpoint,
data: JSON.stringify([message]),
dataType: 'json',
contentType: 'application/json',
});
token_count += Number(data.token_count);
cacheObject[cacheKey] = Number(data.token_count);
}
}
if (!full) token_count -= 2;
return token_count;
}
/**
* Gets the token cache object for the current chat.
* @returns {Object} Token cache object for the current chat.
*/
function getTokenCacheObject() {
let chatId = 'undefined';
try {
if (selected_group) {
chatId = groups.find(x => x.id == selected_group)?.chat_id;
}
else if (this_chid !== undefined) {
chatId = characters[this_chid].chat;
}
} catch {
console.log('No character / group selected. Using default cache item');
}
if (typeof tokenCache[chatId] !== 'object') {
tokenCache[chatId] = {};
}
return tokenCache[String(chatId)];
}
/**
* Count tokens using the server API.
* @param {string} endpoint API endpoint.
* @param {string} str String to tokenize.
* @param {function} [resolve] Promise resolve function.s
* @returns {number} Token count.
*/
function countTokensFromServer(endpoint, str, resolve) {
const isAsync = typeof resolve === 'function';
let tokenCount = 0;
jQuery.ajax({
async: isAsync,
type: 'POST',
url: endpoint,
data: JSON.stringify({ text: str }),
dataType: 'json',
contentType: 'application/json',
success: function (data) {
if (typeof data.count === 'number') {
tokenCount = data.count;
} else {
tokenCount = apiFailureTokenCount(str);
}
isAsync && resolve(tokenCount);
},
});
return tokenCount;
}
/**
* Count tokens using the AI provider's API.
* @param {string} str String to tokenize.
* @param {function} [resolve] Promise resolve function.
* @returns {number} Token count.
*/
function countTokensFromKoboldAPI(str, resolve) {
const isAsync = typeof resolve === 'function';
let tokenCount = 0;
jQuery.ajax({
async: isAsync,
type: 'POST',
url: TOKENIZER_URLS[tokenizers.API_KOBOLD].count,
data: JSON.stringify({
text: str,
url: api_server,
}),
dataType: 'json',
contentType: 'application/json',
success: function (data) {
if (typeof data.count === 'number') {
tokenCount = data.count;
} else {
tokenCount = apiFailureTokenCount(str);
}
isAsync && resolve(tokenCount);
},
});
return tokenCount;
}
function getTextgenAPITokenizationParams(str) {
return {
text: str,
api_type: textgen_settings.type,
url: getTextGenServer(),
legacy_api: textgen_settings.legacy_api && textgen_settings.type === OOBA,
vllm_model: textgen_settings.vllm_model,
aphrodite_model: textgen_settings.aphrodite_model,
};
}
/**
* Count tokens using the AI provider's API.
* @param {string} str String to tokenize.
* @param {function} [resolve] Promise resolve function.
* @returns {number} Token count.
*/
function countTokensFromTextgenAPI(str, resolve) {
const isAsync = typeof resolve === 'function';
let tokenCount = 0;
jQuery.ajax({
async: isAsync,
type: 'POST',
url: TOKENIZER_URLS[tokenizers.API_TEXTGENERATIONWEBUI].count,
data: JSON.stringify(getTextgenAPITokenizationParams(str)),
dataType: 'json',
contentType: 'application/json',
success: function (data) {
if (typeof data.count === 'number') {
tokenCount = data.count;
} else {
tokenCount = apiFailureTokenCount(str);
}
isAsync && resolve(tokenCount);
},
});
return tokenCount;
}
function apiFailureTokenCount(str) {
console.error('Error counting tokens');
let shouldTryAgain = false;
if (!sessionStorage.getItem(TOKENIZER_WARNING_KEY)) {
const bestMatchBefore = getTokenizerBestMatch(main_api);
sessionStorage.setItem(TOKENIZER_WARNING_KEY, String(true));
const bestMatchAfter = getTokenizerBestMatch(main_api);
if ([tokenizers.API_TEXTGENERATIONWEBUI, tokenizers.API_KOBOLD].includes(bestMatchBefore) && bestMatchBefore !== bestMatchAfter) {
shouldTryAgain = true;
}
}
// Only try again if we guarantee not to be looped by the same error
if (shouldTryAgain && power_user.tokenizer === tokenizers.BEST_MATCH) {
return getTokenCount(str);
}
return guesstimate(str);
}
/**
* Calls the underlying tokenizer model to encode a string to tokens.
* @param {string} endpoint API endpoint.
* @param {string} str String to tokenize.
* @param {function} [resolve] Promise resolve function.
* @returns {number[]} Array of token ids.
*/
function getTextTokensFromServer(endpoint, str, resolve) {
const isAsync = typeof resolve === 'function';
let ids = [];
jQuery.ajax({
async: isAsync,
type: 'POST',
url: endpoint,
data: JSON.stringify({ text: str }),
dataType: 'json',
contentType: 'application/json',
success: function (data) {
ids = data.ids;
// Don't want to break reverse compatibility, so sprinkle in some of the JS magic
if (Array.isArray(data.chunks)) {
Object.defineProperty(ids, 'chunks', { value: data.chunks });
}
isAsync && resolve(ids);
},
});
return ids;
}
/**
* Calls the AI provider's tokenize API to encode a string to tokens.
* @param {string} str String to tokenize.
* @param {function} [resolve] Promise resolve function.
* @returns {number[]} Array of token ids.
*/
function getTextTokensFromTextgenAPI(str, resolve) {
const isAsync = typeof resolve === 'function';
let ids = [];
jQuery.ajax({
async: isAsync,
type: 'POST',
url: TOKENIZER_URLS[tokenizers.API_TEXTGENERATIONWEBUI].encode,
data: JSON.stringify(getTextgenAPITokenizationParams(str)),
dataType: 'json',
contentType: 'application/json',
success: function (data) {
ids = data.ids;
isAsync && resolve(ids);
},
});
return ids;
}
/**
* Calls the AI provider's tokenize API to encode a string to tokens.
* @param {string} str String to tokenize.
* @param {function} [resolve] Promise resolve function.
* @returns {number[]} Array of token ids.
*/
function getTextTokensFromKoboldAPI(str, resolve) {
const isAsync = typeof resolve === 'function';
let ids = [];
jQuery.ajax({
async: isAsync,
type: 'POST',
url: TOKENIZER_URLS[tokenizers.API_KOBOLD].encode,
data: JSON.stringify({
text: str,
url: api_server,
}),
dataType: 'json',
contentType: 'application/json',
success: function (data) {
ids = data.ids;
isAsync && resolve(ids);
},
});
return ids;
}
/**
* Calls the underlying tokenizer model to decode token ids to text.
* @param {string} endpoint API endpoint.
* @param {number[]} ids Array of token ids
* @param {function} [resolve] Promise resolve function.
* @returns {({ text: string, chunks?: string[] })} Decoded token text as a single string and individual chunks (if available).
*/
function decodeTextTokensFromServer(endpoint, ids, resolve) {
const isAsync = typeof resolve === 'function';
let text = '';
let chunks = [];
jQuery.ajax({
async: isAsync,
type: 'POST',
url: endpoint,
data: JSON.stringify({ ids: ids }),
dataType: 'json',
contentType: 'application/json',
success: function (data) {
text = data.text;
chunks = data.chunks;
isAsync && resolve({ text, chunks });
},
});
return { text, chunks };
}
/**
* Encodes a string to tokens using the server API.
* @param {number} tokenizerType Tokenizer type.
* @param {string} str String to tokenize.
* @returns {number[]} Array of token ids.
*/
export function getTextTokens(tokenizerType, str) {
switch (tokenizerType) {
case tokenizers.API_CURRENT:
return getTextTokens(currentRemoteTokenizerAPI(), str);
case tokenizers.API_TEXTGENERATIONWEBUI:
return getTextTokensFromTextgenAPI(str);
case tokenizers.API_KOBOLD:
return getTextTokensFromKoboldAPI(str);
default: {
const tokenizerEndpoints = TOKENIZER_URLS[tokenizerType];
if (!tokenizerEndpoints) {
apiFailureTokenCount(str);
console.warn('Unknown tokenizer type', tokenizerType);
return [];
}
let endpointUrl = tokenizerEndpoints.encode;
if (!endpointUrl) {
apiFailureTokenCount(str);
console.warn('This tokenizer type does not support encoding', tokenizerType);
return [];
}
if (tokenizerType === tokenizers.OPENAI) {
endpointUrl += `?model=${getTokenizerModel()}`;
}
return getTextTokensFromServer(endpointUrl, str);
}
}
}
/**
* Decodes token ids to text using the server API.
* @param {number} tokenizerType Tokenizer type.
* @param {number[]} ids Array of token ids
* @returns {({ text: string, chunks?: string[] })} Decoded token text as a single string and individual chunks (if available).
*/
export function decodeTextTokens(tokenizerType, ids) {
// Currently, neither remote API can decode, but this may change in the future. Put this guard here to be safe
if (tokenizerType === tokenizers.API_CURRENT) {
return decodeTextTokens(tokenizers.NONE, ids);
}
const tokenizerEndpoints = TOKENIZER_URLS[tokenizerType];
if (!tokenizerEndpoints) {
console.warn('Unknown tokenizer type', tokenizerType);
return { text: '', chunks: [] };
}
let endpointUrl = tokenizerEndpoints.decode;
if (!endpointUrl) {
console.warn('This tokenizer type does not support decoding', tokenizerType);
return { text: '', chunks: [] };
}
if (tokenizerType === tokenizers.OPENAI) {
endpointUrl += `?model=${getTokenizerModel()}`;
}
return decodeTextTokensFromServer(endpointUrl, ids);
}
export async function initTokenizers() {
await loadTokenCache();
registerDebugFunction('resetTokenCache', 'Reset token cache', 'Purges the calculated token counts. Use this if you want to force a full re-tokenization of all chats or suspect the token counts are wrong.', resetTokenCache);
}