LibreChat/api/utils/tokens.js
Danny Avila 583e978a82
feat(Google): Support all Text/Chat Models, Response streaming, PaLM -> Google 🤖 (#1316)
* feat: update PaLM icons

* feat: add additional google models

* POC: formatting inputs for Vertex AI streaming

* refactor: move endpoints services outside of /routes dir to /services/Endpoints

* refactor: shorten schemas import

* refactor: rename PALM to GOOGLE

* feat: make Google editable endpoint

* feat: reusable Ask and Edit controllers based off Anthropic

* chore: organize imports/logic

* fix(parseConvo): include examples in googleSchema

* fix: google only allows odd number of messages to be sent

* fix: pass proxy to AnthropicClient

* refactor: change `google` altName to `Google`

* refactor: update getModelMaxTokens and related functions to handle maxTokensMap with nested endpoint model key/values

* refactor: google Icon and response sender changes (Codey and Google logo instead of PaLM in all cases)

* feat: google support for maxTokensMap

* feat: google updated endpoints with Ask/Edit controllers, buildOptions, and initializeClient

* feat(GoogleClient): now builds prompt for text models and supports real streaming from Vertex AI through langchain

* chore(GoogleClient): remove comments, left before for reference in git history

* docs: update google instructions (WIP)

* docs(apis_and_tokens.md): add images to google instructions

* docs: remove typo apis_and_tokens.md

* Update apis_and_tokens.md

* feat(Google): use default settings map, fully support context for both text and chat models, fully support examples for chat models

* chore: update more PaLM references to Google

* chore: move playwright out of workflows to avoid failing tests
2023-12-10 14:54:13 -05:00

156 lines
4.1 KiB
JavaScript

const { EModelEndpoint } = require('~/server/services/Endpoints');
const models = [
'text-davinci-003',
'text-davinci-002',
'text-davinci-001',
'text-curie-001',
'text-babbage-001',
'text-ada-001',
'davinci',
'curie',
'babbage',
'ada',
'code-davinci-002',
'code-davinci-001',
'code-cushman-002',
'code-cushman-001',
'davinci-codex',
'cushman-codex',
'text-davinci-edit-001',
'code-davinci-edit-001',
'text-embedding-ada-002',
'text-similarity-davinci-001',
'text-similarity-curie-001',
'text-similarity-babbage-001',
'text-similarity-ada-001',
'text-search-davinci-doc-001',
'text-search-curie-doc-001',
'text-search-babbage-doc-001',
'text-search-ada-doc-001',
'code-search-babbage-code-001',
'code-search-ada-code-001',
'gpt2',
'gpt-4',
'gpt-4-0314',
'gpt-4-32k',
'gpt-4-32k-0314',
'gpt-3.5-turbo',
'gpt-3.5-turbo-0301',
];
// Order is important here: by model series and context size (gpt-4 then gpt-3, ascending)
const maxTokensMap = {
[EModelEndpoint.openAI]: {
'gpt-4': 8191,
'gpt-4-0613': 8191,
'gpt-4-32k': 32767,
'gpt-4-32k-0314': 32767,
'gpt-4-32k-0613': 32767,
'gpt-3.5-turbo': 4095,
'gpt-3.5-turbo-0613': 4095,
'gpt-3.5-turbo-0301': 4095,
'gpt-3.5-turbo-16k': 15999,
'gpt-3.5-turbo-16k-0613': 15999,
'gpt-3.5-turbo-1106': 16380, // -5 from max
'gpt-4-1106': 127995, // -5 from max
},
[EModelEndpoint.google]: {
/* Max I/O is 32k combined, so -1000 to leave room for response */
'text-bison-32k': 31000,
'chat-bison-32k': 31000,
'code-bison-32k': 31000,
'codechat-bison-32k': 31000,
/* Codey, -5 from max: 6144 */
'code-': 6139,
'codechat-': 6139,
/* PaLM2, -5 from max: 8192 */
'text-': 8187,
'chat-': 8187,
},
[EModelEndpoint.anthropic]: {
'claude-2.1': 200000,
'claude-': 100000,
},
};
/**
* Retrieves the maximum tokens for a given model name. If the exact model name isn't found,
* it searches for partial matches within the model name, checking keys in reverse order.
*
* @param {string} modelName - The name of the model to look up.
* @param {string} endpoint - The endpoint (default is 'openAI').
* @returns {number|undefined} The maximum tokens for the given model or undefined if no match is found.
*
* @example
* getModelMaxTokens('gpt-4-32k-0613'); // Returns 32767
* getModelMaxTokens('gpt-4-32k-unknown'); // Returns 32767
* getModelMaxTokens('unknown-model'); // Returns undefined
*/
function getModelMaxTokens(modelName, endpoint = EModelEndpoint.openAI) {
if (typeof modelName !== 'string') {
return undefined;
}
const tokensMap = maxTokensMap[endpoint];
if (!tokensMap) {
return undefined;
}
if (tokensMap[modelName]) {
return tokensMap[modelName];
}
const keys = Object.keys(tokensMap);
for (let i = keys.length - 1; i >= 0; i--) {
if (modelName.includes(keys[i])) {
return tokensMap[keys[i]];
}
}
return undefined;
}
/**
* Retrieves the model name key for a given model name input. If the exact model name isn't found,
* it searches for partial matches within the model name, checking keys in reverse order.
*
* @param {string} modelName - The name of the model to look up.
* @param {string} endpoint - The endpoint (default is 'openAI').
* @returns {string|undefined} The model name key for the given model; returns input if no match is found and is string.
*
* @example
* matchModelName('gpt-4-32k-0613'); // Returns 'gpt-4-32k-0613'
* matchModelName('gpt-4-32k-unknown'); // Returns 'gpt-4-32k'
* matchModelName('unknown-model'); // Returns undefined
*/
function matchModelName(modelName, endpoint = EModelEndpoint.openAI) {
if (typeof modelName !== 'string') {
return undefined;
}
const tokensMap = maxTokensMap[endpoint];
if (!tokensMap) {
return modelName;
}
if (tokensMap[modelName]) {
return modelName;
}
const keys = Object.keys(tokensMap);
for (let i = keys.length - 1; i >= 0; i--) {
if (modelName.includes(keys[i])) {
return keys[i];
}
}
return modelName;
}
module.exports = {
tiktokenModels: new Set(models),
maxTokensMap,
getModelMaxTokens,
matchModelName,
};