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* refactor: Token Limit Processing with Enhanced Efficiency - Added a new test suite for `processTextWithTokenLimit`, ensuring comprehensive coverage of various scenarios including under, at, and exceeding token limits. - Refactored the `processTextWithTokenLimit` function to utilize a ratio-based estimation method, significantly reducing the number of token counting function calls compared to the previous binary search approach. - Improved handling of edge cases and variable token density, ensuring accurate truncation and performance across diverse text inputs. - Included direct comparisons with the old implementation to validate correctness and efficiency improvements. * refactor: Remove Tokenizer Route and Related References - Deleted the tokenizer route from the server and removed its references from the routes index and server files, streamlining the API structure. - This change simplifies the routing configuration by eliminating unused endpoints. * refactor: Migrate countTokens Utility to API Module - Removed the local countTokens utility and integrated it into the @librechat/api module for centralized access. - Updated various files to reference the new countTokens import from the API module, ensuring consistent usage across the application. - Cleaned up unused references and imports related to the previous countTokens implementation. * refactor: Centralize escapeRegExp Utility in API Module - Moved the escapeRegExp function from local utility files to the @librechat/api module for consistent usage across the application. - Updated imports in various files to reference the new centralized escapeRegExp function, ensuring cleaner code and reducing redundancy. - Removed duplicate implementations of escapeRegExp from multiple files, streamlining the codebase. * refactor: Enhance Token Counting Flexibility in Text Processing - Updated the `processTextWithTokenLimit` function to accept both synchronous and asynchronous token counting functions, improving its versatility. - Introduced a new `TokenCountFn` type to define the token counting function signature. - Added comprehensive tests to validate the behavior of `processTextWithTokenLimit` with both sync and async token counting functions, ensuring consistent results. - Implemented a wrapper to track call counts for the `countTokens` function, optimizing performance and reducing unnecessary calls. - Enhanced existing tests to compare the performance of the new implementation against the old one, demonstrating significant improvements in efficiency. * chore: documentation for Truncation Safety Buffer in Token Processing - Added a safety buffer multiplier to the character position estimates during text truncation to prevent overshooting token limits. - Updated the `processTextWithTokenLimit` function to utilize the new `TRUNCATION_SAFETY_BUFFER` constant, enhancing the accuracy of token limit processing. - Improved documentation to clarify the rationale behind the buffer and its impact on performance and efficiency in token counting.
181 lines
4.8 KiB
JavaScript
181 lines
4.8 KiB
JavaScript
const {
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Capabilities,
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EModelEndpoint,
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isAgentsEndpoint,
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isAssistantsEndpoint,
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defaultRetrievalModels,
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defaultAssistantsVersion,
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defaultAgentCapabilities,
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} = require('librechat-data-provider');
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const { sendEvent } = require('@librechat/api');
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const partialRight = require('lodash/partialRight');
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const addSpaceIfNeeded = (text) => (text.length > 0 && !text.endsWith(' ') ? text + ' ' : text);
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const base = { message: true, initial: true };
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const createOnProgress = (
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{ generation = '', onProgress: _onProgress } = {
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generation: '',
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onProgress: null,
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},
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) => {
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let i = 0;
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let tokens = addSpaceIfNeeded(generation);
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const basePayload = Object.assign({}, base, { text: tokens || '' });
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const progressCallback = (chunk, { res, ...rest }) => {
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basePayload.text = basePayload.text + chunk;
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const payload = Object.assign({}, basePayload, rest);
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sendEvent(res, payload);
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if (_onProgress) {
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_onProgress(payload);
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}
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if (i === 0) {
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basePayload.initial = false;
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}
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i++;
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};
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const sendIntermediateMessage = (res, payload, extraTokens = '') => {
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basePayload.text = basePayload.text + extraTokens;
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const message = Object.assign({}, basePayload, payload);
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sendEvent(res, message);
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if (i === 0) {
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basePayload.initial = false;
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}
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i++;
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};
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const onProgress = (opts) => {
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return partialRight(progressCallback, opts);
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};
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const getPartialText = () => {
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return basePayload.text;
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};
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return { onProgress, getPartialText, sendIntermediateMessage };
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};
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const handleText = async (response) => {
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let { text } = response;
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response.text = text;
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return text;
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};
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const isObject = (item) => item && typeof item === 'object' && !Array.isArray(item);
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const getString = (input) => (isObject(input) ? JSON.stringify(input) : input);
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function formatSteps(steps) {
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let output = '';
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for (let i = 0; i < steps.length; i++) {
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const step = steps[i];
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const actionInput = getString(step.action.toolInput);
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const observation = step.observation;
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if (actionInput === 'N/A' || observation?.trim()?.length === 0) {
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continue;
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}
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output += `Input: ${actionInput}\nOutput: ${getString(observation)}`;
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if (steps.length > 1 && i !== steps.length - 1) {
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output += '\n---\n';
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}
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}
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return output;
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}
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function formatAction(action) {
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const formattedAction = {
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plugin: action.tool,
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input: getString(action.toolInput),
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thought: action.log.includes('Thought: ')
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? action.log.split('\n')[0].replace('Thought: ', '')
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: action.log.split('\n')[0],
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};
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formattedAction.thought = getString(formattedAction.thought);
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if (action.tool.toLowerCase() === 'self-reflection' || formattedAction.plugin === 'N/A') {
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formattedAction.inputStr = `{\n\tthought: ${formattedAction.input}${
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!formattedAction.thought.includes(formattedAction.input)
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? ' - ' + formattedAction.thought
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: ''
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}\n}`;
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formattedAction.inputStr = formattedAction.inputStr.replace('N/A - ', '');
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} else {
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const hasThought = formattedAction.thought.length > 0;
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const thought = hasThought ? `\n\tthought: ${formattedAction.thought}` : '';
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formattedAction.inputStr = `{\n\tplugin: ${formattedAction.plugin}\n\tinput: ${formattedAction.input}\n${thought}}`;
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}
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return formattedAction;
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}
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/**
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* Checks if the provided value is 'user_provided'.
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*
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* @param {string} value - The value to check.
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* @returns {boolean} - Returns true if the value is 'user_provided', otherwise false.
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*/
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const isUserProvided = (value) => value === 'user_provided';
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/**
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* Generate the configuration for a given key and base URL.
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* @param {string} key
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* @param {string} [baseURL]
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* @param {string} [endpoint]
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* @returns {boolean | { userProvide: boolean, userProvideURL?: boolean }}
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*/
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function generateConfig(key, baseURL, endpoint) {
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if (!key) {
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return false;
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}
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/** @type {{ userProvide: boolean, userProvideURL?: boolean }} */
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const config = { userProvide: isUserProvided(key) };
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if (baseURL) {
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config.userProvideURL = isUserProvided(baseURL);
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}
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const assistants = isAssistantsEndpoint(endpoint);
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const agents = isAgentsEndpoint(endpoint);
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if (assistants) {
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config.retrievalModels = defaultRetrievalModels;
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config.capabilities = [
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Capabilities.code_interpreter,
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Capabilities.image_vision,
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Capabilities.retrieval,
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Capabilities.actions,
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Capabilities.tools,
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];
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}
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if (agents) {
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config.capabilities = defaultAgentCapabilities;
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}
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if (assistants && endpoint === EModelEndpoint.azureAssistants) {
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config.version = defaultAssistantsVersion.azureAssistants;
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} else if (assistants) {
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config.version = defaultAssistantsVersion.assistants;
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}
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return config;
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}
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module.exports = {
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handleText,
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formatSteps,
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formatAction,
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isUserProvided,
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generateConfig,
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addSpaceIfNeeded,
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createOnProgress,
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};
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