mirror of
https://github.com/danny-avila/LibreChat.git
synced 2025-09-22 06:00:56 +02:00

* ✨ feat: Implement Show Thinking feature; refactor: testing thinking render optimizations * ✨ feat: Refactor Thinking component styles and enhance Markdown rendering * chore: add back removed code, revert type changes * chore: Add back resetCounter effect to Markdown component for improved code block indexing * chore: bump @librechat/agents and google langchain packages * WIP: reasoning type updates * WIP: first pass, reasoning content blocks * chore: revert code * chore: bump @librechat/agents * refactor: optimize reasoning tag handling * style: ul indent padding * feat: add Reasoning component to handle reasoning display * feat: first pass, content reasoning part styling * refactor: add content placeholder for endpoints using new stream handler * refactor: only cache messages when requesting stream audio * fix: circular dep. * fix: add default param * refactor: tts, only request after message stream, fix chrome autoplay * style: update label for submitting state and add localization for 'Thinking...' * fix: improve global audio pause logic and reset active run ID * fix: handle artifact edge cases * fix: remove unnecessary console log from artifact update test * feat: add support for continued message handling with new streaming method --------- Co-authored-by: Marco Beretta <81851188+berry-13@users.noreply.github.com>
205 lines
5.4 KiB
JavaScript
205 lines
5.4 KiB
JavaScript
const { CacheKeys, findLastSeparatorIndex, SEPARATORS, Time } = require('librechat-data-provider');
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const { getMessage } = require('~/models/Message');
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const { getLogStores } = require('~/cache');
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/**
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* @param {string[]} voiceIds - Array of voice IDs
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* @returns {string}
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*/
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function getRandomVoiceId(voiceIds) {
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const randomIndex = Math.floor(Math.random() * voiceIds.length);
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return voiceIds[randomIndex];
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}
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/**
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* @typedef {Object} VoiceSettings
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* @property {number} similarity_boost
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* @property {number} stability
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* @property {boolean} use_speaker_boost
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*/
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/**
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* @typedef {Object} GenerateAudioBulk
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* @property {string} model_id
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* @property {string} text
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* @property {VoiceSettings} voice_settings
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*/
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/**
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* @typedef {Object} TextToSpeechClient
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* @property {function(Object): Promise<stream.Readable>} generate
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*/
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/**
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* @typedef {Object} AudioChunk
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* @property {string} audio
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* @property {boolean} isFinal
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* @property {Object} alignment
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* @property {number[]} alignment.char_start_times_ms
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* @property {number[]} alignment.chars_durations_ms
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* @property {string[]} alignment.chars
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* @property {Object} normalizedAlignment
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* @property {number[]} normalizedAlignment.char_start_times_ms
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* @property {number[]} normalizedAlignment.chars_durations_ms
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* @property {string[]} normalizedAlignment.chars
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*/
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const MAX_NOT_FOUND_COUNT = 6;
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const MAX_NO_CHANGE_COUNT = 10;
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/**
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* @param {string} user
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* @param {string} messageId
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* @returns {() => Promise<{ text: string, isFinished: boolean }[]>}
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*/
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function createChunkProcessor(user, messageId) {
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let notFoundCount = 0;
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let noChangeCount = 0;
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let processedText = '';
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if (!messageId) {
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throw new Error('Message ID is required');
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}
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const messageCache = getLogStores(CacheKeys.MESSAGES);
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/**
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* @returns {Promise<{ text: string, isFinished: boolean }[] | string>}
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*/
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async function processChunks() {
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if (notFoundCount >= MAX_NOT_FOUND_COUNT) {
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return `Message not found after ${MAX_NOT_FOUND_COUNT} attempts`;
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}
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if (noChangeCount >= MAX_NO_CHANGE_COUNT) {
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return `No change in message after ${MAX_NO_CHANGE_COUNT} attempts`;
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}
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/** @type { string | { text: string; complete: boolean } } */
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let message = await messageCache.get(messageId);
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if (!message) {
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message = await getMessage({ user, messageId });
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}
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if (!message) {
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notFoundCount++;
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return [];
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} else {
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messageCache.set(
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messageId,
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{
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text: message.text,
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complete: true,
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},
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Time.FIVE_MINUTES,
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);
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}
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const text = typeof message === 'string' ? message : message.text;
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const complete = typeof message === 'string' ? false : message.complete ?? true;
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if (text === processedText) {
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noChangeCount++;
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}
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const remainingText = text.slice(processedText.length);
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const chunks = [];
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if (!complete && remainingText.length >= 20) {
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const separatorIndex = findLastSeparatorIndex(remainingText);
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if (separatorIndex !== -1) {
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const chunkText = remainingText.slice(0, separatorIndex + 1);
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chunks.push({ text: chunkText, isFinished: false });
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processedText += chunkText;
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} else {
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chunks.push({ text: remainingText, isFinished: false });
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processedText = text;
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}
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} else if (complete && remainingText.trim().length > 0) {
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chunks.push({ text: remainingText.trim(), isFinished: true });
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processedText = text;
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}
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return chunks;
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}
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return processChunks;
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}
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/**
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* @param {string} text
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* @param {number} [chunkSize=4000]
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* @returns {{ text: string, isFinished: boolean }[]}
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*/
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function splitTextIntoChunks(text, chunkSize = 4000) {
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if (!text) {
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throw new Error('Text is required');
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}
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const chunks = [];
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let startIndex = 0;
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const textLength = text.length;
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while (startIndex < textLength) {
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let endIndex = Math.min(startIndex + chunkSize, textLength);
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let chunkText = text.slice(startIndex, endIndex);
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if (endIndex < textLength) {
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let lastSeparatorIndex = -1;
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for (const separator of SEPARATORS) {
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const index = chunkText.lastIndexOf(separator);
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if (index !== -1) {
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lastSeparatorIndex = Math.max(lastSeparatorIndex, index);
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}
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}
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if (lastSeparatorIndex !== -1) {
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endIndex = startIndex + lastSeparatorIndex + 1;
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chunkText = text.slice(startIndex, endIndex);
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} else {
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const nextSeparatorIndex = text.slice(endIndex).search(/\S/);
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if (nextSeparatorIndex !== -1) {
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endIndex += nextSeparatorIndex;
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chunkText = text.slice(startIndex, endIndex);
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}
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}
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}
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chunkText = chunkText.trim();
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if (chunkText) {
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chunks.push({
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text: chunkText,
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isFinished: endIndex >= textLength,
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});
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} else if (chunks.length > 0) {
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chunks[chunks.length - 1].isFinished = true;
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}
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startIndex = endIndex;
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while (startIndex < textLength && text[startIndex].trim() === '') {
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startIndex++;
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}
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}
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return chunks;
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}
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/**
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*
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* @param {AsyncIterable<string>} llmStream
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*/
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async function* llmMessageSource(llmStream) {
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for await (const chunk of llmStream) {
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const message = chunk.choices[0].delta.content;
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if (message) {
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yield message;
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}
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}
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}
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module.exports = {
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findLastSeparatorIndex,
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createChunkProcessor,
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splitTextIntoChunks,
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llmMessageSource,
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getRandomVoiceId,
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};
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