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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.
695 lines
23 KiB
JavaScript
695 lines
23 KiB
JavaScript
const path = require('path');
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const { v4 } = require('uuid');
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const { countTokens, escapeRegExp } = require('@librechat/api');
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const {
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Constants,
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ContentTypes,
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AnnotationTypes,
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defaultOrderQuery,
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} = require('librechat-data-provider');
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const { retrieveAndProcessFile } = require('~/server/services/Files/process');
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const { recordMessage, getMessages } = require('~/models/Message');
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const { spendTokens } = require('~/models/spendTokens');
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const { saveConvo } = require('~/models/Conversation');
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/**
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* Initializes a new thread or adds messages to an existing thread.
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*
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* @param {Object} params - The parameters for initializing a thread.
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* @param {OpenAIClient} params.openai - The OpenAI client instance.
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* @param {Object} params.body - The body of the request.
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* @param {ThreadMessage[]} params.body.messages - A list of messages to start the thread with.
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* @param {Object} [params.body.metadata] - Optional metadata for the thread.
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* @param {string} [params.thread_id] - Optional existing thread ID. If provided, a message will be added to this thread.
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* @return {Promise<Thread>} A promise that resolves to the newly created thread object or the updated thread object.
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*/
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async function initThread({ openai, body, thread_id: _thread_id }) {
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let thread = {};
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const messages = [];
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if (_thread_id) {
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const message = await openai.beta.threads.messages.create(_thread_id, body.messages[0]);
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messages.push(message);
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} else {
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thread = await openai.beta.threads.create(body);
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}
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const thread_id = _thread_id || thread.id;
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return { messages, thread_id, ...thread };
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}
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/**
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* Saves a user message to the DB in the Assistants endpoint format.
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*
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* @param {Object} req - The request object.
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* @param {Object} params - The parameters of the user message
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* @param {string} params.user - The user's ID.
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* @param {string} params.text - The user's prompt.
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* @param {string} params.messageId - The user message Id.
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* @param {string} params.model - The model used by the assistant.
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* @param {string} params.assistant_id - The current assistant Id.
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* @param {string} params.thread_id - The thread Id.
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* @param {string} params.conversationId - The message's conversationId
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* @param {string} params.endpoint - The conversation endpoint
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* @param {string} [params.parentMessageId] - Optional if initial message.
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* Defaults to Constants.NO_PARENT.
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* @param {string} [params.instructions] - Optional: from preset for `instructions` field.
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* Overrides the instructions of the assistant.
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* @param {string} [params.promptPrefix] - Optional: from preset for `additional_instructions` field.
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* @param {import('librechat-data-provider').TFile[]} [params.files] - Optional. List of Attached File Objects.
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* @param {string[]} [params.file_ids] - Optional. List of File IDs attached to the userMessage.
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* @return {Promise<Run>} A promise that resolves to the created run object.
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*/
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async function saveUserMessage(req, params) {
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const tokenCount = await countTokens(params.text);
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// todo: do this on the frontend
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// const { file_ids = [] } = params;
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// let content;
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// if (file_ids.length) {
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// content = [
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// {
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// value: params.text,
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// },
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// ...(
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// file_ids
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// .filter(f => f)
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// .map((file_id) => ({
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// file_id,
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// }))
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// ),
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// ];
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// }
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const userMessage = {
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user: params.user,
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endpoint: params.endpoint,
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messageId: params.messageId,
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conversationId: params.conversationId,
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parentMessageId: params.parentMessageId ?? Constants.NO_PARENT,
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/* For messages, use the assistant_id instead of model */
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model: params.assistant_id,
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thread_id: params.thread_id,
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sender: 'User',
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text: params.text,
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isCreatedByUser: true,
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tokenCount,
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};
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const convo = {
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endpoint: params.endpoint,
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conversationId: params.conversationId,
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promptPrefix: params.promptPrefix,
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instructions: params.instructions,
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assistant_id: params.assistant_id,
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model: params.model,
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};
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if (params.files?.length) {
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userMessage.files = params.files.map(({ file_id }) => ({ file_id }));
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convo.file_ids = params.file_ids;
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}
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const message = await recordMessage(userMessage);
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await saveConvo(req, convo, {
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context: 'api/server/services/Threads/manage.js #saveUserMessage',
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});
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return message;
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}
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/**
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* Saves an Assistant message to the DB in the Assistants endpoint format.
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*
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* @param {Object} req - The request object.
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* @param {Object} params - The parameters of the Assistant message
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* @param {string} params.user - The user's ID.
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* @param {string} params.messageId - The message Id.
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* @param {string} params.text - The concatenated text of the message.
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* @param {string} params.assistant_id - The assistant Id.
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* @param {string} params.thread_id - The thread Id.
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* @param {string} params.model - The model used by the assistant.
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* @param {ContentPart[]} params.content - The message content parts.
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* @param {string} params.conversationId - The message's conversationId
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* @param {string} params.endpoint - The conversation endpoint
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* @param {string} params.parentMessageId - The latest user message that triggered this response.
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* @param {string} [params.instructions] - Optional: from preset for `instructions` field.
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* @param {string} [params.spec] - Optional: Model spec identifier.
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* @param {string} [params.iconURL]
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* Overrides the instructions of the assistant.
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* @param {string} [params.promptPrefix] - Optional: from preset for `additional_instructions` field.
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* @return {Promise<Run>} A promise that resolves to the created run object.
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*/
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async function saveAssistantMessage(req, params) {
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// const tokenCount = // TODO: need to count each content part
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const message = await recordMessage({
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user: params.user,
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endpoint: params.endpoint,
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messageId: params.messageId,
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conversationId: params.conversationId,
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parentMessageId: params.parentMessageId,
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thread_id: params.thread_id,
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/* For messages, use the assistant_id instead of model */
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model: params.assistant_id,
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content: params.content,
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sender: 'Assistant',
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isCreatedByUser: false,
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text: params.text,
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unfinished: false,
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// tokenCount,
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iconURL: params.iconURL,
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spec: params.spec,
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});
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await saveConvo(
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req,
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{
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endpoint: params.endpoint,
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conversationId: params.conversationId,
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promptPrefix: params.promptPrefix,
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instructions: params.instructions,
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assistant_id: params.assistant_id,
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model: params.model,
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iconURL: params.iconURL,
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spec: params.spec,
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},
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{ context: 'api/server/services/Threads/manage.js #saveAssistantMessage' },
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);
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return message;
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}
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/**
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* Records LibreChat messageId to all response messages' metadata
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*
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* @param {Object} params - The parameters for initializing a thread.
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* @param {OpenAIClient} params.openai - The OpenAI client instance.
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* @param {string} params.thread_id - Response thread ID.
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* @param {string} params.messageId - The response `messageId` generated by LibreChat.
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* @param {StepMessage[] | Message[]} params.messages - A list of messages to start the thread with.
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* @return {Promise<ThreadMessage[]>} A promise that resolves to the updated messages
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*/
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async function addThreadMetadata({ openai, thread_id, messageId, messages }) {
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const promises = [];
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for (const message of messages) {
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promises.push(
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openai.beta.threads.messages.update(message.id, {
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thread_id,
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metadata: {
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messageId,
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},
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}),
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);
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}
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return await Promise.all(promises);
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}
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/**
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* Synchronizes LibreChat messages to Thread Messages.
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* Updates the LibreChat DB with any missing Thread Messages and
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* updates the missing Thread Messages' metadata with their corresponding db messageId's.
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*
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* Also updates the existing conversation's file_ids with any new file_ids.
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*
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* @param {Object} params - The parameters for synchronizing messages.
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* @param {OpenAIClient} params.openai - The OpenAI client instance.
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* @param {string} params.endpoint - The current endpoint.
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* @param {string} params.thread_id - The current thread ID.
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* @param {TMessage[]} params.dbMessages - The LibreChat DB messages.
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* @param {ThreadMessage[]} params.apiMessages - The thread messages from the API.
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* @param {string} [params.assistant_id] - The current assistant ID.
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* @param {string} params.conversationId - The current conversation ID.
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* @return {Promise<TMessage[]>} A promise that resolves to the updated messages
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*/
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async function syncMessages({
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openai,
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endpoint,
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thread_id,
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dbMessages,
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apiMessages,
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assistant_id,
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conversationId,
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}) {
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let result = [];
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let dbMessageMap = new Map(dbMessages.map((msg) => [msg.messageId, msg]));
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const modifyPromises = [];
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const recordPromises = [];
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/**
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*
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* Modify API message and save newMessage to DB
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*
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* @param {Object} params - The parameters object
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* @param {TMessage} params.dbMessage
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* @param {dbMessage} params.apiMessage
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*/
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const processNewMessage = async ({ dbMessage, apiMessage }) => {
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recordPromises.push(recordMessage({ ...dbMessage, user: openai.req.user.id }));
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if (!apiMessage.id.includes('msg_')) {
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return;
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}
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if (dbMessage.aggregateMessages?.length > 1) {
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modifyPromises.push(
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addThreadMetadata({
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openai,
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thread_id,
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messageId: dbMessage.messageId,
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messages: dbMessage.aggregateMessages,
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}),
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);
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return;
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}
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modifyPromises.push(
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openai.beta.threads.messages.update(apiMessage.id, {
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thread_id,
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metadata: {
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messageId: dbMessage.messageId,
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},
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}),
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);
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};
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let lastMessage = null;
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for (let i = 0; i < apiMessages.length; i++) {
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const apiMessage = apiMessages[i];
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// Check if the message exists in the database based on metadata
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const dbMessageId = apiMessage.metadata && apiMessage.metadata.messageId;
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let dbMessage = dbMessageMap.get(dbMessageId);
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if (dbMessage) {
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// If message exists in DB, use its messageId and update parentMessageId
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dbMessage.parentMessageId = lastMessage ? lastMessage.messageId : Constants.NO_PARENT;
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lastMessage = dbMessage;
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result.push(dbMessage);
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continue;
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}
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if (apiMessage.role === 'assistant' && lastMessage && lastMessage.role === 'assistant') {
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// Aggregate assistant messages
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lastMessage.content = [...lastMessage.content, ...apiMessage.content];
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lastMessage.files = [...(lastMessage.files ?? []), ...(apiMessage.files ?? [])];
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lastMessage.aggregateMessages.push({ id: apiMessage.id });
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} else {
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// Handle new or missing message
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const newMessage = {
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thread_id,
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conversationId,
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messageId: v4(),
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endpoint,
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parentMessageId: lastMessage ? lastMessage.messageId : Constants.NO_PARENT,
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role: apiMessage.role,
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isCreatedByUser: apiMessage.role === 'user',
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// TODO: process generated files in content parts
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content: apiMessage.content,
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aggregateMessages: [{ id: apiMessage.id }],
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model: apiMessage.role === 'user' ? null : apiMessage.assistant_id,
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user: openai.req.user.id,
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unfinished: false,
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};
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if (apiMessage.file_ids?.length) {
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// TODO: retrieve file objects from API
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newMessage.files = apiMessage.file_ids.map((file_id) => ({ file_id }));
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}
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/* Assign assistant_id if defined */
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if (assistant_id && apiMessage.role === 'assistant' && !newMessage.model) {
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apiMessage.model = assistant_id;
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newMessage.model = assistant_id;
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}
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result.push(newMessage);
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lastMessage = newMessage;
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if (apiMessage.role === 'user') {
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processNewMessage({ dbMessage: newMessage, apiMessage });
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continue;
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}
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}
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const nextMessage = apiMessages[i + 1];
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const processAssistant = !nextMessage || nextMessage.role === 'user';
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if (apiMessage.role === 'assistant' && processAssistant) {
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processNewMessage({ dbMessage: lastMessage, apiMessage });
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}
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}
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const attached_file_ids = apiMessages.reduce((acc, msg) => {
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if (msg.role === 'user' && msg.file_ids?.length) {
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return [...acc, ...msg.file_ids];
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}
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return acc;
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}, []);
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await Promise.all(modifyPromises);
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await Promise.all(recordPromises);
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await saveConvo(
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openai.req,
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{
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conversationId,
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file_ids: attached_file_ids,
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},
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{ context: 'api/server/services/Threads/manage.js #syncMessages' },
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);
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return result;
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}
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/**
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* Maps messages to their corresponding steps. Steps with message creation will be paired with their messages,
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* while steps without message creation will be returned as is.
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*
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* @param {RunStep[]} steps - An array of steps from the run.
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* @param {Message[]} messages - An array of message objects.
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* @returns {(StepMessage | RunStep)[]} An array where each element is either a step with its corresponding message (StepMessage) or a step without a message (RunStep).
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*/
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function mapMessagesToSteps(steps, messages) {
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// Create a map of messages indexed by their IDs for efficient lookup
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const messageMap = messages.reduce((acc, msg) => {
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acc[msg.id] = msg;
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return acc;
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}, {});
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// Map each step to its corresponding message, or return the step as is if no message ID is present
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return steps
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.sort((a, b) => a.created_at - b.created_at)
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.map((step) => {
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const messageId = step.step_details?.message_creation?.message_id;
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if (messageId && messageMap[messageId]) {
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return { step, message: messageMap[messageId] };
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}
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return step;
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});
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}
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/**
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* Checks for any missing messages; if missing,
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* synchronizes LibreChat messages to Thread Messages
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|
*
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* @param {Object} params - The parameters for initializing a thread.
|
|
* @param {OpenAIClient} params.openai - The OpenAI client instance.
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|
* @param {string} params.endpoint - The current endpoint.
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* @param {string} [params.latestMessageId] - Optional: The latest message ID from LibreChat.
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* @param {string} params.thread_id - Response thread ID.
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* @param {string} params.run_id - Response Run ID.
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* @param {string} params.conversationId - LibreChat conversation ID.
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* @return {Promise<TMessage[]>} A promise that resolves to the updated messages
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*/
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async function checkMessageGaps({
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openai,
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endpoint,
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latestMessageId,
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thread_id,
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run_id,
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conversationId,
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}) {
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const promises = [];
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promises.push(openai.beta.threads.messages.list(thread_id, defaultOrderQuery));
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promises.push(openai.beta.threads.runs.steps.list(run_id, { thread_id }));
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/** @type {[{ data: ThreadMessage[] }, { data: RunStep[] }]} */
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const [response, stepsResponse] = await Promise.all(promises);
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const steps = mapMessagesToSteps(stepsResponse.data, response.data);
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/** @type {ThreadMessage} */
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|
const currentMessage = {
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id: v4(),
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content: [],
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assistant_id: null,
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created_at: Math.floor(new Date().getTime() / 1000),
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object: 'thread.message',
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role: 'assistant',
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run_id,
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thread_id,
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endpoint,
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metadata: {
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messageId: latestMessageId,
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},
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};
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for (const step of steps) {
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if (!currentMessage.assistant_id && step.assistant_id) {
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currentMessage.assistant_id = step.assistant_id;
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}
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if (step.message) {
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currentMessage.id = step.message.id;
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currentMessage.created_at = step.message.created_at;
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currentMessage.content = currentMessage.content.concat(step.message.content);
|
|
} else if (step.step_details?.type === 'tool_calls' && step.step_details?.tool_calls?.length) {
|
|
currentMessage.content = currentMessage.content.concat(
|
|
step.step_details?.tool_calls.map((toolCall) => ({
|
|
[ContentTypes.TOOL_CALL]: {
|
|
...toolCall,
|
|
progress: 2,
|
|
},
|
|
type: ContentTypes.TOOL_CALL,
|
|
})),
|
|
);
|
|
}
|
|
}
|
|
|
|
let addedCurrentMessage = false;
|
|
const apiMessages = response.data
|
|
.map((msg) => {
|
|
if (msg.id === currentMessage.id) {
|
|
addedCurrentMessage = true;
|
|
return currentMessage;
|
|
}
|
|
return msg;
|
|
})
|
|
.sort((a, b) => new Date(a.created_at) - new Date(b.created_at));
|
|
|
|
if (!addedCurrentMessage) {
|
|
apiMessages.push(currentMessage);
|
|
}
|
|
|
|
const dbMessages = await getMessages({ conversationId });
|
|
const assistant_id = dbMessages?.[0]?.model;
|
|
|
|
const syncedMessages = await syncMessages({
|
|
openai,
|
|
endpoint,
|
|
thread_id,
|
|
dbMessages,
|
|
apiMessages,
|
|
assistant_id,
|
|
conversationId,
|
|
});
|
|
|
|
return Object.values(
|
|
[...dbMessages, ...syncedMessages].reduce(
|
|
(acc, message) => ({ ...acc, [message.messageId]: message }),
|
|
{},
|
|
),
|
|
);
|
|
}
|
|
|
|
/**
|
|
* Records token usage for a given completion request.
|
|
* @param {Object} params - The parameters for initializing a thread.
|
|
* @param {number} params.prompt_tokens - The number of prompt tokens used.
|
|
* @param {number} params.completion_tokens - The number of completion tokens used.
|
|
* @param {string} params.model - The model used by the assistant run.
|
|
* @param {string} params.user - The user's ID.
|
|
* @param {string} params.conversationId - LibreChat conversation ID.
|
|
* @param {string} [params.context='message'] - The context of the usage. Defaults to 'message'.
|
|
* @return {Promise<TMessage[]>} A promise that resolves to the updated messages
|
|
*/
|
|
const recordUsage = async ({
|
|
prompt_tokens,
|
|
completion_tokens,
|
|
model,
|
|
user,
|
|
conversationId,
|
|
context = 'message',
|
|
}) => {
|
|
await spendTokens(
|
|
{
|
|
user,
|
|
model,
|
|
context,
|
|
conversationId,
|
|
},
|
|
{ promptTokens: prompt_tokens, completionTokens: completion_tokens },
|
|
);
|
|
};
|
|
|
|
const uniqueCitationStart = '^====||===';
|
|
const uniqueCitationEnd = '==|||||^';
|
|
|
|
/**
|
|
* Sorts, processes, and flattens messages to a single string.
|
|
*
|
|
* @param {object} params - The parameters for processing messages.
|
|
* @param {OpenAIClient} params.openai - The OpenAI client instance.
|
|
* @param {RunClient} params.client - The LibreChat client that manages the run: either refers to `OpenAI` or `StreamRunManager`.
|
|
* @param {ThreadMessage[]} params.messages - An array of messages.
|
|
* @returns {Promise<{messages: ThreadMessage[], text: string, edited: boolean}>} The sorted messages, the flattened text, and whether it was edited.
|
|
*/
|
|
async function processMessages({ openai, client, messages = [] }) {
|
|
const sorted = messages.sort((a, b) => a.created_at - b.created_at);
|
|
|
|
let text = '';
|
|
let edited = false;
|
|
const sources = new Map();
|
|
const fileRetrievalPromises = [];
|
|
|
|
for (const message of sorted) {
|
|
message.files = [];
|
|
for (const content of message.content) {
|
|
const type = content.type;
|
|
const contentType = content[type];
|
|
const currentFileId = contentType?.file_id;
|
|
|
|
if (type === ContentTypes.IMAGE_FILE && !client.processedFileIds.has(currentFileId)) {
|
|
fileRetrievalPromises.push(
|
|
retrieveAndProcessFile({
|
|
openai,
|
|
client,
|
|
file_id: currentFileId,
|
|
basename: `${currentFileId}.png`,
|
|
})
|
|
.then((file) => {
|
|
client.processedFileIds.add(currentFileId);
|
|
message.files.push(file);
|
|
})
|
|
.catch((error) => {
|
|
console.error(`Failed to retrieve file: ${error.message}`);
|
|
}),
|
|
);
|
|
continue;
|
|
}
|
|
|
|
let currentText = contentType?.value ?? '';
|
|
|
|
/** @type {{ annotations: Annotation[] }} */
|
|
const { annotations } = contentType ?? {};
|
|
|
|
if (!annotations?.length) {
|
|
text += currentText;
|
|
continue;
|
|
}
|
|
|
|
const replacements = [];
|
|
const annotationPromises = annotations.map(async (annotation) => {
|
|
const type = annotation.type;
|
|
const annotationType = annotation[type];
|
|
const file_id = annotationType?.file_id;
|
|
const alreadyProcessed = client.processedFileIds.has(file_id);
|
|
|
|
let file;
|
|
let replacementText = '';
|
|
|
|
try {
|
|
if (alreadyProcessed) {
|
|
file = await retrieveAndProcessFile({ openai, client, file_id, unknownType: true });
|
|
} else if (type === AnnotationTypes.FILE_PATH) {
|
|
const basename = path.basename(annotation.text);
|
|
file = await retrieveAndProcessFile({
|
|
openai,
|
|
client,
|
|
file_id,
|
|
basename,
|
|
});
|
|
replacementText = file.filepath;
|
|
} else if (type === AnnotationTypes.FILE_CITATION && file_id) {
|
|
file = await retrieveAndProcessFile({
|
|
openai,
|
|
client,
|
|
file_id,
|
|
unknownType: true,
|
|
});
|
|
if (file && file.filename) {
|
|
if (!sources.has(file.filename)) {
|
|
sources.set(file.filename, sources.size + 1);
|
|
}
|
|
replacementText = `${uniqueCitationStart}${sources.get(
|
|
file.filename,
|
|
)}${uniqueCitationEnd}`;
|
|
}
|
|
}
|
|
|
|
if (file && replacementText) {
|
|
replacements.push({
|
|
start: annotation.start_index,
|
|
end: annotation.end_index,
|
|
text: replacementText,
|
|
});
|
|
edited = true;
|
|
if (!alreadyProcessed) {
|
|
client.processedFileIds.add(file_id);
|
|
message.files.push(file);
|
|
}
|
|
}
|
|
} catch (error) {
|
|
console.error(`Failed to process annotation: ${error.message}`);
|
|
}
|
|
});
|
|
|
|
await Promise.all(annotationPromises);
|
|
|
|
// Apply replacements in reverse order
|
|
replacements.sort((a, b) => b.start - a.start);
|
|
for (const { start, end, text: replacementText } of replacements) {
|
|
currentText = currentText.slice(0, start) + replacementText + currentText.slice(end);
|
|
}
|
|
|
|
text += currentText;
|
|
}
|
|
}
|
|
|
|
await Promise.all(fileRetrievalPromises);
|
|
|
|
// Handle adjacent identical citations with the unique format
|
|
const adjacentCitationRegex = new RegExp(
|
|
`${escapeRegExp(uniqueCitationStart)}(\\d+)${escapeRegExp(
|
|
uniqueCitationEnd,
|
|
)}(\\s*)${escapeRegExp(uniqueCitationStart)}(\\d+)${escapeRegExp(uniqueCitationEnd)}`,
|
|
'g',
|
|
);
|
|
text = text.replace(adjacentCitationRegex, (match, num1, space, num2) => {
|
|
return num1 === num2
|
|
? `${uniqueCitationStart}${num1}${uniqueCitationEnd}`
|
|
: `${uniqueCitationStart}${num1}${uniqueCitationEnd}${space}${uniqueCitationStart}${num2}${uniqueCitationEnd}`;
|
|
});
|
|
|
|
// Remove any remaining adjacent identical citations
|
|
const remainingAdjacentRegex = new RegExp(
|
|
`(${escapeRegExp(uniqueCitationStart)}(\\d+)${escapeRegExp(uniqueCitationEnd)})\\s*\\1+`,
|
|
'g',
|
|
);
|
|
text = text.replace(remainingAdjacentRegex, '$1');
|
|
|
|
// Replace the unique citation format with the final format
|
|
text = text.replace(new RegExp(escapeRegExp(uniqueCitationStart), 'g'), '^');
|
|
text = text.replace(new RegExp(escapeRegExp(uniqueCitationEnd), 'g'), '^');
|
|
|
|
if (sources.size) {
|
|
text += '\n\n';
|
|
Array.from(sources.entries()).forEach(([source, index], arrayIndex) => {
|
|
text += `^${index}.^ ${source}${arrayIndex === sources.size - 1 ? '' : '\n'}`;
|
|
});
|
|
}
|
|
|
|
return { messages: sorted, text, edited };
|
|
}
|
|
|
|
module.exports = {
|
|
initThread,
|
|
recordUsage,
|
|
processMessages,
|
|
saveUserMessage,
|
|
checkMessageGaps,
|
|
addThreadMetadata,
|
|
mapMessagesToSteps,
|
|
saveAssistantMessage,
|
|
};
|