LibreChat/api/server/utils/import/importBatchBuilder.js
Danny Avila a6fb257bcf
📦 refactor: Consolidate DB models, encapsulating Mongoose usage in data-schemas (#11830)
* chore: move database model methods to /packages/data-schemas

* chore: add TypeScript ESLint rule to warn on unused variables

* refactor: model imports to streamline access

- Consolidated model imports across various files to improve code organization and reduce redundancy.
- Updated imports for models such as Assistant, Message, Conversation, and others to a unified import path.
- Adjusted middleware and service files to reflect the new import structure, ensuring functionality remains intact.
- Enhanced test files to align with the new import paths, maintaining test coverage and integrity.

* chore: migrate database models to packages/data-schemas and refactor all direct Mongoose Model usage outside of data-schemas

* test: update agent model mocks in unit tests

- Added `getAgent` mock to `client.test.js` to enhance test coverage for agent-related functionality.
- Removed redundant `getAgent` and `getAgents` mocks from `openai.spec.js` and `responses.unit.spec.js` to streamline test setup and reduce duplication.
- Ensured consistency in agent mock implementations across test files.

* fix: update types in data-schemas

* refactor: enhance type definitions in transaction and spending methods

- Updated type definitions in `checkBalance.ts` to use specific request and response types.
- Refined `spendTokens.ts` to utilize a new `SpendTxData` interface for better clarity and type safety.
- Improved transaction handling in `transaction.ts` by introducing `TransactionResult` and `TxData` interfaces, ensuring consistent data structures across methods.
- Adjusted unit tests in `transaction.spec.ts` to accommodate new type definitions and enhance robustness.

* refactor: streamline model imports and enhance code organization

- Consolidated model imports across various controllers and services to a unified import path, improving code clarity and reducing redundancy.
- Updated multiple files to reflect the new import structure, ensuring all functionalities remain intact.
- Enhanced overall code organization by removing duplicate import statements and optimizing the usage of model methods.

* feat: implement loadAddedAgent and refactor agent loading logic

- Introduced `loadAddedAgent` function to handle loading agents from added conversations, supporting multi-convo parallel execution.
- Created a new `load.ts` file to encapsulate agent loading functionalities, including `loadEphemeralAgent` and `loadAgent`.
- Updated the `index.ts` file to export the new `load` module instead of the deprecated `loadAgent`.
- Enhanced type definitions and improved error handling in the agent loading process.
- Adjusted unit tests to reflect changes in the agent loading structure and ensure comprehensive coverage.

* refactor: enhance balance handling with new update interface

- Introduced `IBalanceUpdate` interface to streamline balance update operations across the codebase.
- Updated `upsertBalanceFields` method signatures in `balance.ts`, `transaction.ts`, and related tests to utilize the new interface for improved type safety.
- Adjusted type imports in `balance.spec.ts` to include `IBalanceUpdate`, ensuring consistency in balance management functionalities.
- Enhanced overall code clarity and maintainability by refining type definitions related to balance operations.

* feat: add unit tests for loadAgent functionality and enhance agent loading logic

- Introduced comprehensive unit tests for the `loadAgent` function, covering various scenarios including null and empty agent IDs, loading of ephemeral agents, and permission checks.
- Enhanced the `initializeClient` function by moving `getConvoFiles` to the correct position in the database method exports, ensuring proper functionality.
- Improved test coverage for agent loading, including handling of non-existent agents and user permissions.

* chore: reorder memory method exports for consistency

- Moved `deleteAllUserMemories` to the correct position in the exported memory methods, ensuring a consistent and logical order of method exports in `memory.ts`.
2026-02-18 00:31:36 -05:00

166 lines
5.9 KiB
JavaScript

const { v4: uuidv4 } = require('uuid');
const { logger } = require('@librechat/data-schemas');
const { EModelEndpoint, Constants, openAISettings } = require('librechat-data-provider');
const { bulkIncrementTagCounts, bulkSaveConvos, bulkSaveMessages } = require('~/models');
/**
* Factory function for creating an instance of ImportBatchBuilder.
* @param {string} requestUserId - The ID of the user making the request.
* @returns {ImportBatchBuilder} - The newly created ImportBatchBuilder instance.
*/
function createImportBatchBuilder(requestUserId) {
return new ImportBatchBuilder(requestUserId);
}
/**
* Class for building a batch of conversations and messages and pushing them to DB for Conversation Import functionality
*/
class ImportBatchBuilder {
/**
* Creates an instance of ImportBatchBuilder.
* @param {string} requestUserId - The ID of the user making the import request.
*/
constructor(requestUserId) {
this.requestUserId = requestUserId;
this.conversations = [];
this.messages = [];
}
/**
* Starts a new conversation in the batch.
* @param {string} [endpoint=EModelEndpoint.openAI] - The endpoint for the conversation. Defaults to EModelEndpoint.openAI.
* @returns {void}
*/
startConversation(endpoint) {
// we are simplifying by using a single model for the entire conversation
this.endpoint = endpoint || EModelEndpoint.openAI;
this.conversationId = uuidv4();
this.lastMessageId = Constants.NO_PARENT;
}
/**
* Adds a user message to the current conversation.
* @param {string} text - The text of the user message.
* @returns {object} The saved message object.
*/
addUserMessage(text) {
const message = this.saveMessage({ text, sender: 'user', isCreatedByUser: true });
return message;
}
/**
* Adds a GPT message to the current conversation.
* @param {string} text - The text of the GPT message.
* @param {string} [model='defaultModel'] - The model used for generating the GPT message. Defaults to 'defaultModel'.
* @param {string} [sender='GPT-3.5'] - The sender of the GPT message. Defaults to 'GPT-3.5'.
* @returns {object} The saved message object.
*/
addGptMessage(text, model, sender = 'GPT-3.5') {
const message = this.saveMessage({
text,
sender,
isCreatedByUser: false,
model: model || openAISettings.model.default,
});
return message;
}
/**
* Finishes the current conversation and adds it to the batch.
* @param {string} [title='Imported Chat'] - The title of the conversation. Defaults to 'Imported Chat'.
* @param {Date} [createdAt] - The creation date of the conversation.
* @param {TConversation} [originalConvo] - The original conversation.
* @returns {{ conversation: TConversation, messages: TMessage[] }} The resulting conversation and messages.
*/
finishConversation(title, createdAt, originalConvo = {}) {
const convo = {
...originalConvo,
user: this.requestUserId,
conversationId: this.conversationId,
title: title || 'Imported Chat',
createdAt: createdAt,
updatedAt: createdAt,
overrideTimestamp: true,
endpoint: this.endpoint,
model: originalConvo.model ?? openAISettings.model.default,
};
convo._id && delete convo._id;
this.conversations.push(convo);
return { conversation: convo, messages: this.messages };
}
/**
* Saves the batch of conversations and messages to the DB.
* Also increments tag counts for any existing tags.
* @returns {Promise<void>} A promise that resolves when the batch is saved.
* @throws {Error} If there is an error saving the batch.
*/
async saveBatch() {
try {
const promises = [];
promises.push(bulkSaveConvos(this.conversations));
promises.push(bulkSaveMessages(this.messages, true));
promises.push(
bulkIncrementTagCounts(
this.requestUserId,
this.conversations.flatMap((convo) => convo.tags),
),
);
await Promise.all(promises);
logger.debug(
`user: ${this.requestUserId} | Added ${this.conversations.length} conversations and ${this.messages.length} messages to the DB.`,
);
} catch (error) {
logger.error('Error saving batch', error);
throw error;
}
}
/**
* Saves a message to the current conversation.
* @param {object} messageDetails - The details of the message.
* @param {string} messageDetails.text - The text of the message.
* @param {string} messageDetails.sender - The sender of the message.
* @param {string} [messageDetails.messageId] - The ID of the current message.
* @param {boolean} messageDetails.isCreatedByUser - Indicates whether the message is created by the user.
* @param {string} [messageDetails.model] - The model used for generating the message.
* @param {string} [messageDetails.endpoint] - The endpoint used for generating the message.
* @param {string} [messageDetails.parentMessageId=this.lastMessageId] - The ID of the parent message.
* @param {Partial<TMessage>} messageDetails.rest - Additional properties that may be included in the message.
* @returns {object} The saved message object.
*/
saveMessage({
text,
sender,
isCreatedByUser,
model,
messageId,
parentMessageId = this.lastMessageId,
endpoint,
...rest
}) {
const newMessageId = messageId ?? uuidv4();
const message = {
...rest,
parentMessageId,
messageId: newMessageId,
conversationId: this.conversationId,
isCreatedByUser: isCreatedByUser,
model: model || this.model,
user: this.requestUserId,
endpoint: endpoint ?? this.endpoint,
unfinished: false,
isEdited: false,
error: false,
sender,
text,
};
message._id && delete message._id;
this.lastMessageId = newMessageId;
this.messages.push(message);
return message;
}
}
module.exports = { ImportBatchBuilder, createImportBatchBuilder };