LibreChat/api/server/controllers/assistants/v1.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

383 lines
12 KiB
JavaScript

const fs = require('fs').promises;
const { logger } = require('@librechat/data-schemas');
const { FileContext } = require('librechat-data-provider');
const { deleteFileByFilter, updateAssistantDoc, getAssistants } = require('~/models');
const { uploadImageBuffer, filterFile } = require('~/server/services/Files/process');
const validateAuthor = require('~/server/middleware/assistants/validateAuthor');
const { getStrategyFunctions } = require('~/server/services/Files/strategies');
const { deleteAssistantActions } = require('~/server/services/ActionService');
const { getOpenAIClient, fetchAssistants } = require('./helpers');
const { getCachedTools } = require('~/server/services/Config');
const { manifestToolMap } = require('~/app/clients/tools');
/**
* Create an assistant.
* @route POST /assistants
* @param {AssistantCreateParams} req.body - The assistant creation parameters.
* @returns {Assistant} 201 - success response - application/json
*/
const createAssistant = async (req, res) => {
try {
const { openai } = await getOpenAIClient({ req, res });
const {
tools = [],
endpoint,
conversation_starters,
append_current_datetime,
...assistantData
} = req.body;
delete assistantData.conversation_starters;
delete assistantData.append_current_datetime;
const toolDefinitions = (await getCachedTools()) ?? {};
assistantData.tools = tools
.map((tool) => {
if (typeof tool !== 'string') {
return tool;
}
const toolDef = toolDefinitions[tool];
if (!toolDef && manifestToolMap[tool] && manifestToolMap[tool].toolkit === true) {
return Object.entries(toolDefinitions)
.filter(([key]) => key.startsWith(`${tool}_`))
.map(([_, val]) => val);
}
return toolDef;
})
.filter((tool) => tool)
.flat();
let azureModelIdentifier = null;
if (openai.locals?.azureOptions) {
azureModelIdentifier = assistantData.model;
assistantData.model = openai.locals.azureOptions.azureOpenAIApiDeploymentName;
}
assistantData.metadata = {
author: req.user.id,
endpoint,
};
const assistant = await openai.beta.assistants.create(assistantData);
const createData = { user: req.user.id };
if (conversation_starters) {
createData.conversation_starters = conversation_starters;
}
if (append_current_datetime !== undefined) {
createData.append_current_datetime = append_current_datetime;
}
const document = await updateAssistantDoc({ assistant_id: assistant.id }, createData);
if (azureModelIdentifier) {
assistant.model = azureModelIdentifier;
}
if (document.conversation_starters) {
assistant.conversation_starters = document.conversation_starters;
}
if (append_current_datetime !== undefined) {
assistant.append_current_datetime = append_current_datetime;
}
logger.debug('/assistants/', assistant);
res.status(201).json(assistant);
} catch (error) {
logger.error('[/assistants] Error creating assistant', error);
res.status(500).json({ error: error.message });
}
};
/**
* Retrieves an assistant.
* @route GET /assistants/:id
* @param {string} req.params.id - Assistant identifier.
* @returns {Assistant} 200 - success response - application/json
*/
const retrieveAssistant = async (req, res) => {
try {
/* NOTE: not actually being used right now */
const { openai } = await getOpenAIClient({ req, res });
const assistant_id = req.params.id;
const assistant = await openai.beta.assistants.retrieve(assistant_id);
res.json(assistant);
} catch (error) {
logger.error('[/assistants/:id] Error retrieving assistant', error);
res.status(500).json({ error: error.message });
}
};
/**
* Modifies an assistant.
* @route PATCH /assistants/:id
* @param {object} req - Express Request
* @param {object} req.params - Request params
* @param {string} req.params.id - Assistant identifier.
* @param {AssistantUpdateParams} req.body - The assistant update parameters.
* @returns {Assistant} 200 - success response - application/json
*/
const patchAssistant = async (req, res) => {
try {
const { openai } = await getOpenAIClient({ req, res });
await validateAuthor({ req, openai });
const assistant_id = req.params.id;
const {
endpoint: _e,
conversation_starters,
append_current_datetime,
...updateData
} = req.body;
const toolDefinitions = (await getCachedTools()) ?? {};
updateData.tools = (updateData.tools ?? [])
.map((tool) => {
if (typeof tool !== 'string') {
return tool;
}
const toolDef = toolDefinitions[tool];
if (!toolDef && manifestToolMap[tool] && manifestToolMap[tool].toolkit === true) {
return Object.entries(toolDefinitions)
.filter(([key]) => key.startsWith(`${tool}_`))
.map(([_, val]) => val);
}
return toolDef;
})
.filter((tool) => tool)
.flat();
if (openai.locals?.azureOptions && updateData.model) {
updateData.model = openai.locals.azureOptions.azureOpenAIApiDeploymentName;
}
const updatedAssistant = await openai.beta.assistants.update(assistant_id, updateData);
if (conversation_starters !== undefined) {
const conversationStartersUpdate = await updateAssistantDoc(
{ assistant_id },
{ conversation_starters },
);
updatedAssistant.conversation_starters = conversationStartersUpdate.conversation_starters;
}
if (append_current_datetime !== undefined) {
await updateAssistantDoc({ assistant_id }, { append_current_datetime });
updatedAssistant.append_current_datetime = append_current_datetime;
}
res.json(updatedAssistant);
} catch (error) {
logger.error('[/assistants/:id] Error updating assistant', error);
res.status(500).json({ error: error.message });
}
};
/**
* Deletes an assistant.
* @route DELETE /assistants/:id
* @param {object} req - Express Request
* @param {object} req.params - Request params
* @param {string} req.params.id - Assistant identifier.
* @returns {Assistant} 200 - success response - application/json
*/
const deleteAssistant = async (req, res) => {
try {
const { openai } = await getOpenAIClient({ req, res });
await validateAuthor({ req, openai });
const assistant_id = req.params.id;
const deletionStatus = await openai.beta.assistants.delete(assistant_id);
if (deletionStatus?.deleted) {
await deleteAssistantActions({ req, assistant_id });
}
res.json(deletionStatus);
} catch (error) {
logger.error('[/assistants/:id] Error deleting assistant', error);
res.status(500).json({ error: 'Error deleting assistant' });
}
};
/**
* Returns a list of assistants.
* @route GET /assistants
* @param {object} req - Express Request
* @param {AssistantListParams} req.query - The assistant list parameters for pagination and sorting.
* @returns {AssistantListResponse} 200 - success response - application/json
*/
const listAssistants = async (req, res) => {
try {
const body = await fetchAssistants({ req, res });
res.json(body);
} catch (error) {
logger.error('[/assistants] Error listing assistants', error);
res.status(500).json({ message: 'Error listing assistants' });
}
};
/**
* Filter assistants based on configuration.
*
* @param {object} params - The parameters object.
* @param {string} params.userId - The user ID to filter private assistants.
* @param {AssistantDocument[]} params.assistants - The list of assistants to filter.
* @param {Partial<TAssistantEndpoint>} [params.assistantsConfig] - The assistant configuration.
* @returns {AssistantDocument[]} - The filtered list of assistants.
*/
function filterAssistantDocs({ documents, userId, assistantsConfig = {} }) {
const { supportedIds, excludedIds, privateAssistants } = assistantsConfig;
const removeUserId = (doc) => {
const { user: _u, ...document } = doc;
return document;
};
if (privateAssistants) {
return documents.filter((doc) => userId === doc.user.toString()).map(removeUserId);
} else if (supportedIds?.length) {
return documents.filter((doc) => supportedIds.includes(doc.assistant_id)).map(removeUserId);
} else if (excludedIds?.length) {
return documents.filter((doc) => !excludedIds.includes(doc.assistant_id)).map(removeUserId);
}
return documents.map(removeUserId);
}
/**
* Returns a list of the user's assistant documents (metadata saved to database).
* @route GET /assistants/documents
* @returns {AssistantDocument[]} 200 - success response - application/json
*/
const getAssistantDocuments = async (req, res) => {
try {
const appConfig = req.config;
const endpoint = req.query?.endpoint;
const assistantsConfig = appConfig.endpoints?.[endpoint];
const documents = await getAssistants(
{},
{
user: 1,
assistant_id: 1,
conversation_starters: 1,
createdAt: 1,
updatedAt: 1,
append_current_datetime: 1,
},
);
const docs = filterAssistantDocs({
documents,
userId: req.user.id,
assistantsConfig,
});
res.json(docs);
} catch (error) {
logger.error('[/assistants/documents] Error listing assistant documents', error);
res.status(500).json({ error: error.message });
}
};
/**
* Uploads and updates an avatar for a specific assistant.
* @route POST /:assistant_id/avatar
* @param {object} req - Express Request
* @param {object} req.params - Request params
* @param {string} req.params.assistant_id - The ID of the assistant.
* @param {Express.Multer.File} req.file - The avatar image file.
* @param {object} req.body - Request body
* @returns {Object} 200 - success response - application/json
*/
const uploadAssistantAvatar = async (req, res) => {
try {
const appConfig = req.config;
filterFile({ req, file: req.file, image: true, isAvatar: true });
const { assistant_id } = req.params;
if (!assistant_id) {
return res.status(400).json({ message: 'Assistant ID is required' });
}
const { openai } = await getOpenAIClient({ req, res });
await validateAuthor({ req, openai });
const buffer = await fs.readFile(req.file.path);
const image = await uploadImageBuffer({
req,
context: FileContext.avatar,
metadata: { buffer },
});
let _metadata;
try {
const assistant = await openai.beta.assistants.retrieve(assistant_id);
if (assistant) {
_metadata = assistant.metadata;
}
} catch (error) {
logger.error('[/:assistant_id/avatar] Error fetching assistant', error);
_metadata = {};
}
if (_metadata.avatar && _metadata.avatar_source) {
const { deleteFile } = getStrategyFunctions(_metadata.avatar_source);
try {
await deleteFile(req, { filepath: _metadata.avatar });
await deleteFileByFilter({ user: req.user.id, filepath: _metadata.avatar });
} catch (error) {
logger.error('[/:assistant_id/avatar] Error deleting old avatar', error);
}
}
const metadata = {
..._metadata,
avatar: image.filepath,
avatar_source: appConfig.fileStrategy,
};
const promises = [];
promises.push(
updateAssistantDoc(
{ assistant_id },
{
avatar: {
filepath: image.filepath,
source: appConfig.fileStrategy,
},
user: req.user.id,
},
),
);
promises.push(openai.beta.assistants.update(assistant_id, { metadata }));
const resolved = await Promise.all(promises);
res.status(201).json(resolved[1]);
} catch (error) {
const message = 'An error occurred while updating the Assistant Avatar';
logger.error(message, error);
res.status(500).json({ message });
} finally {
try {
await fs.unlink(req.file.path);
logger.debug('[/:agent_id/avatar] Temp. image upload file deleted');
} catch {
logger.debug('[/:agent_id/avatar] Temp. image upload file already deleted');
}
}
};
module.exports = {
createAssistant,
retrieveAssistant,
patchAssistant,
deleteAssistant,
listAssistants,
getAssistantDocuments,
uploadAssistantAvatar,
};