mirror of
https://github.com/danny-avila/LibreChat.git
synced 2026-01-06 10:38:50 +01:00
🧠 feat: User Memories for Conversational Context (#7760)
* 🧠 feat: User Memories for Conversational Context
chore: mcp typing, use `t`
WIP: first pass, Memories UI
- Added MemoryViewer component for displaying, editing, and deleting user memories.
- Integrated data provider hooks for fetching, updating, and deleting memories.
- Implemented pagination and loading states for better user experience.
- Created unit tests for MemoryViewer to ensure functionality and interaction with data provider.
- Updated translation files to include new UI strings related to memories.
chore: move mcp-related files to own directory
chore: rename librechat-mcp to librechat-api
WIP: first pass, memory processing and data schemas
chore: linting in fileSearch.js query description
chore: rename librechat-api to @librechat/api across the project
WIP: first pass, functional memory agent
feat: add MemoryEditDialog and MemoryViewer components for managing user memories
- Introduced MemoryEditDialog for editing memory entries with validation and toast notifications.
- Updated MemoryViewer to support editing and deleting memories, including pagination and loading states.
- Enhanced data provider to handle memory updates with optional original key for better management.
- Added new localization strings for memory-related UI elements.
feat: add memory permissions management
- Implemented memory permissions in the backend, allowing roles to have specific permissions for using, creating, updating, and reading memories.
- Added new API endpoints for updating memory permissions associated with roles.
- Created a new AdminSettings component for managing memory permissions in the frontend.
- Integrated memory permissions into the existing roles and permissions schemas.
- Updated the interface to include memory settings and permissions.
- Enhanced the MemoryViewer component to conditionally render admin settings based on user roles.
- Added localization support for memory permissions in the translation files.
feat: move AdminSettings component to a new position in MemoryViewer for better visibility
refactor: clean up commented code in MemoryViewer component
feat: enhance MemoryViewer with search functionality and improve MemoryEditDialog integration
- Added a search input to filter memories in the MemoryViewer component.
- Refactored MemoryEditDialog to accept children for better customization.
- Updated MemoryViewer to utilize the new EditMemoryButton and DeleteMemoryButton components for editing and deleting memories.
- Improved localization support by adding new strings for memory filtering and deletion confirmation.
refactor: optimize memory filtering in MemoryViewer using match-sorter
- Replaced manual filtering logic with match-sorter for improved search functionality.
- Enhanced performance and readability of the filteredMemories computation.
feat: enhance MemoryEditDialog with triggerRef and improve updateMemory mutation handling
feat: implement access control for MemoryEditDialog and MemoryViewer components
refactor: remove commented out code and create runMemory method
refactor: rename role based files
feat: implement access control for memory usage in AgentClient
refactor: simplify checkVisionRequest method in AgentClient by removing commented-out code
refactor: make `agents` dir in api package
refactor: migrate Azure utilities to TypeScript and consolidate imports
refactor: move sanitizeFilename function to a new file and update imports, add related tests
refactor: update LLM configuration types and consolidate Azure options in the API package
chore: linting
chore: import order
refactor: replace getLLMConfig with getOpenAIConfig and remove unused LLM configuration file
chore: update winston-daily-rotate-file to version 5.0.0 and add object-hash dependency in package-lock.json
refactor: move primeResources and optionalChainWithEmptyCheck functions to resources.ts and update imports
refactor: move createRun function to a new run.ts file and update related imports
fix: ensure safeAttachments is correctly typed as an array of TFile
chore: add node-fetch dependency and refactor fetch-related functions into packages/api/utils, removing the old generators file
refactor: enhance TEndpointOption type by using Pick to streamline endpoint fields and add new properties for model parameters and client options
feat: implement initializeOpenAIOptions function and update OpenAI types for enhanced configuration handling
fix: update types due to new TEndpointOption typing
fix: ensure safe access to group parameters in initializeOpenAIOptions function
fix: remove redundant API key validation comment in initializeOpenAIOptions function
refactor: rename initializeOpenAIOptions to initializeOpenAI for consistency and update related documentation
refactor: decouple req.body fields and tool loading from initializeAgentOptions
chore: linting
refactor: adjust column widths in MemoryViewer for improved layout
refactor: simplify agent initialization by creating loadAgent function and removing unused code
feat: add memory configuration loading and validation functions
WIP: first pass, memory processing with config
feat: implement memory callback and artifact handling
feat: implement memory artifacts display and processing updates
feat: add memory configuration options and schema validation for validKeys
fix: update MemoryEditDialog and MemoryViewer to handle memory state and display improvements
refactor: remove padding from BookmarkTable and MemoryViewer headers for consistent styling
WIP: initial tokenLimit config and move Tokenizer to @librechat/api
refactor: update mongoMeili plugin methods to use callback for better error handling
feat: enhance memory management with token tracking and usage metrics
- Added token counting for memory entries to enforce limits and provide usage statistics.
- Updated memory retrieval and update routes to include total token usage and limit.
- Enhanced MemoryEditDialog and MemoryViewer components to display memory usage and token information.
- Refactored memory processing functions to handle token limits and provide feedback on memory capacity.
feat: implement memory artifact handling in attachment handler
- Enhanced useAttachmentHandler to process memory artifacts when receiving updates.
- Introduced handleMemoryArtifact utility to manage memory updates and deletions.
- Updated query client to reflect changes in memory state based on incoming data.
refactor: restructure web search key extraction logic
- Moved the logic for extracting API keys from the webSearchAuth configuration into a dedicated function, getWebSearchKeys.
- Updated webSearchKeys to utilize the new function for improved clarity and maintainability.
- Prevents build time errors
feat: add personalization settings and memory preferences management
- Introduced a new Personalization tab in settings to manage user memory preferences.
- Implemented API endpoints and client-side logic for updating memory preferences.
- Enhanced user interface components to reflect personalization options and memory usage.
- Updated permissions to allow users to opt out of memory features.
- Added localization support for new settings and messages related to personalization.
style: personalization switch class
feat: add PersonalizationIcon and align Side Panel UI
feat: implement memory creation functionality
- Added a new API endpoint for creating memory entries, including validation for key and value.
- Introduced MemoryCreateDialog component for user interface to facilitate memory creation.
- Integrated token limit checks to prevent exceeding user memory capacity.
- Updated MemoryViewer to include a button for opening the memory creation dialog.
- Enhanced localization support for new messages related to memory creation.
feat: enhance message processing with configurable window size
- Updated AgentClient to use a configurable message window size for processing messages.
- Introduced messageWindowSize option in memory configuration schema with a default value of 5.
- Improved logic for selecting messages to process based on the configured window size.
chore: update librechat-data-provider version to 0.7.87 in package.json and package-lock.json
chore: remove OpenAPIPlugin and its associated tests
chore: remove MIGRATION_README.md as migration tasks are completed
ci: fix backend tests
chore: remove unused translation keys from localization file
chore: remove problematic test file and unused var in AgentClient
chore: remove unused import and import directly for JSDoc
* feat: add api package build stage in Dockerfile for improved modularity
* docs: reorder build steps in contributing guide for clarity
This commit is contained in:
parent
cd7dd576c1
commit
29ef91b4dd
170 changed files with 5700 additions and 3632 deletions
1
packages/api/src/endpoints/index.ts
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1
packages/api/src/endpoints/index.ts
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export * from './openai';
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2
packages/api/src/endpoints/openai/index.ts
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2
packages/api/src/endpoints/openai/index.ts
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@ -0,0 +1,2 @@
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export * from './llm';
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export * from './initialize';
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176
packages/api/src/endpoints/openai/initialize.ts
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176
packages/api/src/endpoints/openai/initialize.ts
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import {
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ErrorTypes,
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EModelEndpoint,
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resolveHeaders,
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mapModelToAzureConfig,
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} from 'librechat-data-provider';
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import type {
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LLMConfigOptions,
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UserKeyValues,
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InitializeOpenAIOptionsParams,
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OpenAIOptionsResult,
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} from '~/types';
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import { createHandleLLMNewToken } from '~/utils/generators';
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import { getAzureCredentials } from '~/utils/azure';
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import { isUserProvided } from '~/utils/common';
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import { getOpenAIConfig } from './llm';
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/**
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* Initializes OpenAI options for agent usage. This function always returns configuration
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* options and never creates a client instance (equivalent to optionsOnly=true behavior).
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*
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* @param params - Configuration parameters
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* @returns Promise resolving to OpenAI configuration options
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* @throws Error if API key is missing or user key has expired
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*/
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export const initializeOpenAI = async ({
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req,
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overrideModel,
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endpointOption,
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overrideEndpoint,
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getUserKeyValues,
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checkUserKeyExpiry,
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}: InitializeOpenAIOptionsParams): Promise<OpenAIOptionsResult> => {
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const { PROXY, OPENAI_API_KEY, AZURE_API_KEY, OPENAI_REVERSE_PROXY, AZURE_OPENAI_BASEURL } =
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process.env;
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const { key: expiresAt } = req.body;
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const modelName = overrideModel ?? req.body.model;
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const endpoint = overrideEndpoint ?? req.body.endpoint;
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if (!endpoint) {
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throw new Error('Endpoint is required');
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}
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const credentials = {
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[EModelEndpoint.openAI]: OPENAI_API_KEY,
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[EModelEndpoint.azureOpenAI]: AZURE_API_KEY,
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};
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const baseURLOptions = {
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[EModelEndpoint.openAI]: OPENAI_REVERSE_PROXY,
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[EModelEndpoint.azureOpenAI]: AZURE_OPENAI_BASEURL,
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};
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const userProvidesKey = isUserProvided(credentials[endpoint as keyof typeof credentials]);
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const userProvidesURL = isUserProvided(baseURLOptions[endpoint as keyof typeof baseURLOptions]);
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let userValues: UserKeyValues | null = null;
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if (expiresAt && (userProvidesKey || userProvidesURL)) {
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checkUserKeyExpiry(expiresAt, endpoint);
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userValues = await getUserKeyValues({ userId: req.user.id, name: endpoint });
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}
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let apiKey = userProvidesKey
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? userValues?.apiKey
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: credentials[endpoint as keyof typeof credentials];
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const baseURL = userProvidesURL
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? userValues?.baseURL
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: baseURLOptions[endpoint as keyof typeof baseURLOptions];
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const clientOptions: LLMConfigOptions = {
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proxy: PROXY ?? undefined,
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reverseProxyUrl: baseURL || undefined,
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streaming: true,
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};
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const isAzureOpenAI = endpoint === EModelEndpoint.azureOpenAI;
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const azureConfig = isAzureOpenAI && req.app.locals[EModelEndpoint.azureOpenAI];
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if (isAzureOpenAI && azureConfig) {
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const { modelGroupMap, groupMap } = azureConfig;
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const {
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azureOptions,
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baseURL: configBaseURL,
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headers = {},
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serverless,
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} = mapModelToAzureConfig({
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modelName: modelName || '',
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modelGroupMap,
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groupMap,
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});
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clientOptions.reverseProxyUrl = configBaseURL ?? clientOptions.reverseProxyUrl;
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clientOptions.headers = resolveHeaders({ ...headers, ...(clientOptions.headers ?? {}) });
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const groupName = modelGroupMap[modelName || '']?.group;
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if (groupName && groupMap[groupName]) {
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clientOptions.addParams = groupMap[groupName]?.addParams;
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clientOptions.dropParams = groupMap[groupName]?.dropParams;
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}
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apiKey = azureOptions.azureOpenAIApiKey;
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clientOptions.azure = !serverless ? azureOptions : undefined;
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if (serverless === true) {
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clientOptions.defaultQuery = azureOptions.azureOpenAIApiVersion
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? { 'api-version': azureOptions.azureOpenAIApiVersion }
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: undefined;
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if (!clientOptions.headers) {
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clientOptions.headers = {};
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}
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clientOptions.headers['api-key'] = apiKey;
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}
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} else if (isAzureOpenAI) {
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clientOptions.azure =
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userProvidesKey && userValues?.apiKey ? JSON.parse(userValues.apiKey) : getAzureCredentials();
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apiKey = clientOptions.azure?.azureOpenAIApiKey;
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}
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if (userProvidesKey && !apiKey) {
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throw new Error(
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JSON.stringify({
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type: ErrorTypes.NO_USER_KEY,
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}),
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);
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}
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if (!apiKey) {
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throw new Error(`${endpoint} API Key not provided.`);
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}
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const modelOptions = {
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...endpointOption.model_parameters,
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model: modelName,
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user: req.user.id,
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};
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const finalClientOptions: LLMConfigOptions = {
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...clientOptions,
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modelOptions,
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};
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const options = getOpenAIConfig(apiKey, finalClientOptions, endpoint);
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const openAIConfig = req.app.locals[EModelEndpoint.openAI];
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const allConfig = req.app.locals.all;
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const azureRate = modelName?.includes('gpt-4') ? 30 : 17;
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let streamRate: number | undefined;
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if (isAzureOpenAI && azureConfig) {
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streamRate = azureConfig.streamRate ?? azureRate;
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} else if (!isAzureOpenAI && openAIConfig) {
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streamRate = openAIConfig.streamRate;
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}
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if (allConfig?.streamRate) {
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streamRate = allConfig.streamRate;
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}
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if (streamRate) {
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options.llmConfig.callbacks = [
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{
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handleLLMNewToken: createHandleLLMNewToken(streamRate),
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},
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];
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}
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const result: OpenAIOptionsResult = {
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...options,
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streamRate,
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};
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return result;
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};
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156
packages/api/src/endpoints/openai/llm.ts
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156
packages/api/src/endpoints/openai/llm.ts
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import { HttpsProxyAgent } from 'https-proxy-agent';
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import { KnownEndpoints } from 'librechat-data-provider';
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import type * as t from '~/types';
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import { sanitizeModelName, constructAzureURL } from '~/utils/azure';
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import { isEnabled } from '~/utils/common';
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/**
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* Generates configuration options for creating a language model (LLM) instance.
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* @param apiKey - The API key for authentication.
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* @param options - Additional options for configuring the LLM.
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* @param endpoint - The endpoint name
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* @returns Configuration options for creating an LLM instance.
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*/
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export function getOpenAIConfig(
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apiKey: string,
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options: t.LLMConfigOptions = {},
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endpoint?: string | null,
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): t.LLMConfigResult {
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const {
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modelOptions = {},
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reverseProxyUrl,
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defaultQuery,
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headers,
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proxy,
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azure,
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streaming = true,
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addParams,
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dropParams,
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} = options;
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const llmConfig: Partial<t.ClientOptions> & Partial<t.OpenAIParameters> = Object.assign(
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{
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streaming,
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model: modelOptions.model ?? '',
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},
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modelOptions,
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);
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if (addParams && typeof addParams === 'object') {
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Object.assign(llmConfig, addParams);
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}
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// Note: OpenAI Web Search models do not support any known parameters besides `max_tokens`
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if (modelOptions.model && /gpt-4o.*search/.test(modelOptions.model)) {
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const searchExcludeParams = [
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'frequency_penalty',
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'presence_penalty',
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'temperature',
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'top_p',
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'top_k',
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'stop',
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'logit_bias',
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'seed',
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'response_format',
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'n',
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'logprobs',
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'user',
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];
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const updatedDropParams = dropParams || [];
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const combinedDropParams = [...new Set([...updatedDropParams, ...searchExcludeParams])];
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combinedDropParams.forEach((param) => {
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if (param in llmConfig) {
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delete llmConfig[param as keyof t.ClientOptions];
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}
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});
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} else if (dropParams && Array.isArray(dropParams)) {
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dropParams.forEach((param) => {
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if (param in llmConfig) {
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delete llmConfig[param as keyof t.ClientOptions];
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}
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});
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}
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let useOpenRouter = false;
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const configOptions: t.OpenAIConfiguration = {};
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if (
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(reverseProxyUrl && reverseProxyUrl.includes(KnownEndpoints.openrouter)) ||
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(endpoint && endpoint.toLowerCase().includes(KnownEndpoints.openrouter))
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) {
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useOpenRouter = true;
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llmConfig.include_reasoning = true;
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configOptions.baseURL = reverseProxyUrl;
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configOptions.defaultHeaders = Object.assign(
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{
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'HTTP-Referer': 'https://librechat.ai',
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'X-Title': 'LibreChat',
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},
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headers,
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);
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} else if (reverseProxyUrl) {
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configOptions.baseURL = reverseProxyUrl;
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if (headers) {
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configOptions.defaultHeaders = headers;
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}
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}
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if (defaultQuery) {
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configOptions.defaultQuery = defaultQuery;
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}
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if (proxy) {
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const proxyAgent = new HttpsProxyAgent(proxy);
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configOptions.httpAgent = proxyAgent;
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}
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if (azure) {
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const useModelName = isEnabled(process.env.AZURE_USE_MODEL_AS_DEPLOYMENT_NAME);
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const updatedAzure = { ...azure };
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updatedAzure.azureOpenAIApiDeploymentName = useModelName
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? sanitizeModelName(llmConfig.model || '')
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: azure.azureOpenAIApiDeploymentName;
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if (process.env.AZURE_OPENAI_DEFAULT_MODEL) {
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llmConfig.model = process.env.AZURE_OPENAI_DEFAULT_MODEL;
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}
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if (configOptions.baseURL) {
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const azureURL = constructAzureURL({
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baseURL: configOptions.baseURL,
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azureOptions: updatedAzure,
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});
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updatedAzure.azureOpenAIBasePath = azureURL.split(
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`/${updatedAzure.azureOpenAIApiDeploymentName}`,
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)[0];
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}
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Object.assign(llmConfig, updatedAzure);
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llmConfig.model = updatedAzure.azureOpenAIApiDeploymentName;
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} else {
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llmConfig.apiKey = apiKey;
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}
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if (process.env.OPENAI_ORGANIZATION && azure) {
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configOptions.organization = process.env.OPENAI_ORGANIZATION;
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}
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if (useOpenRouter && llmConfig.reasoning_effort != null) {
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llmConfig.reasoning = {
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effort: llmConfig.reasoning_effort,
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};
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delete llmConfig.reasoning_effort;
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}
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if (llmConfig.max_tokens != null) {
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llmConfig.maxTokens = llmConfig.max_tokens;
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delete llmConfig.max_tokens;
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}
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return {
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llmConfig,
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configOptions,
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};
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}
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