LibreChat/api/server/services/Config/loadDefaultModels.js

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const { logger } = require('@librechat/data-schemas');
const { EModelEndpoint } = require('librechat-data-provider');
const {
getAnthropicModels,
getBedrockModels,
getOpenAIModels,
getGoogleModels,
🧵 refactor: Migrate Endpoint Initialization to TypeScript (#10794) * refactor: move endpoint initialization methods to typescript * refactor: move agent init to packages/api - Introduced `initialize.ts` for agent initialization, including file processing and tool loading. - Updated `resources.ts` to allow optional appConfig parameter. - Enhanced endpoint configuration handling in various initialization files to support model parameters. - Added new artifacts and prompts for React component generation. - Refactored existing code to improve type safety and maintainability. * refactor: streamline endpoint initialization and enhance type safety - Updated initialization functions across various endpoints to use a consistent request structure, replacing `unknown` types with `ServerResponse`. - Simplified request handling by directly extracting keys from the request body. - Improved type safety by ensuring user IDs are safely accessed with optional chaining. - Removed unnecessary parameters and streamlined model options handling for better clarity and maintainability. * refactor: moved ModelService and extractBaseURL to packages/api - Added comprehensive tests for the models fetching functionality, covering scenarios for OpenAI, Anthropic, Google, and Ollama models. - Updated existing endpoint index to include the new models module. - Enhanced utility functions for URL extraction and model data processing. - Improved type safety and error handling across the models fetching logic. * refactor: consolidate utility functions and remove unused files - Merged `deriveBaseURL` and `extractBaseURL` into the `@librechat/api` module for better organization. - Removed redundant utility files and their associated tests to streamline the codebase. - Updated imports across various client files to utilize the new consolidated functions. - Enhanced overall maintainability by reducing the number of utility modules. * refactor: replace ModelService references with direct imports from @librechat/api and remove ModelService file * refactor: move encrypt/decrypt methods and key db methods to data-schemas, use `getProviderConfig` from `@librechat/api` * chore: remove unused 'res' from options in AgentClient * refactor: file model imports and methods - Updated imports in various controllers and services to use the unified file model from '~/models' instead of '~/models/File'. - Consolidated file-related methods into a new file methods module in the data-schemas package. - Added comprehensive tests for file methods including creation, retrieval, updating, and deletion. - Enhanced the initializeAgent function to accept dependency injection for file-related methods. - Improved error handling and logging in file methods. * refactor: streamline database method references in agent initialization * refactor: enhance file method tests and update type references to IMongoFile * refactor: consolidate database method imports in agent client and initialization * chore: remove redundant import of initializeAgent from @librechat/api * refactor: move checkUserKeyExpiry utility to @librechat/api and update references across endpoints * refactor: move updateUserPlugins logic to user.ts and simplify UserController * refactor: update imports for user key management and remove UserService * refactor: remove unused Anthropics and Bedrock endpoint files and clean up imports * refactor: consolidate and update encryption imports across various files to use @librechat/data-schemas * chore: update file model mock to use unified import from '~/models' * chore: import order * refactor: remove migrated to TS agent.js file and its associated logic from the endpoints * chore: add reusable function to extract imports from source code in unused-packages workflow * chore: enhance unused-packages workflow to include @librechat/api dependencies and improve dependency extraction * chore: improve dependency extraction in unused-packages workflow with enhanced error handling and debugging output * chore: add detailed debugging output to unused-packages workflow for better visibility into unused dependencies and exclusion lists * chore: refine subpath handling in unused-packages workflow to correctly process scoped and non-scoped package imports * chore: clean up unused debug output in unused-packages workflow and reorganize type imports in initialize.ts
2025-12-03 17:21:41 -05:00
} = require('@librechat/api');
🤖 feat: Anthropic Vertex AI Support (#10780) * feat: Add Anthropic Vertex AI Support * Remove changes from the unused AnthropicClient class * Add @anthropic-ai/vertex-sdk as peerDependency to packages/api * Clean up Vertex AI credentials handling * feat: websearch header * feat: add prompt caching support for Anthropic Vertex AI - Support both OpenAI format (input_token_details) and Anthropic format (cache_*_input_tokens) for token usage tracking - Filter out unsupported anthropic-beta header values for Vertex AI (prompt-caching, max-tokens, output-128k, token-efficient-tools, context-1m) * ✨ feat: Add Vertex AI support for Anthropic models - Introduced configuration options for running Anthropic models via Google Cloud Vertex AI in the YAML file. - Updated ModelService to prioritize Vertex AI models from the configuration. - Enhanced endpoint configuration to enable Anthropic endpoint when Vertex AI is configured. - Implemented validation and processing for Vertex AI credentials and options. - Added new types and schemas for Vertex AI configuration in the data provider. - Created utility functions for loading and validating Vertex AI credentials and configurations. - Updated various services to integrate Vertex AI options into the Anthropic client setup. * 🔒 fix: Improve error handling for missing credentials in LLM configuration - Updated the `getLLMConfig` function to throw a specific error message when credentials are missing, enhancing clarity for users. - Refactored the `parseCredentials` function to handle plain API key strings more gracefully, returning them wrapped in an object if JSON parsing fails. * 🔧 refactor: Clean up code formatting and improve readability - Updated the `setOptions` method in `AgentClient` to use a parameter name for clarity. - Refactored error handling in `loadDefaultModels` for better readability. - Removed unnecessary blank lines in `initialize.js`, `endpoints.ts`, and `vertex.ts` to streamline the code. - Enhanced formatting in `validateVertexConfig` for improved consistency and clarity. * 🔧 refactor: Enhance Vertex AI Model Configuration and Integration - Updated the YAML configuration to support visible model names and deployment mappings for Vertex AI. - Refactored the `loadDefaultModels` function to utilize the new model name structure. - Improved the `initializeClient` function to pass full Vertex AI configuration, including model mappings. - Added utility functions to map visible model names to deployment names, enhancing the integration of Vertex AI models. - Updated various services and types to accommodate the new model configuration schema and improve overall clarity and functionality. * 🔧 chore: Update @anthropic-ai/sdk dependency to version 0.71.0 in package.json and package-lock.json * refactor: Change clientOptions declaration from let to const in initialize.ts for better code clarity * chore: repository cleanup * 🌊 feat: Resumable LLM Streams with Horizontal Scaling (#10926) * ✨ feat: Implement Resumable Generation Jobs with SSE Support - Introduced GenerationJobManager to handle resumable LLM generation jobs independently of HTTP connections. - Added support for subscribing to ongoing generation jobs via SSE, allowing clients to reconnect and receive updates without losing progress. - Enhanced existing agent controllers and routes to integrate resumable functionality, including job creation, completion, and error handling. - Updated client-side hooks to manage adaptive SSE streams, switching between standard and resumable modes based on user settings. - Added UI components and settings for enabling/disabling resumable streams, improving user experience during unstable connections. * WIP: resuming * WIP: resumable stream * feat: Enhance Stream Management with Abort Functionality - Updated the abort endpoint to support aborting ongoing generation streams using either streamId or conversationId. - Introduced a new mutation hook `useAbortStreamMutation` for client-side integration. - Added `useStreamStatus` query to monitor stream status and facilitate resuming conversations. - Enhanced `useChatHelpers` to incorporate abort functionality when stopping generation. - Improved `useResumableSSE` to handle stream errors and token refresh seamlessly. - Updated `useResumeOnLoad` to check for active streams and resume conversations appropriately. * fix: Update query parameter handling in useChatHelpers - Refactored the logic for determining the query parameter used in fetching messages to prioritize paramId from the URL, falling back to conversationId only if paramId is not available. This change ensures consistency with the ChatView component's expectations. * fix: improve syncing when switching conversations * fix: Prevent memory leaks in useResumableSSE by clearing handler maps on stream completion and cleanup * fix: Improve content type mismatch handling in useStepHandler - Enhanced the condition for detecting content type mismatches to include additional checks, ensuring more robust validation of content types before processing updates. * fix: Allow dynamic content creation in useChatFunctions - Updated the initial response handling to avoid pre-initializing content types, enabling dynamic creation of content parts based on incoming delta events. This change supports various content types such as think and text. * fix: Refine response message handling in useStepHandler - Updated logic to determine the appropriate response message based on the last message's origin, ensuring correct message replacement or appending based on user interaction. This change enhances the accuracy of message updates in the chat flow. * refactor: Enhance GenerationJobManager with In-Memory Implementations - Introduced InMemoryJobStore, InMemoryEventTransport, and InMemoryContentState for improved job management and event handling. - Updated GenerationJobManager to utilize these new implementations, allowing for better separation of concerns and easier maintenance. - Enhanced job metadata handling to support user messages and response IDs for resumable functionality. - Improved cleanup and state management processes to prevent memory leaks and ensure efficient resource usage. * refactor: Enhance GenerationJobManager with improved subscriber handling - Updated RuntimeJobState to include allSubscribersLeftHandlers for managing client disconnections without affecting subscriber count. - Refined createJob and subscribe methods to ensure generation starts only when the first real client connects. - Added detailed documentation for methods and properties to clarify the synchronization of job generation with client readiness. - Improved logging for subscriber checks and event handling to facilitate debugging and monitoring. * chore: Adjust timeout for subscriber readiness in ResumableAgentController - Reduced the timeout duration from 5000ms to 2500ms in the startGeneration function to improve responsiveness when waiting for subscriber readiness. This change aims to enhance the efficiency of the agent's background generation process. * refactor: Update GenerationJobManager documentation and structure - Enhanced the documentation for GenerationJobManager to clarify the architecture and pluggable service design. - Updated comments to reflect the potential for Redis integration and the need for async refactoring. - Improved the structure of the GenerationJob facade to emphasize the unified API while allowing for implementation swapping without affecting consumer code. * refactor: Convert GenerationJobManager methods to async for improved performance - Updated methods in GenerationJobManager and InMemoryJobStore to be asynchronous, enhancing the handling of job creation, retrieval, and management. - Adjusted the ResumableAgentController and related routes to await job operations, ensuring proper flow and error handling. - Increased timeout duration in ResumableAgentController's startGeneration function to 3500ms for better subscriber readiness management. * refactor: Simplify initial response handling in useChatFunctions - Removed unnecessary pre-initialization of content types in the initial response, allowing for dynamic content creation based on incoming delta events. This change enhances flexibility in handling various content types in the chat flow. * refactor: Clarify content handling logic in useStepHandler - Updated comments to better explain the handling of initialContent and existingContent in edit and resume scenarios. - Simplified the logic for merging content, ensuring that initialContent is used directly when available, improving clarity and maintainability. * refactor: Improve message handling logic in useStepHandler - Enhanced the logic for managing messages in multi-tab scenarios, ensuring that the most up-to-date message history is utilized. - Removed existing response placeholders and ensured user messages are included, improving the accuracy of message updates in the chat flow. * fix: remove unnecessary content length logging in the chat stream response, simplifying the debug message while retaining essential information about run steps. This change enhances clarity in logging without losing critical context. * refactor: Integrate streamId handling for improved resumable functionality for attachments - Added streamId parameter to various functions to support resumable mode in tool loading and memory processing. - Updated related methods to ensure proper handling of attachments and responses based on the presence of streamId, enhancing the overall streaming experience. - Improved logging and attachment management to accommodate both standard and resumable modes. * refactor: Streamline abort handling and integrate GenerationJobManager for improved job management - Removed the abortControllers middleware and integrated abort handling directly into GenerationJobManager. - Updated abortMessage function to utilize GenerationJobManager for aborting jobs by conversation ID, enhancing clarity and efficiency. - Simplified cleanup processes and improved error handling during abort operations. - Enhanced metadata management for jobs, including endpoint and model information, to facilitate better tracking and resource management. * refactor: Unify streamId and conversationId handling for improved job management - Updated ResumableAgentController and AgentController to generate conversationId upfront, ensuring it matches streamId for consistency. - Simplified job creation and metadata management by removing redundant conversationId updates from callbacks. - Refactored abortMiddleware and related methods to utilize the unified streamId/conversationId approach, enhancing clarity in job handling. - Removed deprecated methods from GenerationJobManager and InMemoryJobStore, streamlining the codebase and improving maintainability. * refactor: Enhance resumable SSE handling with improved UI state management and error recovery - Added UI state restoration on successful SSE connection to indicate ongoing submission. - Implemented detailed error handling for network failures, including retry logic with exponential backoff. - Introduced abort event handling to reset UI state on intentional stream closure. - Enhanced debugging capabilities for testing reconnection and clean close scenarios. - Updated generation function to retry on network errors, improving resilience during submission processes. * refactor: Consolidate content state management into IJobStore for improved job handling - Removed InMemoryContentState and integrated its functionality into InMemoryJobStore, streamlining content state management. - Updated GenerationJobManager to utilize jobStore for content state operations, enhancing clarity and reducing redundancy. - Introduced RedisJobStore for horizontal scaling, allowing for efficient job management and content reconstruction from chunks. - Updated IJobStore interface to reflect changes in content state handling, ensuring consistency across implementations. * feat: Introduce Redis-backed stream services for enhanced job management - Added createStreamServices function to configure job store and event transport, supporting both Redis and in-memory options. - Updated GenerationJobManager to allow configuration with custom job stores and event transports, improving flexibility for different deployment scenarios. - Refactored IJobStore interface to support asynchronous content retrieval, ensuring compatibility with Redis implementations. - Implemented RedisEventTransport for real-time event delivery across instances, enhancing scalability and responsiveness. - Updated InMemoryJobStore to align with new async patterns for content and run step retrieval, ensuring consistent behavior across storage options. * refactor: Remove redundant debug logging in GenerationJobManager and RedisEventTransport - Eliminated unnecessary debug statements in GenerationJobManager related to subscriber actions and job updates, enhancing log clarity. - Removed debug logging in RedisEventTransport for subscription and subscriber disconnection events, streamlining the logging output. - Cleaned up debug messages in RedisJobStore to focus on essential information, improving overall logging efficiency. * refactor: Enhance job state management and TTL configuration in RedisJobStore - Updated the RedisJobStore to allow customizable TTL values for job states, improving flexibility in job management. - Refactored the handling of job expiration and cleanup processes to align with new TTL configurations. - Simplified the response structure in the chat status endpoint by consolidating state retrieval, enhancing clarity and performance. - Improved comments and documentation for better understanding of the changes made. * refactor: cleanupOnComplete option to GenerationJobManager for flexible resource management - Introduced a new configuration option, cleanupOnComplete, allowing immediate cleanup of event transport and job resources upon job completion. - Updated completeJob and abortJob methods to respect the cleanupOnComplete setting, enhancing memory management. - Improved cleanup logic in the cleanup method to handle orphaned resources effectively. - Enhanced documentation and comments for better clarity on the new functionality. * refactor: Update TTL configuration for completed jobs in InMemoryJobStore - Changed the TTL for completed jobs from 5 minutes to 0, allowing for immediate cleanup. - Enhanced cleanup logic to respect the new TTL setting, improving resource management. - Updated comments for clarity on the behavior of the TTL configuration. * refactor: Enhance RedisJobStore with local graph caching for improved performance - Introduced a local cache for graph references using WeakRef to optimize reconnects for the same instance. - Updated job deletion and cleanup methods to manage the local cache effectively, ensuring stale entries are removed. - Enhanced content retrieval methods to prioritize local cache access, reducing Redis round-trips for same-instance reconnects. - Improved documentation and comments for clarity on the caching mechanism and its benefits. * feat: Add integration tests for GenerationJobManager, RedisEventTransport, and RedisJobStore, add Redis Cluster support - Introduced comprehensive integration tests for GenerationJobManager, covering both in-memory and Redis modes to ensure consistent job management and event handling. - Added tests for RedisEventTransport to validate pub/sub functionality, including cross-instance event delivery and error handling. - Implemented integration tests for RedisJobStore, focusing on multi-instance job access, content reconstruction from chunks, and consumer group behavior. - Enhanced test setup and teardown processes to ensure a clean environment for each test run, improving reliability and maintainability. * fix: Improve error handling in GenerationJobManager for allSubscribersLeft handlers - Enhanced the error handling logic when retrieving content parts for allSubscribersLeft handlers, ensuring that any failures are logged appropriately. - Updated the promise chain to catch errors from getContentParts, improving robustness and clarity in error reporting. * ci: Improve Redis client disconnection handling in integration tests - Updated the afterAll cleanup logic in integration tests for GenerationJobManager, RedisEventTransport, and RedisJobStore to use `quit()` for graceful disconnection of the Redis client. - Added fallback to `disconnect()` if `quit()` fails, enhancing robustness in resource management during test teardown. - Improved comments for clarity on the disconnection process and error handling. * refactor: Enhance GenerationJobManager and event transports for improved resource management - Updated GenerationJobManager to prevent immediate cleanup of eventTransport upon job completion, allowing final events to transmit fully before cleanup. - Added orphaned stream cleanup logic in GenerationJobManager to handle streams without corresponding jobs. - Introduced getTrackedStreamIds method in both InMemoryEventTransport and RedisEventTransport for better management of orphaned streams. - Improved comments for clarity on resource management and cleanup processes. * refactor: Update GenerationJobManager and ResumableAgentController for improved event handling - Modified GenerationJobManager to resolve readyPromise immediately, eliminating startup latency and allowing early event buffering for late subscribers. - Enhanced event handling logic to replay buffered events when the first subscriber connects, ensuring no events are lost due to race conditions. - Updated comments for clarity on the new event synchronization mechanism and its benefits in both Redis and in-memory modes. * fix: Update cache integration test command for stream to ensure proper execution - Modified the test command for cache integration related to streams by adding the --forceExit flag to prevent hanging tests. - This change enhances the reliability of the test suite by ensuring all tests complete as expected. * feat: Add active job management for user and show progress in conversation list - Implemented a new endpoint to retrieve active generation job IDs for the current user, enhancing user experience by allowing visibility of ongoing tasks. - Integrated active job tracking in the Conversations component, displaying generation indicators based on active jobs. - Optimized job management in the GenerationJobManager and InMemoryJobStore to support user-specific job queries, ensuring efficient resource handling and cleanup. - Updated relevant components and hooks to utilize the new active jobs feature, improving overall application responsiveness and user feedback. * feat: Implement active job tracking by user in RedisJobStore - Added functionality to retrieve active job IDs for a specific user, enhancing user experience by allowing visibility of ongoing tasks. - Implemented self-healing cleanup for stale job entries, ensuring accurate tracking of active jobs. - Updated job creation, update, and deletion methods to manage user-specific job sets effectively. - Enhanced integration tests to validate the new user-specific job management features. * refactor: Simplify job deletion logic by removing user job cleanup from InMemoryJobStore and RedisJobStore * WIP: Add backend inspect script for easier debugging in production * refactor: title generation logic - Changed the title generation endpoint from POST to GET, allowing for more efficient retrieval of titles based on conversation ID. - Implemented exponential backoff for title fetching retries, improving responsiveness and reducing server load. - Introduced a queuing mechanism for title generation, ensuring titles are generated only after job completion. - Updated relevant components and hooks to utilize the new title generation logic, enhancing user experience and application performance. * feat: Enhance updateConvoInAllQueries to support moving conversations to the top * chore: temp. remove added multi convo * refactor: Update active jobs query integration for optimistic updates on abort - Introduced a new interface for active jobs response to standardize data handling. - Updated query keys for active jobs to ensure consistency across components. - Enhanced job management logic in hooks to properly reflect active job states, improving overall application responsiveness. * refactor: useResumableStreamToggle hook to manage resumable streams for legacy/assistants endpoints - Introduced a new hook, useResumableStreamToggle, to automatically toggle resumable streams off for assistants endpoints and restore the previous value when switching away. - Updated ChatView component to utilize the new hook, enhancing the handling of streaming behavior based on endpoint type. - Refactored imports in ChatView for better organization. * refactor: streamline conversation title generation handling - Removed unused type definition for TGenTitleMutation in mutations.ts to clean up the codebase. - Integrated queueTitleGeneration call in useEventHandlers to trigger title generation for new conversations, enhancing the responsiveness of the application. * feat: Add USE_REDIS_STREAMS configuration for stream job storage - Introduced USE_REDIS_STREAMS to control Redis usage for resumable stream job storage, defaulting to true if USE_REDIS is enabled but not explicitly set. - Updated cacheConfig to include USE_REDIS_STREAMS and modified createStreamServices to utilize this new configuration. - Enhanced unit tests to validate the behavior of USE_REDIS_STREAMS under various environment settings, ensuring correct defaults and overrides. * fix: title generation queue management for assistants - Introduced a queueListeners mechanism to notify changes in the title generation queue, improving responsiveness for non-resumable streams. - Updated the useTitleGeneration hook to track queue changes with a queueVersion state, ensuring accurate updates when jobs complete. - Refactored the queueTitleGeneration function to trigger listeners upon adding new conversation IDs, enhancing the overall title generation flow. * refactor: streamline agent controller and remove legacy resumable handling - Updated the AgentController to route all requests to ResumableAgentController, simplifying the logic. - Deprecated the legacy non-resumable path, providing a clear migration path for future use. - Adjusted setHeaders middleware to remove unnecessary checks for resumable mode. - Cleaned up the useResumableSSE hook to eliminate redundant query parameters, enhancing clarity and performance. * feat: Add USE_REDIS_STREAMS configuration to .env.example - Updated .env.example to include USE_REDIS_STREAMS setting, allowing control over Redis usage for resumable LLM streams. - Provided additional context on the behavior of USE_REDIS_STREAMS when not explicitly set, enhancing clarity for configuration management. * refactor: remove unused setHeaders middleware from chat route - Eliminated the setHeaders middleware from the chat route, streamlining the request handling process. - This change contributes to cleaner code and improved performance by reducing unnecessary middleware checks. * fix: Add streamId parameter for resumable stream handling across services (actions, mcp oauth) * fix(flow): add immediate abort handling and fix intervalId initialization - Add immediate abort handler that responds instantly to abort signal - Declare intervalId before cleanup function to prevent 'Cannot access before initialization' error - Consolidate cleanup logic into single function to avoid duplicate cleanup - Properly remove abort event listener on cleanup * fix(mcp): clean up OAuth flows on abort and simplify flow handling - Add abort handler in reconnectServer to clean up mcp_oauth and mcp_get_tokens flows - Update createAbortHandler to clean up both flow types on tool call abort - Pass abort signal to createFlow in returnOnOAuth path - Simplify handleOAuthRequired to always cancel existing flows and start fresh - This ensures user always gets a new OAuth URL instead of waiting for stale flows * fix(agents): handle 'new' conversationId and improve abort reliability - Treat 'new' as placeholder that needs UUID in request controller - Send JSON response immediately before tool loading for faster SSE connection - Use job's abort controller instead of prelimAbortController - Emit errors to stream if headers already sent - Skip 'new' as valid ID in abort endpoint - Add fallback to find active jobs by userId when conversationId is 'new' * fix(stream): detect early abort and prevent navigation to non-existent conversation - Abort controller on job completion to signal pending operations - Detect early abort (no content, no responseMessageId) in abortJob - Set conversation and responseMessage to null for early aborts - Add earlyAbort flag to final event for frontend detection - Remove unused text field from AbortResult interface - Frontend handles earlyAbort by staying on/navigating to new chat * test(mcp): update test to expect signal parameter in createFlow * 🔧 refactor: Update Vertex AI Configuration Handling - Simplified the logic for enabling Vertex AI in the Anthropic initialization process, ensuring it defaults to enabled unless explicitly set to false. - Adjusted the Vertex AI schema to make the 'enabled' property optional, defaulting to true when the configuration is present. - Updated related comments and documentation for clarity on the configuration behavior. * 🔧 chore: Update Anthropic Configuration and Logging Enhancements - Changed the default region for Anthropic Vertex AI from 'global' to 'us-east5' in the .env.example file for better regional alignment. - Added debug logging to handle non-JSON credentials in the Anthropic client, improving error visibility during credential parsing. - Updated the service key path resolution in the Vertex AI client to use the current working directory, enhancing flexibility in file location. --------- Co-authored-by: Ziyan <5621658+Ziyann@users.noreply.github.com> Co-authored-by: Aron Gates <aron@muonspace.com> Co-authored-by: Danny Avila <danny@librechat.ai> Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-30 18:16:52 -05:00
const { getAppConfig } = require('./app');
/**
* Loads the default models for the application.
* @async
* @function
🛜 refactor: Streamline App Config Usage (#9234) * WIP: app.locals refactoring WIP: appConfig fix: update memory configuration retrieval to use getAppConfig based on user role fix: update comment for AppConfig interface to clarify purpose 🏷️ refactor: Update tests to use getAppConfig for endpoint configurations ci: Update AppService tests to initialize app config instead of app.locals ci: Integrate getAppConfig into remaining tests refactor: Update multer storage destination to use promise-based getAppConfig and improve error handling in tests refactor: Rename initializeAppConfig to setAppConfig and update related tests ci: Mock getAppConfig in various tests to provide default configurations refactor: Update convertMCPToolsToPlugins to use mcpManager for server configuration and adjust related tests chore: rename `Config/getAppConfig` -> `Config/app` fix: streamline OpenAI image tools configuration by removing direct appConfig dependency and using function parameters chore: correct parameter documentation for imageOutputType in ToolService.js refactor: remove `getCustomConfig` dependency in config route refactor: update domain validation to use appConfig for allowed domains refactor: use appConfig registration property chore: remove app parameter from AppService invocation refactor: update AppConfig interface to correct registration and turnstile configurations refactor: remove getCustomConfig dependency and use getAppConfig in PluginController, multer, and MCP services refactor: replace getCustomConfig with getAppConfig in STTService, TTSService, and related files refactor: replace getCustomConfig with getAppConfig in Conversation and Message models, update tempChatRetention functions to use AppConfig type refactor: update getAppConfig calls in Conversation and Message models to include user role for temporary chat expiration ci: update related tests refactor: update getAppConfig call in getCustomConfigSpeech to include user role fix: update appConfig usage to access allowedDomains from actions instead of registration refactor: enhance AppConfig to include fileStrategies and update related file strategy logic refactor: update imports to use normalizeEndpointName from @librechat/api and remove redundant definitions chore: remove deprecated unused RunManager refactor: get balance config primarily from appConfig refactor: remove customConfig dependency for appConfig and streamline loadConfigModels logic refactor: remove getCustomConfig usage and use app config in file citations refactor: consolidate endpoint loading logic into loadEndpoints function refactor: update appConfig access to use endpoints structure across various services refactor: implement custom endpoints configuration and streamline endpoint loading logic refactor: update getAppConfig call to include user role parameter refactor: streamline endpoint configuration and enhance appConfig usage across services refactor: replace getMCPAuthMap with getUserMCPAuthMap and remove unused getCustomConfig file refactor: add type annotation for loadedEndpoints in loadEndpoints function refactor: move /services/Files/images/parse to TS API chore: add missing FILE_CITATIONS permission to IRole interface refactor: restructure toolkits to TS API refactor: separate manifest logic into its own module refactor: consolidate tool loading logic into a new tools module for startup logic refactor: move interface config logic to TS API refactor: migrate checkEmailConfig to TypeScript and update imports refactor: add FunctionTool interface and availableTools to AppConfig refactor: decouple caching and DB operations from AppService, make part of consolidated `getAppConfig` WIP: fix tests * fix: rebase conflicts * refactor: remove app.locals references * refactor: replace getBalanceConfig with getAppConfig in various strategies and middleware * refactor: replace appConfig?.balance with getBalanceConfig in various controllers and clients * test: add balance configuration to titleConvo method in AgentClient tests * chore: remove unused `openai-chat-tokens` package * chore: remove unused imports in initializeMCPs.js * refactor: update balance configuration to use getAppConfig instead of getBalanceConfig * refactor: integrate configMiddleware for centralized configuration handling * refactor: optimize email domain validation by removing unnecessary async calls * refactor: simplify multer storage configuration by removing async calls * refactor: reorder imports for better readability in user.js * refactor: replace getAppConfig calls with req.config for improved performance * chore: replace getAppConfig calls with req.config in tests for centralized configuration handling * chore: remove unused override config * refactor: add configMiddleware to endpoint route and replace getAppConfig with req.config * chore: remove customConfig parameter from TTSService constructor * refactor: pass appConfig from request to processFileCitations for improved configuration handling * refactor: remove configMiddleware from endpoint route and retrieve appConfig directly in getEndpointsConfig if not in `req.config` * test: add mockAppConfig to processFileCitations tests for improved configuration handling * fix: pass req.config to hasCustomUserVars and call without await after synchronous refactor * fix: type safety in useExportConversation * refactor: retrieve appConfig using getAppConfig in PluginController and remove configMiddleware from plugins route, to avoid always retrieving when plugins are cached * chore: change `MongoUser` typedef to `IUser` * fix: Add `user` and `config` fields to ServerRequest and update JSDoc type annotations from Express.Request to ServerRequest * fix: remove unused setAppConfig mock from Server configuration tests
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* @param {ServerRequest} req - The Express request object.
*/
async function loadDefaultModels(req) {
try {
🤖 feat: Anthropic Vertex AI Support (#10780) * feat: Add Anthropic Vertex AI Support * Remove changes from the unused AnthropicClient class * Add @anthropic-ai/vertex-sdk as peerDependency to packages/api * Clean up Vertex AI credentials handling * feat: websearch header * feat: add prompt caching support for Anthropic Vertex AI - Support both OpenAI format (input_token_details) and Anthropic format (cache_*_input_tokens) for token usage tracking - Filter out unsupported anthropic-beta header values for Vertex AI (prompt-caching, max-tokens, output-128k, token-efficient-tools, context-1m) * ✨ feat: Add Vertex AI support for Anthropic models - Introduced configuration options for running Anthropic models via Google Cloud Vertex AI in the YAML file. - Updated ModelService to prioritize Vertex AI models from the configuration. - Enhanced endpoint configuration to enable Anthropic endpoint when Vertex AI is configured. - Implemented validation and processing for Vertex AI credentials and options. - Added new types and schemas for Vertex AI configuration in the data provider. - Created utility functions for loading and validating Vertex AI credentials and configurations. - Updated various services to integrate Vertex AI options into the Anthropic client setup. * 🔒 fix: Improve error handling for missing credentials in LLM configuration - Updated the `getLLMConfig` function to throw a specific error message when credentials are missing, enhancing clarity for users. - Refactored the `parseCredentials` function to handle plain API key strings more gracefully, returning them wrapped in an object if JSON parsing fails. * 🔧 refactor: Clean up code formatting and improve readability - Updated the `setOptions` method in `AgentClient` to use a parameter name for clarity. - Refactored error handling in `loadDefaultModels` for better readability. - Removed unnecessary blank lines in `initialize.js`, `endpoints.ts`, and `vertex.ts` to streamline the code. - Enhanced formatting in `validateVertexConfig` for improved consistency and clarity. * 🔧 refactor: Enhance Vertex AI Model Configuration and Integration - Updated the YAML configuration to support visible model names and deployment mappings for Vertex AI. - Refactored the `loadDefaultModels` function to utilize the new model name structure. - Improved the `initializeClient` function to pass full Vertex AI configuration, including model mappings. - Added utility functions to map visible model names to deployment names, enhancing the integration of Vertex AI models. - Updated various services and types to accommodate the new model configuration schema and improve overall clarity and functionality. * 🔧 chore: Update @anthropic-ai/sdk dependency to version 0.71.0 in package.json and package-lock.json * refactor: Change clientOptions declaration from let to const in initialize.ts for better code clarity * chore: repository cleanup * 🌊 feat: Resumable LLM Streams with Horizontal Scaling (#10926) * ✨ feat: Implement Resumable Generation Jobs with SSE Support - Introduced GenerationJobManager to handle resumable LLM generation jobs independently of HTTP connections. - Added support for subscribing to ongoing generation jobs via SSE, allowing clients to reconnect and receive updates without losing progress. - Enhanced existing agent controllers and routes to integrate resumable functionality, including job creation, completion, and error handling. - Updated client-side hooks to manage adaptive SSE streams, switching between standard and resumable modes based on user settings. - Added UI components and settings for enabling/disabling resumable streams, improving user experience during unstable connections. * WIP: resuming * WIP: resumable stream * feat: Enhance Stream Management with Abort Functionality - Updated the abort endpoint to support aborting ongoing generation streams using either streamId or conversationId. - Introduced a new mutation hook `useAbortStreamMutation` for client-side integration. - Added `useStreamStatus` query to monitor stream status and facilitate resuming conversations. - Enhanced `useChatHelpers` to incorporate abort functionality when stopping generation. - Improved `useResumableSSE` to handle stream errors and token refresh seamlessly. - Updated `useResumeOnLoad` to check for active streams and resume conversations appropriately. * fix: Update query parameter handling in useChatHelpers - Refactored the logic for determining the query parameter used in fetching messages to prioritize paramId from the URL, falling back to conversationId only if paramId is not available. This change ensures consistency with the ChatView component's expectations. * fix: improve syncing when switching conversations * fix: Prevent memory leaks in useResumableSSE by clearing handler maps on stream completion and cleanup * fix: Improve content type mismatch handling in useStepHandler - Enhanced the condition for detecting content type mismatches to include additional checks, ensuring more robust validation of content types before processing updates. * fix: Allow dynamic content creation in useChatFunctions - Updated the initial response handling to avoid pre-initializing content types, enabling dynamic creation of content parts based on incoming delta events. This change supports various content types such as think and text. * fix: Refine response message handling in useStepHandler - Updated logic to determine the appropriate response message based on the last message's origin, ensuring correct message replacement or appending based on user interaction. This change enhances the accuracy of message updates in the chat flow. * refactor: Enhance GenerationJobManager with In-Memory Implementations - Introduced InMemoryJobStore, InMemoryEventTransport, and InMemoryContentState for improved job management and event handling. - Updated GenerationJobManager to utilize these new implementations, allowing for better separation of concerns and easier maintenance. - Enhanced job metadata handling to support user messages and response IDs for resumable functionality. - Improved cleanup and state management processes to prevent memory leaks and ensure efficient resource usage. * refactor: Enhance GenerationJobManager with improved subscriber handling - Updated RuntimeJobState to include allSubscribersLeftHandlers for managing client disconnections without affecting subscriber count. - Refined createJob and subscribe methods to ensure generation starts only when the first real client connects. - Added detailed documentation for methods and properties to clarify the synchronization of job generation with client readiness. - Improved logging for subscriber checks and event handling to facilitate debugging and monitoring. * chore: Adjust timeout for subscriber readiness in ResumableAgentController - Reduced the timeout duration from 5000ms to 2500ms in the startGeneration function to improve responsiveness when waiting for subscriber readiness. This change aims to enhance the efficiency of the agent's background generation process. * refactor: Update GenerationJobManager documentation and structure - Enhanced the documentation for GenerationJobManager to clarify the architecture and pluggable service design. - Updated comments to reflect the potential for Redis integration and the need for async refactoring. - Improved the structure of the GenerationJob facade to emphasize the unified API while allowing for implementation swapping without affecting consumer code. * refactor: Convert GenerationJobManager methods to async for improved performance - Updated methods in GenerationJobManager and InMemoryJobStore to be asynchronous, enhancing the handling of job creation, retrieval, and management. - Adjusted the ResumableAgentController and related routes to await job operations, ensuring proper flow and error handling. - Increased timeout duration in ResumableAgentController's startGeneration function to 3500ms for better subscriber readiness management. * refactor: Simplify initial response handling in useChatFunctions - Removed unnecessary pre-initialization of content types in the initial response, allowing for dynamic content creation based on incoming delta events. This change enhances flexibility in handling various content types in the chat flow. * refactor: Clarify content handling logic in useStepHandler - Updated comments to better explain the handling of initialContent and existingContent in edit and resume scenarios. - Simplified the logic for merging content, ensuring that initialContent is used directly when available, improving clarity and maintainability. * refactor: Improve message handling logic in useStepHandler - Enhanced the logic for managing messages in multi-tab scenarios, ensuring that the most up-to-date message history is utilized. - Removed existing response placeholders and ensured user messages are included, improving the accuracy of message updates in the chat flow. * fix: remove unnecessary content length logging in the chat stream response, simplifying the debug message while retaining essential information about run steps. This change enhances clarity in logging without losing critical context. * refactor: Integrate streamId handling for improved resumable functionality for attachments - Added streamId parameter to various functions to support resumable mode in tool loading and memory processing. - Updated related methods to ensure proper handling of attachments and responses based on the presence of streamId, enhancing the overall streaming experience. - Improved logging and attachment management to accommodate both standard and resumable modes. * refactor: Streamline abort handling and integrate GenerationJobManager for improved job management - Removed the abortControllers middleware and integrated abort handling directly into GenerationJobManager. - Updated abortMessage function to utilize GenerationJobManager for aborting jobs by conversation ID, enhancing clarity and efficiency. - Simplified cleanup processes and improved error handling during abort operations. - Enhanced metadata management for jobs, including endpoint and model information, to facilitate better tracking and resource management. * refactor: Unify streamId and conversationId handling for improved job management - Updated ResumableAgentController and AgentController to generate conversationId upfront, ensuring it matches streamId for consistency. - Simplified job creation and metadata management by removing redundant conversationId updates from callbacks. - Refactored abortMiddleware and related methods to utilize the unified streamId/conversationId approach, enhancing clarity in job handling. - Removed deprecated methods from GenerationJobManager and InMemoryJobStore, streamlining the codebase and improving maintainability. * refactor: Enhance resumable SSE handling with improved UI state management and error recovery - Added UI state restoration on successful SSE connection to indicate ongoing submission. - Implemented detailed error handling for network failures, including retry logic with exponential backoff. - Introduced abort event handling to reset UI state on intentional stream closure. - Enhanced debugging capabilities for testing reconnection and clean close scenarios. - Updated generation function to retry on network errors, improving resilience during submission processes. * refactor: Consolidate content state management into IJobStore for improved job handling - Removed InMemoryContentState and integrated its functionality into InMemoryJobStore, streamlining content state management. - Updated GenerationJobManager to utilize jobStore for content state operations, enhancing clarity and reducing redundancy. - Introduced RedisJobStore for horizontal scaling, allowing for efficient job management and content reconstruction from chunks. - Updated IJobStore interface to reflect changes in content state handling, ensuring consistency across implementations. * feat: Introduce Redis-backed stream services for enhanced job management - Added createStreamServices function to configure job store and event transport, supporting both Redis and in-memory options. - Updated GenerationJobManager to allow configuration with custom job stores and event transports, improving flexibility for different deployment scenarios. - Refactored IJobStore interface to support asynchronous content retrieval, ensuring compatibility with Redis implementations. - Implemented RedisEventTransport for real-time event delivery across instances, enhancing scalability and responsiveness. - Updated InMemoryJobStore to align with new async patterns for content and run step retrieval, ensuring consistent behavior across storage options. * refactor: Remove redundant debug logging in GenerationJobManager and RedisEventTransport - Eliminated unnecessary debug statements in GenerationJobManager related to subscriber actions and job updates, enhancing log clarity. - Removed debug logging in RedisEventTransport for subscription and subscriber disconnection events, streamlining the logging output. - Cleaned up debug messages in RedisJobStore to focus on essential information, improving overall logging efficiency. * refactor: Enhance job state management and TTL configuration in RedisJobStore - Updated the RedisJobStore to allow customizable TTL values for job states, improving flexibility in job management. - Refactored the handling of job expiration and cleanup processes to align with new TTL configurations. - Simplified the response structure in the chat status endpoint by consolidating state retrieval, enhancing clarity and performance. - Improved comments and documentation for better understanding of the changes made. * refactor: cleanupOnComplete option to GenerationJobManager for flexible resource management - Introduced a new configuration option, cleanupOnComplete, allowing immediate cleanup of event transport and job resources upon job completion. - Updated completeJob and abortJob methods to respect the cleanupOnComplete setting, enhancing memory management. - Improved cleanup logic in the cleanup method to handle orphaned resources effectively. - Enhanced documentation and comments for better clarity on the new functionality. * refactor: Update TTL configuration for completed jobs in InMemoryJobStore - Changed the TTL for completed jobs from 5 minutes to 0, allowing for immediate cleanup. - Enhanced cleanup logic to respect the new TTL setting, improving resource management. - Updated comments for clarity on the behavior of the TTL configuration. * refactor: Enhance RedisJobStore with local graph caching for improved performance - Introduced a local cache for graph references using WeakRef to optimize reconnects for the same instance. - Updated job deletion and cleanup methods to manage the local cache effectively, ensuring stale entries are removed. - Enhanced content retrieval methods to prioritize local cache access, reducing Redis round-trips for same-instance reconnects. - Improved documentation and comments for clarity on the caching mechanism and its benefits. * feat: Add integration tests for GenerationJobManager, RedisEventTransport, and RedisJobStore, add Redis Cluster support - Introduced comprehensive integration tests for GenerationJobManager, covering both in-memory and Redis modes to ensure consistent job management and event handling. - Added tests for RedisEventTransport to validate pub/sub functionality, including cross-instance event delivery and error handling. - Implemented integration tests for RedisJobStore, focusing on multi-instance job access, content reconstruction from chunks, and consumer group behavior. - Enhanced test setup and teardown processes to ensure a clean environment for each test run, improving reliability and maintainability. * fix: Improve error handling in GenerationJobManager for allSubscribersLeft handlers - Enhanced the error handling logic when retrieving content parts for allSubscribersLeft handlers, ensuring that any failures are logged appropriately. - Updated the promise chain to catch errors from getContentParts, improving robustness and clarity in error reporting. * ci: Improve Redis client disconnection handling in integration tests - Updated the afterAll cleanup logic in integration tests for GenerationJobManager, RedisEventTransport, and RedisJobStore to use `quit()` for graceful disconnection of the Redis client. - Added fallback to `disconnect()` if `quit()` fails, enhancing robustness in resource management during test teardown. - Improved comments for clarity on the disconnection process and error handling. * refactor: Enhance GenerationJobManager and event transports for improved resource management - Updated GenerationJobManager to prevent immediate cleanup of eventTransport upon job completion, allowing final events to transmit fully before cleanup. - Added orphaned stream cleanup logic in GenerationJobManager to handle streams without corresponding jobs. - Introduced getTrackedStreamIds method in both InMemoryEventTransport and RedisEventTransport for better management of orphaned streams. - Improved comments for clarity on resource management and cleanup processes. * refactor: Update GenerationJobManager and ResumableAgentController for improved event handling - Modified GenerationJobManager to resolve readyPromise immediately, eliminating startup latency and allowing early event buffering for late subscribers. - Enhanced event handling logic to replay buffered events when the first subscriber connects, ensuring no events are lost due to race conditions. - Updated comments for clarity on the new event synchronization mechanism and its benefits in both Redis and in-memory modes. * fix: Update cache integration test command for stream to ensure proper execution - Modified the test command for cache integration related to streams by adding the --forceExit flag to prevent hanging tests. - This change enhances the reliability of the test suite by ensuring all tests complete as expected. * feat: Add active job management for user and show progress in conversation list - Implemented a new endpoint to retrieve active generation job IDs for the current user, enhancing user experience by allowing visibility of ongoing tasks. - Integrated active job tracking in the Conversations component, displaying generation indicators based on active jobs. - Optimized job management in the GenerationJobManager and InMemoryJobStore to support user-specific job queries, ensuring efficient resource handling and cleanup. - Updated relevant components and hooks to utilize the new active jobs feature, improving overall application responsiveness and user feedback. * feat: Implement active job tracking by user in RedisJobStore - Added functionality to retrieve active job IDs for a specific user, enhancing user experience by allowing visibility of ongoing tasks. - Implemented self-healing cleanup for stale job entries, ensuring accurate tracking of active jobs. - Updated job creation, update, and deletion methods to manage user-specific job sets effectively. - Enhanced integration tests to validate the new user-specific job management features. * refactor: Simplify job deletion logic by removing user job cleanup from InMemoryJobStore and RedisJobStore * WIP: Add backend inspect script for easier debugging in production * refactor: title generation logic - Changed the title generation endpoint from POST to GET, allowing for more efficient retrieval of titles based on conversation ID. - Implemented exponential backoff for title fetching retries, improving responsiveness and reducing server load. - Introduced a queuing mechanism for title generation, ensuring titles are generated only after job completion. - Updated relevant components and hooks to utilize the new title generation logic, enhancing user experience and application performance. * feat: Enhance updateConvoInAllQueries to support moving conversations to the top * chore: temp. remove added multi convo * refactor: Update active jobs query integration for optimistic updates on abort - Introduced a new interface for active jobs response to standardize data handling. - Updated query keys for active jobs to ensure consistency across components. - Enhanced job management logic in hooks to properly reflect active job states, improving overall application responsiveness. * refactor: useResumableStreamToggle hook to manage resumable streams for legacy/assistants endpoints - Introduced a new hook, useResumableStreamToggle, to automatically toggle resumable streams off for assistants endpoints and restore the previous value when switching away. - Updated ChatView component to utilize the new hook, enhancing the handling of streaming behavior based on endpoint type. - Refactored imports in ChatView for better organization. * refactor: streamline conversation title generation handling - Removed unused type definition for TGenTitleMutation in mutations.ts to clean up the codebase. - Integrated queueTitleGeneration call in useEventHandlers to trigger title generation for new conversations, enhancing the responsiveness of the application. * feat: Add USE_REDIS_STREAMS configuration for stream job storage - Introduced USE_REDIS_STREAMS to control Redis usage for resumable stream job storage, defaulting to true if USE_REDIS is enabled but not explicitly set. - Updated cacheConfig to include USE_REDIS_STREAMS and modified createStreamServices to utilize this new configuration. - Enhanced unit tests to validate the behavior of USE_REDIS_STREAMS under various environment settings, ensuring correct defaults and overrides. * fix: title generation queue management for assistants - Introduced a queueListeners mechanism to notify changes in the title generation queue, improving responsiveness for non-resumable streams. - Updated the useTitleGeneration hook to track queue changes with a queueVersion state, ensuring accurate updates when jobs complete. - Refactored the queueTitleGeneration function to trigger listeners upon adding new conversation IDs, enhancing the overall title generation flow. * refactor: streamline agent controller and remove legacy resumable handling - Updated the AgentController to route all requests to ResumableAgentController, simplifying the logic. - Deprecated the legacy non-resumable path, providing a clear migration path for future use. - Adjusted setHeaders middleware to remove unnecessary checks for resumable mode. - Cleaned up the useResumableSSE hook to eliminate redundant query parameters, enhancing clarity and performance. * feat: Add USE_REDIS_STREAMS configuration to .env.example - Updated .env.example to include USE_REDIS_STREAMS setting, allowing control over Redis usage for resumable LLM streams. - Provided additional context on the behavior of USE_REDIS_STREAMS when not explicitly set, enhancing clarity for configuration management. * refactor: remove unused setHeaders middleware from chat route - Eliminated the setHeaders middleware from the chat route, streamlining the request handling process. - This change contributes to cleaner code and improved performance by reducing unnecessary middleware checks. * fix: Add streamId parameter for resumable stream handling across services (actions, mcp oauth) * fix(flow): add immediate abort handling and fix intervalId initialization - Add immediate abort handler that responds instantly to abort signal - Declare intervalId before cleanup function to prevent 'Cannot access before initialization' error - Consolidate cleanup logic into single function to avoid duplicate cleanup - Properly remove abort event listener on cleanup * fix(mcp): clean up OAuth flows on abort and simplify flow handling - Add abort handler in reconnectServer to clean up mcp_oauth and mcp_get_tokens flows - Update createAbortHandler to clean up both flow types on tool call abort - Pass abort signal to createFlow in returnOnOAuth path - Simplify handleOAuthRequired to always cancel existing flows and start fresh - This ensures user always gets a new OAuth URL instead of waiting for stale flows * fix(agents): handle 'new' conversationId and improve abort reliability - Treat 'new' as placeholder that needs UUID in request controller - Send JSON response immediately before tool loading for faster SSE connection - Use job's abort controller instead of prelimAbortController - Emit errors to stream if headers already sent - Skip 'new' as valid ID in abort endpoint - Add fallback to find active jobs by userId when conversationId is 'new' * fix(stream): detect early abort and prevent navigation to non-existent conversation - Abort controller on job completion to signal pending operations - Detect early abort (no content, no responseMessageId) in abortJob - Set conversation and responseMessage to null for early aborts - Add earlyAbort flag to final event for frontend detection - Remove unused text field from AbortResult interface - Frontend handles earlyAbort by staying on/navigating to new chat * test(mcp): update test to expect signal parameter in createFlow * 🔧 refactor: Update Vertex AI Configuration Handling - Simplified the logic for enabling Vertex AI in the Anthropic initialization process, ensuring it defaults to enabled unless explicitly set to false. - Adjusted the Vertex AI schema to make the 'enabled' property optional, defaulting to true when the configuration is present. - Updated related comments and documentation for clarity on the configuration behavior. * 🔧 chore: Update Anthropic Configuration and Logging Enhancements - Changed the default region for Anthropic Vertex AI from 'global' to 'us-east5' in the .env.example file for better regional alignment. - Added debug logging to handle non-JSON credentials in the Anthropic client, improving error visibility during credential parsing. - Updated the service key path resolution in the Vertex AI client to use the current working directory, enhancing flexibility in file location. --------- Co-authored-by: Ziyan <5621658+Ziyann@users.noreply.github.com> Co-authored-by: Aron Gates <aron@muonspace.com> Co-authored-by: Danny Avila <danny@librechat.ai> Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-30 18:16:52 -05:00
const appConfig = req.config ?? (await getAppConfig({ role: req.user?.role }));
const vertexConfig = appConfig?.endpoints?.[EModelEndpoint.anthropic]?.vertexConfig;
const [openAI, anthropic, azureOpenAI, assistants, azureAssistants, google, bedrock] =
await Promise.all([
getOpenAIModels({ user: req.user.id }).catch((error) => {
logger.error('Error fetching OpenAI models:', error);
return [];
}),
🤖 feat: Anthropic Vertex AI Support (#10780) * feat: Add Anthropic Vertex AI Support * Remove changes from the unused AnthropicClient class * Add @anthropic-ai/vertex-sdk as peerDependency to packages/api * Clean up Vertex AI credentials handling * feat: websearch header * feat: add prompt caching support for Anthropic Vertex AI - Support both OpenAI format (input_token_details) and Anthropic format (cache_*_input_tokens) for token usage tracking - Filter out unsupported anthropic-beta header values for Vertex AI (prompt-caching, max-tokens, output-128k, token-efficient-tools, context-1m) * ✨ feat: Add Vertex AI support for Anthropic models - Introduced configuration options for running Anthropic models via Google Cloud Vertex AI in the YAML file. - Updated ModelService to prioritize Vertex AI models from the configuration. - Enhanced endpoint configuration to enable Anthropic endpoint when Vertex AI is configured. - Implemented validation and processing for Vertex AI credentials and options. - Added new types and schemas for Vertex AI configuration in the data provider. - Created utility functions for loading and validating Vertex AI credentials and configurations. - Updated various services to integrate Vertex AI options into the Anthropic client setup. * 🔒 fix: Improve error handling for missing credentials in LLM configuration - Updated the `getLLMConfig` function to throw a specific error message when credentials are missing, enhancing clarity for users. - Refactored the `parseCredentials` function to handle plain API key strings more gracefully, returning them wrapped in an object if JSON parsing fails. * 🔧 refactor: Clean up code formatting and improve readability - Updated the `setOptions` method in `AgentClient` to use a parameter name for clarity. - Refactored error handling in `loadDefaultModels` for better readability. - Removed unnecessary blank lines in `initialize.js`, `endpoints.ts`, and `vertex.ts` to streamline the code. - Enhanced formatting in `validateVertexConfig` for improved consistency and clarity. * 🔧 refactor: Enhance Vertex AI Model Configuration and Integration - Updated the YAML configuration to support visible model names and deployment mappings for Vertex AI. - Refactored the `loadDefaultModels` function to utilize the new model name structure. - Improved the `initializeClient` function to pass full Vertex AI configuration, including model mappings. - Added utility functions to map visible model names to deployment names, enhancing the integration of Vertex AI models. - Updated various services and types to accommodate the new model configuration schema and improve overall clarity and functionality. * 🔧 chore: Update @anthropic-ai/sdk dependency to version 0.71.0 in package.json and package-lock.json * refactor: Change clientOptions declaration from let to const in initialize.ts for better code clarity * chore: repository cleanup * 🌊 feat: Resumable LLM Streams with Horizontal Scaling (#10926) * ✨ feat: Implement Resumable Generation Jobs with SSE Support - Introduced GenerationJobManager to handle resumable LLM generation jobs independently of HTTP connections. - Added support for subscribing to ongoing generation jobs via SSE, allowing clients to reconnect and receive updates without losing progress. - Enhanced existing agent controllers and routes to integrate resumable functionality, including job creation, completion, and error handling. - Updated client-side hooks to manage adaptive SSE streams, switching between standard and resumable modes based on user settings. - Added UI components and settings for enabling/disabling resumable streams, improving user experience during unstable connections. * WIP: resuming * WIP: resumable stream * feat: Enhance Stream Management with Abort Functionality - Updated the abort endpoint to support aborting ongoing generation streams using either streamId or conversationId. - Introduced a new mutation hook `useAbortStreamMutation` for client-side integration. - Added `useStreamStatus` query to monitor stream status and facilitate resuming conversations. - Enhanced `useChatHelpers` to incorporate abort functionality when stopping generation. - Improved `useResumableSSE` to handle stream errors and token refresh seamlessly. - Updated `useResumeOnLoad` to check for active streams and resume conversations appropriately. * fix: Update query parameter handling in useChatHelpers - Refactored the logic for determining the query parameter used in fetching messages to prioritize paramId from the URL, falling back to conversationId only if paramId is not available. This change ensures consistency with the ChatView component's expectations. * fix: improve syncing when switching conversations * fix: Prevent memory leaks in useResumableSSE by clearing handler maps on stream completion and cleanup * fix: Improve content type mismatch handling in useStepHandler - Enhanced the condition for detecting content type mismatches to include additional checks, ensuring more robust validation of content types before processing updates. * fix: Allow dynamic content creation in useChatFunctions - Updated the initial response handling to avoid pre-initializing content types, enabling dynamic creation of content parts based on incoming delta events. This change supports various content types such as think and text. * fix: Refine response message handling in useStepHandler - Updated logic to determine the appropriate response message based on the last message's origin, ensuring correct message replacement or appending based on user interaction. This change enhances the accuracy of message updates in the chat flow. * refactor: Enhance GenerationJobManager with In-Memory Implementations - Introduced InMemoryJobStore, InMemoryEventTransport, and InMemoryContentState for improved job management and event handling. - Updated GenerationJobManager to utilize these new implementations, allowing for better separation of concerns and easier maintenance. - Enhanced job metadata handling to support user messages and response IDs for resumable functionality. - Improved cleanup and state management processes to prevent memory leaks and ensure efficient resource usage. * refactor: Enhance GenerationJobManager with improved subscriber handling - Updated RuntimeJobState to include allSubscribersLeftHandlers for managing client disconnections without affecting subscriber count. - Refined createJob and subscribe methods to ensure generation starts only when the first real client connects. - Added detailed documentation for methods and properties to clarify the synchronization of job generation with client readiness. - Improved logging for subscriber checks and event handling to facilitate debugging and monitoring. * chore: Adjust timeout for subscriber readiness in ResumableAgentController - Reduced the timeout duration from 5000ms to 2500ms in the startGeneration function to improve responsiveness when waiting for subscriber readiness. This change aims to enhance the efficiency of the agent's background generation process. * refactor: Update GenerationJobManager documentation and structure - Enhanced the documentation for GenerationJobManager to clarify the architecture and pluggable service design. - Updated comments to reflect the potential for Redis integration and the need for async refactoring. - Improved the structure of the GenerationJob facade to emphasize the unified API while allowing for implementation swapping without affecting consumer code. * refactor: Convert GenerationJobManager methods to async for improved performance - Updated methods in GenerationJobManager and InMemoryJobStore to be asynchronous, enhancing the handling of job creation, retrieval, and management. - Adjusted the ResumableAgentController and related routes to await job operations, ensuring proper flow and error handling. - Increased timeout duration in ResumableAgentController's startGeneration function to 3500ms for better subscriber readiness management. * refactor: Simplify initial response handling in useChatFunctions - Removed unnecessary pre-initialization of content types in the initial response, allowing for dynamic content creation based on incoming delta events. This change enhances flexibility in handling various content types in the chat flow. * refactor: Clarify content handling logic in useStepHandler - Updated comments to better explain the handling of initialContent and existingContent in edit and resume scenarios. - Simplified the logic for merging content, ensuring that initialContent is used directly when available, improving clarity and maintainability. * refactor: Improve message handling logic in useStepHandler - Enhanced the logic for managing messages in multi-tab scenarios, ensuring that the most up-to-date message history is utilized. - Removed existing response placeholders and ensured user messages are included, improving the accuracy of message updates in the chat flow. * fix: remove unnecessary content length logging in the chat stream response, simplifying the debug message while retaining essential information about run steps. This change enhances clarity in logging without losing critical context. * refactor: Integrate streamId handling for improved resumable functionality for attachments - Added streamId parameter to various functions to support resumable mode in tool loading and memory processing. - Updated related methods to ensure proper handling of attachments and responses based on the presence of streamId, enhancing the overall streaming experience. - Improved logging and attachment management to accommodate both standard and resumable modes. * refactor: Streamline abort handling and integrate GenerationJobManager for improved job management - Removed the abortControllers middleware and integrated abort handling directly into GenerationJobManager. - Updated abortMessage function to utilize GenerationJobManager for aborting jobs by conversation ID, enhancing clarity and efficiency. - Simplified cleanup processes and improved error handling during abort operations. - Enhanced metadata management for jobs, including endpoint and model information, to facilitate better tracking and resource management. * refactor: Unify streamId and conversationId handling for improved job management - Updated ResumableAgentController and AgentController to generate conversationId upfront, ensuring it matches streamId for consistency. - Simplified job creation and metadata management by removing redundant conversationId updates from callbacks. - Refactored abortMiddleware and related methods to utilize the unified streamId/conversationId approach, enhancing clarity in job handling. - Removed deprecated methods from GenerationJobManager and InMemoryJobStore, streamlining the codebase and improving maintainability. * refactor: Enhance resumable SSE handling with improved UI state management and error recovery - Added UI state restoration on successful SSE connection to indicate ongoing submission. - Implemented detailed error handling for network failures, including retry logic with exponential backoff. - Introduced abort event handling to reset UI state on intentional stream closure. - Enhanced debugging capabilities for testing reconnection and clean close scenarios. - Updated generation function to retry on network errors, improving resilience during submission processes. * refactor: Consolidate content state management into IJobStore for improved job handling - Removed InMemoryContentState and integrated its functionality into InMemoryJobStore, streamlining content state management. - Updated GenerationJobManager to utilize jobStore for content state operations, enhancing clarity and reducing redundancy. - Introduced RedisJobStore for horizontal scaling, allowing for efficient job management and content reconstruction from chunks. - Updated IJobStore interface to reflect changes in content state handling, ensuring consistency across implementations. * feat: Introduce Redis-backed stream services for enhanced job management - Added createStreamServices function to configure job store and event transport, supporting both Redis and in-memory options. - Updated GenerationJobManager to allow configuration with custom job stores and event transports, improving flexibility for different deployment scenarios. - Refactored IJobStore interface to support asynchronous content retrieval, ensuring compatibility with Redis implementations. - Implemented RedisEventTransport for real-time event delivery across instances, enhancing scalability and responsiveness. - Updated InMemoryJobStore to align with new async patterns for content and run step retrieval, ensuring consistent behavior across storage options. * refactor: Remove redundant debug logging in GenerationJobManager and RedisEventTransport - Eliminated unnecessary debug statements in GenerationJobManager related to subscriber actions and job updates, enhancing log clarity. - Removed debug logging in RedisEventTransport for subscription and subscriber disconnection events, streamlining the logging output. - Cleaned up debug messages in RedisJobStore to focus on essential information, improving overall logging efficiency. * refactor: Enhance job state management and TTL configuration in RedisJobStore - Updated the RedisJobStore to allow customizable TTL values for job states, improving flexibility in job management. - Refactored the handling of job expiration and cleanup processes to align with new TTL configurations. - Simplified the response structure in the chat status endpoint by consolidating state retrieval, enhancing clarity and performance. - Improved comments and documentation for better understanding of the changes made. * refactor: cleanupOnComplete option to GenerationJobManager for flexible resource management - Introduced a new configuration option, cleanupOnComplete, allowing immediate cleanup of event transport and job resources upon job completion. - Updated completeJob and abortJob methods to respect the cleanupOnComplete setting, enhancing memory management. - Improved cleanup logic in the cleanup method to handle orphaned resources effectively. - Enhanced documentation and comments for better clarity on the new functionality. * refactor: Update TTL configuration for completed jobs in InMemoryJobStore - Changed the TTL for completed jobs from 5 minutes to 0, allowing for immediate cleanup. - Enhanced cleanup logic to respect the new TTL setting, improving resource management. - Updated comments for clarity on the behavior of the TTL configuration. * refactor: Enhance RedisJobStore with local graph caching for improved performance - Introduced a local cache for graph references using WeakRef to optimize reconnects for the same instance. - Updated job deletion and cleanup methods to manage the local cache effectively, ensuring stale entries are removed. - Enhanced content retrieval methods to prioritize local cache access, reducing Redis round-trips for same-instance reconnects. - Improved documentation and comments for clarity on the caching mechanism and its benefits. * feat: Add integration tests for GenerationJobManager, RedisEventTransport, and RedisJobStore, add Redis Cluster support - Introduced comprehensive integration tests for GenerationJobManager, covering both in-memory and Redis modes to ensure consistent job management and event handling. - Added tests for RedisEventTransport to validate pub/sub functionality, including cross-instance event delivery and error handling. - Implemented integration tests for RedisJobStore, focusing on multi-instance job access, content reconstruction from chunks, and consumer group behavior. - Enhanced test setup and teardown processes to ensure a clean environment for each test run, improving reliability and maintainability. * fix: Improve error handling in GenerationJobManager for allSubscribersLeft handlers - Enhanced the error handling logic when retrieving content parts for allSubscribersLeft handlers, ensuring that any failures are logged appropriately. - Updated the promise chain to catch errors from getContentParts, improving robustness and clarity in error reporting. * ci: Improve Redis client disconnection handling in integration tests - Updated the afterAll cleanup logic in integration tests for GenerationJobManager, RedisEventTransport, and RedisJobStore to use `quit()` for graceful disconnection of the Redis client. - Added fallback to `disconnect()` if `quit()` fails, enhancing robustness in resource management during test teardown. - Improved comments for clarity on the disconnection process and error handling. * refactor: Enhance GenerationJobManager and event transports for improved resource management - Updated GenerationJobManager to prevent immediate cleanup of eventTransport upon job completion, allowing final events to transmit fully before cleanup. - Added orphaned stream cleanup logic in GenerationJobManager to handle streams without corresponding jobs. - Introduced getTrackedStreamIds method in both InMemoryEventTransport and RedisEventTransport for better management of orphaned streams. - Improved comments for clarity on resource management and cleanup processes. * refactor: Update GenerationJobManager and ResumableAgentController for improved event handling - Modified GenerationJobManager to resolve readyPromise immediately, eliminating startup latency and allowing early event buffering for late subscribers. - Enhanced event handling logic to replay buffered events when the first subscriber connects, ensuring no events are lost due to race conditions. - Updated comments for clarity on the new event synchronization mechanism and its benefits in both Redis and in-memory modes. * fix: Update cache integration test command for stream to ensure proper execution - Modified the test command for cache integration related to streams by adding the --forceExit flag to prevent hanging tests. - This change enhances the reliability of the test suite by ensuring all tests complete as expected. * feat: Add active job management for user and show progress in conversation list - Implemented a new endpoint to retrieve active generation job IDs for the current user, enhancing user experience by allowing visibility of ongoing tasks. - Integrated active job tracking in the Conversations component, displaying generation indicators based on active jobs. - Optimized job management in the GenerationJobManager and InMemoryJobStore to support user-specific job queries, ensuring efficient resource handling and cleanup. - Updated relevant components and hooks to utilize the new active jobs feature, improving overall application responsiveness and user feedback. * feat: Implement active job tracking by user in RedisJobStore - Added functionality to retrieve active job IDs for a specific user, enhancing user experience by allowing visibility of ongoing tasks. - Implemented self-healing cleanup for stale job entries, ensuring accurate tracking of active jobs. - Updated job creation, update, and deletion methods to manage user-specific job sets effectively. - Enhanced integration tests to validate the new user-specific job management features. * refactor: Simplify job deletion logic by removing user job cleanup from InMemoryJobStore and RedisJobStore * WIP: Add backend inspect script for easier debugging in production * refactor: title generation logic - Changed the title generation endpoint from POST to GET, allowing for more efficient retrieval of titles based on conversation ID. - Implemented exponential backoff for title fetching retries, improving responsiveness and reducing server load. - Introduced a queuing mechanism for title generation, ensuring titles are generated only after job completion. - Updated relevant components and hooks to utilize the new title generation logic, enhancing user experience and application performance. * feat: Enhance updateConvoInAllQueries to support moving conversations to the top * chore: temp. remove added multi convo * refactor: Update active jobs query integration for optimistic updates on abort - Introduced a new interface for active jobs response to standardize data handling. - Updated query keys for active jobs to ensure consistency across components. - Enhanced job management logic in hooks to properly reflect active job states, improving overall application responsiveness. * refactor: useResumableStreamToggle hook to manage resumable streams for legacy/assistants endpoints - Introduced a new hook, useResumableStreamToggle, to automatically toggle resumable streams off for assistants endpoints and restore the previous value when switching away. - Updated ChatView component to utilize the new hook, enhancing the handling of streaming behavior based on endpoint type. - Refactored imports in ChatView for better organization. * refactor: streamline conversation title generation handling - Removed unused type definition for TGenTitleMutation in mutations.ts to clean up the codebase. - Integrated queueTitleGeneration call in useEventHandlers to trigger title generation for new conversations, enhancing the responsiveness of the application. * feat: Add USE_REDIS_STREAMS configuration for stream job storage - Introduced USE_REDIS_STREAMS to control Redis usage for resumable stream job storage, defaulting to true if USE_REDIS is enabled but not explicitly set. - Updated cacheConfig to include USE_REDIS_STREAMS and modified createStreamServices to utilize this new configuration. - Enhanced unit tests to validate the behavior of USE_REDIS_STREAMS under various environment settings, ensuring correct defaults and overrides. * fix: title generation queue management for assistants - Introduced a queueListeners mechanism to notify changes in the title generation queue, improving responsiveness for non-resumable streams. - Updated the useTitleGeneration hook to track queue changes with a queueVersion state, ensuring accurate updates when jobs complete. - Refactored the queueTitleGeneration function to trigger listeners upon adding new conversation IDs, enhancing the overall title generation flow. * refactor: streamline agent controller and remove legacy resumable handling - Updated the AgentController to route all requests to ResumableAgentController, simplifying the logic. - Deprecated the legacy non-resumable path, providing a clear migration path for future use. - Adjusted setHeaders middleware to remove unnecessary checks for resumable mode. - Cleaned up the useResumableSSE hook to eliminate redundant query parameters, enhancing clarity and performance. * feat: Add USE_REDIS_STREAMS configuration to .env.example - Updated .env.example to include USE_REDIS_STREAMS setting, allowing control over Redis usage for resumable LLM streams. - Provided additional context on the behavior of USE_REDIS_STREAMS when not explicitly set, enhancing clarity for configuration management. * refactor: remove unused setHeaders middleware from chat route - Eliminated the setHeaders middleware from the chat route, streamlining the request handling process. - This change contributes to cleaner code and improved performance by reducing unnecessary middleware checks. * fix: Add streamId parameter for resumable stream handling across services (actions, mcp oauth) * fix(flow): add immediate abort handling and fix intervalId initialization - Add immediate abort handler that responds instantly to abort signal - Declare intervalId before cleanup function to prevent 'Cannot access before initialization' error - Consolidate cleanup logic into single function to avoid duplicate cleanup - Properly remove abort event listener on cleanup * fix(mcp): clean up OAuth flows on abort and simplify flow handling - Add abort handler in reconnectServer to clean up mcp_oauth and mcp_get_tokens flows - Update createAbortHandler to clean up both flow types on tool call abort - Pass abort signal to createFlow in returnOnOAuth path - Simplify handleOAuthRequired to always cancel existing flows and start fresh - This ensures user always gets a new OAuth URL instead of waiting for stale flows * fix(agents): handle 'new' conversationId and improve abort reliability - Treat 'new' as placeholder that needs UUID in request controller - Send JSON response immediately before tool loading for faster SSE connection - Use job's abort controller instead of prelimAbortController - Emit errors to stream if headers already sent - Skip 'new' as valid ID in abort endpoint - Add fallback to find active jobs by userId when conversationId is 'new' * fix(stream): detect early abort and prevent navigation to non-existent conversation - Abort controller on job completion to signal pending operations - Detect early abort (no content, no responseMessageId) in abortJob - Set conversation and responseMessage to null for early aborts - Add earlyAbort flag to final event for frontend detection - Remove unused text field from AbortResult interface - Frontend handles earlyAbort by staying on/navigating to new chat * test(mcp): update test to expect signal parameter in createFlow * 🔧 refactor: Update Vertex AI Configuration Handling - Simplified the logic for enabling Vertex AI in the Anthropic initialization process, ensuring it defaults to enabled unless explicitly set to false. - Adjusted the Vertex AI schema to make the 'enabled' property optional, defaulting to true when the configuration is present. - Updated related comments and documentation for clarity on the configuration behavior. * 🔧 chore: Update Anthropic Configuration and Logging Enhancements - Changed the default region for Anthropic Vertex AI from 'global' to 'us-east5' in the .env.example file for better regional alignment. - Added debug logging to handle non-JSON credentials in the Anthropic client, improving error visibility during credential parsing. - Updated the service key path resolution in the Vertex AI client to use the current working directory, enhancing flexibility in file location. --------- Co-authored-by: Ziyan <5621658+Ziyann@users.noreply.github.com> Co-authored-by: Aron Gates <aron@muonspace.com> Co-authored-by: Danny Avila <danny@librechat.ai> Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-30 18:16:52 -05:00
getAnthropicModels({ user: req.user.id, vertexModels: vertexConfig?.modelNames }).catch(
(error) => {
logger.error('Error fetching Anthropic models:', error);
return [];
},
),
getOpenAIModels({ user: req.user.id, azure: true }).catch((error) => {
logger.error('Error fetching Azure OpenAI models:', error);
return [];
}),
getOpenAIModels({ assistants: true }).catch((error) => {
logger.error('Error fetching OpenAI Assistants API models:', error);
return [];
}),
getOpenAIModels({ azureAssistants: true }).catch((error) => {
logger.error('Error fetching Azure OpenAI Assistants API models:', error);
return [];
}),
Promise.resolve(getGoogleModels()).catch((error) => {
logger.error('Error getting Google models:', error);
return [];
}),
Promise.resolve(getBedrockModels()).catch((error) => {
logger.error('Error getting Bedrock models:', error);
return [];
}),
]);
return {
[EModelEndpoint.openAI]: openAI,
[EModelEndpoint.google]: google,
[EModelEndpoint.anthropic]: anthropic,
[EModelEndpoint.azureOpenAI]: azureOpenAI,
[EModelEndpoint.assistants]: assistants,
[EModelEndpoint.azureAssistants]: azureAssistants,
[EModelEndpoint.bedrock]: bedrock,
};
} catch (error) {
logger.error('Error fetching default models:', error);
throw new Error(`Failed to load default models: ${error.message}`);
}
}
module.exports = loadDefaultModels;