* 🔧 chore: Update @librechat/agents to version 3.0.35
* ✨ feat: Add DeepSeek Model Pricing and Token Handling
- Introduced pricing and token limits for 'deepseek-chat' and 'deepseek-reasoner' models, including prompt and completion rates.
- Enhanced tests to validate pricing and token limits for DeepSeek models, ensuring correct handling of model variations and provider prefixes.
- Updated cache multipliers for DeepSeek models to reflect new pricing structure.
- Improved max output token handling for DeepSeek models, ensuring consistency across different endpoints.
* 🤖 feat: Latest Grok Model Pricing & Context Rates
- Introduced 'grok-4-fast', 'grok-4-1-fast', and 'grok-code-fast' models with their respective prompt and completion rates.
- Enhanced unit tests to validate prompt and completion rates for the new models, including variations with prefixes.
- Updated token limits for the new models in the tokens utility, ensuring accurate handling in tests.
* 🔧 refactor: Optimize JSON Export Logic in useExportConversation Hook
Updated the export logic to create a Blob from the JSON string before downloading, improving compatibility and performance for file downloads. This change enhances the handling of deeply nested exports while maintaining the file size reduction achieved in previous updates.
* 🤖 feat: Claude Opus 4.5 Token Rates and Window Limits
- Introduced new model 'claude-opus-4-5' with defined prompt and completion values in tokenValues and cacheTokenValues.
- Updated tests to validate prompt, completion, and cache rates for the new model.
- Enhanced model name handling to accommodate variations for 'claude-opus-4-5' across different contexts.
- Adjusted schemas to ensure correct max output token limits for the new model.
* ci: Add tests for "prompt-caching" beta header in Claude Opus 4.5 models
- Implemented tests to verify the addition of the "prompt-caching" beta header for the 'claude-opus-4-5' model and its variations.
- Updated future-proofing logic to ensure correct max token limits for Claude 4.x and 5.x Opus models, adjusting defaults to 64K where applicable.
- Enhanced existing tests to reflect changes in expected max token values for future Claude models.
* chore: Remove redundant max output check for Anthropic settings
- Eliminated the unnecessary check for ANTHROPIC_MAX_OUTPUT in the anthropicSettings schema, streamlining the logic for handling max output values.
* feat: Add support for model in token configurations and tests
* chore: Update @librechat/agents to version 3.0.26 in package.json and package-lock.json
* updated gpt5-pro
it is here and on openrouter
https://platform.openai.com/docs/models/gpt-5-pro
* feat: Add gpt-5-pro pricing
- Implemented handling for the new gpt-5-pro model in the getValueKey function.
- Updated tests to ensure correct behavior for gpt-5-pro across various scenarios.
- Adjusted token limits and multipliers for gpt-5-pro in the tokens utility files.
- Enhanced model matching functionality to include gpt-5-pro variations.
* refactor: optimize model pricing and validation logic
- Added new model pricing entries for llama2, llama3, and qwen variants in tx.js.
- Updated tokenValues to include additional models and their pricing structures.
- Implemented validation tests in tx.spec.js to ensure all models resolve correctly to pricing.
- Refactored getValueKey function to improve model matching and resolution efficiency.
- Removed outdated model entries from tokens.ts to streamline pricing management.
* fix: add missing pricing
* chore: update model pricing for qwen and gemma variants
* chore: update model pricing and add validation for context windows
- Removed outdated model entries from tx.js and updated tokenValues with new models.
- Added a test in tx.spec.js to ensure all models with pricing have corresponding context windows defined in tokens.ts.
- Introduced 'command-text' model pricing in tokens.ts to maintain consistency across model definitions.
* chore: update model names and pricing for AI21 and Amazon models
- Refactored model names in tx.js for AI21 and Amazon models to remove versioning and improve consistency.
- Updated pricing values in tokens.ts to reflect the new model names.
- Added comprehensive tests in tx.spec.js to validate pricing for both short and full model names across AI21 and Amazon models.
* feat: add pricing and validation for Claude Haiku 4.5 model
* chore: increase default max context tokens to 18000 for agents
* feat: add Qwen3 model pricing and validation tests
* chore: reorganize and update Qwen model pricing in tx.js and tokens.ts
---------
Co-authored-by: khfung <68192841+khfung@users.noreply.github.com>
* fix: update @librechat/agents to v2.4.83 to handle reasoning edge case encountered with GLM models
* feat: GLM Context Window & Pricing Support
* feat: Add support for glm4 model in token values and tests
* refactor: modularize openai llm config logic into new getOpenAILLMConfig function (#9412)
* ✈️ refactor: Migrate Anthropic's getLLMConfig to TypeScript (#9413)
* refactor: move tokens.js over to packages/api and update imports
* refactor: port tokens.js to typescript
* refactor: move helpers.js over to packages/api and update imports
* refactor: port helpers.js to typescript
* refactor: move anthropic/llm.js over to packages/api and update imports
* refactor: port anthropic/llm.js to typescript with supporting types in types/anthropic.ts and updated tests in llm.spec.js
* refactor: move llm.spec.js over to packages/api and update import
* refactor: port llm.spec.js over to typescript
* 📝 Add Prompt Parameter Support for Anthropic Custom Endpoints (#9414)
feat: add anthropic llm config support for openai-like (custom) endpoints
* fix: missed compiler / type issues from addition of getAnthropicLLMConfig
* refactor: update tokens.ts to export constants and functions, enhance type definitions, and adjust default values
* WIP: first pass, decouple `llmConfig` from `configOptions`
* chore: update import path for OpenAI configuration from 'llm' to 'config'
* refactor: enhance type definitions for ThinkingConfig and update modelOptions in AnthropicConfigOptions
* refactor: cleanup type, introduce openai transform from alt provider
* chore: integrate removeNullishValues in Google llmConfig and update OpenAI exports
* chore: bump version of @librechat/api to 1.3.5 in package.json and package-lock.json
* refactor: update customParams type in OpenAIConfigOptions to use TConfig['customParams']
* refactor: enhance transformToOpenAIConfig to include fromEndpoint and improve config extraction
* refactor: conform userId field for anthropic/openai, cleanup anthropic typing
* ci: add backward compatibility tests for getOpenAIConfig with various endpoints and configurations
* ci: replace userId with user in clientOptions for getLLMConfig
* test: add Azure OpenAI endpoint tests for various configurations in getOpenAIConfig
* refactor: defaultHeaders retrieval for prompt caching for anthropic-based custom endpoint (litellm)
* test: add unit tests for getOpenAIConfig with various Anthropic model configurations
* test: enhance Anthropic compatibility tests with addParams and dropParams handling
* chore: update @librechat/agents dependency to version 2.4.78 in package.json and package-lock.json
* chore: update @librechat/agents dependency to version 2.4.79 in package.json and package-lock.json
---------
Co-authored-by: Danny Avila <danny@librechat.ai>
* adding beta header context-1m-2025-08-07 to claude sonnet 4 to increase contact window to 1M tokens
* adding context-1m beta header to test cases
* ci: Update Anthropic `getLLMConfig` tests and headers for model variations
- Refactored test cases to ensure proper handling of model variations for 'claude-sonnet-4'.
- Cleaned up unused mock implementations in tests for better clarity and performance.
* refactor: regex in header retrieval for 'claude-sonnet-4' models
* refactor: default tokens for 'claude-sonnet-4' to `1,000,000`
* refactor: add token value retrieval and pattern matching to model tests
---------
Co-authored-by: Dirk Petersen <no-reply@nowhere.com>
* refactor: Update AnthropicClient to support Claude model naming changes
* Renamed `isClaude3` to `isClaudeLatest` to accommodate newer Claude models.
* Updated logic to determine if the model is part of the Claude family.
* Adjusted `useMessages` property to reflect the new model naming convention.
* Cleaned up client properties during disposal to match the updated naming.
* feat: Claude-4 Support
* feat: Add Thinking and Prompt caching support for Claude 4
* chore: Update ANTHROPIC_MODELS in .env.example for latest model versions
* feat: Add support for new OpenAI models (o4-mini, o3) and update related logic
* 🔧 fix: Rename 'resubmitFiles' to 'isResubmission' for consistency across types and hooks
* 🔧 fix: Replace hardcoded 'pending_req' with CacheKeys.PENDING_REQ for consistency in cache handling
* 🔧 fix: Update cache handling to use Time.ONE_MINUTE instead of hardcoded TTL and streamline imports
* 🔧 fix: Enhance message handling logic to correctly identify parent messages and streamline imports in useSSE
* fix: Agent Builder setting not applying in useSideNavLinks
* fix: Remove unused type imports in useSideNavLinks
* feat: gpt-4.1
* fix: Update getCacheMultiplier and getMultiplier tests to use dynamic token values
* feat: Add gpt-4.1 to the list of vision models
* chore: Bump version of librechat-data-provider to 0.7.792
* chore: remove unused redis file
* chore: bump keyv dependencies, and update related imports
* refactor: Implement IoRedis client for rate limiting across middleware, as node-redis via keyv not compatible
* fix: Set max listeners to expected amount
* WIP: memory improvements
* refactor: Simplify getAbortData assignment in createAbortController
* refactor: Update getAbortData to use WeakRef for content management
* WIP: memory improvements in agent chat requests
* refactor: Enhance memory management with finalization registry and cleanup functions
* refactor: Simplify domainParser calls by removing unnecessary request parameter
* refactor: Update parameter types for action tools and agent loading functions to use minimal configs
* refactor: Simplify domainParser tests by removing unnecessary request parameter
* refactor: Simplify domainParser call by removing unnecessary request parameter
* refactor: Enhance client disposal by nullifying additional properties to improve memory management
* refactor: Improve title generation by adding abort controller and timeout handling, consolidate request cleanup
* refactor: Update checkIdleConnections to skip current user when checking for idle connections if passed
* refactor: Update createMCPTool to derive userId from config and handle abort signals
* refactor: Introduce createTokenCounter function and update tokenCounter usage; enhance disposeClient to reset Graph values
* refactor: Update getMCPManager to accept userId parameter for improved idle connection handling
* refactor: Extract logToolError function for improved error handling in AgentClient
* refactor: Update disposeClient to clear handlerRegistry and graphRunnable references in client.run
* refactor: Extract createHandleNewToken function to streamline token handling in initializeClient
* chore: bump @librechat/agents
* refactor: Improve timeout handling in addTitle function for better error management
* refactor: Introduce createFetch instead of using class method
* refactor: Enhance client disposal and request data handling in AskController and EditController
* refactor: Update import statements for AnthropicClient and OpenAIClient to use specific paths
* refactor: Use WeakRef for response handling in SplitStreamHandler to prevent memory leaks
* refactor: Simplify client disposal and rename getReqData to processReqData in AskController and EditController
* refactor: Improve logging structure and parameter handling in OpenAIClient
* refactor: Remove unused GraphEvents and improve stream event handling in AnthropicClient and OpenAIClient
* refactor: Simplify client initialization in AskController and EditController
* refactor: Remove unused mock functions and implement in-memory store for KeyvMongo
* chore: Update dependencies in package-lock.json to latest versions
* refactor: Await token usage recording in OpenAIClient to ensure proper async handling
* refactor: Remove handleAbort route from multiple endpoints and enhance client disposal logic
* refactor: Enhance abort controller logic by managing abortKey more effectively
* refactor: Add newConversation handling in useEventHandlers for improved conversation management
* fix: dropparams
* refactor: Use optional chaining for safer access to request properties in BaseClient
* refactor: Move client disposal and request data processing logic to cleanup module for better organization
* refactor: Remove aborted request check from addTitle function for cleaner logic
* feat: Add Grok 3 model pricing and update tests for new models
* chore: Remove trace warnings and inspect flags from backend start script used for debugging
* refactor: Replace user identifier handling with userId for consistency across controllers, use UserId in clientRegistry
* refactor: Enhance client disposal logic to prevent memory leaks by clearing additional references
* chore: Update @librechat/agents to version 2.4.14 in package.json and package-lock.json
* wip: first pass, dropdown for selecting sequential agents
* refactor: Improve agent selection logic and enhance performance in SequentialAgents component
* wip: seq. agents working ideas
* wip: sequential agents style change
* refactor: move agent form options/submission outside of AgentConfig
* refactor: prevent repeating code
* refactor: simplify current agent display in SequentialAgents component
* feat: persist form value handling in AgentSelect component for agent_ids
* feat: first pass, sequential agnets agent update
* feat: enhance message display with agent updates and empty text handling
* chore: update Icon component to use EModelEndpoint for agent endpoints
* feat: update content type checks in BaseClient to use constants for better readability
* feat: adjust max context tokens calculation to use 90% of the model's max tokens
* feat: first pass, agent run message pruning
* chore: increase max listeners for abort controller to prevent memory leaks
* feat: enhance runAgent function to include current index count map for improved token tracking
* chore: update @librechat/agents dependency to version 2.2.5
* feat: update icons and style of SequentialAgents component for improved UI consistency
* feat: add AdvancedButton and AdvancedPanel components for enhanced agent settings navigation, update styling for agent form
* chore: adjust minimum height of AdvancedPanel component for better layout consistency
* chore: update @librechat/agents dependency to version 2.2.6
* feat: enhance message formatting by incorporating tool set into agent message processing, in order to allow better mix/matching of agents (as tool calls for tools not found in set will be stringified)
* refactor: reorder components in AgentConfig for improved readability and maintainability
* refactor: enhance layout of AgentUpdate component for improved visual structure
* feat: add DeepSeek provider to Bedrock settings and schemas
* feat: enhance link styling in mobile.css for better visibility and accessibility
* fix: update banner model import in update banner script; export Banner model
* refactor: `duplicateAgentHandler` to include tool_resources only for OCR context files
* feat: add 'qwen-vl' to visionModels for enhanced model support
* fix: change image format from JPEG to PNG in DALLE3 response
* feat: reorganize Advanced components and add localizations
* refactor: simplify JSX structure in AgentChain component to defer container styling to parent
* feat: add FormInput component for reusable input handling
* feat: make agent recursion limit configurable from builder
* feat: add support for agent capabilities chain in AdvancedPanel and update data-provider version
* feat: add maxRecursionLimit configuration for agents and update related documentation
* fix: update CONFIG_VERSION to 1.2.3 in data provider configuration
* feat: replace recursion limit input with MaxAgentSteps component and enhance input handling
* feat: enhance AgentChain component with hover card for additional information and update related labels
* fix: pass request and response objects to `createActionTool` when using assistant actions to prevent auth error
* feat: update AgentChain component layout to include agent count display
* feat: increase default max listeners and implement capability check function for agent chain
* fix: update link styles in mobile.css for better visibility in dark mode
* chore: temp. remove agents package while bumping shared packages
* chore: update @langchain/google-genai package to version 0.1.11
* chore: update @langchain/google-vertexai package to version 0.2.2
* chore: add @librechat/agents package at version 2.2.8
* feat: add deepseek.r1 model with token rate and context values for bedrock
* 🔧 refactor: Update settings to use 'as const' for improved type safety and make gpt-4o-mini default model (cheapest)
* 📖 docs: Update README to reflect support for GPT-4.5 in image analysis feature
* 🔧 refactor: Update model handling to use default settings and improve encoding logic
* 🔧 refactor: Enhance model version extraction logic for improved compatibility with future GPT and omni models
* feat: GPT-4.5 tx/token update, vision support
* fix: $ref resolution logic in OpenAPI handling
* feat: add new 'anthropic-beta' header for Claude 3.7 to include token-efficient tools; ref: https://docs.anthropic.com/en/docs/build-with-claude/tool-use/token-efficient-tool-use
* fix: missing console color methods for admin scripts
* feat: Anthropic Claude 3.7 Sonnet Support
* feat: update eventsource to version 3.0.2 and upgrade @modelcontextprotocol/sdk to 1.4.1
* fix: update DynamicInput to handle number type and improve initial value logic
* feat: first pass Anthropic Reasoning (Claude 3.7)
* feat: implement streaming support in AnthropicClient with reasoning UI handling
* feat: add missing xAI (grok) models
* 🤖 refactor: streamline model selection logic for title model in GoogleClient
* refactor: add options for empty object schemas in convertJsonSchemaToZod
* refactor: add utility function to check for empty object schemas in convertJsonSchemaToZod
* fix: Google MCP Tool errors, and remove Object Unescaping as Google fixed this
* fix: google safetySettings
* feat: add safety settings exclusion via GOOGLE_EXCLUDE_SAFETY_SETTINGS environment variable
* fix: rename environment variable for console JSON string length
* fix: disable portal for dropdown in ExportModal component
* fix: screenshot functionality to use image placeholder for remote images
* feat: add visionMode property to BaseClient and initialize in GoogleClient to fix resendFiles issue
* fix: enhance formatMessages to include image URLs in message content for Vertex AI
* fix: safety settings for titleChatCompletion
* fix: remove deprecated model assignment in GoogleClient and streamline title model retrieval
* fix: remove unused image preloading logic in ScreenshotContext
* chore: update default google models to latest models shared by vertex ai and gen ai
* refactor: enhance Google error messaging
* fix: update token values and model limits for Gemini models
* ci: fix model matching
* chore: bump version of librechat-data-provider to 0.7.699
* fix: google-thinking model safety settings fix
* chore: update pricing/context for deepseek models
* ci: update Deepseek model token limits to use dynamic mapping
* feat: Add BedrockIcon component to SVG library
* feat: EModelEndpoint.bedrock
* feat: first pass, bedrock chat. note: AgentClient is returning `agents` as conversation.endpoint
* fix: declare endpoint in initialization step
* chore: Update @librechat/agents dependency to version 1.4.5
* feat: backend content aggregation for agents/bedrock
* feat: abort agent requests
* feat: AWS Bedrock icons
* WIP: agent provider schema parsing
* chore: Update EditIcon props type
* refactor(useGenerationsByLatest): make agents and bedrock editable
* refactor: non-assistant message content, parts
* fix: Bedrock response `sender`
* fix: use endpointOption.model_parameters not endpointOption.modelOptions
* fix: types for step handler
* refactor: Update Agents.ToolCallDelta type
* refactor: Remove unnecessary assignment of parentMessageId in AskController
* refactor: remove unnecessary assignment of parentMessageId (agent request handler)
* fix(bedrock/agents): message regeneration
* refactor: dynamic form elements using react-hook-form Controllers
* fix: agent icons/labels for messages
* fix: agent actions
* fix: use of new dynamic tags causing application crash
* refactor: dynamic settings touch-ups
* refactor: update Slider component to allow custom track class name
* refactor: update DynamicSlider component styles
* refactor: use Constants value for GLOBAL_PROJECT_NAME (enum)
* feat: agent share global methods/controllers
* fix: agents query
* fix: `getResponseModel`
* fix: share prompt a11y issue
* refactor: update SharePrompt dialog theme styles
* refactor: explicit typing for SharePrompt
* feat: add agent roles/permissions
* chore: update @librechat/agents dependency to version 1.4.7 for tool_call_ids edge case
* fix(Anthropic): messages.X.content.Y.tool_use.input: Input should be a valid dictionary
* fix: handle text parts with tool_call_ids and empty text
* fix: role initialization
* refactor: don't make instructions required
* refactor: improve typing of Text part
* fix: setShowStopButton for agents route
* chore: remove params for now
* fix: add streamBuffer and streamRate to help prevent 'Overloaded' errors from Anthropic API
* refactor: remove console.log statement in ContentRender component
* chore: typing, rename Context to Delete Button
* chore(DeleteButton): logging
* refactor(Action): make accessible
* style(Action): improve a11y again
* refactor: remove use/mention of mongoose sessions
* feat: first pass, sharing agents
* feat: visual indicator for global agent, remove author when serving to non-author
* wip: params
* chore: fix typing issues
* fix(schemas): typing
* refactor: improve accessibility of ListCard component and fix console React warning
* wip: reset templates for non-legacy new convos
* Revert "wip: params"
This reverts commit f8067e91d4.
* Revert "refactor: dynamic form elements using react-hook-form Controllers"
This reverts commit 2150c4815d.
* fix(Parameters): types and parameter effect update to only update local state to parameters
* refactor: optimize useDebouncedInput hook for better performance
* feat: first pass, anthropic bedrock params
* chore: paramEndpoints check for endpointType too
* fix: maxTokens to use coerceNumber.optional(),
* feat: extra chat model params
* chore: reduce code repetition
* refactor: improve preset title handling in SaveAsPresetDialog component
* refactor: improve preset handling in HeaderOptions component
* chore: improve typing, replace legacy dialog for SaveAsPresetDialog
* feat: save as preset from parameters panel
* fix: multi-search in select dropdown when using Option type
* refactor: update default showDefault value to false in Dynamic components
* feat: Bedrock presets settings
* chore: config, fix agents schema, update config version
* refactor: update AWS region variable name in bedrock options endpoint to BEDROCK_AWS_DEFAULT_REGION
* refactor: update baseEndpointSchema in config.ts to include baseURL property
* refactor: update createRun function to include req parameter and set streamRate based on provider
* feat: availableRegions via config
* refactor: remove unused demo agent controller file
* WIP: title
* Update @librechat/agents to version 1.5.0
* chore: addTitle.js to handle empty responseText
* feat: support images and titles
* feat: context token updates
* Refactor BaseClient test to use expect.objectContaining
* refactor: add model select, remove header options params, move side panel params below prompts
* chore: update models list, catch title error
* feat: model service for bedrock models (env)
* chore: Remove verbose debug log in AgentClient class following stream
* feat(bedrock): track token spend; fix: token rates, value key mapping for AWS models
* refactor: handle streamRate in `handleLLMNewToken` callback
* chore: AWS Bedrock example config in `.env.example`
* refactor: Rename bedrockMeta to bedrockGeneral in settings.ts and use for AI21 and Amazon Bedrock providers
* refactor: Update `.env.example` with AWS Bedrock model IDs URL and additional notes
* feat: titleModel support for bedrock
* refactor: Update `.env.example` with additional notes for AWS Bedrock model IDs
* WIP: gemini-1.5 support
* feat: extended vertex ai support
* fix: handle possibly undefined modelName
* fix: gpt-4-turbo-preview invalid vision model
* feat: specify `fileConfig.imageOutputType` and make PNG default image conversion type
* feat: better truncation for errors including base64 strings
* fix: gemini inlineData formatting
* feat: RAG augmented prompt for gemini-1.5
* feat: gemini-1.5 rates and token window
* chore: adjust tokens, update docs, update vision Models
* chore: add back `ChatGoogleVertexAI` for chat models via vertex ai
* refactor: ask/edit controllers to not use `unfinished` field for google endpoint
* chore: remove comment
* chore(ci): fix AppService test
* chore: remove comment
* refactor(GoogleSearch): use `GOOGLE_SEARCH_API_KEY` instead, issue warning for old variable
* chore: bump data-provider to 0.5.4
* chore: update docs
* fix: condition for gemini-1.5 using generative ai lib
* chore: update docs
* ci: add additional AppService test for `imageOutputType`
* refactor: optimize new config value `imageOutputType`
* chore: bump CONFIG_VERSION
* fix(assistants): avatar upload
* refactor: add gemini-pro to google Models list; use defaultModels for central model listing
* refactor(SetKeyDialog): create useMultipleKeys hook to use for Azure, export `isJson` from utils, use EModelEndpoint
* refactor(useUserKey): change variable names to make keyName setting more clear
* refactor(FileUpload): allow passing container className string
* feat(GoogleClient): Gemini support
* refactor(GoogleClient): alternate stream speed for Gemini models
* feat(Gemini): styling/settings configuration for Gemini
* refactor(GoogleClient): substract max response tokens from max context tokens if context is above 32k (I/O max is combined between the two)
* refactor(tokens): correct google max token counts and subtract max response tokens when input/output count are combined towards max context count
* feat(google/initializeClient): handle both local and user_provided credentials and write tests
* fix(GoogleClient): catch if credentials are undefined, handle if serviceKey is string or object correctly, handle no examples passed, throw error if not a Generative Language model and no service account JSON key is provided, throw error if it is a Generative m
odel, but not google API key was provided
* refactor(loadAsyncEndpoints/google): activate Google endpoint if either the service key JSON file is provided in /api/data, or a GOOGLE_KEY is defined.
* docs: updated Google configuration
* fix(ci): Mock import of Service Account Key JSON file (auth.json)
* Update apis_and_tokens.md
* feat: increase max output tokens slider for gemini pro
* refactor(GoogleSettings): handle max and default maxOutputTokens on model change
* chore: add sensitive redact regex
* docs: add warning about data privacy
* Update apis_and_tokens.md
* chore: bump vite, vitejs/plugin-react, mark client package as esm, move react-query as a peer dep in data-provider
* chore: import changes due to new data-provider export strategy, also fix type imports where applicable
* chore: export react-query services as separate to avoid react dependencies in /api/
* chore: suppress sourcemap warnings and polyfill node:path which is used by filenamify
TODO: replace filenamify with an alternative and REMOVE polyfill
* chore: /api/ changes to support `librechat-data-provider`
* refactor: rewrite Dockerfile.multi in light of /api/ changes to support `librechat-data-provider`
* chore: remove volume mapping to node_modules directories in default compose file
* chore: remove schemas from /api/ as is no longer needed with use of `librechat-data-provider`
* fix(ci): jest `librechat-data-provider/react-query` module resolution
* feat: update PaLM icons
* feat: add additional google models
* POC: formatting inputs for Vertex AI streaming
* refactor: move endpoints services outside of /routes dir to /services/Endpoints
* refactor: shorten schemas import
* refactor: rename PALM to GOOGLE
* feat: make Google editable endpoint
* feat: reusable Ask and Edit controllers based off Anthropic
* chore: organize imports/logic
* fix(parseConvo): include examples in googleSchema
* fix: google only allows odd number of messages to be sent
* fix: pass proxy to AnthropicClient
* refactor: change `google` altName to `Google`
* refactor: update getModelMaxTokens and related functions to handle maxTokensMap with nested endpoint model key/values
* refactor: google Icon and response sender changes (Codey and Google logo instead of PaLM in all cases)
* feat: google support for maxTokensMap
* feat: google updated endpoints with Ask/Edit controllers, buildOptions, and initializeClient
* feat(GoogleClient): now builds prompt for text models and supports real streaming from Vertex AI through langchain
* chore(GoogleClient): remove comments, left before for reference in git history
* docs: update google instructions (WIP)
* docs(apis_and_tokens.md): add images to google instructions
* docs: remove typo apis_and_tokens.md
* Update apis_and_tokens.md
* feat(Google): use default settings map, fully support context for both text and chat models, fully support examples for chat models
* chore: update more PaLM references to Google
* chore: move playwright out of workflows to avoid failing tests
* fix: correct preset title for Anthropic endpoint
* fix(Settings/Anthropic): show correct default value for LLM temperature
* fix(AnthropicClient): use `getModelMaxTokens` to get the correct LLM max context tokens, correctly set default temperature to 1, use only 2 params for class constructor, use `getResponseSender` to add correct sender to response message
* refactor(/api/ask|edit/anthropic): save messages to database after the final response is sent to the client, and do not save conversation from route controller
* fix(initializeClient/anthropic): correctly pass client options (endpointOption) to class initialization
* feat(ModelService/Anthropic): add claude-1.2
* chore: update model rates with 11/06 rates
* chore: add new models to env.example for OPENAI_MODELS
* chore: reference actual maxTokensMap in ci tests
* refactor(Chains/llms): allow passing callbacks
* refactor(BaseClient): accurately count completion tokens as generation only
* refactor(OpenAIClient): remove unused getTokenCountForResponse, pass streaming var and callbacks in initializeLLM
* wip: summary prompt tokens
* refactor(summarizeMessages): new cut-off strategy that generates a better summary by adding context from beginning, truncating the middle, and providing the end
wip: draft out relevant providers and variables for token tracing
* refactor(createLLM): make streaming prop false by default
* chore: remove use of getTokenCountForResponse
* refactor(agents): use BufferMemory as ConversationSummaryBufferMemory token usage not easy to trace
* chore: remove passing of streaming prop, also console log useful vars for tracing
* feat: formatFromLangChain helper function to count tokens for ChatModelStart
* refactor(initializeLLM): add role for LLM tracing
* chore(formatFromLangChain): update JSDoc
* feat(formatMessages): formats langChain messages into OpenAI payload format
* chore: install openai-chat-tokens
* refactor(formatMessage): optimize conditional langChain logic
fix(formatFromLangChain): fix destructuring
* feat: accurate prompt tokens for ChatModelStart before generation
* refactor(handleChatModelStart): move to callbacks dir, use factory function
* refactor(initializeLLM): rename 'role' to 'context'
* feat(Balance/Transaction): new schema/models for tracking token spend
refactor(Key): factor out model export to separate file
* refactor(initializeClient): add req,res objects to client options
* feat: add-balance script to add to an existing users' token balance
refactor(Transaction): use multiplier map/function, return balance update
* refactor(Tx): update enum for tokenType, return 1 for multiplier if no map match
* refactor(Tx): add fair fallback value multiplier incase the config result is undefined
* refactor(Balance): rename 'tokens' to 'tokenCredits'
* feat: balance check, add tx.js for new tx-related methods and tests
* chore(summaryPrompts): update prompt token count
* refactor(callbacks): pass req, res
wip: check balance
* refactor(Tx): make convoId a String type, fix(calculateTokenValue)
* refactor(BaseClient): add conversationId as client prop when assigned
* feat(RunManager): track LLM runs with manager, track token spend from LLM,
refactor(OpenAIClient): use RunManager to create callbacks, pass user prop to langchain api calls
* feat(spendTokens): helper to spend prompt/completion tokens
* feat(checkBalance): add helper to check, log, deny request if balance doesn't have enough funds
refactor(Balance): static check method to return object instead of boolean now
wip(OpenAIClient): implement use of checkBalance
* refactor(initializeLLM): add token buffer to assure summary isn't generated when subsequent payload is too large
refactor(OpenAIClient): add checkBalance
refactor(createStartHandler): add checkBalance
* chore: remove prompt and completion token logging from route handler
* chore(spendTokens): add JSDoc
* feat(logTokenCost): record transactions for basic api calls
* chore(ask/edit): invoke getResponseSender only once per API call
* refactor(ask/edit): pass promptTokens to getIds and include in abort data
* refactor(getIds -> getReqData): rename function
* refactor(Tx): increase value if incomplete message
* feat: record tokenUsage when message is aborted
* refactor: subtract tokens when payload includes function_call
* refactor: add namespace for token_balance
* fix(spendTokens): only execute if corresponding token type amounts are defined
* refactor(checkBalance): throws Error if not enough token credits
* refactor(runTitleChain): pass and use signal, spread object props in create helpers, and use 'call' instead of 'run'
* fix(abortMiddleware): circular dependency, and default to empty string for completionTokens
* fix: properly cancel title requests when there isn't enough tokens to generate
* feat(predictNewSummary): custom chain for summaries to allow signal passing
refactor(summaryBuffer): use new custom chain
* feat(RunManager): add getRunByConversationId method, refactor: remove run and throw llm error on handleLLMError
* refactor(createStartHandler): if summary, add error details to runs
* fix(OpenAIClient): support aborting from summarization & showing error to user
refactor(summarizeMessages): remove unnecessary operations counting summaryPromptTokens and note for alternative, pass signal to summaryBuffer
* refactor(logTokenCost -> recordTokenUsage): rename
* refactor(checkBalance): include promptTokens in errorMessage
* refactor(checkBalance/spendTokens): move to models dir
* fix(createLanguageChain): correctly pass config
* refactor(initializeLLM/title): add tokenBuffer of 150 for balance check
* refactor(openAPIPlugin): pass signal and memory, filter functions by the one being called
* refactor(createStartHandler): add error to run if context is plugins as well
* refactor(RunManager/handleLLMError): throw error immediately if plugins, don't remove run
* refactor(PluginsClient): pass memory and signal to tools, cleanup error handling logic
* chore: use absolute equality for addTitle condition
* refactor(checkBalance): move checkBalance to execute after userMessage and tokenCounts are saved, also make conditional
* style: icon changes to match official
* fix(BaseClient): getTokenCountForResponse -> getTokenCount
* fix(formatLangChainMessages): add kwargs as fallback prop from lc_kwargs, update JSDoc
* refactor(Tx.create): does not update balance if CHECK_BALANCE is not enabled
* fix(e2e/cleanUp): cleanup new collections, import all model methods from index
* fix(config/add-balance): add uncaughtException listener
* fix: circular dependency
* refactor(initializeLLM/checkBalance): append new generations to errorMessage if cost exceeds balance
* fix(handleResponseMessage): only record token usage in this method if not error and completion is not skipped
* fix(createStartHandler): correct condition for generations
* chore: bump postcss due to moderate severity vulnerability
* chore: bump zod due to low severity vulnerability
* chore: bump openai & data-provider version
* feat(types): OpenAI Message types
* chore: update bun lockfile
* refactor(CodeBlock): add error block formatting
* refactor(utils/Plugin): factor out formatJSON and cn to separate files (json.ts and cn.ts), add extractJSON
* chore(logViolation): delete user_id after error is logged
* refactor(getMessageError -> Error): change to React.FC, add token_balance handling, use extractJSON to determine JSON instead of regex
* fix(DALL-E): use latest openai SDK
* chore: reorganize imports, fix type issue
* feat(server): add balance route
* fix(api/models): add auth
* feat(data-provider): /api/balance query
* feat: show balance if checking is enabled, refetch on final message or error
* chore: update docs, .env.example with token_usage info, add balance script command
* fix(Balance): fallback to empty obj for balance query
* style: slight adjustment of balance element
* docs(token_usage): add PR notes
* refactor: pass model in message edit payload, use encoder in standalone util function
* feat: add summaryBuffer helper
* refactor(api/messages): use new countTokens helper and add auth middleware at top
* wip: ConversationSummaryBufferMemory
* refactor: move pre-generation helpers to prompts dir
* chore: remove console log
* chore: remove test as payload will no longer carry tokenCount
* chore: update getMessagesWithinTokenLimit JSDoc
* refactor: optimize getMessagesForConversation and also break on summary, feat(ci): getMessagesForConversation tests
* refactor(getMessagesForConvo): count '00000000-0000-0000-0000-000000000000' as root message
* chore: add newer model to token map
* fix: condition was point to prop of array instead of message prop
* refactor(BaseClient): use object for refineMessages param, rename 'summary' to 'summaryMessage', add previous_summary
refactor(getMessagesWithinTokenLimit): replace text and tokenCount if should summarize, summary, and summaryTokenCount are present
fix/refactor(handleContextStrategy): use the right comparison length for context diff, and replace payload first message when a summary is present
* chore: log previous_summary if debugging
* refactor(formatMessage): assume if role is defined that it's a valid value
* refactor(getMessagesWithinTokenLimit): remove summary logic
refactor(handleContextStrategy): add usePrevSummary logic in case only summary was pruned
refactor(loadHistory): initial message query will return all ordered messages but keep track of the latest summary
refactor(getMessagesForConversation): use object for single param, edit jsdoc, edit all files using the method
refactor(ChatGPTClient): order messages before buildPrompt is called, TODO: add convoSumBuffMemory logic
* fix: undefined handling and summarizing only when shouldRefineContext is true
* chore(BaseClient): fix test results omitting system role for summaries and test edge case
* chore: export summaryBuffer from index file
* refactor(OpenAIClient/BaseClient): move refineMessages to subclass, implement LLM initialization for summaryBuffer
* feat: add OPENAI_SUMMARIZE to enable summarizing, refactor: rename client prop 'shouldRefineContext' to 'shouldSummarize', change contextStrategy value to 'summarize' from 'refine'
* refactor: rename refineMessages method to summarizeMessages for clarity
* chore: clarify summary future intent in .env.example
* refactor(initializeLLM): handle case for either 'model' or 'modelName' being passed
* feat(gptPlugins): enable summarization for plugins
* refactor(gptPlugins): utilize new initializeLLM method and formatting methods for messages, use payload array for currentMessages and assign pastMessages sooner
* refactor(agents): use ConversationSummaryBufferMemory for both agent types
* refactor(formatMessage): optimize original method for langchain, add helper function for langchain messages, add JSDocs and tests
* refactor(summaryBuffer): add helper to createSummaryBufferMemory, and use new formatting helpers
* fix: forgot to spread formatMessages also took opportunity to pluralize filename
* refactor: pass memory to tools, namely openapi specs. not used and may never be used by new method but added for testing
* ci(formatMessages): add more exhaustive checks for langchain messages
* feat: add debug env var for OpenAI
* chore: delete unnecessary comments
* chore: add extra note about summary feature
* fix: remove tokenCount from payload instructions
* fix: test fail
* fix: only pass instructions to payload when defined or not empty object
* refactor: fromPromptMessages is deprecated, use renamed method fromMessages
* refactor: use 'includes' instead of 'startsWith' for extended OpenRouter compatibility
* fix(PluginsClient.buildPromptBody): handle undefined message strings
* chore: log langchain titling error
* feat: getModelMaxTokens helper
* feat: tokenSplit helper
* feat: summary prompts updated
* fix: optimize _CUT_OFF_SUMMARIZER prompt
* refactor(summaryBuffer): use custom summary prompt, allow prompt to be passed, pass humanPrefix and aiPrefix to memory, along with any future variables, rename messagesToRefine to context
* fix(summaryBuffer): handle edge case where messagesToRefine exceeds summary context,
refactor(BaseClient): allow custom maxContextTokens to be passed to getMessagesWithinTokenLimit, add defined check before unshifting summaryMessage, update shouldSummarize based on this
refactor(OpenAIClient): use getModelMaxTokens, use cut-off message method for summary if no messages were left after pruning
* fix(handleContextStrategy): handle case where incoming prompt is bigger than model context
* chore: rename refinedContent to splitText
* chore: remove unnecessary debug log
