* feat: add claude-3-haiku-20240307 to default anthropic list
* refactor: optimize `saveMessage` calls mid-stream via throttling
* chore: remove addMetadata operations and consolidate in BaseClient
* fix(listAssistantsForAzure): attempt to specify correct model mapping as accurately as possible (#2177)
* refactor(client): update last conversation setup with current assistant model, call newConvo again when assistants load to allow fast initial load and ensure assistant model is always the default, not the last selected model
* refactor(cache): explicitly add TTL of 2 minutes when setting titleCache and add default TTL of 10 minutes to abortKeys cache
* feat(AnthropicClient): conversation titling using Anthropic Function Calling
* chore: remove extraneous token usage logging
* fix(convos): unhandled edge case for conversation grouping (undefined conversation)
* style: Improved style of Search Bar after recent UI update
* chore: remove unused code, content part helpers
* feat: always show code option
* chore: bump anthropic SDK
* chore: update anthropic config settings (fileSupport, default models)
* feat: anthropic multi modal formatting
* refactor: update vision models and use endpoint specific max long side resizing
* feat(anthropic): multimodal messages, retry logic, and messages payload
* chore: add more safety to trimming content due to whitespace error for assistant messages
* feat(anthropic): token accounting and resending multiple images in progress
* chore: bump data-provider
* feat(anthropic): resendImages feature
* chore: optimize Edit/Ask controllers, switch model back to req model
* fix: false positive of invalid model
* refactor(validateVisionModel): use object as arg, pass in additional/available models
* refactor(validateModel): use helper function, `getModelsConfig`
* feat: add modelsConfig to endpointOption so it gets passed to all clients, use for properly validating vision models
* refactor: initialize default vision model and make sure it's available before assigning it
* refactor(useSSE): avoid resetting model if user selected a new model between request and response
* feat: show rate in transaction logging
* fix: return tokenCountMap regardless of payload shape
* WIP(backend/api): custom endpoint
* WIP(frontend/client): custom endpoint
* chore: adjust typedefs for configs
* refactor: use data-provider for cache keys and rename enums and custom endpoint for better clarity and compatibility
* feat: loadYaml utility
* refactor: rename back to from and proof-of-concept for creating schemas from user-defined defaults
* refactor: remove custom endpoint from default endpointsConfig as it will be exclusively managed by yaml config
* refactor(EndpointController): rename variables for clarity
* feat: initial load custom config
* feat(server/utils): add simple `isUserProvided` helper
* chore(types): update TConfig type
* refactor: remove custom endpoint handling from model services as will be handled by config, modularize fetching of models
* feat: loadCustomConfig, loadConfigEndpoints, loadConfigModels
* chore: reorganize server init imports, invoke loadCustomConfig
* refactor(loadConfigEndpoints/Models): return each custom endpoint as standalone endpoint
* refactor(Endpoint/ModelController): spread config values after default (temporary)
* chore(client): fix type issues
* WIP: first pass for multiple custom endpoints
- add endpointType to Conversation schema
- add update zod schemas for both convo/presets to allow non-EModelEndpoint value as endpoint (also using type assertion)
- use `endpointType` value as `endpoint` where mapping to type is necessary using this field
- use custom defined `endpoint` value and not type for mapping to modelsConfig
- misc: add return type to `getDefaultEndpoint`
- in `useNewConvo`, add the endpointType if it wasn't already added to conversation
- EndpointsMenu: use user-defined endpoint name as Title in menu
- TODO: custom icon via custom config, change unknown to robot icon
* refactor(parseConvo): pass args as an object and change where used accordingly; chore: comment out 'create schema' code
* chore: remove unused availableModels field in TConfig type
* refactor(parseCompactConvo): pass args as an object and change where used accordingly
* feat: chat through custom endpoint
* chore(message/convoSchemas): avoid saving empty arrays
* fix(BaseClient/saveMessageToDatabase): save endpointType
* refactor(ChatRoute): show Spinner if endpointsQuery or modelsQuery are still loading, which is apparent with slow fetching of models/remote config on first serve
* fix(useConversation): assign endpointType if it's missing
* fix(SaveAsPreset): pass real endpoint and endpointType when saving Preset)
* chore: recorganize types order for TConfig, add `iconURL`
* feat: custom endpoint icon support:
- use UnknownIcon in all icon contexts
- add mistral and openrouter as known endpoints, and add their icons
- iconURL support
* fix(presetSchema): move endpointType to default schema definitions shared between convoSchema and defaults
* refactor(Settings/OpenAI): remove legacy `isOpenAI` flag
* fix(OpenAIClient): do not invoke abortCompletion on completion error
* feat: add responseSender/label support for custom endpoints:
- use defaultModelLabel field in endpointOption
- add model defaults for custom endpoints in `getResponseSender`
- add `useGetSender` hook which uses EndpointsQuery to determine `defaultModelLabel`
- include defaultModelLabel from endpointConfig in custom endpoint client options
- pass `endpointType` to `getResponseSender`
* feat(OpenAIClient): use custom options from config file
* refactor: rename `defaultModelLabel` to `modelDisplayLabel`
* refactor(data-provider): separate concerns from `schemas` into `parsers`, `config`, and fix imports elsewhere
* feat: `iconURL` and extract environment variables from custom endpoint config values
* feat: custom config validation via zod schema, rename and move to `./projectRoot/librechat.yaml`
* docs: custom config docs and examples
* fix(OpenAIClient/mistral): mistral does not allow singular system message, also add `useChatCompletion` flag to use openai-node for title completions
* fix(custom/initializeClient): extract env var and use `isUserProvided` function
* Update librechat.example.yaml
* feat(InputWithLabel): add className props, and forwardRef
* fix(streamResponse): handle error edge case where either messages or convos query throws an error
* fix(useSSE): handle errorHandler edge cases where error response is and is not properly formatted from API, especially when a conversationId is not yet provided, which ensures stream is properly closed on error
* feat: user_provided keys for custom endpoints
* fix(config/endpointSchema): do not allow default endpoint values in custom endpoint `name`
* feat(loadConfigModels): extract env variables and optimize fetching models
* feat: support custom endpoint iconURL for messages and Nav
* feat(OpenAIClient): add/dropParams support
* docs: update docs with default params, add/dropParams, and notes to use config file instead of `OPENAI_REVERSE_PROXY`
* docs: update docs with additional notes
* feat(maxTokensMap): add mistral models (32k context)
* docs: update openrouter notes
* Update ai_setup.md
* docs(custom_config): add table of contents and fix note about custom name
* docs(custom_config): reorder ToC
* Update custom_config.md
* Add note about `max_tokens` field in custom_config.md
* fix(Message): avoid overwriting unprovided properties
* fix(OpenAIClient): return intermediateReply on user abort
* fix(AskController): do not send/save final message if abort was triggered
* fix(countTokens): avoid fetching remote registry and exclusively use cl100k_base or p50k_base weights for token counting
* refactor(Message/messageSchema): rely on messageSchema for default values when saving messages
* fix(EditController): do not send/save final message if abort was triggered
* fix(config/helpers): fix module resolution error
* chore: bump langchain to v0.0.213 from v0.0.186
* fix: handle abort edge cases:
- abort message server-side if response experienced error mid-generation
- attempt to recover message if aborting resulted in error
- if abortKey is not provided, use conversationId if it exists
- if headers were already sent, send an Event stream message
- issue warning for possible Google censor/filter
refactor(streamResponse): for `sendError`, allow passing overrides so that error can include partial generation, improve typing for `sendMessage`
* chore(MessageContent): remove eslint warning for unused `i`, rephrase unfinished message text
* fix(useSSE): avoid invoking cancelHandler if the abort response was 404
* chore(TMessage): remove unnecessary, unused legacy message property `submitting`
* chore(TMessage): remove unnecessary legacy message property `cancelled`
* chore(abortMiddleware): remove unused `errorText` property to avoid confusion
* refactor(Ask/Edit): consolidate ask/edit controllers between the main modules and openAI controllers to reduce repetition of code and increase reusability
* fix(winston/logger): circular dependency issue
* fix(config/scripts): fix script imports
* refactor(indexSync): make not configured message an info log message
* chore: create a rollup script for api/server/index.js to check circular dependencies
* chore: bump @keyv/redis
* WIP: initial logging changes
add several transports in ~/config/winston
omit messages in logs, truncate long strings
add short blurb in dotenv for debug logging
GoogleClient: using logger
OpenAIClient: using logger, handleOpenAIErrors
Adding typedef for payload message
bumped winston and using winston-daily-rotate-file
moved config for server paths to ~/config dir
Added `DEBUG_LOGGING=true` to .env.example
* WIP: Refactor logging statements in code
* WIP: Refactor logging statements and import configurations
* WIP: Refactor logging statements and import configurations
* refactor: broadcast Redis initialization message with `info` not `debug`
* refactor: complete Refactor logging statements and import configurations
* chore: delete unused tools
* fix: circular dependencies due to accessing logger
* refactor(handleText): handle booleans and write tests
* refactor: redact sensitive values, better formatting
* chore: improve log formatting, avoid passing strings to 2nd arg
* fix(ci): fix jest tests due to logger changes
* refactor(getAvailablePluginsController): cache plugins as they are static and avoids async addOpenAPISpecs call every time
* chore: update docs
* chore: update docs
* chore: create separate meiliSync logger, clean up logs to avoid being unnecessarily verbose
* chore: spread objects where they are commonly logged to allow string truncation
* chore: improve error log formatting
* 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
