* fix: load all existing conversation settings on refresh
* refactor(buildDefaultConvo): use `lastConversationSetup.endpointType` before `conversation.endpointType`
* refactor(TMessage/messageSchema): add `endpoint` field to messages to differentiate generation origin
* feat(useNewConvo): `keepLatestMessage` param to prevent reseting the `latestMessage` mid-conversation
* style(Settings): adjust height styling to allow more space in dialog for additional settings
* feat: Modular Chat: experimental setting to Enable switching Endpoints mid-conversation
* fix(ChatRoute): fix potential parsing issue with tPresetSchema
* 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
* feat: add GOOGLE_MODELS env var
* feat: add gemini vision support
* refactor(GoogleClient): adjust clientOptions handling depending on model
* fix(logger): fix redact logic and redact errors only
* fix(GoogleClient): do not allow non-multiModal messages when gemini-pro-vision is selected
* refactor(OpenAIClient): use `isVisionModel` client property to avoid calling validateVisionModel multiple times
* refactor: better debug logging by correctly traversing, redacting sensitive info, and logging condensed versions of long values
* refactor(GoogleClient): allow response errors to be thrown/caught above client handling so user receives meaningful error message
debug orderedMessages, parentMessageId, and buildMessages result
* refactor(AskController): use model from client.modelOptions.model when saving intermediate messages, which requires for the progress callback to be initialized after the client is initialized
* feat(useSSE): revert to previous model if the model was auto-switched by backend due to message attachments
* docs: update with google updates, notes about Gemini Pro Vision
* fix: redis should not be initialized without USE_REDIS and increase max listeners to 20
* 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
