* fix: sanitize filename in multer storage callback
* fix: ensure temporary image upload file is deleted after processing
* fix: prevent cleanup flag from being set to false before actually deleted
* refactor: user avatar, typing, use 'file' for formData instead of 'input', add disk storage, use localization
* fix: update Avatar component to include image dimensions in formData and refactor editor reference type
* fix: refactor avatar upload handling to use fs for file reading and enhance file validation
* fix: ensure temporary image upload file is deleted after processing
* fix: refactor avatar upload routes and handlers for agents and assistants, improve file handling and validation
* fix: improve audio file validation and cleanup
* fix: add filename sanitization utility and integrate it into multer storage configuration
* fix: update group project ID check for null and refactor delete prompt group response type
* fix: invalid access control for deleting prompt groups
* fix: add error handling and logging to checkBan middleware
* fix: catch conversation parsing errors
* chore: revert unnecessary height and width parameters from avatar upload
* chore: update librechat-data-provider version to 0.7.55
* style: ensure KaTeX can spread across visible space
* wip: first pass for azure endpoint schema
* refactor: azure config to return groupMap and modelConfigMap
* wip: naming and schema changes
* refactor(errorsToString): move to data-provider
* feat: rename to azureGroups, add additional tests, tests all expected outcomes, return errors
* feat(AppService): load Azure groups
* refactor(azure): use imported types, write `mapModelToAzureConfig`
* refactor: move `extractEnvVariable` to data-provider
* refactor(validateAzureGroups): throw on duplicate groups or models; feat(mapModelToAzureConfig): throw if env vars not present, add tests
* refactor(AppService): ensure each model is properly configured on startup
* refactor: deprecate azureOpenAI environment variables in favor of librechat.yaml config
* feat: use helper functions to handle and order enabled/default endpoints; initialize azureOpenAI from config file
* refactor: redefine types as well as load azureOpenAI models from config file
* chore(ci): fix test description naming
* feat(azureOpenAI): use validated model grouping for request authentication
* chore: bump data-provider following rebase
* chore: bump config file version noting significant changes
* feat: add title options and switch azure configs for titling and vision requests
* feat: enable azure plugins from config file
* fix(ci): pass tests
* chore(.env.example): mark `PLUGINS_USE_AZURE` as deprecated
* fix(fetchModels): early return if apiKey not passed
* chore: fix azure config typing
* refactor(mapModelToAzureConfig): return baseURL and headers as well as azureOptions
* feat(createLLM): use `azureOpenAIBasePath`
* feat(parsers): resolveHeaders
* refactor(extractBaseURL): handle invalid input
* feat(OpenAIClient): handle headers and baseURL for azureConfig
* fix(ci): pass `OpenAIClient` tests
* chore: extract env var for azureOpenAI group config, baseURL
* docs: azureOpenAI config setup docs
* feat: safe check of potential conflicting env vars that map to unique placeholders
* fix: reset apiKey when model switches from originally requested model (vision or title)
* chore: linting
* docs: CONFIG_PATH notes in custom_config.md
* 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
* 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
