💫 feat: Config File & Custom Endpoints (#1474)

* 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

docs/install/configuration/dotenv.md

@@ -302,12 +302,14 @@ OPENAI_TITLE_MODEL=gpt-3.5-turbo
 OPENAI_SUMMARIZE=true
 ```
 
-> **Not yet implemented**: this will be a conversation option enabled by default to save users on tokens. We are using the ConversationSummaryBufferMemory method to summarize messages. To learn more about this, see this article: [https://www.pinecone.io/learn/series/langchain/langchain-conversational-memory/](https://www.pinecone.io/learn/series/langchain/langchain-conversational-memory/)
+> **Experimental**: We are using the ConversationSummaryBufferMemory method to summarize messages. To learn more about this, see this article: [https://www.pinecone.io/learn/series/langchain/langchain-conversational-memory/](https://www.pinecone.io/learn/series/langchain/langchain-conversational-memory/)
 
 - Reverse proxy settings for OpenAI:
     - see: [LiteLLM](./litellm.md) 
     - see also: [Free AI APIs](./free_ai_apis.md#nagaai)
 
+**Important**: As of v0.6.6, it's recommend you use the `librechat.yaml` [Configuration file (guide here)](./custom_config.md) to add Reverse Proxies as separate endpoints.
+
 ```bash
 OPENAI_REVERSE_PROXY=
 ```