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* 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
76 lines
2.9 KiB
YAML
76 lines
2.9 KiB
YAML
# Configuration version (required)
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version: 1.0.0
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# Cache settings: Set to true to enable caching
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cache: true
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# Definition of custom endpoints
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endpoints:
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custom:
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# Mistral AI API
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- name: "Mistral" # Unique name for the endpoint
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# For `apiKey` and `baseURL`, you can use environment variables that you define.
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# recommended environment variables:
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apiKey: "${MISTRAL_API_KEY}"
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baseURL: "https://api.mistral.ai/v1"
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# Models configuration
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models:
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# List of default models to use. At least one value is required.
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default: ["mistral-tiny", "mistral-small", "mistral-medium"]
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# Fetch option: Set to true to fetch models from API.
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fetch: true # Defaults to false.
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# Optional configurations
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# Title Conversation setting
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titleConvo: true # Set to true to enable title conversation
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# Title Method: Choose between "completion" or "functions".
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titleMethod: "completion" # Defaults to "completion" if omitted.
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# Title Model: Specify the model to use for titles.
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titleModel: "mistral-tiny" # Defaults to "gpt-3.5-turbo" if omitted.
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# Summarize setting: Set to true to enable summarization.
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summarize: false
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# Summary Model: Specify the model to use if summarization is enabled.
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summaryModel: "mistral-tiny" # Defaults to "gpt-3.5-turbo" if omitted.
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# Force Prompt setting: If true, sends a `prompt` parameter instead of `messages`.
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forcePrompt: false
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# The label displayed for the AI model in messages.
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modelDisplayLabel: "Mistral" # Default is "AI" when not set.
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# Add additional parameters to the request. Default params will be overwritten.
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addParams:
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safe_mode: true # This field is specific to Mistral AI: https://docs.mistral.ai/api/
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# Drop Default params parameters from the request. See default params in guide linked below.
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dropParams: ["stop", "temperature", "top_p"]
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# - stop # dropped since it's not recognized by Mistral AI API
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# `temperature` and `top_p` are removed to allow Mistral AI API defaults to be used:
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# - temperature
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# - top_p
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# OpenRouter.ai Example
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- name: "OpenRouter"
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# For `apiKey` and `baseURL`, you can use environment variables that you define.
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# recommended environment variables:
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# Known issue: you should not use `OPENROUTER_API_KEY` as it will then override the `openAI` endpoint to use OpenRouter as well.
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apiKey: "${OPENROUTER_KEY}"
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baseURL: "https://openrouter.ai/api/v1"
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models:
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default: ["gpt-3.5-turbo"]
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fetch: true
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titleConvo: true
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titleModel: "gpt-3.5-turbo"
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summarize: false
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summaryModel: "gpt-3.5-turbo"
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forcePrompt: false
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modelDisplayLabel: "OpenRouter"
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# See the Custom Configuration Guide for more information:
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# https://docs.librechat.ai/install/configuration/custom_config.html
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