💫 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
2024-01-03 09:22:48 -05:00
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# Configuration version (required)
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2024-02-05 08:14:52 +01:00
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version: 1.0.2
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💫 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
2024-01-03 09:22:48 -05:00
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# Cache settings: Set to true to enable caching
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cache: true
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2024-02-05 08:14:52 +01:00
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# Example Registration Object Structure (optional)
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# registration:
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# allowedDomains:
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# - "gmail.com"
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💫 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
2024-01-03 09:22:48 -05:00
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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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2024-01-13 08:19:09 -05:00
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safe_prompt: true # This field is specific to Mistral AI: https://docs.mistral.ai/api/
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💫 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
2024-01-03 09:22:48 -05:00
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# Drop Default params parameters from the request. See default params in guide linked below.
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2024-01-11 15:50:04 -05:00
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# NOTE: For Mistral, it is necessary to drop the following parameters or you will encounter a 422 Error:
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dropParams: ["stop", "user", "frequency_penalty", "presence_penalty"]
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💫 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
2024-01-03 09:22:48 -05:00
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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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