* chore: bump browserslist-db@latest
* refactor(EndpointService): simplify with `generateConfig`, utilize optional baseURL for OpenAI-based endpoints, use `isUserProvided` helper fn wherever needed
* refactor(custom/initializeClient): use standardized naming for common variables
* feat: user provided baseURL for openAI-based endpoints
* refactor(custom/initializeClient): re-order operations
* fix: knownendpoints enum definition and add FetchTokenConfig, bump data-provider
* refactor(custom): use tokenKey dependent on userProvided conditions for caching and fetching endpointTokenConfig, anticipate token rates from custom config
* refactor(custom): assure endpointTokenConfig is only accessed from cache if qualifies for fetching
* fix(ci): update tests for initializeClient based on userProvideURL changes
* fix(EndpointService): correct baseURL env var for assistants: `ASSISTANTS_BASE_URL`
* fix: unnecessary run cancellation on res.close() when response.run is completed
* feat(assistants): user provided URL option
* ci: update tests and add test for `assistants` endpoint
* chore: leaner condition for request closing
* chore: more descriptive error message to provide keys again
* 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
* refactor(useUpdateUserKeysMutation): only invalidate the endpoint whose key is being updated by user
* fix(assistants): await `getUserKeyExpiry` call
* chore: fix spinner loading color
* refactor(initializeClient): make known which endpoint api Key is missing
* fix: prevent an `endpointType` mismatch by making it impossible to assign when the `endpointsConfig` doesn't have a `type` defined, also prefer `getQueryData` call to useQuery in useChatHelpers
* 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
2023-12-10 14:54:13 -05:00
Renamed from api/server/routes/endpoints/openAI/initializeClient.spec.js (Browse further)
