mirror of
https://github.com/danny-avila/LibreChat.git
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* WIP: app.locals refactoring
WIP: appConfig
fix: update memory configuration retrieval to use getAppConfig based on user role
fix: update comment for AppConfig interface to clarify purpose
🏷️ refactor: Update tests to use getAppConfig for endpoint configurations
ci: Update AppService tests to initialize app config instead of app.locals
ci: Integrate getAppConfig into remaining tests
refactor: Update multer storage destination to use promise-based getAppConfig and improve error handling in tests
refactor: Rename initializeAppConfig to setAppConfig and update related tests
ci: Mock getAppConfig in various tests to provide default configurations
refactor: Update convertMCPToolsToPlugins to use mcpManager for server configuration and adjust related tests
chore: rename `Config/getAppConfig` -> `Config/app`
fix: streamline OpenAI image tools configuration by removing direct appConfig dependency and using function parameters
chore: correct parameter documentation for imageOutputType in ToolService.js
refactor: remove `getCustomConfig` dependency in config route
refactor: update domain validation to use appConfig for allowed domains
refactor: use appConfig registration property
chore: remove app parameter from AppService invocation
refactor: update AppConfig interface to correct registration and turnstile configurations
refactor: remove getCustomConfig dependency and use getAppConfig in PluginController, multer, and MCP services
refactor: replace getCustomConfig with getAppConfig in STTService, TTSService, and related files
refactor: replace getCustomConfig with getAppConfig in Conversation and Message models, update tempChatRetention functions to use AppConfig type
refactor: update getAppConfig calls in Conversation and Message models to include user role for temporary chat expiration
ci: update related tests
refactor: update getAppConfig call in getCustomConfigSpeech to include user role
fix: update appConfig usage to access allowedDomains from actions instead of registration
refactor: enhance AppConfig to include fileStrategies and update related file strategy logic
refactor: update imports to use normalizeEndpointName from @librechat/api and remove redundant definitions
chore: remove deprecated unused RunManager
refactor: get balance config primarily from appConfig
refactor: remove customConfig dependency for appConfig and streamline loadConfigModels logic
refactor: remove getCustomConfig usage and use app config in file citations
refactor: consolidate endpoint loading logic into loadEndpoints function
refactor: update appConfig access to use endpoints structure across various services
refactor: implement custom endpoints configuration and streamline endpoint loading logic
refactor: update getAppConfig call to include user role parameter
refactor: streamline endpoint configuration and enhance appConfig usage across services
refactor: replace getMCPAuthMap with getUserMCPAuthMap and remove unused getCustomConfig file
refactor: add type annotation for loadedEndpoints in loadEndpoints function
refactor: move /services/Files/images/parse to TS API
chore: add missing FILE_CITATIONS permission to IRole interface
refactor: restructure toolkits to TS API
refactor: separate manifest logic into its own module
refactor: consolidate tool loading logic into a new tools module for startup logic
refactor: move interface config logic to TS API
refactor: migrate checkEmailConfig to TypeScript and update imports
refactor: add FunctionTool interface and availableTools to AppConfig
refactor: decouple caching and DB operations from AppService, make part of consolidated `getAppConfig`
WIP: fix tests
* fix: rebase conflicts
* refactor: remove app.locals references
* refactor: replace getBalanceConfig with getAppConfig in various strategies and middleware
* refactor: replace appConfig?.balance with getBalanceConfig in various controllers and clients
* test: add balance configuration to titleConvo method in AgentClient tests
* chore: remove unused `openai-chat-tokens` package
* chore: remove unused imports in initializeMCPs.js
* refactor: update balance configuration to use getAppConfig instead of getBalanceConfig
* refactor: integrate configMiddleware for centralized configuration handling
* refactor: optimize email domain validation by removing unnecessary async calls
* refactor: simplify multer storage configuration by removing async calls
* refactor: reorder imports for better readability in user.js
* refactor: replace getAppConfig calls with req.config for improved performance
* chore: replace getAppConfig calls with req.config in tests for centralized configuration handling
* chore: remove unused override config
* refactor: add configMiddleware to endpoint route and replace getAppConfig with req.config
* chore: remove customConfig parameter from TTSService constructor
* refactor: pass appConfig from request to processFileCitations for improved configuration handling
* refactor: remove configMiddleware from endpoint route and retrieve appConfig directly in getEndpointsConfig if not in `req.config`
* test: add mockAppConfig to processFileCitations tests for improved configuration handling
* fix: pass req.config to hasCustomUserVars and call without await after synchronous refactor
* fix: type safety in useExportConversation
* refactor: retrieve appConfig using getAppConfig in PluginController and remove configMiddleware from plugins route, to avoid always retrieving when plugins are cached
* chore: change `MongoUser` typedef to `IUser`
* fix: Add `user` and `config` fields to ServerRequest and update JSDoc type annotations from Express.Request to ServerRequest
* fix: remove unused setAppConfig mock from Server configuration tests
400 lines
12 KiB
JavaScript
400 lines
12 KiB
JavaScript
const { fetchModels } = require('~/server/services/ModelService');
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const loadConfigModels = require('./loadConfigModels');
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const { getAppConfig } = require('./app');
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jest.mock('~/server/services/ModelService');
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jest.mock('./app');
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const exampleConfig = {
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endpoints: {
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custom: [
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{
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name: 'Mistral',
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apiKey: '${MY_PRECIOUS_MISTRAL_KEY}',
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baseURL: 'https://api.mistral.ai/v1',
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models: {
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default: ['mistral-tiny', 'mistral-small', 'mistral-medium', 'mistral-large-latest'],
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fetch: true,
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},
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dropParams: ['stop', 'user', 'frequency_penalty', 'presence_penalty'],
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},
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{
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name: 'OpenRouter',
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apiKey: '${MY_OPENROUTER_API_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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},
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dropParams: ['stop'],
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},
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{
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name: 'groq',
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apiKey: 'user_provided',
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baseURL: 'https://api.groq.com/openai/v1/',
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models: {
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default: ['llama2-70b-4096', 'mixtral-8x7b-32768'],
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fetch: false,
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},
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},
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{
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name: 'Ollama',
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apiKey: 'user_provided',
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baseURL: 'http://localhost:11434/v1/',
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models: {
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default: ['mistral', 'llama2:13b'],
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fetch: false,
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},
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},
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{
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name: 'MLX',
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apiKey: 'user_provided',
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baseURL: 'http://localhost:8080/v1/',
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models: {
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default: ['Meta-Llama-3-8B-Instruct-4bit'],
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fetch: false,
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},
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},
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],
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},
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};
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describe('loadConfigModels', () => {
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const mockRequest = { user: { id: 'testUserId' } };
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const originalEnv = process.env;
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beforeEach(() => {
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jest.resetAllMocks();
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jest.resetModules();
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process.env = { ...originalEnv };
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// Default mock for getAppConfig
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getAppConfig.mockResolvedValue({});
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});
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afterEach(() => {
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process.env = originalEnv;
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});
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it('should return an empty object if customConfig is null', async () => {
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getAppConfig.mockResolvedValue(null);
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const result = await loadConfigModels(mockRequest);
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expect(result).toEqual({});
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});
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it('handles azure models and endpoint correctly', async () => {
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getAppConfig.mockResolvedValue({
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endpoints: {
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azureOpenAI: { modelNames: ['model1', 'model2'] },
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},
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});
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const result = await loadConfigModels(mockRequest);
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expect(result.azureOpenAI).toEqual(['model1', 'model2']);
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});
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it('fetches custom models based on the unique key', async () => {
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process.env.BASE_URL = 'http://example.com';
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process.env.API_KEY = 'some-api-key';
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const customEndpoints = [
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{
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baseURL: '${BASE_URL}',
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apiKey: '${API_KEY}',
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name: 'CustomModel',
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models: { fetch: true },
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},
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];
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getAppConfig.mockResolvedValue({ endpoints: { custom: customEndpoints } });
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fetchModels.mockResolvedValue(['customModel1', 'customModel2']);
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const result = await loadConfigModels(mockRequest);
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expect(fetchModels).toHaveBeenCalled();
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expect(result.CustomModel).toEqual(['customModel1', 'customModel2']);
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});
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it('correctly associates models to names using unique keys', async () => {
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getAppConfig.mockResolvedValue({
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endpoints: {
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custom: [
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{
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baseURL: 'http://example.com',
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apiKey: 'API_KEY1',
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name: 'Model1',
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models: { fetch: true },
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},
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{
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baseURL: 'http://example.com',
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apiKey: 'API_KEY2',
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name: 'Model2',
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models: { fetch: true },
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},
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],
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},
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});
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fetchModels.mockImplementation(({ apiKey }) =>
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Promise.resolve(apiKey === 'API_KEY1' ? ['model1Data'] : ['model2Data']),
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);
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const result = await loadConfigModels(mockRequest);
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expect(result.Model1).toEqual(['model1Data']);
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expect(result.Model2).toEqual(['model2Data']);
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});
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it('correctly handles multiple endpoints with the same baseURL but different apiKeys', async () => {
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// Mock the custom configuration to simulate the user's scenario
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getAppConfig.mockResolvedValue({
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endpoints: {
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custom: [
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{
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name: 'LiteLLM',
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apiKey: '${LITELLM_ALL_MODELS}',
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baseURL: '${LITELLM_HOST}',
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models: { fetch: true },
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},
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{
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name: 'OpenAI',
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apiKey: '${LITELLM_OPENAI_MODELS}',
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baseURL: '${LITELLM_SECOND_HOST}',
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models: { fetch: true },
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},
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{
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name: 'Google',
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apiKey: '${LITELLM_GOOGLE_MODELS}',
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baseURL: '${LITELLM_SECOND_HOST}',
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models: { fetch: true },
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},
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],
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},
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});
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// Mock `fetchModels` to return different models based on the apiKey
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fetchModels.mockImplementation(({ apiKey }) => {
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switch (apiKey) {
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case '${LITELLM_ALL_MODELS}':
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return Promise.resolve(['AllModel1', 'AllModel2']);
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case '${LITELLM_OPENAI_MODELS}':
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return Promise.resolve(['OpenAIModel']);
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case '${LITELLM_GOOGLE_MODELS}':
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return Promise.resolve(['GoogleModel']);
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default:
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return Promise.resolve([]);
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}
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});
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const result = await loadConfigModels(mockRequest);
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// Assert that the models are correctly fetched and mapped based on unique keys
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expect(result.LiteLLM).toEqual(['AllModel1', 'AllModel2']);
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expect(result.OpenAI).toEqual(['OpenAIModel']);
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expect(result.Google).toEqual(['GoogleModel']);
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// Ensure that fetchModels was called with correct parameters
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expect(fetchModels).toHaveBeenCalledTimes(3);
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expect(fetchModels).toHaveBeenCalledWith(
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expect.objectContaining({ apiKey: '${LITELLM_ALL_MODELS}' }),
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);
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expect(fetchModels).toHaveBeenCalledWith(
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expect.objectContaining({ apiKey: '${LITELLM_OPENAI_MODELS}' }),
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);
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expect(fetchModels).toHaveBeenCalledWith(
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expect.objectContaining({ apiKey: '${LITELLM_GOOGLE_MODELS}' }),
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);
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});
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it('loads models based on custom endpoint configuration respecting fetch rules', async () => {
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process.env.MY_PRECIOUS_MISTRAL_KEY = 'actual_mistral_api_key';
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process.env.MY_OPENROUTER_API_KEY = 'actual_openrouter_api_key';
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// Setup custom configuration with specific API keys for Mistral and OpenRouter
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// and "user_provided" for groq and Ollama, indicating no fetch for the latter two
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getAppConfig.mockResolvedValue(exampleConfig);
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// Assuming fetchModels would be called only for Mistral and OpenRouter
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fetchModels.mockImplementation(({ name }) => {
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switch (name) {
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case 'Mistral':
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return Promise.resolve([
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'mistral-tiny',
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'mistral-small',
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'mistral-medium',
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'mistral-large-latest',
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]);
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case 'OpenRouter':
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return Promise.resolve(['gpt-3.5-turbo']);
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default:
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return Promise.resolve([]);
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}
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});
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const result = await loadConfigModels(mockRequest);
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// Since fetch is true and apiKey is not "user_provided", fetching occurs for Mistral and OpenRouter
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expect(result.Mistral).toEqual([
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'mistral-tiny',
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'mistral-small',
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'mistral-medium',
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'mistral-large-latest',
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]);
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expect(fetchModels).toHaveBeenCalledWith(
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expect.objectContaining({
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name: 'Mistral',
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apiKey: process.env.MY_PRECIOUS_MISTRAL_KEY,
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}),
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);
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expect(result.OpenRouter).toEqual(['gpt-3.5-turbo']);
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expect(fetchModels).toHaveBeenCalledWith(
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expect.objectContaining({
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name: 'OpenRouter',
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apiKey: process.env.MY_OPENROUTER_API_KEY,
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}),
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);
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// For groq and ollama, since the apiKey is "user_provided", models should not be fetched
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// Depending on your implementation's behavior regarding "default" models without fetching,
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// you may need to adjust the following assertions:
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expect(result.groq).toBe(exampleConfig.endpoints.custom[2].models.default);
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expect(result.ollama).toBe(exampleConfig.endpoints.custom[3].models.default);
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// Verifying fetchModels was not called for groq and ollama
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expect(fetchModels).not.toHaveBeenCalledWith(
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expect.objectContaining({
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name: 'groq',
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}),
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);
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expect(fetchModels).not.toHaveBeenCalledWith(
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expect.objectContaining({
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name: 'ollama',
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}),
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);
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});
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it('falls back to default models if fetching returns an empty array', async () => {
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getAppConfig.mockResolvedValue({
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endpoints: {
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custom: [
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{
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name: 'EndpointWithSameFetchKey',
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apiKey: 'API_KEY',
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baseURL: 'http://example.com',
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models: {
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fetch: true,
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default: ['defaultModel1'],
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},
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},
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{
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name: 'EmptyFetchModel',
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apiKey: 'API_KEY',
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baseURL: 'http://example.com',
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models: {
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fetch: true,
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default: ['defaultModel1', 'defaultModel2'],
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},
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},
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],
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},
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});
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fetchModels.mockResolvedValue([]);
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const result = await loadConfigModels(mockRequest);
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expect(fetchModels).toHaveBeenCalledTimes(1);
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expect(result.EmptyFetchModel).toEqual(['defaultModel1', 'defaultModel2']);
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});
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it('falls back to default models if fetching returns a falsy value', async () => {
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getAppConfig.mockResolvedValue({
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endpoints: {
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custom: [
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{
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name: 'FalsyFetchModel',
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apiKey: 'API_KEY',
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baseURL: 'http://example.com',
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models: {
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fetch: true,
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default: ['defaultModel1', 'defaultModel2'],
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},
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},
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],
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},
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});
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fetchModels.mockResolvedValue(false);
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const result = await loadConfigModels(mockRequest);
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expect(fetchModels).toHaveBeenCalledWith(
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expect.objectContaining({
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name: 'FalsyFetchModel',
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apiKey: 'API_KEY',
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}),
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);
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expect(result.FalsyFetchModel).toEqual(['defaultModel1', 'defaultModel2']);
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});
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it('normalizes Ollama endpoint name to lowercase', async () => {
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const testCases = [
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{
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name: 'Ollama',
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apiKey: 'user_provided',
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baseURL: 'http://localhost:11434/v1/',
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models: {
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default: ['mistral', 'llama2'],
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fetch: false,
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},
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},
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{
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name: 'OLLAMA',
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apiKey: 'user_provided',
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baseURL: 'http://localhost:11434/v1/',
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models: {
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default: ['mixtral', 'codellama'],
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fetch: false,
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},
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},
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{
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name: 'OLLaMA',
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apiKey: 'user_provided',
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baseURL: 'http://localhost:11434/v1/',
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models: {
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default: ['phi', 'neural-chat'],
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fetch: false,
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},
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},
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];
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getAppConfig.mockResolvedValue({
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endpoints: {
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custom: testCases,
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},
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});
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const result = await loadConfigModels(mockRequest);
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// All variations of "Ollama" should be normalized to lowercase "ollama"
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// and the last config in the array should override previous ones
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expect(result.Ollama).toBeUndefined();
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expect(result.OLLAMA).toBeUndefined();
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expect(result.OLLaMA).toBeUndefined();
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expect(result.ollama).toEqual(['phi', 'neural-chat']);
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// Verify fetchModels was not called since these are user_provided
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expect(fetchModels).not.toHaveBeenCalledWith(
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expect.objectContaining({
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name: 'Ollama',
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}),
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);
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expect(fetchModels).not.toHaveBeenCalledWith(
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expect.objectContaining({
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name: 'OLLAMA',
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}),
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);
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expect(fetchModels).not.toHaveBeenCalledWith(
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expect.objectContaining({
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name: 'OLLaMA',
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}),
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);
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});
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});
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