LibreChat/api/server/services/Endpoints/gptPlugins/initializeClient.spec.js

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// gptPlugins/initializeClient.spec.js
feat(Google): Support all Text/Chat Models, Response streaming, `PaLM` -> `Google` 🤖 (#1316) * 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
const { PluginsClient } = require('~/app');
const initializeClient = require('./initializeClient');
feat(Google): Support all Text/Chat Models, Response streaming, `PaLM` -> `Google` 🤖 (#1316) * 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
const { getUserKey } = require('../../UserService');
// Mock getUserKey since it's the only function we want to mock
feat(Google): Support all Text/Chat Models, Response streaming, `PaLM` -> `Google` 🤖 (#1316) * 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
jest.mock('~/server/services/UserService', () => ({
getUserKey: jest.fn(),
feat(Google): Support all Text/Chat Models, Response streaming, `PaLM` -> `Google` 🤖 (#1316) * 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
checkUserKeyExpiry: jest.requireActual('~/server/services/UserService').checkUserKeyExpiry,
}));
describe('gptPlugins/initializeClient', () => {
// Set up environment variables
const originalEnvironment = process.env;
beforeEach(() => {
jest.resetModules(); // Clears the cache
process.env = { ...originalEnvironment }; // Make a copy
});
afterAll(() => {
process.env = originalEnvironment; // Restore original env vars
});
test('should initialize PluginsClient with OpenAI API key and default options', async () => {
process.env.OPENAI_API_KEY = 'test-openai-api-key';
process.env.PLUGINS_USE_AZURE = 'false';
process.env.DEBUG_PLUGINS = 'false';
process.env.OPENAI_SUMMARIZE = 'false';
const req = {
body: { key: null },
user: { id: '123' },
};
const res = {};
const endpointOption = { modelOptions: { model: 'default-model' } };
const { client, openAIApiKey } = await initializeClient({ req, res, endpointOption });
expect(openAIApiKey).toBe('test-openai-api-key');
expect(client).toBeInstanceOf(PluginsClient);
});
test('should initialize PluginsClient with Azure credentials when PLUGINS_USE_AZURE is true', async () => {
process.env.AZURE_API_KEY = 'test-azure-api-key';
(process.env.AZURE_OPENAI_API_INSTANCE_NAME = 'some-value'),
(process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME = 'some-value'),
(process.env.AZURE_OPENAI_API_VERSION = 'some-value'),
(process.env.AZURE_OPENAI_API_COMPLETIONS_DEPLOYMENT_NAME = 'some-value'),
(process.env.AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME = 'some-value'),
(process.env.PLUGINS_USE_AZURE = 'true');
process.env.DEBUG_PLUGINS = 'false';
process.env.OPENAI_SUMMARIZE = 'false';
const req = {
body: { key: null },
user: { id: '123' },
};
const res = {};
const endpointOption = { modelOptions: { model: 'test-model' } };
const { client, azure } = await initializeClient({ req, res, endpointOption });
expect(azure.azureOpenAIApiKey).toBe('test-azure-api-key');
expect(client).toBeInstanceOf(PluginsClient);
});
test('should use the debug option when DEBUG_PLUGINS is enabled', async () => {
process.env.OPENAI_API_KEY = 'test-openai-api-key';
process.env.DEBUG_PLUGINS = 'true';
const req = {
body: { key: null },
user: { id: '123' },
};
const res = {};
const endpointOption = { modelOptions: { model: 'default-model' } };
const { client } = await initializeClient({ req, res, endpointOption });
expect(client.options.debug).toBe(true);
});
test('should set contextStrategy to summarize when OPENAI_SUMMARIZE is enabled', async () => {
process.env.OPENAI_API_KEY = 'test-openai-api-key';
process.env.OPENAI_SUMMARIZE = 'true';
const req = {
body: { key: null },
user: { id: '123' },
};
const res = {};
const endpointOption = { modelOptions: { model: 'default-model' } };
const { client } = await initializeClient({ req, res, endpointOption });
expect(client.options.contextStrategy).toBe('summarize');
});
// ... additional tests for reverseProxyUrl, proxy, user-provided keys, etc.
test('should throw an error if no API keys are provided in the environment', async () => {
// Clear the environment variables for API keys
delete process.env.OPENAI_API_KEY;
delete process.env.AZURE_API_KEY;
const req = {
body: { key: null },
user: { id: '123' },
};
const res = {};
const endpointOption = { modelOptions: { model: 'default-model' } };
await expect(initializeClient({ req, res, endpointOption })).rejects.toThrow(
'API key not provided.',
);
});
// Additional tests for gptPlugins/initializeClient.spec.js
// ... (previous test setup code)
test('should handle user-provided OpenAI keys and check expiry', async () => {
process.env.OPENAI_API_KEY = 'user_provided';
process.env.PLUGINS_USE_AZURE = 'false';
const futureDate = new Date(Date.now() + 10000).toISOString();
const req = {
body: { key: futureDate },
user: { id: '123' },
};
const res = {};
const endpointOption = { modelOptions: { model: 'default-model' } };
getUserKey.mockResolvedValue('test-user-provided-openai-api-key');
const { openAIApiKey } = await initializeClient({ req, res, endpointOption });
expect(openAIApiKey).toBe('test-user-provided-openai-api-key');
});
test('should handle user-provided Azure keys and check expiry', async () => {
process.env.AZURE_API_KEY = 'user_provided';
process.env.PLUGINS_USE_AZURE = 'true';
const futureDate = new Date(Date.now() + 10000).toISOString();
const req = {
body: { key: futureDate },
user: { id: '123' },
};
const res = {};
const endpointOption = { modelOptions: { model: 'test-model' } };
getUserKey.mockResolvedValue(
JSON.stringify({
azureOpenAIApiKey: 'test-user-provided-azure-api-key',
azureOpenAIApiDeploymentName: 'test-deployment',
}),
);
const { azure } = await initializeClient({ req, res, endpointOption });
expect(azure.azureOpenAIApiKey).toBe('test-user-provided-azure-api-key');
});
test('should throw an error if the user-provided key has expired', async () => {
process.env.OPENAI_API_KEY = 'user_provided';
process.env.PLUGINS_USE_AZURE = 'FALSE';
const expiresAt = new Date(Date.now() - 10000).toISOString(); // Expired
const req = {
body: { key: expiresAt },
user: { id: '123' },
};
const res = {};
const endpointOption = { modelOptions: { model: 'default-model' } };
await expect(initializeClient({ req, res, endpointOption })).rejects.toThrow(
/Your OpenAI API key has expired/,
);
});
test('should throw an error if the user-provided Azure key is invalid JSON', async () => {
process.env.AZURE_API_KEY = 'user_provided';
process.env.PLUGINS_USE_AZURE = 'true';
const req = {
body: { key: new Date(Date.now() + 10000).toISOString() },
user: { id: '123' },
};
const res = {};
const endpointOption = { modelOptions: { model: 'default-model' } };
// Simulate an invalid JSON string returned from getUserKey
getUserKey.mockResolvedValue('invalid-json');
await expect(initializeClient({ req, res, endpointOption })).rejects.toThrow(
/Unexpected token/,
);
});
test('should correctly handle the presence of a reverse proxy', async () => {
process.env.OPENAI_REVERSE_PROXY = 'http://reverse.proxy';
process.env.PROXY = 'http://proxy';
process.env.OPENAI_API_KEY = 'test-openai-api-key';
const req = {
body: { key: null },
user: { id: '123' },
};
const res = {};
const endpointOption = { modelOptions: { model: 'default-model' } };
const { client } = await initializeClient({ req, res, endpointOption });
expect(client.options.reverseProxyUrl).toBe('http://reverse.proxy');
expect(client.options.proxy).toBe('http://proxy');
});
});