LibreChat/api/server/controllers/agents/__tests__/openai.spec.js
Danny Avila 9a38af5875
📉 feat: Add Token Usage Tracking for Agents API Routes (#11600)
* feat: Implement token usage tracking for OpenAI and Responses controllers

- Added functionality to record token usage against user balances in OpenAIChatCompletionController and createResponse functions.
- Introduced new utility functions for managing token spending and structured token usage.
- Enhanced error handling for token recording to improve logging and debugging capabilities.
- Updated imports to include new usage tracking methods and configurations.

* test: Add unit tests for recordCollectedUsage function in usage.spec.ts

- Introduced comprehensive tests for the recordCollectedUsage function, covering various scenarios including handling empty and null collectedUsage, single and multiple usage entries, and sequential and parallel execution cases.
- Enhanced token handling tests to ensure correct calculations for both OpenAI and Anthropic formats, including cache token management.
- Improved overall test coverage for usage tracking functionality, ensuring robust validation of expected behaviors and outcomes.

* test: Add unit tests for OpenAI and Responses API controllers

- Introduced comprehensive unit tests for the OpenAIChatCompletionController and createResponse functions, focusing on the correct invocation of recordCollectedUsage for token spending.
- Enhanced tests to validate the passing of balance and transactions configuration to the recordCollectedUsage function.
- Ensured proper dependency injection of spendTokens and spendStructuredTokens in the usage recording process.
- Improved overall test coverage for token usage tracking, ensuring robust validation of expected behaviors and outcomes.
2026-02-01 21:36:51 -05:00

207 lines
6.4 KiB
JavaScript

/**
* Unit tests for OpenAI-compatible API controller
* Tests that recordCollectedUsage is called correctly for token spending
*/
const mockSpendTokens = jest.fn().mockResolvedValue({});
const mockSpendStructuredTokens = jest.fn().mockResolvedValue({});
const mockRecordCollectedUsage = jest
.fn()
.mockResolvedValue({ input_tokens: 100, output_tokens: 50 });
const mockGetBalanceConfig = jest.fn().mockReturnValue({ enabled: true });
const mockGetTransactionsConfig = jest.fn().mockReturnValue({ enabled: true });
jest.mock('nanoid', () => ({
nanoid: jest.fn(() => 'mock-nanoid-123'),
}));
jest.mock('@librechat/data-schemas', () => ({
logger: {
debug: jest.fn(),
error: jest.fn(),
warn: jest.fn(),
},
}));
jest.mock('@librechat/agents', () => ({
Callback: { TOOL_ERROR: 'TOOL_ERROR' },
ToolEndHandler: jest.fn(),
formatAgentMessages: jest.fn().mockReturnValue({
messages: [],
indexTokenCountMap: {},
}),
ChatModelStreamHandler: jest.fn().mockImplementation(() => ({
handle: jest.fn(),
})),
}));
jest.mock('@librechat/api', () => ({
writeSSE: jest.fn(),
createRun: jest.fn().mockResolvedValue({
processStream: jest.fn().mockResolvedValue(undefined),
}),
createChunk: jest.fn().mockReturnValue({}),
buildToolSet: jest.fn().mockReturnValue(new Set()),
sendFinalChunk: jest.fn(),
createSafeUser: jest.fn().mockReturnValue({ id: 'user-123' }),
validateRequest: jest
.fn()
.mockReturnValue({ request: { model: 'agent-123', messages: [], stream: false } }),
initializeAgent: jest.fn().mockResolvedValue({
model: 'gpt-4',
model_parameters: {},
toolRegistry: {},
}),
getBalanceConfig: mockGetBalanceConfig,
createErrorResponse: jest.fn(),
getTransactionsConfig: mockGetTransactionsConfig,
recordCollectedUsage: mockRecordCollectedUsage,
buildNonStreamingResponse: jest.fn().mockReturnValue({ id: 'resp-123' }),
createOpenAIStreamTracker: jest.fn().mockReturnValue({
addText: jest.fn(),
addReasoning: jest.fn(),
toolCalls: new Map(),
usage: { promptTokens: 0, completionTokens: 0, reasoningTokens: 0 },
}),
createOpenAIContentAggregator: jest.fn().mockReturnValue({
addText: jest.fn(),
addReasoning: jest.fn(),
getText: jest.fn().mockReturnValue(''),
getReasoning: jest.fn().mockReturnValue(''),
toolCalls: new Map(),
usage: { promptTokens: 100, completionTokens: 50, reasoningTokens: 0 },
}),
createToolExecuteHandler: jest.fn().mockReturnValue({ handle: jest.fn() }),
isChatCompletionValidationFailure: jest.fn().mockReturnValue(false),
}));
jest.mock('~/server/services/ToolService', () => ({
loadAgentTools: jest.fn().mockResolvedValue([]),
loadToolsForExecution: jest.fn().mockResolvedValue([]),
}));
jest.mock('~/models/spendTokens', () => ({
spendTokens: mockSpendTokens,
spendStructuredTokens: mockSpendStructuredTokens,
}));
jest.mock('~/server/controllers/agents/callbacks', () => ({
createToolEndCallback: jest.fn().mockReturnValue(jest.fn()),
}));
jest.mock('~/server/services/PermissionService', () => ({
findAccessibleResources: jest.fn().mockResolvedValue([]),
}));
jest.mock('~/models/Conversation', () => ({
getConvoFiles: jest.fn().mockResolvedValue([]),
}));
jest.mock('~/models/Agent', () => ({
getAgent: jest.fn().mockResolvedValue({
id: 'agent-123',
provider: 'openAI',
model_parameters: { model: 'gpt-4' },
}),
getAgents: jest.fn().mockResolvedValue([]),
}));
jest.mock('~/models', () => ({
getFiles: jest.fn(),
getUserKey: jest.fn(),
getMessages: jest.fn(),
updateFilesUsage: jest.fn(),
getUserKeyValues: jest.fn(),
getUserCodeFiles: jest.fn(),
getToolFilesByIds: jest.fn(),
getCodeGeneratedFiles: jest.fn(),
}));
describe('OpenAIChatCompletionController', () => {
let OpenAIChatCompletionController;
let req, res;
beforeEach(() => {
jest.clearAllMocks();
const controller = require('../openai');
OpenAIChatCompletionController = controller.OpenAIChatCompletionController;
req = {
body: {
model: 'agent-123',
messages: [{ role: 'user', content: 'Hello' }],
stream: false,
},
user: { id: 'user-123' },
config: {
endpoints: {
agents: { allowedProviders: ['openAI'] },
},
},
on: jest.fn(),
};
res = {
status: jest.fn().mockReturnThis(),
json: jest.fn(),
setHeader: jest.fn(),
flushHeaders: jest.fn(),
end: jest.fn(),
write: jest.fn(),
};
});
describe('token usage recording', () => {
it('should call recordCollectedUsage after successful non-streaming completion', async () => {
await OpenAIChatCompletionController(req, res);
expect(mockRecordCollectedUsage).toHaveBeenCalledTimes(1);
expect(mockRecordCollectedUsage).toHaveBeenCalledWith(
{ spendTokens: mockSpendTokens, spendStructuredTokens: mockSpendStructuredTokens },
expect.objectContaining({
user: 'user-123',
conversationId: expect.any(String),
collectedUsage: expect.any(Array),
context: 'message',
balance: { enabled: true },
transactions: { enabled: true },
}),
);
});
it('should pass balance and transactions config to recordCollectedUsage', async () => {
mockGetBalanceConfig.mockReturnValue({ enabled: true, startBalance: 1000 });
mockGetTransactionsConfig.mockReturnValue({ enabled: true, rateLimit: 100 });
await OpenAIChatCompletionController(req, res);
expect(mockRecordCollectedUsage).toHaveBeenCalledWith(
expect.any(Object),
expect.objectContaining({
balance: { enabled: true, startBalance: 1000 },
transactions: { enabled: true, rateLimit: 100 },
}),
);
});
it('should pass spendTokens and spendStructuredTokens as dependencies', async () => {
await OpenAIChatCompletionController(req, res);
const [deps] = mockRecordCollectedUsage.mock.calls[0];
expect(deps).toHaveProperty('spendTokens', mockSpendTokens);
expect(deps).toHaveProperty('spendStructuredTokens', mockSpendStructuredTokens);
});
it('should include model from primaryConfig in recordCollectedUsage params', async () => {
await OpenAIChatCompletionController(req, res);
expect(mockRecordCollectedUsage).toHaveBeenCalledWith(
expect.any(Object),
expect.objectContaining({
model: 'gpt-4',
}),
);
});
});
});