LibreChat/api/server/controllers/agents/recordCollectedUsage.spec.js
Danny Avila d24fe17a4b
🪢 chore: Consolidate Pricing and Tx Imports After tx.js Module Removal (#12086)
* 🧹 chore: resolve imports due to rebase

* chore: Update model mocks in unit tests for consistency

- Consolidated model mock implementations across various test files to streamline setup and reduce redundancy.
- Removed duplicate mock definitions for `getMultiplier` and `getCacheMultiplier`, ensuring a unified approach in `recordCollectedUsage.spec.js`, `openai.spec.js`, `responses.unit.spec.js`, and `abortMiddleware.spec.js`.
- Enhanced clarity and maintainability of test files by aligning mock structures with the latest model updates.

* fix: Safeguard token credit checks in transaction tests

- Updated assertions in `transaction.spec.ts` to handle potential null values for `updatedBalance` by using optional chaining.
- Enhanced robustness of tests related to token credit calculations, ensuring they correctly account for scenarios where the balance may not be found.

* chore: transaction methods with bulk insert functionality

- Introduced `bulkInsertTransactions` method in `transaction.ts` to facilitate batch insertion of transaction documents.
- Updated test file `transactions.bulk-parity.spec.ts` to utilize new pricing function assignments and handle potential null values in calculations, improving test robustness.
- Refactored pricing function initialization for clarity and consistency.

* refactor: Enhance type definitions and introduce new utility functions for model matching

- Added `findMatchingPattern` and `matchModelName` utility functions to improve model name matching logic in transaction methods.
- Updated type definitions for `findMatchingPattern` to accept a more specific tokensMap structure, enhancing type safety.
- Refactored `dbMethods` initialization in `transactions.bulk-parity.spec.ts` to include the new utility functions, improving test clarity and functionality.

* refactor: Update database method imports and enhance transaction handling

- Refactored `abortMiddleware.js` to utilize centralized database methods for message handling and conversation retrieval, improving code consistency.
- Enhanced `bulkInsertTransactions` in `transaction.ts` to handle empty document arrays gracefully and added error logging for better debugging.
- Updated type definitions in `transactions.ts` to enforce stricter typing for token types, enhancing type safety across transaction methods.
- Improved test setup in `transactions.bulk-parity.spec.ts` by refining pricing function assignments and ensuring robust handling of potential null values.

* refactor: Update database method references and improve transaction multiplier handling

- Refactored `client.js` to update database method references for `bulkInsertTransactions` and `updateBalance`, ensuring consistency in method usage.
- Enhanced transaction multiplier calculations in `transaction.spec.ts` to provide fallback values for write and read multipliers, improving robustness in cost calculations across structured token spending tests.
2026-03-05 16:01:52 -05:00

358 lines
12 KiB
JavaScript

/**
* Tests for AgentClient.recordCollectedUsage
*
* This is a critical function that handles token spending for agent LLM calls.
* The client now delegates to the TS recordCollectedUsage from @librechat/api,
* passing pricing and bulkWriteOps deps.
*/
const { EModelEndpoint } = require('librechat-data-provider');
const mockSpendTokens = jest.fn().mockResolvedValue();
const mockSpendStructuredTokens = jest.fn().mockResolvedValue();
const mockGetMultiplier = jest.fn().mockReturnValue(1);
const mockGetCacheMultiplier = jest.fn().mockReturnValue(null);
const mockUpdateBalance = jest.fn().mockResolvedValue({});
const mockBulkInsertTransactions = jest.fn().mockResolvedValue(undefined);
const mockRecordCollectedUsage = jest
.fn()
.mockResolvedValue({ input_tokens: 100, output_tokens: 50 });
jest.mock('~/models', () => ({
spendTokens: (...args) => mockSpendTokens(...args),
spendStructuredTokens: (...args) => mockSpendStructuredTokens(...args),
getMultiplier: mockGetMultiplier,
getCacheMultiplier: mockGetCacheMultiplier,
updateBalance: mockUpdateBalance,
bulkInsertTransactions: mockBulkInsertTransactions,
}));
jest.mock('~/config', () => ({
logger: {
debug: jest.fn(),
error: jest.fn(),
warn: jest.fn(),
info: jest.fn(),
},
getMCPManager: jest.fn(() => ({
formatInstructionsForContext: jest.fn(),
})),
}));
jest.mock('@librechat/agents', () => ({
...jest.requireActual('@librechat/agents'),
createMetadataAggregator: () => ({
handleLLMEnd: jest.fn(),
collected: [],
}),
}));
jest.mock('@librechat/api', () => {
const actual = jest.requireActual('@librechat/api');
return {
...actual,
recordCollectedUsage: (...args) => mockRecordCollectedUsage(...args),
};
});
const AgentClient = require('./client');
describe('AgentClient - recordCollectedUsage', () => {
let client;
let mockAgent;
let mockOptions;
beforeEach(() => {
jest.clearAllMocks();
mockAgent = {
id: 'agent-123',
endpoint: EModelEndpoint.openAI,
provider: EModelEndpoint.openAI,
model_parameters: {
model: 'gpt-4',
},
};
mockOptions = {
req: {
user: { id: 'user-123' },
body: { model: 'gpt-4', endpoint: EModelEndpoint.openAI },
},
res: {},
agent: mockAgent,
endpointTokenConfig: {},
};
client = new AgentClient(mockOptions);
client.conversationId = 'convo-123';
client.user = 'user-123';
});
describe('basic functionality', () => {
it('should delegate to recordCollectedUsage with full deps', async () => {
const collectedUsage = [{ input_tokens: 100, output_tokens: 50, model: 'gpt-4' }];
await client.recordCollectedUsage({
collectedUsage,
balance: { enabled: true },
transactions: { enabled: true },
});
expect(mockRecordCollectedUsage).toHaveBeenCalledTimes(1);
const [deps, params] = mockRecordCollectedUsage.mock.calls[0];
expect(deps).toHaveProperty('spendTokens');
expect(deps).toHaveProperty('spendStructuredTokens');
expect(deps).toHaveProperty('pricing');
expect(deps.pricing).toHaveProperty('getMultiplier');
expect(deps.pricing).toHaveProperty('getCacheMultiplier');
expect(deps).toHaveProperty('bulkWriteOps');
expect(deps.bulkWriteOps).toHaveProperty('insertMany');
expect(deps.bulkWriteOps).toHaveProperty('updateBalance');
expect(params).toEqual(
expect.objectContaining({
user: 'user-123',
conversationId: 'convo-123',
collectedUsage,
context: 'message',
balance: { enabled: true },
transactions: { enabled: true },
}),
);
});
it('should not set this.usage if collectedUsage is empty (returns undefined)', async () => {
mockRecordCollectedUsage.mockResolvedValue(undefined);
await client.recordCollectedUsage({
collectedUsage: [],
balance: { enabled: true },
transactions: { enabled: true },
});
expect(client.usage).toBeUndefined();
});
it('should not set this.usage if collectedUsage is null (returns undefined)', async () => {
mockRecordCollectedUsage.mockResolvedValue(undefined);
await client.recordCollectedUsage({
collectedUsage: null,
balance: { enabled: true },
transactions: { enabled: true },
});
expect(client.usage).toBeUndefined();
});
it('should set this.usage from recordCollectedUsage result', async () => {
mockRecordCollectedUsage.mockResolvedValue({ input_tokens: 200, output_tokens: 75 });
const collectedUsage = [{ input_tokens: 200, output_tokens: 75, model: 'gpt-4' }];
await client.recordCollectedUsage({
collectedUsage,
balance: { enabled: true },
transactions: { enabled: true },
});
expect(client.usage).toEqual({ input_tokens: 200, output_tokens: 75 });
});
});
describe('sequential execution (single agent with tool calls)', () => {
it('should pass all usage entries to recordCollectedUsage', async () => {
const collectedUsage = [
{ input_tokens: 100, output_tokens: 50, model: 'gpt-4' },
{ input_tokens: 150, output_tokens: 30, model: 'gpt-4' },
{ input_tokens: 180, output_tokens: 20, model: 'gpt-4' },
];
mockRecordCollectedUsage.mockResolvedValue({ input_tokens: 100, output_tokens: 100 });
await client.recordCollectedUsage({
collectedUsage,
balance: { enabled: true },
transactions: { enabled: true },
});
expect(mockRecordCollectedUsage).toHaveBeenCalledTimes(1);
const [, params] = mockRecordCollectedUsage.mock.calls[0];
expect(params.collectedUsage).toHaveLength(3);
expect(client.usage.output_tokens).toBe(100);
expect(client.usage.input_tokens).toBe(100);
});
});
describe('parallel execution (multiple agents)', () => {
it('should pass parallel agent usage to recordCollectedUsage', async () => {
const collectedUsage = [
{ input_tokens: 100, output_tokens: 50, model: 'gpt-4' },
{ input_tokens: 80, output_tokens: 40, model: 'gpt-4' },
];
mockRecordCollectedUsage.mockResolvedValue({ input_tokens: 100, output_tokens: 90 });
await client.recordCollectedUsage({
collectedUsage,
balance: { enabled: true },
transactions: { enabled: true },
});
expect(mockRecordCollectedUsage).toHaveBeenCalledTimes(1);
expect(client.usage.output_tokens).toBe(90);
expect(client.usage.output_tokens).toBeGreaterThan(0);
});
/** Bug regression: parallel agents where second agent has LOWER input tokens produced negative output via incremental calculation. */
it('should NOT produce negative output_tokens', async () => {
const collectedUsage = [
{ input_tokens: 200, output_tokens: 100, model: 'gpt-4' },
{ input_tokens: 50, output_tokens: 30, model: 'gpt-4' },
];
mockRecordCollectedUsage.mockResolvedValue({ input_tokens: 200, output_tokens: 130 });
await client.recordCollectedUsage({
collectedUsage,
balance: { enabled: true },
transactions: { enabled: true },
});
expect(client.usage.output_tokens).toBeGreaterThan(0);
expect(client.usage.output_tokens).toBe(130);
});
});
describe('real-world scenarios', () => {
it('should correctly handle sequential tool calls with growing context', async () => {
const collectedUsage = [
{ input_tokens: 31596, output_tokens: 151, model: 'claude-opus-4-5-20251101' },
{ input_tokens: 35368, output_tokens: 150, model: 'claude-opus-4-5-20251101' },
{ input_tokens: 58362, output_tokens: 295, model: 'claude-opus-4-5-20251101' },
{ input_tokens: 112604, output_tokens: 193, model: 'claude-opus-4-5-20251101' },
{ input_tokens: 257440, output_tokens: 2217, model: 'claude-opus-4-5-20251101' },
];
mockRecordCollectedUsage.mockResolvedValue({ input_tokens: 31596, output_tokens: 3006 });
await client.recordCollectedUsage({
collectedUsage,
balance: { enabled: true },
transactions: { enabled: true },
});
expect(client.usage.input_tokens).toBe(31596);
expect(client.usage.output_tokens).toBe(3006);
});
it('should correctly handle cache tokens', async () => {
const collectedUsage = [
{
input_tokens: 788,
output_tokens: 163,
input_token_details: { cache_read: 0, cache_creation: 30808 },
model: 'claude-opus-4-5-20251101',
},
];
mockRecordCollectedUsage.mockResolvedValue({ input_tokens: 31596, output_tokens: 163 });
await client.recordCollectedUsage({
collectedUsage,
balance: { enabled: true },
transactions: { enabled: true },
});
expect(client.usage.input_tokens).toBe(31596);
expect(client.usage.output_tokens).toBe(163);
});
});
describe('model fallback', () => {
it('should use param model when available', async () => {
mockRecordCollectedUsage.mockResolvedValue({ input_tokens: 100, output_tokens: 50 });
const collectedUsage = [{ input_tokens: 100, output_tokens: 50 }];
await client.recordCollectedUsage({
model: 'param-model',
collectedUsage,
balance: { enabled: true },
transactions: { enabled: true },
});
const [, params] = mockRecordCollectedUsage.mock.calls[0];
expect(params.model).toBe('param-model');
});
it('should fallback to client.model when param model is missing', async () => {
client.model = 'client-model';
mockRecordCollectedUsage.mockResolvedValue({ input_tokens: 100, output_tokens: 50 });
const collectedUsage = [{ input_tokens: 100, output_tokens: 50 }];
await client.recordCollectedUsage({
collectedUsage,
balance: { enabled: true },
transactions: { enabled: true },
});
const [, params] = mockRecordCollectedUsage.mock.calls[0];
expect(params.model).toBe('client-model');
});
it('should fallback to agent model_parameters.model as last resort', async () => {
mockRecordCollectedUsage.mockResolvedValue({ input_tokens: 100, output_tokens: 50 });
const collectedUsage = [{ input_tokens: 100, output_tokens: 50 }];
await client.recordCollectedUsage({
collectedUsage,
balance: { enabled: true },
transactions: { enabled: true },
});
const [, params] = mockRecordCollectedUsage.mock.calls[0];
expect(params.model).toBe('gpt-4');
});
});
describe('getStreamUsage integration', () => {
it('should return the usage object set by recordCollectedUsage', async () => {
mockRecordCollectedUsage.mockResolvedValue({ input_tokens: 100, output_tokens: 50 });
const collectedUsage = [{ input_tokens: 100, output_tokens: 50, model: 'gpt-4' }];
await client.recordCollectedUsage({
collectedUsage,
balance: { enabled: true },
transactions: { enabled: true },
});
const usage = client.getStreamUsage();
expect(usage).toEqual({ input_tokens: 100, output_tokens: 50 });
});
it('should return undefined before recordCollectedUsage is called', () => {
const usage = client.getStreamUsage();
expect(usage).toBeUndefined();
});
/** Verifies usage passes the check in BaseClient.sendMessage: if (usage != null && Number(usage[this.outputTokensKey]) > 0) */
it('should have output_tokens > 0 for BaseClient.sendMessage check', async () => {
mockRecordCollectedUsage.mockResolvedValue({ input_tokens: 200, output_tokens: 130 });
const collectedUsage = [
{ input_tokens: 200, output_tokens: 100, model: 'gpt-4' },
{ input_tokens: 50, output_tokens: 30, model: 'gpt-4' },
];
await client.recordCollectedUsage({
collectedUsage,
balance: { enabled: true },
transactions: { enabled: true },
});
const usage = client.getStreamUsage();
expect(usage).not.toBeNull();
expect(Number(usage.output_tokens)).toBeGreaterThan(0);
});
});
});