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chore: import upstream snapshot with attribution
2026-07-13 12:08:12 +08:00

196 lines
6.3 KiB
JavaScript

jest.mock('@librechat/data-schemas', () => ({
logger: { error: jest.fn(), debug: jest.fn() },
}));
jest.mock('@librechat/api', () => ({
sendEvent: jest.fn(),
emitEvent: jest.fn(),
createToolExecuteHandler: jest.fn(),
markSummarizationUsage: (usage) => usage,
}));
jest.mock('~/server/services/Files/Citations', () => ({
processFileCitations: jest.fn(),
}));
jest.mock('~/server/services/Files/Code/process', () => ({
processCodeOutput: jest.fn(),
runPreviewFinalize: jest.fn(),
}));
jest.mock('~/server/services/Files/process', () => ({
saveBase64Image: jest.fn(),
}));
const { ModelEndHandler } = require('../callbacks');
const buildGraph = () => ({
getAgentContext: () => ({
provider: 'vertexai',
clientOptions: { model: 'gemini-3.1-flash-lite-preview' },
}),
});
describe('ModelEndHandler — Vertex thoughtSignature capture (issue #13006 follow-up)', () => {
it('maps non-empty signatures onto tool_call_ids in order', async () => {
const collectedUsage = [];
const collectedThoughtSignatures = {};
const handler = new ModelEndHandler(collectedUsage, collectedThoughtSignatures);
await handler.handle(
'on_chat_model_end',
{
output: {
usage_metadata: { input_tokens: 10, output_tokens: 5, total_tokens: 15 },
tool_calls: [
{ id: 'tc_a', name: 'a', args: {} },
{ id: 'tc_b', name: 'b', args: {} },
],
additional_kwargs: { signatures: ['SIG_A', '', 'SIG_B'] },
},
},
{ ls_model_name: 'gemini-3.1-flash-lite-preview', user_id: 'u1' },
buildGraph(),
);
expect(collectedThoughtSignatures).toEqual({ tc_a: 'SIG_A', tc_b: 'SIG_B' });
expect(collectedUsage).toHaveLength(1);
});
it('accumulates per-id across multiple model_end events (multi-step tool turn)', async () => {
const collectedUsage = [];
const collectedThoughtSignatures = {};
const handler = new ModelEndHandler(collectedUsage, collectedThoughtSignatures);
await handler.handle(
'on_chat_model_end',
{
output: {
usage_metadata: { input_tokens: 5, output_tokens: 5, total_tokens: 10 },
tool_calls: [{ id: 'tc_step1', name: 'a', args: {} }],
additional_kwargs: { signatures: ['SIG_step1'] },
},
},
{ ls_model_name: 'g', user_id: 'u' },
buildGraph(),
);
await handler.handle(
'on_chat_model_end',
{
output: {
usage_metadata: { input_tokens: 5, output_tokens: 5, total_tokens: 10 },
tool_calls: [{ id: 'tc_step2', name: 'b', args: {} }],
additional_kwargs: { signatures: ['SIG_step2'] },
},
},
{ ls_model_name: 'g', user_id: 'u' },
buildGraph(),
);
expect(collectedThoughtSignatures).toEqual({
tc_step1: 'SIG_step1',
tc_step2: 'SIG_step2',
});
});
it('is a no-op for signatures when collectedThoughtSignatures is null', async () => {
const collectedUsage = [];
const handler = new ModelEndHandler(collectedUsage, null);
await handler.handle(
'on_chat_model_end',
{
output: {
usage_metadata: { input_tokens: 5, output_tokens: 5, total_tokens: 10 },
tool_calls: [{ id: 'tc1', name: 'a', args: {} }],
additional_kwargs: { signatures: ['SIG'] },
},
},
{ ls_model_name: 'g', user_id: 'u' },
buildGraph(),
);
expect(collectedUsage).toHaveLength(1);
});
it('does not store anything when signatures field is missing (non-Vertex providers)', async () => {
const collectedUsage = [];
const collectedThoughtSignatures = {};
const handler = new ModelEndHandler(collectedUsage, collectedThoughtSignatures);
await handler.handle(
'on_chat_model_end',
{
output: {
usage_metadata: { input_tokens: 5, output_tokens: 5, total_tokens: 10 },
tool_calls: [{ id: 'tc1', name: 'a', args: {} }],
additional_kwargs: {},
},
},
{ ls_model_name: 'gpt-4', user_id: 'u' },
buildGraph(),
);
expect(collectedThoughtSignatures).toEqual({});
});
it('does not store anything when tool_calls is missing', async () => {
const collectedUsage = [];
const collectedThoughtSignatures = {};
const handler = new ModelEndHandler(collectedUsage, collectedThoughtSignatures);
await handler.handle(
'on_chat_model_end',
{
output: {
usage_metadata: { input_tokens: 5, output_tokens: 5, total_tokens: 10 },
additional_kwargs: { signatures: ['SIG_orphan'] },
},
},
{ ls_model_name: 'g', user_id: 'u' },
buildGraph(),
);
expect(collectedThoughtSignatures).toEqual({});
});
it('tags the producing agent on collected + emitted usage for per-endpoint pricing', async () => {
const collectedUsage = [];
const emitUsage = jest.fn();
const handler = new ModelEndHandler(collectedUsage, null, emitUsage);
const graph = {
getAgentContext: () => ({
provider: 'openai',
agentId: 'agent_sub',
clientOptions: { model: 'gpt-4' },
}),
};
await handler.handle(
'on_chat_model_end',
{ output: { usage_metadata: { input_tokens: 10, output_tokens: 5, total_tokens: 15 } } },
{ ls_model_name: 'gpt-4', run_id: 'r1', user_id: 'u1' },
graph,
);
expect(collectedUsage[0].agentId).toBe('agent_sub');
expect(emitUsage).toHaveBeenCalledWith(expect.objectContaining({ agentId: 'agent_sub' }));
});
it('leaves usage untagged when the graph context has no agentId (single-endpoint)', async () => {
const collectedUsage = [];
const emitUsage = jest.fn();
const handler = new ModelEndHandler(collectedUsage, null, emitUsage);
await handler.handle(
'on_chat_model_end',
{ output: { usage_metadata: { input_tokens: 10, output_tokens: 5, total_tokens: 15 } } },
{ ls_model_name: 'gemini-3.1-flash-lite-preview', run_id: 'r1', user_id: 'u1' },
buildGraph(),
);
expect(collectedUsage[0].agentId).toBeUndefined();
expect(emitUsage).toHaveBeenCalledWith(expect.objectContaining({ agentId: undefined }));
});
it('throws when collectedUsage is not an array (existing contract)', () => {
expect(() => new ModelEndHandler(null)).toThrow('collectedUsage must be an array');
});
});