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first commit
2026-03-17 16:22:57 +03:30

183 lines
5.5 KiB
TypeScript

import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
import type { AgentExecutor } from '@langchain/classic/agents';
import type { IExecuteFunctions } from 'n8n-workflow';
import { NodeConnectionTypes } from 'n8n-workflow';
import { GuardrailError } from '../../actions/types';
import { getChatModel, runLLMValidation } from '../../helpers/model';
import { ChatPromptTemplate } from '@langchain/core/prompts';
import { StructuredOutputParser } from '@langchain/core/output_parsers';
jest.mock('@langchain/core/prompts', () => ({
ChatPromptTemplate: {
fromMessages: jest.fn(() => ({
format: jest.fn(),
pipe: jest.fn().mockReturnValue({
pipe: jest.fn().mockReturnValue({
invoke: jest.fn(),
}),
}),
})),
},
}));
jest.mock('@langchain/classic/agents', () => ({
AgentExecutor: jest.fn().mockImplementation(() => ({
invoke: jest.fn(),
})),
createToolCallingAgent: jest.fn(() => ({
streamRunnable: false,
})),
}));
jest.mock('@langchain/core/output_parsers', () => ({
StructuredOutputParser: jest.fn().mockImplementation(() => ({
invoke: jest.fn(),
getFormatInstructions: jest.fn().mockReturnValue('Format instructions'),
})),
OutputParserException: jest.fn().mockImplementation((message) => ({
message,
name: 'OutputParserException',
})),
}));
describe('model helper', () => {
let mockExecuteFunctions: IExecuteFunctions;
let mockModel: BaseChatModel;
beforeEach(() => {
mockModel = {
invoke: jest.fn(),
} as any;
mockExecuteFunctions = {
getInputConnectionData: jest.fn(),
} as any;
});
afterEach(() => {
jest.clearAllMocks();
});
describe('getChatModel', () => {
it('should return model when getInputConnectionData returns a single model', async () => {
(mockExecuteFunctions.getInputConnectionData as jest.Mock).mockResolvedValue(mockModel);
const result = await getChatModel.call(mockExecuteFunctions);
expect(mockExecuteFunctions.getInputConnectionData).toHaveBeenCalledWith(
NodeConnectionTypes.AiLanguageModel,
0,
);
expect(result).toBe(mockModel);
});
it('should return first model when getInputConnectionData returns an array', async () => {
const models = [mockModel, {} as BaseChatModel];
(mockExecuteFunctions.getInputConnectionData as jest.Mock).mockResolvedValue(models);
const result = await getChatModel.call(mockExecuteFunctions);
expect(mockExecuteFunctions.getInputConnectionData).toHaveBeenCalledWith(
NodeConnectionTypes.AiLanguageModel,
0,
);
expect(result).toBe(mockModel);
});
it('should handle empty array from getInputConnectionData', async () => {
(mockExecuteFunctions.getInputConnectionData as jest.Mock).mockResolvedValue([]);
const result = await getChatModel.call(mockExecuteFunctions);
expect(result).toBeUndefined();
});
});
describe('runLLMValidation', () => {
it('should return failed GuardrailResult when agent execution fails', async () => {
const mockAgentExecutor = {
invoke: jest.fn().mockRejectedValue(new Error('Agent execution failed')),
};
jest
.mocked((await import('@langchain/classic/agents')).AgentExecutor)
.mockImplementation(() => mockAgentExecutor as unknown as AgentExecutor);
const result = await runLLMValidation('test-guardrail', 'Test input', {
model: mockModel,
prompt: 'Test prompt',
threshold: 0.5,
});
expect(result).toEqual({
guardrailName: 'test-guardrail',
tripwireTriggered: true,
executionFailed: true,
originalException: expect.any(GuardrailError),
info: {},
});
expect(result.originalException).toBeInstanceOf(GuardrailError);
expect((result.originalException as GuardrailError).guardrailName).toBe('test-guardrail');
});
it('should return failed GuardrailResult when agent does not call tool', async () => {
const mockAgentExecutor = {
invoke: jest.fn().mockResolvedValue({}), // No tool call
};
jest
.mocked((await import('@langchain/classic/agents')).AgentExecutor)
.mockImplementation(() => mockAgentExecutor as unknown as AgentExecutor);
const result = await runLLMValidation('test-guardrail', 'Test input', {
model: mockModel,
prompt: 'Test prompt',
threshold: 0.5,
});
expect(result).toEqual({
guardrailName: 'test-guardrail',
tripwireTriggered: true,
executionFailed: true,
originalException: expect.any(GuardrailError),
info: {},
});
});
it('should use provided systemMessage instead of default rules', async () => {
const invokeMock = jest.fn().mockResolvedValue({
content: [{ type: 'text', text: '{"confidenceScore":0.6,"flagged":true}' }],
});
jest.mocked(ChatPromptTemplate.fromMessages).mockImplementationOnce(
() =>
({
pipe: jest.fn().mockReturnValue({ invoke: invokeMock }),
}) as unknown as any,
);
jest.mocked(StructuredOutputParser).mockImplementationOnce(
() =>
({
getFormatInstructions: jest.fn().mockReturnValue('Format instructions'),
parse: jest.fn().mockResolvedValue({ confidenceScore: 0.6, flagged: true }),
}) as unknown as any,
);
const model = { invoke: jest.fn() } as unknown as BaseChatModel;
await runLLMValidation('test-guardrail', 'Input text', {
model,
prompt: 'System Prompt',
threshold: 0.5,
systemMessage: 'CUSTOM_RULES',
});
expect(invokeMock).toHaveBeenCalled();
const callArg = invokeMock.mock.calls[0][0];
expect(callArg.system_message).toContain('CUSTOM_RULES');
expect(callArg.system_message).not.toContain('Only respond with the json object');
});
});
});