mirror of
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synced 2026-02-06 13:33:11 +00:00
fix: resolve TypeScript compilation errors in integration tests
Fixed multiple TypeScript errors preventing clean build: - Fixed import paths for ValidationResponse type (5 test files) - Fixed validateBasicLLMChain function signature (removed extra workflow parameter) - Enhanced ValidationResponse interface to include missing properties: - Added code, nodeName fields to errors/warnings - Added info array for informational messages - Added suggestions array - Fixed type assertion in mergeConnections helper - Fixed implicit any type in chat-trigger-validation test All tests now compile cleanly with no TypeScript errors. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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czlonkowski
395
tests/integration/ai-validation/e2e-validation.test.ts
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395
tests/integration/ai-validation/e2e-validation.test.ts
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/**
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* Integration Tests: End-to-End AI Workflow Validation
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*
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* Tests complete AI workflow validation and creation flow.
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* Validates multi-error detection and workflow creation after validation.
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*/
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import { describe, it, expect, beforeEach, afterEach, afterAll } from 'vitest';
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import { createTestContext, TestContext, createTestWorkflowName } from '../n8n-api/utils/test-context';
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import { getTestN8nClient } from '../n8n-api/utils/n8n-client';
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import { N8nApiClient } from '../../../src/services/n8n-api-client';
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import { cleanupOrphanedWorkflows } from '../n8n-api/utils/cleanup-helpers';
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import { createMcpContext } from '../n8n-api/utils/mcp-context';
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import { InstanceContext } from '../../../src/types/instance-context';
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import { handleValidateWorkflow, handleCreateWorkflow } from '../../../src/mcp/handlers-n8n-manager';
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import { getNodeRepository, closeNodeRepository } from '../n8n-api/utils/node-repository';
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import { NodeRepository } from '../../../src/database/node-repository';
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import { ValidationResponse } from '../n8n-api/types/mcp-responses';
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import {
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createChatTriggerNode,
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createAIAgentNode,
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createLanguageModelNode,
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createHTTPRequestToolNode,
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createCodeToolNode,
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createMemoryNode,
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createRespondNode,
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createAIConnection,
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createMainConnection,
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mergeConnections,
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createAIWorkflow
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} from './helpers';
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describe('Integration: End-to-End AI Workflow Validation', () => {
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let context: TestContext;
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let client: N8nApiClient;
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let mcpContext: InstanceContext;
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let repository: NodeRepository;
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beforeEach(async () => {
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context = createTestContext();
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client = getTestN8nClient();
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mcpContext = createMcpContext();
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repository = await getNodeRepository();
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});
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afterEach(async () => {
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await context.cleanup();
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});
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afterAll(async () => {
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await closeNodeRepository();
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if (!process.env.CI) {
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await cleanupOrphanedWorkflows();
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}
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});
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// ======================================================================
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// TEST 1: Validate and Create Complex AI Workflow
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// ======================================================================
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it('should validate and create complex AI workflow', async () => {
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const chatTrigger = createChatTriggerNode({
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name: 'Chat Trigger',
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responseMode: 'lastNode'
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});
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const languageModel = createLanguageModelNode('openai', {
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name: 'OpenAI Chat Model'
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});
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const httpTool = createHTTPRequestToolNode({
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name: 'Weather API',
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toolDescription: 'Fetches current weather data from weather API',
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url: 'https://api.weather.com/current',
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method: 'GET'
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});
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const codeTool = createCodeToolNode({
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name: 'Data Processor',
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toolDescription: 'Processes and formats weather data',
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code: 'return { formatted: JSON.stringify($input.all()) };'
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});
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const memory = createMemoryNode({
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name: 'Conversation Memory',
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contextWindowLength: 10
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});
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const agent = createAIAgentNode({
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name: 'Weather Assistant',
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promptType: 'define',
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text: 'You are a weather assistant. Help users understand weather data.',
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systemMessage: 'You are an AI assistant specialized in weather information. You have access to weather APIs and can process data. Always provide clear, helpful responses.'
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});
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const respond = createRespondNode({
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name: 'Respond to User'
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});
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const workflow = createAIWorkflow(
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[chatTrigger, languageModel, httpTool, codeTool, memory, agent, respond],
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mergeConnections(
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createMainConnection('Chat Trigger', 'Weather Assistant'),
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createAIConnection('OpenAI Chat Model', 'Weather Assistant', 'ai_languageModel'),
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createAIConnection('Weather API', 'Weather Assistant', 'ai_tool'),
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createAIConnection('Data Processor', 'Weather Assistant', 'ai_tool'),
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createAIConnection('Conversation Memory', 'Weather Assistant', 'ai_memory'),
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createMainConnection('Weather Assistant', 'Respond to User')
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),
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{
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name: createTestWorkflowName('E2E - Complex AI Workflow'),
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tags: ['mcp-integration-test', 'ai-validation', 'e2e']
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}
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);
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// Step 1: Create workflow
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const created = await client.createWorkflow(workflow);
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context.trackWorkflow(created.id!);
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// Step 2: Validate workflow
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const validationResponse = await handleValidateWorkflow(
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{ id: created.id },
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repository,
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mcpContext
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);
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expect(validationResponse.success).toBe(true);
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const validationData = validationResponse.data as ValidationResponse;
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// Workflow should be valid
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expect(validationData.valid).toBe(true);
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expect(validationData.errors).toBeUndefined();
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expect(validationData.summary.errorCount).toBe(0);
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// Verify all nodes detected
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expect(validationData.summary.totalNodes).toBe(7);
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expect(validationData.summary.triggerNodes).toBe(1);
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// Step 3: Since it's valid, it's already created and ready to use
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// Just verify it exists
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const retrieved = await client.getWorkflow(created.id!);
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expect(retrieved.id).toBe(created.id);
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expect(retrieved.nodes.length).toBe(7);
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});
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// ======================================================================
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// TEST 2: Detect Multiple Validation Errors
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// ======================================================================
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it('should detect multiple validation errors', async () => {
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const chatTrigger = createChatTriggerNode({
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name: 'Chat Trigger',
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responseMode: 'streaming'
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});
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const httpTool = createHTTPRequestToolNode({
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name: 'HTTP Tool',
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toolDescription: '', // ERROR: missing description
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url: '', // ERROR: missing URL
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method: 'GET'
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});
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const codeTool = createCodeToolNode({
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name: 'Code Tool',
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toolDescription: 'Short', // WARNING: too short
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code: '' // ERROR: missing code
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});
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const agent = createAIAgentNode({
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name: 'AI Agent',
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promptType: 'define',
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text: '', // ERROR: missing prompt text
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// ERROR: missing language model connection
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// ERROR: has main output in streaming mode
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});
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const respond = createRespondNode({
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name: 'Respond'
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});
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const workflow = createAIWorkflow(
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[chatTrigger, httpTool, codeTool, agent, respond],
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mergeConnections(
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createMainConnection('Chat Trigger', 'AI Agent'),
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createAIConnection('HTTP Tool', 'AI Agent', 'ai_tool'),
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createAIConnection('Code Tool', 'AI Agent', 'ai_tool'),
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createMainConnection('AI Agent', 'Respond') // ERROR in streaming mode
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),
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{
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name: createTestWorkflowName('E2E - Multiple Errors'),
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tags: ['mcp-integration-test', 'ai-validation', 'e2e']
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}
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);
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const created = await client.createWorkflow(workflow);
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context.trackWorkflow(created.id!);
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const validationResponse = await handleValidateWorkflow(
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{ id: created.id },
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repository,
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mcpContext
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);
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expect(validationResponse.success).toBe(true);
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const validationData = validationResponse.data as ValidationResponse;
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// Should be invalid with multiple errors
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expect(validationData.valid).toBe(false);
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expect(validationData.errors).toBeDefined();
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expect(validationData.errors!.length).toBeGreaterThan(3);
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// Verify specific errors are detected
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const errorCodes = validationData.errors!.map(e => e.code);
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expect(errorCodes).toContain('MISSING_LANGUAGE_MODEL'); // AI Agent
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expect(errorCodes).toContain('MISSING_PROMPT_TEXT'); // AI Agent
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expect(errorCodes).toContain('MISSING_TOOL_DESCRIPTION'); // HTTP Tool
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expect(errorCodes).toContain('MISSING_URL'); // HTTP Tool
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expect(errorCodes).toContain('MISSING_CODE'); // Code Tool
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// Should also have streaming error
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const streamingErrors = validationData.errors!.filter(e =>
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e.code === 'STREAMING_WITH_MAIN_OUTPUT' ||
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e.code === 'STREAMING_AGENT_HAS_OUTPUT'
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);
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expect(streamingErrors.length).toBeGreaterThan(0);
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// Verify error messages are actionable
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for (const error of validationData.errors!) {
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expect(error.message).toBeDefined();
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expect(error.message.length).toBeGreaterThan(10);
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expect(error.nodeName).toBeDefined();
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}
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});
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// ======================================================================
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// TEST 3: Validate Streaming Workflow (No Main Output)
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// ======================================================================
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it('should validate streaming workflow without main output', async () => {
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const chatTrigger = createChatTriggerNode({
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name: 'Chat Trigger',
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responseMode: 'streaming'
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});
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const languageModel = createLanguageModelNode('anthropic', {
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name: 'Claude Model'
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});
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const agent = createAIAgentNode({
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name: 'Streaming Agent',
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text: 'You are a helpful assistant',
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systemMessage: 'Provide helpful, streaming responses to user queries'
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});
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const workflow = createAIWorkflow(
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[chatTrigger, languageModel, agent],
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mergeConnections(
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createMainConnection('Chat Trigger', 'Streaming Agent'),
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createAIConnection('Claude Model', 'Streaming Agent', 'ai_languageModel')
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// No main output from agent - streaming mode
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),
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{
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name: createTestWorkflowName('E2E - Streaming Workflow'),
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tags: ['mcp-integration-test', 'ai-validation', 'e2e']
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}
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);
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const created = await client.createWorkflow(workflow);
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context.trackWorkflow(created.id!);
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const validationResponse = await handleValidateWorkflow(
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{ id: created.id },
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repository,
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mcpContext
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);
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expect(validationResponse.success).toBe(true);
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const validationData = validationResponse.data as ValidationResponse;
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expect(validationData.valid).toBe(true);
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expect(validationData.errors).toBeUndefined();
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expect(validationData.summary.errorCount).toBe(0);
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});
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// ======================================================================
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// TEST 4: Validate Non-Streaming Workflow (With Main Output)
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// ======================================================================
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it('should validate non-streaming workflow with main output', async () => {
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const chatTrigger = createChatTriggerNode({
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name: 'Chat Trigger',
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responseMode: 'lastNode'
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});
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const languageModel = createLanguageModelNode('openai', {
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name: 'GPT Model'
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});
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const agent = createAIAgentNode({
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name: 'Non-Streaming Agent',
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text: 'You are a helpful assistant'
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});
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const respond = createRespondNode({
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name: 'Final Response'
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});
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const workflow = createAIWorkflow(
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[chatTrigger, languageModel, agent, respond],
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mergeConnections(
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createMainConnection('Chat Trigger', 'Non-Streaming Agent'),
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createAIConnection('GPT Model', 'Non-Streaming Agent', 'ai_languageModel'),
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createMainConnection('Non-Streaming Agent', 'Final Response')
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),
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{
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name: createTestWorkflowName('E2E - Non-Streaming Workflow'),
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tags: ['mcp-integration-test', 'ai-validation', 'e2e']
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}
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);
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const created = await client.createWorkflow(workflow);
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context.trackWorkflow(created.id!);
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const validationResponse = await handleValidateWorkflow(
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{ id: created.id },
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repository,
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mcpContext
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);
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expect(validationResponse.success).toBe(true);
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const validationData = validationResponse.data as ValidationResponse;
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expect(validationData.valid).toBe(true);
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expect(validationData.errors).toBeUndefined();
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});
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// ======================================================================
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// TEST 5: Test Node Type Normalization (Bug Fix Validation)
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// ======================================================================
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it('should correctly normalize node types during validation', async () => {
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// This test validates the v2.17.0 fix for node type normalization
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const languageModel = createLanguageModelNode('openai', {
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name: 'OpenAI Model'
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});
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const agent = createAIAgentNode({
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name: 'AI Agent',
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text: 'Test agent'
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});
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const httpTool = createHTTPRequestToolNode({
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name: 'API Tool',
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toolDescription: 'Calls external API',
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url: 'https://api.example.com/test'
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});
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const workflow = createAIWorkflow(
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[languageModel, agent, httpTool],
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mergeConnections(
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createAIConnection('OpenAI Model', 'AI Agent', 'ai_languageModel'),
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createAIConnection('API Tool', 'AI Agent', 'ai_tool')
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),
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{
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name: createTestWorkflowName('E2E - Type Normalization'),
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tags: ['mcp-integration-test', 'ai-validation', 'e2e']
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}
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);
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const created = await client.createWorkflow(workflow);
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context.trackWorkflow(created.id!);
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const validationResponse = await handleValidateWorkflow(
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{ id: created.id },
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repository,
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mcpContext
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);
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expect(validationResponse.success).toBe(true);
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const validationData = validationResponse.data as ValidationResponse;
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// Should be valid - no false "no tools connected" warning
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expect(validationData.valid).toBe(true);
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// Should NOT have false warnings about tools
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if (validationData.warnings) {
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const falseToolWarnings = validationData.warnings.filter(w =>
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w.message.toLowerCase().includes('no ai_tool') &&
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w.nodeName === 'AI Agent'
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);
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expect(falseToolWarnings.length).toBe(0);
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}
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});
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});
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