mirror of
https://github.com/czlonkowski/n8n-mcp.git
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>
This commit is contained in:
czlonkowski
317
tests/integration/ai-validation/chat-trigger-validation.test.ts
Normal file
317
tests/integration/ai-validation/chat-trigger-validation.test.ts
Normal file
@@ -0,0 +1,317 @@
|
||||
/**
|
||||
* Integration Tests: Chat Trigger Validation
|
||||
*
|
||||
* Tests Chat Trigger validation against real n8n instance.
|
||||
*/
|
||||
|
||||
import { describe, it, expect, beforeEach, afterEach, afterAll } from 'vitest';
|
||||
import { createTestContext, TestContext, createTestWorkflowName } from '../n8n-api/utils/test-context';
|
||||
import { getTestN8nClient } from '../n8n-api/utils/n8n-client';
|
||||
import { N8nApiClient } from '../../../src/services/n8n-api-client';
|
||||
import { cleanupOrphanedWorkflows } from '../n8n-api/utils/cleanup-helpers';
|
||||
import { createMcpContext } from '../n8n-api/utils/mcp-context';
|
||||
import { InstanceContext } from '../../../src/types/instance-context';
|
||||
import { handleValidateWorkflow } from '../../../src/mcp/handlers-n8n-manager';
|
||||
import { getNodeRepository, closeNodeRepository } from '../n8n-api/utils/node-repository';
|
||||
import { NodeRepository } from '../../../src/database/node-repository';
|
||||
import { ValidationResponse } from '../n8n-api/types/mcp-responses';
|
||||
import {
|
||||
createChatTriggerNode,
|
||||
createAIAgentNode,
|
||||
createLanguageModelNode,
|
||||
createRespondNode,
|
||||
createAIConnection,
|
||||
createMainConnection,
|
||||
mergeConnections,
|
||||
createAIWorkflow
|
||||
} from './helpers';
|
||||
import { WorkflowNode } from '../../../src/types/n8n-api';
|
||||
|
||||
describe('Integration: Chat Trigger Validation', () => {
|
||||
let context: TestContext;
|
||||
let client: N8nApiClient;
|
||||
let mcpContext: InstanceContext;
|
||||
let repository: NodeRepository;
|
||||
|
||||
beforeEach(async () => {
|
||||
context = createTestContext();
|
||||
client = getTestN8nClient();
|
||||
mcpContext = createMcpContext();
|
||||
repository = await getNodeRepository();
|
||||
});
|
||||
|
||||
afterEach(async () => {
|
||||
await context.cleanup();
|
||||
});
|
||||
|
||||
afterAll(async () => {
|
||||
await closeNodeRepository();
|
||||
if (!process.env.CI) {
|
||||
await cleanupOrphanedWorkflows();
|
||||
}
|
||||
});
|
||||
|
||||
// ======================================================================
|
||||
// TEST 1: Streaming to Non-AI-Agent
|
||||
// ======================================================================
|
||||
|
||||
it('should detect streaming to non-AI-Agent', async () => {
|
||||
const chatTrigger = createChatTriggerNode({
|
||||
name: 'Chat Trigger',
|
||||
responseMode: 'streaming'
|
||||
});
|
||||
|
||||
// Regular node (not AI Agent)
|
||||
const regularNode: WorkflowNode = {
|
||||
id: 'set-1',
|
||||
name: 'Set',
|
||||
type: 'n8n-nodes-base.set',
|
||||
typeVersion: 3.4,
|
||||
position: [450, 300],
|
||||
parameters: {
|
||||
assignments: {
|
||||
assignments: []
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
const workflow = createAIWorkflow(
|
||||
[chatTrigger, regularNode],
|
||||
createMainConnection('Chat Trigger', 'Set'),
|
||||
{
|
||||
name: createTestWorkflowName('Chat Trigger - Wrong Target'),
|
||||
tags: ['mcp-integration-test', 'ai-validation']
|
||||
}
|
||||
);
|
||||
|
||||
const created = await client.createWorkflow(workflow);
|
||||
context.trackWorkflow(created.id!);
|
||||
|
||||
const response = await handleValidateWorkflow(
|
||||
{ id: created.id },
|
||||
repository,
|
||||
mcpContext
|
||||
);
|
||||
|
||||
expect(response.success).toBe(true);
|
||||
const data = response.data as ValidationResponse;
|
||||
|
||||
expect(data.valid).toBe(false);
|
||||
expect(data.errors).toBeDefined();
|
||||
|
||||
const errorCodes = data.errors!.map(e => e.code);
|
||||
expect(errorCodes).toContain('STREAMING_WRONG_TARGET');
|
||||
|
||||
const errorMessages = data.errors!.map(e => e.message).join(' ');
|
||||
expect(errorMessages).toMatch(/streaming.*AI Agent/i);
|
||||
});
|
||||
|
||||
// ======================================================================
|
||||
// TEST 2: Missing Connections
|
||||
// ======================================================================
|
||||
|
||||
it('should detect missing connections', async () => {
|
||||
const chatTrigger = createChatTriggerNode({
|
||||
name: 'Chat Trigger'
|
||||
});
|
||||
|
||||
const workflow = createAIWorkflow(
|
||||
[chatTrigger],
|
||||
{}, // No connections
|
||||
{
|
||||
name: createTestWorkflowName('Chat Trigger - No Connections'),
|
||||
tags: ['mcp-integration-test', 'ai-validation']
|
||||
}
|
||||
);
|
||||
|
||||
const created = await client.createWorkflow(workflow);
|
||||
context.trackWorkflow(created.id!);
|
||||
|
||||
const response = await handleValidateWorkflow(
|
||||
{ id: created.id },
|
||||
repository,
|
||||
mcpContext
|
||||
);
|
||||
|
||||
expect(response.success).toBe(true);
|
||||
const data = response.data as ValidationResponse;
|
||||
|
||||
expect(data.valid).toBe(false);
|
||||
expect(data.errors).toBeDefined();
|
||||
|
||||
const errorCodes = data.errors!.map(e => e.code);
|
||||
expect(errorCodes).toContain('MISSING_CONNECTIONS');
|
||||
});
|
||||
|
||||
// ======================================================================
|
||||
// TEST 3: Valid Streaming Setup
|
||||
// ======================================================================
|
||||
|
||||
it('should validate valid streaming setup', async () => {
|
||||
const chatTrigger = createChatTriggerNode({
|
||||
name: 'Chat Trigger',
|
||||
responseMode: 'streaming'
|
||||
});
|
||||
|
||||
const languageModel = createLanguageModelNode('openai', {
|
||||
name: 'OpenAI Chat Model'
|
||||
});
|
||||
|
||||
const agent = createAIAgentNode({
|
||||
name: 'AI Agent',
|
||||
text: 'You are a helpful assistant'
|
||||
// No main output connections - streaming mode
|
||||
});
|
||||
|
||||
const workflow = createAIWorkflow(
|
||||
[chatTrigger, languageModel, agent],
|
||||
mergeConnections(
|
||||
createMainConnection('Chat Trigger', 'AI Agent'),
|
||||
createAIConnection('OpenAI Chat Model', 'AI Agent', 'ai_languageModel')
|
||||
// NO main output from AI Agent
|
||||
),
|
||||
{
|
||||
name: createTestWorkflowName('Chat Trigger - Valid Streaming'),
|
||||
tags: ['mcp-integration-test', 'ai-validation']
|
||||
}
|
||||
);
|
||||
|
||||
const created = await client.createWorkflow(workflow);
|
||||
context.trackWorkflow(created.id!);
|
||||
|
||||
const response = await handleValidateWorkflow(
|
||||
{ id: created.id },
|
||||
repository,
|
||||
mcpContext
|
||||
);
|
||||
|
||||
expect(response.success).toBe(true);
|
||||
const data = response.data as ValidationResponse;
|
||||
|
||||
expect(data.valid).toBe(true);
|
||||
expect(data.errors).toBeUndefined();
|
||||
expect(data.summary.errorCount).toBe(0);
|
||||
});
|
||||
|
||||
// ======================================================================
|
||||
// TEST 4: LastNode Mode (Default)
|
||||
// ======================================================================
|
||||
|
||||
it('should validate lastNode mode with AI Agent', async () => {
|
||||
const chatTrigger = createChatTriggerNode({
|
||||
name: 'Chat Trigger',
|
||||
responseMode: 'lastNode'
|
||||
});
|
||||
|
||||
const languageModel = createLanguageModelNode('openai', {
|
||||
name: 'OpenAI Chat Model'
|
||||
});
|
||||
|
||||
const agent = createAIAgentNode({
|
||||
name: 'AI Agent',
|
||||
text: 'You are a helpful assistant'
|
||||
});
|
||||
|
||||
const respond = createRespondNode({
|
||||
name: 'Respond to Webhook'
|
||||
});
|
||||
|
||||
const workflow = createAIWorkflow(
|
||||
[chatTrigger, languageModel, agent, respond],
|
||||
mergeConnections(
|
||||
createMainConnection('Chat Trigger', 'AI Agent'),
|
||||
createAIConnection('OpenAI Chat Model', 'AI Agent', 'ai_languageModel'),
|
||||
createMainConnection('AI Agent', 'Respond to Webhook')
|
||||
),
|
||||
{
|
||||
name: createTestWorkflowName('Chat Trigger - LastNode Mode'),
|
||||
tags: ['mcp-integration-test', 'ai-validation']
|
||||
}
|
||||
);
|
||||
|
||||
const created = await client.createWorkflow(workflow);
|
||||
context.trackWorkflow(created.id!);
|
||||
|
||||
const response = await handleValidateWorkflow(
|
||||
{ id: created.id },
|
||||
repository,
|
||||
mcpContext
|
||||
);
|
||||
|
||||
expect(response.success).toBe(true);
|
||||
const data = response.data as ValidationResponse;
|
||||
|
||||
// Should be valid (lastNode mode allows main output)
|
||||
expect(data.valid).toBe(true);
|
||||
|
||||
// May have info suggestion about using streaming
|
||||
if (data.info) {
|
||||
const streamingSuggestion = data.info.find((i: any) =>
|
||||
i.message.toLowerCase().includes('streaming')
|
||||
);
|
||||
// This is optional - just checking the suggestion exists if present
|
||||
if (streamingSuggestion) {
|
||||
expect(streamingSuggestion.severity).toBe('info');
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
// ======================================================================
|
||||
// TEST 5: Streaming Agent with Output Connection (Error)
|
||||
// ======================================================================
|
||||
|
||||
it('should detect streaming agent with output connection', async () => {
|
||||
const chatTrigger = createChatTriggerNode({
|
||||
name: 'Chat Trigger',
|
||||
responseMode: 'streaming'
|
||||
});
|
||||
|
||||
const languageModel = createLanguageModelNode('openai', {
|
||||
name: 'OpenAI Chat Model'
|
||||
});
|
||||
|
||||
const agent = createAIAgentNode({
|
||||
name: 'AI Agent',
|
||||
text: 'You are a helpful assistant'
|
||||
});
|
||||
|
||||
const respond = createRespondNode({
|
||||
name: 'Respond to Webhook'
|
||||
});
|
||||
|
||||
const workflow = createAIWorkflow(
|
||||
[chatTrigger, languageModel, agent, respond],
|
||||
mergeConnections(
|
||||
createMainConnection('Chat Trigger', 'AI Agent'),
|
||||
createAIConnection('OpenAI Chat Model', 'AI Agent', 'ai_languageModel'),
|
||||
createMainConnection('AI Agent', 'Respond to Webhook') // ERROR in streaming mode
|
||||
),
|
||||
{
|
||||
name: createTestWorkflowName('Chat Trigger - Streaming With Output'),
|
||||
tags: ['mcp-integration-test', 'ai-validation']
|
||||
}
|
||||
);
|
||||
|
||||
const created = await client.createWorkflow(workflow);
|
||||
context.trackWorkflow(created.id!);
|
||||
|
||||
const response = await handleValidateWorkflow(
|
||||
{ id: created.id },
|
||||
repository,
|
||||
mcpContext
|
||||
);
|
||||
|
||||
expect(response.success).toBe(true);
|
||||
const data = response.data as ValidationResponse;
|
||||
|
||||
expect(data.valid).toBe(false);
|
||||
expect(data.errors).toBeDefined();
|
||||
|
||||
// Should detect streaming agent has output
|
||||
const streamingErrors = data.errors!.filter(e =>
|
||||
e.code === 'STREAMING_AGENT_HAS_OUTPUT' ||
|
||||
e.message.toLowerCase().includes('streaming')
|
||||
);
|
||||
expect(streamingErrors.length).toBeGreaterThan(0);
|
||||
});
|
||||
});
|
||||
Reference in New Issue
Block a user