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
332
tests/integration/ai-validation/llm-chain-validation.test.ts
Normal file
332
tests/integration/ai-validation/llm-chain-validation.test.ts
Normal file
@@ -0,0 +1,332 @@
|
||||
/**
|
||||
* Integration Tests: Basic LLM Chain Validation
|
||||
*
|
||||
* Tests Basic LLM Chain 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 {
|
||||
createBasicLLMChainNode,
|
||||
createLanguageModelNode,
|
||||
createMemoryNode,
|
||||
createAIConnection,
|
||||
mergeConnections,
|
||||
createAIWorkflow
|
||||
} from './helpers';
|
||||
import { WorkflowNode } from '../../../src/types/n8n-api';
|
||||
|
||||
describe('Integration: Basic LLM Chain 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: Missing Language Model
|
||||
// ======================================================================
|
||||
|
||||
it('should detect missing language model', async () => {
|
||||
const llmChain = createBasicLLMChainNode({
|
||||
name: 'Basic LLM Chain',
|
||||
promptType: 'define',
|
||||
text: 'Test prompt'
|
||||
});
|
||||
|
||||
const workflow = createAIWorkflow(
|
||||
[llmChain],
|
||||
{}, // No connections
|
||||
{
|
||||
name: createTestWorkflowName('LLM Chain - Missing Model'),
|
||||
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_LANGUAGE_MODEL');
|
||||
});
|
||||
|
||||
// ======================================================================
|
||||
// TEST 2: Missing Prompt Text (promptType=define)
|
||||
// ======================================================================
|
||||
|
||||
it('should detect missing prompt text', async () => {
|
||||
const languageModel = createLanguageModelNode('openai', {
|
||||
name: 'OpenAI Chat Model'
|
||||
});
|
||||
|
||||
const llmChain = createBasicLLMChainNode({
|
||||
name: 'Basic LLM Chain',
|
||||
promptType: 'define',
|
||||
text: '' // Empty prompt text
|
||||
});
|
||||
|
||||
const workflow = createAIWorkflow(
|
||||
[languageModel, llmChain],
|
||||
createAIConnection('OpenAI Chat Model', 'Basic LLM Chain', 'ai_languageModel'),
|
||||
{
|
||||
name: createTestWorkflowName('LLM Chain - Missing Prompt'),
|
||||
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_PROMPT_TEXT');
|
||||
});
|
||||
|
||||
// ======================================================================
|
||||
// TEST 3: Valid Complete LLM Chain
|
||||
// ======================================================================
|
||||
|
||||
it('should validate complete LLM Chain', async () => {
|
||||
const languageModel = createLanguageModelNode('openai', {
|
||||
name: 'OpenAI Chat Model'
|
||||
});
|
||||
|
||||
const llmChain = createBasicLLMChainNode({
|
||||
name: 'Basic LLM Chain',
|
||||
promptType: 'define',
|
||||
text: 'You are a helpful assistant. Answer the following: {{ $json.question }}'
|
||||
});
|
||||
|
||||
const workflow = createAIWorkflow(
|
||||
[languageModel, llmChain],
|
||||
createAIConnection('OpenAI Chat Model', 'Basic LLM Chain', 'ai_languageModel'),
|
||||
{
|
||||
name: createTestWorkflowName('LLM Chain - Valid'),
|
||||
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: LLM Chain with Memory
|
||||
// ======================================================================
|
||||
|
||||
it('should validate LLM Chain with memory', async () => {
|
||||
const languageModel = createLanguageModelNode('anthropic', {
|
||||
name: 'Anthropic Chat Model'
|
||||
});
|
||||
|
||||
const memory = createMemoryNode({
|
||||
name: 'Window Buffer Memory',
|
||||
contextWindowLength: 10
|
||||
});
|
||||
|
||||
const llmChain = createBasicLLMChainNode({
|
||||
name: 'Basic LLM Chain',
|
||||
promptType: 'auto'
|
||||
});
|
||||
|
||||
const workflow = createAIWorkflow(
|
||||
[languageModel, memory, llmChain],
|
||||
mergeConnections(
|
||||
createAIConnection('Anthropic Chat Model', 'Basic LLM Chain', 'ai_languageModel'),
|
||||
createAIConnection('Window Buffer Memory', 'Basic LLM Chain', 'ai_memory')
|
||||
),
|
||||
{
|
||||
name: createTestWorkflowName('LLM Chain - With Memory'),
|
||||
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();
|
||||
});
|
||||
|
||||
// ======================================================================
|
||||
// TEST 5: LLM Chain with Multiple Language Models (Error)
|
||||
// ======================================================================
|
||||
|
||||
it('should detect multiple language models', async () => {
|
||||
const languageModel1 = createLanguageModelNode('openai', {
|
||||
id: 'model-1',
|
||||
name: 'OpenAI Chat Model 1'
|
||||
});
|
||||
|
||||
const languageModel2 = createLanguageModelNode('anthropic', {
|
||||
id: 'model-2',
|
||||
name: 'Anthropic Chat Model'
|
||||
});
|
||||
|
||||
const llmChain = createBasicLLMChainNode({
|
||||
name: 'Basic LLM Chain',
|
||||
promptType: 'define',
|
||||
text: 'Test prompt'
|
||||
});
|
||||
|
||||
const workflow = createAIWorkflow(
|
||||
[languageModel1, languageModel2, llmChain],
|
||||
mergeConnections(
|
||||
createAIConnection('OpenAI Chat Model 1', 'Basic LLM Chain', 'ai_languageModel'),
|
||||
createAIConnection('Anthropic Chat Model', 'Basic LLM Chain', 'ai_languageModel') // ERROR: multiple models
|
||||
),
|
||||
{
|
||||
name: createTestWorkflowName('LLM Chain - Multiple Models'),
|
||||
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('MULTIPLE_LANGUAGE_MODELS');
|
||||
});
|
||||
|
||||
// ======================================================================
|
||||
// TEST 6: LLM Chain with Tools (Error - not supported)
|
||||
// ======================================================================
|
||||
|
||||
it('should detect tools connection (not supported)', async () => {
|
||||
const languageModel = createLanguageModelNode('openai', {
|
||||
name: 'OpenAI Chat Model'
|
||||
});
|
||||
|
||||
// Manually create a tool node
|
||||
const toolNode: WorkflowNode = {
|
||||
id: 'tool-1',
|
||||
name: 'Calculator',
|
||||
type: '@n8n/n8n-nodes-langchain.toolCalculator',
|
||||
typeVersion: 1,
|
||||
position: [250, 400],
|
||||
parameters: {}
|
||||
};
|
||||
|
||||
const llmChain = createBasicLLMChainNode({
|
||||
name: 'Basic LLM Chain',
|
||||
promptType: 'define',
|
||||
text: 'Calculate something'
|
||||
});
|
||||
|
||||
const workflow = createAIWorkflow(
|
||||
[languageModel, toolNode, llmChain],
|
||||
mergeConnections(
|
||||
createAIConnection('OpenAI Chat Model', 'Basic LLM Chain', 'ai_languageModel'),
|
||||
createAIConnection('Calculator', 'Basic LLM Chain', 'ai_tool') // ERROR: tools not supported
|
||||
),
|
||||
{
|
||||
name: createTestWorkflowName('LLM Chain - With Tools'),
|
||||
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('TOOLS_NOT_SUPPORTED');
|
||||
|
||||
const errorMessages = data.errors!.map(e => e.message).join(' ');
|
||||
expect(errorMessages).toMatch(/AI Agent/i); // Should suggest using AI Agent
|
||||
});
|
||||
});
|
||||
Reference in New Issue
Block a user