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* fix: AI node connection validation in partial workflow updates (#357) Fix critical validation issue where n8n_update_partial_workflow incorrectly required 'main' connections for AI nodes that exclusively use AI-specific connection types (ai_languageModel, ai_memory, ai_embedding, ai_vectorStore, ai_tool). Problem: - Workflows containing AI nodes could not be updated via n8n_update_partial_workflow - Validation incorrectly expected ALL nodes to have 'main' connections - AI nodes only have AI-specific connection types, never 'main' Root Cause: - Zod schema in src/services/n8n-validation.ts defined 'main' as required field - Schema didn't support AI-specific connection types Fixed: - Made 'main' connection optional in Zod schema - Added support for all AI connection types: ai_tool, ai_languageModel, ai_memory, ai_embedding, ai_vectorStore - Created comprehensive test suite (13 tests) covering all AI connection scenarios - Updated documentation to clarify AI nodes don't require 'main' connections Testing: - All 13 new integration tests passing - Tested with actual workflow 019Vrw56aROeEzVj from issue #357 - Zero breaking changes (making required fields optional is always safe) Files Changed: - src/services/n8n-validation.ts - Fixed Zod schema - tests/integration/workflow-diff/ai-node-connection-validation.test.ts - New test suite - src/mcp/tool-docs/workflow_management/n8n-update-partial-workflow.ts - Updated docs - package.json - Version bump to 2.21.1 - CHANGELOG.md - Comprehensive release notes Closes #357 🤖 Generated with Claude Code (https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> Conceived by Romuald Członkowski - www.aiadvisors.pl/en * fix: Add missing id parameter in test file and JSDoc comment Address code review feedback from PR #358: - Add 'id' field to all applyDiff calls in test file (fixes TypeScript errors) - Add JSDoc comment explaining why 'main' is optional in schema - Ensures TypeScript compilation succeeds Changes: - tests/integration/workflow-diff/ai-node-connection-validation.test.ts: Added id parameter to all 13 test cases - src/services/n8n-validation.ts: Added JSDoc explaining optional main connections Testing: - npm run typecheck: PASS ✅ - npm run build: PASS ✅ - All 13 tests: PASS ✅ 🤖 Generated with Claude Code (https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> --------- Co-authored-by: Claude <noreply@anthropic.com>
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CHANGELOG.md
133
CHANGELOG.md
@@ -7,6 +7,139 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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## [Unreleased]
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## [2.21.1] - 2025-10-23
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### 🐛 Bug Fixes
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**Issue #357: Fix AI Node Connection Validation in Partial Workflow Updates**
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Fixed critical validation issue where `n8n_update_partial_workflow` incorrectly required `main` connections for AI nodes that exclusively use AI-specific connection types (`ai_languageModel`, `ai_memory`, `ai_embedding`, `ai_vectorStore`, `ai_tool`).
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#### Problem
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Workflows containing AI nodes (OpenAI Chat Model, Postgres Chat Memory, Embeddings OpenAI, Supabase Vector Store) could not be updated via `n8n_update_partial_workflow`, even for trivial changes to unrelated nodes. The validation logic incorrectly expected ALL nodes to have `main` connections, causing false positive errors:
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```
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Invalid connections: [
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{
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"code": "invalid_type",
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"expected": "array",
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"received": "undefined",
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"path": ["OpenAI Chat Model", "main"],
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"message": "Required"
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}
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]
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```
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**Impact**: Users could not update any workflows containing AI Agent nodes via MCP tools, forcing manual updates through the n8n UI.
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#### Root Cause
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The Zod schema in `src/services/n8n-validation.ts` (lines 27-39) defined `main` connections as a **required field** for all nodes, without support for AI-specific connection types:
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```typescript
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// BEFORE (Broken):
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export const workflowConnectionSchema = z.record(
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z.object({
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main: z.array(...), // Required - WRONG for AI nodes!
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})
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);
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```
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AI nodes use specialized connection types exclusively:
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- **ai_languageModel** - Language models (OpenAI, Anthropic, etc.)
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- **ai_memory** - Memory systems (Postgres Chat Memory, etc.)
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- **ai_embedding** - Embedding models (Embeddings OpenAI, etc.)
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- **ai_vectorStore** - Vector stores (Supabase Vector Store, etc.)
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- **ai_tool** - Tools for AI agents
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These nodes **never have `main` connections** - they only have their AI-specific connection types.
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#### Fixed
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**1. Updated Zod Schema** (`src/services/n8n-validation.ts` lines 27-49):
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```typescript
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// AFTER (Fixed):
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const connectionArraySchema = z.array(
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z.array(
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z.object({
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node: z.string(),
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type: z.string(),
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index: z.number(),
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})
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)
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);
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export const workflowConnectionSchema = z.record(
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z.object({
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main: connectionArraySchema.optional(), // Now optional
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error: connectionArraySchema.optional(), // Error connections
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ai_tool: connectionArraySchema.optional(), // AI tool connections
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ai_languageModel: connectionArraySchema.optional(), // Language model connections
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ai_memory: connectionArraySchema.optional(), // Memory connections
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ai_embedding: connectionArraySchema.optional(), // Embedding connections
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ai_vectorStore: connectionArraySchema.optional(), // Vector store connections
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})
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);
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```
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**2. Comprehensive Test Suite** (New file: `tests/integration/workflow-diff/ai-node-connection-validation.test.ts`):
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- 13 test scenarios covering all AI connection types
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- Tests for AI nodes with ONLY AI-specific connections (no `main`)
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- Tests for mixed workflows (regular nodes + AI nodes)
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- Tests for the exact scenario from issue #357
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- All tests passing ✅
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**3. Updated Documentation** (`src/mcp/tool-docs/workflow_management/n8n-update-partial-workflow.ts`):
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- Added clarification that AI nodes do NOT require `main` connections
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- Documented fix for issue #357
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- Updated best practices for AI workflows
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#### Testing
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**Before Fix**:
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- ❌ `n8n_validate_workflow`: Returns `valid: true` (correct)
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- ❌ `n8n_update_partial_workflow`: FAILS with "main connections required" errors
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- ❌ Cannot update workflows containing AI nodes at all
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**After Fix**:
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- ✅ `n8n_validate_workflow`: Returns `valid: true` (still correct)
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- ✅ `n8n_update_partial_workflow`: SUCCEEDS without validation errors
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- ✅ AI nodes correctly recognized with AI-specific connection types only
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- ✅ All 13 new integration tests passing
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- ✅ Tested with actual workflow `019Vrw56aROeEzVj` from issue #357
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#### Impact
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**Zero Breaking Changes**:
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- Making required fields optional is always backward compatible
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- All existing workflows continue working
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- Validation now correctly matches n8n's actual connection model
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**Fixes**:
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- Users can now update AI workflows via `n8n_update_partial_workflow`
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- AI nodes no longer generate false positive validation errors
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- Consistent validation between `n8n_validate_workflow` and `n8n_update_partial_workflow`
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#### Files Changed
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**Modified (3 files)**:
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- `src/services/n8n-validation.ts` - Fixed Zod schema to support all connection types
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- `src/mcp/tool-docs/workflow_management/n8n-update-partial-workflow.ts` - Updated documentation
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- `package.json` - Version bump to 2.21.1
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**Added (1 file)**:
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- `tests/integration/workflow-diff/ai-node-connection-validation.test.ts` - Comprehensive test suite (13 tests)
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#### References
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- **Issue**: #357 - n8n_update_partial_workflow incorrectly validates AI nodes requiring 'main' connections
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- **Workflow**: `019Vrw56aROeEzVj` (WOO_Workflow_21_POST_Chat_Send_AI_Agent)
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- **Investigation**: Deep code analysis by Explore agent identified exact root cause in Zod schema
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- **Confirmation**: n8n-mcp-tester agent verified fix with real workflow
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Conceived by Romuald Członkowski - [www.aiadvisors.pl/en](https://www.aiadvisors.pl/en)
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## [2.21.0] - 2025-10-23
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### ✨ Features
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BIN
data/nodes.db
BIN
data/nodes.db
Binary file not shown.
@@ -1,6 +1,6 @@
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{
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"name": "n8n-mcp",
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"version": "2.21.0",
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"version": "2.21.1",
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"description": "Integration between n8n workflow automation and Model Context Protocol (MCP)",
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"main": "dist/index.js",
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"types": "dist/index.d.ts",
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@@ -81,6 +81,10 @@ Full support for all 8 AI connection types used in n8n AI workflows:
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- Multiple tools: Batch multiple \`sourceOutput: "ai_tool"\` connections to one AI Agent
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- Vector retrieval: Chain ai_embedding → ai_vectorStore → ai_tool → AI Agent
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**Important Notes**:
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- **AI nodes do NOT require main connections**: Nodes like OpenAI Chat Model, Postgres Chat Memory, Embeddings OpenAI, and Supabase Vector Store use AI-specific connection types exclusively. They should ONLY have connections like \`ai_languageModel\`, \`ai_memory\`, \`ai_embedding\`, or \`ai_tool\` - NOT \`main\` connections.
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- **Fixed in v2.21.1**: Validation now correctly recognizes AI nodes that only have AI-specific connections without requiring \`main\` connections (resolves issue #357).
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**Best Practices**:
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- Always specify \`sourceOutput\` for AI connections (defaults to "main" if omitted)
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- Connect language model BEFORE creating/enabling AI Agent (validation requirement)
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@@ -24,9 +24,8 @@ export const workflowNodeSchema = z.object({
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executeOnce: z.boolean().optional(),
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});
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export const workflowConnectionSchema = z.record(
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z.object({
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main: z.array(
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// Connection array schema used by all connection types
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const connectionArraySchema = z.array(
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z.array(
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z.object({
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node: z.string(),
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@@ -34,7 +33,22 @@ export const workflowConnectionSchema = z.record(
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index: z.number(),
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})
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)
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),
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);
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/**
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* Workflow connection schema supporting all connection types.
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* Note: 'main' is optional because AI nodes exclusively use AI-specific
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* connection types (ai_languageModel, ai_memory, etc.) without main connections.
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*/
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export const workflowConnectionSchema = z.record(
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z.object({
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main: connectionArraySchema.optional(),
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error: connectionArraySchema.optional(),
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ai_tool: connectionArraySchema.optional(),
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ai_languageModel: connectionArraySchema.optional(),
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ai_memory: connectionArraySchema.optional(),
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ai_embedding: connectionArraySchema.optional(),
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ai_vectorStore: connectionArraySchema.optional(),
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})
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);
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@@ -0,0 +1,722 @@
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/**
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* Integration tests for AI node connection validation in workflow diff operations
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* Tests that AI nodes with AI-specific connection types (ai_languageModel, ai_memory, etc.)
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* are properly validated without requiring main connections
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*
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* Related to issue #357
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*/
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import { describe, test, expect } from 'vitest';
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import { WorkflowDiffEngine } from '../../../src/services/workflow-diff-engine';
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describe('AI Node Connection Validation', () => {
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describe('AI-specific connection types', () => {
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test('should accept workflow with ai_languageModel connections', async () => {
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const workflow = {
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id: 'test-workflow',
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name: 'AI Language Model Test',
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nodes: [
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{
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id: 'agent-node',
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name: 'AI Agent',
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type: '@n8n/n8n-nodes-langchain.agent',
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typeVersion: 1,
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position: [0, 0],
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parameters: {}
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},
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{
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id: 'llm-node',
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name: 'OpenAI Chat Model',
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type: '@n8n/n8n-nodes-langchain.lmChatOpenAi',
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typeVersion: 1,
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position: [200, 0],
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parameters: {}
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}
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],
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connections: {
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'OpenAI Chat Model': {
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ai_languageModel: [
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[{ node: 'AI Agent', type: 'ai_languageModel', index: 0 }]
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]
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}
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}
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};
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const engine = new WorkflowDiffEngine();
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const result = await engine.applyDiff(workflow as any, {
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id: workflow.id,
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operations: []
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});
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expect(result.success).toBe(true);
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expect(result.workflow).toBeDefined();
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});
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test('should accept workflow with ai_memory connections', async () => {
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const workflow = {
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id: 'test-workflow',
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name: 'AI Memory Test',
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nodes: [
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{
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id: 'agent-node',
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name: 'AI Agent',
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type: '@n8n/n8n-nodes-langchain.agent',
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typeVersion: 1,
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position: [0, 0],
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parameters: {}
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},
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{
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id: 'memory-node',
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name: 'Postgres Chat Memory',
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type: '@n8n/n8n-nodes-langchain.memoryPostgresChat',
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typeVersion: 1,
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position: [200, 0],
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parameters: {}
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}
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],
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connections: {
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'Postgres Chat Memory': {
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ai_memory: [
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[{ node: 'AI Agent', type: 'ai_memory', index: 0 }]
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]
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}
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}
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};
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const engine = new WorkflowDiffEngine();
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const result = await engine.applyDiff(workflow as any, {
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id: workflow.id,
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operations: []
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});
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expect(result.success).toBe(true);
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expect(result.workflow).toBeDefined();
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});
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test('should accept workflow with ai_embedding connections', async () => {
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const workflow = {
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id: 'test-workflow',
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name: 'AI Embedding Test',
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nodes: [
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{
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id: 'vectorstore-node',
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name: 'Vector Store',
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type: '@n8n/n8n-nodes-langchain.vectorStoreSupabase',
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typeVersion: 1,
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position: [0, 0],
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parameters: {}
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},
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{
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id: 'embedding-node',
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name: 'Embeddings OpenAI',
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type: '@n8n/n8n-nodes-langchain.embeddingsOpenAi',
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typeVersion: 1,
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position: [200, 0],
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parameters: {}
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}
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],
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connections: {
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'Embeddings OpenAI': {
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ai_embedding: [
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[{ node: 'Vector Store', type: 'ai_embedding', index: 0 }]
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]
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}
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}
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};
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const engine = new WorkflowDiffEngine();
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const result = await engine.applyDiff(workflow as any, {
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id: workflow.id,
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operations: []
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});
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expect(result.success).toBe(true);
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expect(result.workflow).toBeDefined();
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});
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test('should accept workflow with ai_tool connections', async () => {
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const workflow = {
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id: 'test-workflow',
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name: 'AI Tool Test',
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nodes: [
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{
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id: 'agent-node',
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name: 'AI Agent',
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type: '@n8n/n8n-nodes-langchain.agent',
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typeVersion: 1,
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position: [0, 0],
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parameters: {}
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},
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{
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id: 'vectorstore-node',
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name: 'Vector Store Tool',
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type: '@n8n/n8n-nodes-langchain.vectorStoreSupabase',
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typeVersion: 1,
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position: [200, 0],
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parameters: {}
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}
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],
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connections: {
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'Vector Store Tool': {
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ai_tool: [
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[{ node: 'AI Agent', type: 'ai_tool', index: 0 }]
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]
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}
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}
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};
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const engine = new WorkflowDiffEngine();
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const result = await engine.applyDiff(workflow as any, {
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id: workflow.id,
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operations: []
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});
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expect(result.success).toBe(true);
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expect(result.workflow).toBeDefined();
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});
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test('should accept workflow with ai_vectorStore connections', async () => {
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const workflow = {
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id: 'test-workflow',
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name: 'AI Vector Store Test',
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nodes: [
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{
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id: 'agent-node',
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name: 'AI Agent',
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type: '@n8n/n8n-nodes-langchain.agent',
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typeVersion: 1,
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position: [0, 0],
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parameters: {}
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},
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{
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id: 'vectorstore-node',
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name: 'Supabase Vector Store',
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type: '@n8n/n8n-nodes-langchain.vectorStoreSupabase',
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typeVersion: 1,
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position: [200, 0],
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parameters: {}
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}
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],
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connections: {
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'Supabase Vector Store': {
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ai_vectorStore: [
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[{ node: 'AI Agent', type: 'ai_vectorStore', index: 0 }]
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]
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}
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}
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};
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const engine = new WorkflowDiffEngine();
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const result = await engine.applyDiff(workflow as any, {
|
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id: workflow.id,
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operations: []
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});
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expect(result.success).toBe(true);
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expect(result.workflow).toBeDefined();
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});
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});
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describe('Mixed connection types', () => {
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test('should accept workflow mixing main and AI connections', async () => {
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const workflow = {
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id: 'test-workflow',
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name: 'Mixed Connections Test',
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nodes: [
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{
|
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id: 'webhook-node',
|
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name: 'Webhook',
|
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type: 'n8n-nodes-base.webhook',
|
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typeVersion: 1,
|
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position: [0, 0],
|
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parameters: {}
|
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},
|
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{
|
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id: 'agent-node',
|
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name: 'AI Agent',
|
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type: '@n8n/n8n-nodes-langchain.agent',
|
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typeVersion: 1,
|
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position: [200, 0],
|
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parameters: {}
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},
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{
|
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id: 'llm-node',
|
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name: 'OpenAI Chat Model',
|
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type: '@n8n/n8n-nodes-langchain.lmChatOpenAi',
|
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typeVersion: 1,
|
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position: [200, 200],
|
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parameters: {}
|
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},
|
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{
|
||||
id: 'respond-node',
|
||||
name: 'Respond to Webhook',
|
||||
type: 'n8n-nodes-base.respondToWebhook',
|
||||
typeVersion: 1,
|
||||
position: [400, 0],
|
||||
parameters: {}
|
||||
}
|
||||
],
|
||||
connections: {
|
||||
'Webhook': {
|
||||
main: [
|
||||
[{ node: 'AI Agent', type: 'main', index: 0 }]
|
||||
]
|
||||
},
|
||||
'AI Agent': {
|
||||
main: [
|
||||
[{ node: 'Respond to Webhook', type: 'main', index: 0 }]
|
||||
]
|
||||
},
|
||||
'OpenAI Chat Model': {
|
||||
ai_languageModel: [
|
||||
[{ node: 'AI Agent', type: 'ai_languageModel', index: 0 }]
|
||||
]
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
const engine = new WorkflowDiffEngine();
|
||||
const result = await engine.applyDiff(workflow as any, {
|
||||
id: workflow.id,
|
||||
operations: []
|
||||
});
|
||||
|
||||
expect(result.success).toBe(true);
|
||||
expect(result.workflow).toBeDefined();
|
||||
});
|
||||
|
||||
test('should accept workflow with error connections alongside AI connections', async () => {
|
||||
const workflow = {
|
||||
id: 'test-workflow',
|
||||
name: 'Error + AI Connections Test',
|
||||
nodes: [
|
||||
{
|
||||
id: 'webhook-node',
|
||||
name: 'Webhook',
|
||||
type: 'n8n-nodes-base.webhook',
|
||||
typeVersion: 1,
|
||||
position: [0, 0],
|
||||
parameters: {}
|
||||
},
|
||||
{
|
||||
id: 'agent-node',
|
||||
name: 'AI Agent',
|
||||
type: '@n8n/n8n-nodes-langchain.agent',
|
||||
typeVersion: 1,
|
||||
position: [200, 0],
|
||||
parameters: {}
|
||||
},
|
||||
{
|
||||
id: 'llm-node',
|
||||
name: 'OpenAI Chat Model',
|
||||
type: '@n8n/n8n-nodes-langchain.lmChatOpenAi',
|
||||
typeVersion: 1,
|
||||
position: [200, 200],
|
||||
parameters: {}
|
||||
},
|
||||
{
|
||||
id: 'error-handler',
|
||||
name: 'Error Handler',
|
||||
type: 'n8n-nodes-base.set',
|
||||
typeVersion: 1,
|
||||
position: [200, -200],
|
||||
parameters: {}
|
||||
}
|
||||
],
|
||||
connections: {
|
||||
'Webhook': {
|
||||
main: [
|
||||
[{ node: 'AI Agent', type: 'main', index: 0 }]
|
||||
]
|
||||
},
|
||||
'AI Agent': {
|
||||
error: [
|
||||
[{ node: 'Error Handler', type: 'main', index: 0 }]
|
||||
]
|
||||
},
|
||||
'OpenAI Chat Model': {
|
||||
ai_languageModel: [
|
||||
[{ node: 'AI Agent', type: 'ai_languageModel', index: 0 }]
|
||||
]
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
const engine = new WorkflowDiffEngine();
|
||||
const result = await engine.applyDiff(workflow as any, {
|
||||
id: workflow.id,
|
||||
operations: []
|
||||
});
|
||||
|
||||
expect(result.success).toBe(true);
|
||||
expect(result.workflow).toBeDefined();
|
||||
});
|
||||
});
|
||||
|
||||
describe('Complex AI workflow (Issue #357 scenario)', () => {
|
||||
test('should accept full AI agent workflow with RAG components', async () => {
|
||||
// Simplified version of the workflow from issue #357
|
||||
const workflow = {
|
||||
id: 'test-workflow',
|
||||
name: 'AI Agent with RAG',
|
||||
nodes: [
|
||||
{
|
||||
id: 'webhook-node',
|
||||
name: 'Webhook',
|
||||
type: 'n8n-nodes-base.webhook',
|
||||
typeVersion: 2,
|
||||
position: [0, 0],
|
||||
parameters: {}
|
||||
},
|
||||
{
|
||||
id: 'code-node',
|
||||
name: 'Prepare Inputs',
|
||||
type: 'n8n-nodes-base.code',
|
||||
typeVersion: 2,
|
||||
position: [200, 0],
|
||||
parameters: {}
|
||||
},
|
||||
{
|
||||
id: 'agent-node',
|
||||
name: 'AI Agent',
|
||||
type: '@n8n/n8n-nodes-langchain.agent',
|
||||
typeVersion: 1.7,
|
||||
position: [400, 0],
|
||||
parameters: {}
|
||||
},
|
||||
{
|
||||
id: 'llm-node',
|
||||
name: 'OpenAI Chat Model',
|
||||
type: '@n8n/n8n-nodes-langchain.lmChatOpenAi',
|
||||
typeVersion: 1,
|
||||
position: [400, 200],
|
||||
parameters: {}
|
||||
},
|
||||
{
|
||||
id: 'memory-node',
|
||||
name: 'Postgres Chat Memory',
|
||||
type: '@n8n/n8n-nodes-langchain.memoryPostgresChat',
|
||||
typeVersion: 1.1,
|
||||
position: [500, 200],
|
||||
parameters: {}
|
||||
},
|
||||
{
|
||||
id: 'embedding-node',
|
||||
name: 'Embeddings OpenAI',
|
||||
type: '@n8n/n8n-nodes-langchain.embeddingsOpenAi',
|
||||
typeVersion: 1,
|
||||
position: [600, 400],
|
||||
parameters: {}
|
||||
},
|
||||
{
|
||||
id: 'vectorstore-node',
|
||||
name: 'Supabase Vector Store',
|
||||
type: '@n8n/n8n-nodes-langchain.vectorStoreSupabase',
|
||||
typeVersion: 1.3,
|
||||
position: [600, 200],
|
||||
parameters: {}
|
||||
},
|
||||
{
|
||||
id: 'respond-node',
|
||||
name: 'Respond to Webhook',
|
||||
type: 'n8n-nodes-base.respondToWebhook',
|
||||
typeVersion: 1.1,
|
||||
position: [600, 0],
|
||||
parameters: {}
|
||||
}
|
||||
],
|
||||
connections: {
|
||||
'Webhook': {
|
||||
main: [
|
||||
[{ node: 'Prepare Inputs', type: 'main', index: 0 }]
|
||||
]
|
||||
},
|
||||
'Prepare Inputs': {
|
||||
main: [
|
||||
[{ node: 'AI Agent', type: 'main', index: 0 }]
|
||||
]
|
||||
},
|
||||
'AI Agent': {
|
||||
main: [
|
||||
[{ node: 'Respond to Webhook', type: 'main', index: 0 }]
|
||||
]
|
||||
},
|
||||
'OpenAI Chat Model': {
|
||||
ai_languageModel: [
|
||||
[{ node: 'AI Agent', type: 'ai_languageModel', index: 0 }]
|
||||
]
|
||||
},
|
||||
'Postgres Chat Memory': {
|
||||
ai_memory: [
|
||||
[{ node: 'AI Agent', type: 'ai_memory', index: 0 }]
|
||||
]
|
||||
},
|
||||
'Embeddings OpenAI': {
|
||||
ai_embedding: [
|
||||
[{ node: 'Supabase Vector Store', type: 'ai_embedding', index: 0 }]
|
||||
]
|
||||
},
|
||||
'Supabase Vector Store': {
|
||||
ai_tool: [
|
||||
[{ node: 'AI Agent', type: 'ai_tool', index: 0 }]
|
||||
]
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
const engine = new WorkflowDiffEngine();
|
||||
const result = await engine.applyDiff(workflow as any, {
|
||||
id: workflow.id,
|
||||
operations: []
|
||||
});
|
||||
|
||||
expect(result.success).toBe(true);
|
||||
expect(result.workflow).toBeDefined();
|
||||
expect(result.errors || []).toHaveLength(0);
|
||||
});
|
||||
|
||||
test('should successfully update AI workflow nodes without connection errors', async () => {
|
||||
// Test that we can update nodes in an AI workflow without triggering validation errors
|
||||
const workflow = {
|
||||
id: 'test-workflow',
|
||||
name: 'AI Workflow Update Test',
|
||||
nodes: [
|
||||
{
|
||||
id: 'webhook-node',
|
||||
name: 'Webhook',
|
||||
type: 'n8n-nodes-base.webhook',
|
||||
typeVersion: 2,
|
||||
position: [0, 0],
|
||||
parameters: { path: 'test' }
|
||||
},
|
||||
{
|
||||
id: 'agent-node',
|
||||
name: 'AI Agent',
|
||||
type: '@n8n/n8n-nodes-langchain.agent',
|
||||
typeVersion: 1,
|
||||
position: [200, 0],
|
||||
parameters: {}
|
||||
},
|
||||
{
|
||||
id: 'llm-node',
|
||||
name: 'OpenAI Chat Model',
|
||||
type: '@n8n/n8n-nodes-langchain.lmChatOpenAi',
|
||||
typeVersion: 1,
|
||||
position: [200, 200],
|
||||
parameters: {}
|
||||
}
|
||||
],
|
||||
connections: {
|
||||
'Webhook': {
|
||||
main: [
|
||||
[{ node: 'AI Agent', type: 'main', index: 0 }]
|
||||
]
|
||||
},
|
||||
'OpenAI Chat Model': {
|
||||
ai_languageModel: [
|
||||
[{ node: 'AI Agent', type: 'ai_languageModel', index: 0 }]
|
||||
]
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
const engine = new WorkflowDiffEngine();
|
||||
|
||||
// Update the webhook node (unrelated to AI nodes)
|
||||
const result = await engine.applyDiff(workflow as any, {
|
||||
id: workflow.id,
|
||||
operations: [
|
||||
{
|
||||
type: 'updateNode',
|
||||
nodeId: 'webhook-node',
|
||||
updates: {
|
||||
notes: 'Updated webhook configuration'
|
||||
}
|
||||
}
|
||||
]
|
||||
});
|
||||
|
||||
expect(result.success).toBe(true);
|
||||
expect(result.workflow).toBeDefined();
|
||||
expect(result.errors || []).toHaveLength(0);
|
||||
|
||||
// Verify the update was applied
|
||||
const updatedNode = result.workflow.nodes.find((n: any) => n.id === 'webhook-node');
|
||||
expect(updatedNode?.notes).toBe('Updated webhook configuration');
|
||||
});
|
||||
});
|
||||
|
||||
describe('Node-only AI nodes (no main connections)', () => {
|
||||
test('should accept AI nodes with ONLY ai_languageModel connections', async () => {
|
||||
const workflow = {
|
||||
id: 'test-workflow',
|
||||
name: 'AI Node Without Main',
|
||||
nodes: [
|
||||
{
|
||||
id: 'agent-node',
|
||||
name: 'AI Agent',
|
||||
type: '@n8n/n8n-nodes-langchain.agent',
|
||||
typeVersion: 1,
|
||||
position: [0, 0],
|
||||
parameters: {}
|
||||
},
|
||||
{
|
||||
id: 'llm-node',
|
||||
name: 'OpenAI Chat Model',
|
||||
type: '@n8n/n8n-nodes-langchain.lmChatOpenAi',
|
||||
typeVersion: 1,
|
||||
position: [200, 0],
|
||||
parameters: {}
|
||||
}
|
||||
],
|
||||
connections: {
|
||||
// OpenAI Chat Model has NO main connections, ONLY ai_languageModel
|
||||
'OpenAI Chat Model': {
|
||||
ai_languageModel: [
|
||||
[{ node: 'AI Agent', type: 'ai_languageModel', index: 0 }]
|
||||
]
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
const engine = new WorkflowDiffEngine();
|
||||
const result = await engine.applyDiff(workflow as any, {
|
||||
id: workflow.id,
|
||||
operations: []
|
||||
});
|
||||
|
||||
expect(result.success).toBe(true);
|
||||
expect(result.workflow).toBeDefined();
|
||||
expect(result.errors || []).toHaveLength(0);
|
||||
});
|
||||
|
||||
test('should accept AI nodes with ONLY ai_memory connections', async () => {
|
||||
const workflow = {
|
||||
id: 'test-workflow',
|
||||
name: 'Memory Node Without Main',
|
||||
nodes: [
|
||||
{
|
||||
id: 'agent-node',
|
||||
name: 'AI Agent',
|
||||
type: '@n8n/n8n-nodes-langchain.agent',
|
||||
typeVersion: 1,
|
||||
position: [0, 0],
|
||||
parameters: {}
|
||||
},
|
||||
{
|
||||
id: 'memory-node',
|
||||
name: 'Postgres Chat Memory',
|
||||
type: '@n8n/n8n-nodes-langchain.memoryPostgresChat',
|
||||
typeVersion: 1,
|
||||
position: [200, 0],
|
||||
parameters: {}
|
||||
}
|
||||
],
|
||||
connections: {
|
||||
// Memory node has NO main connections, ONLY ai_memory
|
||||
'Postgres Chat Memory': {
|
||||
ai_memory: [
|
||||
[{ node: 'AI Agent', type: 'ai_memory', index: 0 }]
|
||||
]
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
const engine = new WorkflowDiffEngine();
|
||||
const result = await engine.applyDiff(workflow as any, {
|
||||
id: workflow.id,
|
||||
operations: []
|
||||
});
|
||||
|
||||
expect(result.success).toBe(true);
|
||||
expect(result.workflow).toBeDefined();
|
||||
expect(result.errors || []).toHaveLength(0);
|
||||
});
|
||||
|
||||
test('should accept embedding nodes with ONLY ai_embedding connections', async () => {
|
||||
const workflow = {
|
||||
id: 'test-workflow',
|
||||
name: 'Embedding Node Without Main',
|
||||
nodes: [
|
||||
{
|
||||
id: 'vectorstore-node',
|
||||
name: 'Vector Store',
|
||||
type: '@n8n/n8n-nodes-langchain.vectorStoreSupabase',
|
||||
typeVersion: 1,
|
||||
position: [0, 0],
|
||||
parameters: {}
|
||||
},
|
||||
{
|
||||
id: 'embedding-node',
|
||||
name: 'Embeddings OpenAI',
|
||||
type: '@n8n/n8n-nodes-langchain.embeddingsOpenAi',
|
||||
typeVersion: 1,
|
||||
position: [200, 0],
|
||||
parameters: {}
|
||||
}
|
||||
],
|
||||
connections: {
|
||||
// Embedding node has NO main connections, ONLY ai_embedding
|
||||
'Embeddings OpenAI': {
|
||||
ai_embedding: [
|
||||
[{ node: 'Vector Store', type: 'ai_embedding', index: 0 }]
|
||||
]
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
const engine = new WorkflowDiffEngine();
|
||||
const result = await engine.applyDiff(workflow as any, {
|
||||
id: workflow.id,
|
||||
operations: []
|
||||
});
|
||||
|
||||
expect(result.success).toBe(true);
|
||||
expect(result.workflow).toBeDefined();
|
||||
expect(result.errors || []).toHaveLength(0);
|
||||
});
|
||||
|
||||
test('should accept vector store nodes with ONLY ai_tool connections', async () => {
|
||||
const workflow = {
|
||||
id: 'test-workflow',
|
||||
name: 'Vector Store Node Without Main',
|
||||
nodes: [
|
||||
{
|
||||
id: 'agent-node',
|
||||
name: 'AI Agent',
|
||||
type: '@n8n/n8n-nodes-langchain.agent',
|
||||
typeVersion: 1,
|
||||
position: [0, 0],
|
||||
parameters: {}
|
||||
},
|
||||
{
|
||||
id: 'vectorstore-node',
|
||||
name: 'Supabase Vector Store',
|
||||
type: '@n8n/n8n-nodes-langchain.vectorStoreSupabase',
|
||||
typeVersion: 1,
|
||||
position: [200, 0],
|
||||
parameters: {}
|
||||
}
|
||||
],
|
||||
connections: {
|
||||
// Vector store has NO main connections, ONLY ai_tool
|
||||
'Supabase Vector Store': {
|
||||
ai_tool: [
|
||||
[{ node: 'AI Agent', type: 'ai_tool', index: 0 }]
|
||||
]
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
const engine = new WorkflowDiffEngine();
|
||||
const result = await engine.applyDiff(workflow as any, {
|
||||
id: workflow.id,
|
||||
operations: []
|
||||
});
|
||||
|
||||
expect(result.success).toBe(true);
|
||||
expect(result.workflow).toBeDefined();
|
||||
expect(result.errors || []).toHaveLength(0);
|
||||
});
|
||||
});
|
||||
});
|
||||
Reference in New Issue
Block a user