feat(Guardrails Node): Require Chat model only for LLM checks

packages/@n8n/nodes-langchain/nodes/Guardrails/Guardrails.node.ts

@@ -1,50 +1,43 @@
-import type { IExecuteFunctions, INodeExecutionData, INodeType } from 'n8n-workflow';
+import {
+	VersionedNodeType,
+	type INodeTypeBaseDescription,
+	type IVersionedNodeType,
+} from 'n8n-workflow';
 
-import { process } from './actions/process';
-import { versionDescription } from './description';
-import { getChatModel } from './helpers/model';
+import { GuardrailsV1 } from './v1/GuardrailsV1.node';
+import { GuardrailsV2 } from './v2/GuardrailsV2.node';
 
-export class Guardrails implements INodeType {
-	description = versionDescription;
+export class Guardrails extends VersionedNodeType {
+	constructor() {
+		const baseDescription: INodeTypeBaseDescription = {
+			displayName: 'Guardrails',
+			name: 'guardrails',
+			icon: 'file:guardrails.svg',
+			group: ['transform'],
+			defaultVersion: 2,
+			description:
+				'Safeguard AI models from malicious input or prevent them from generating undesirable responses',
+			codex: {
+				alias: ['LangChain', 'Guardrails', 'PII', 'Secret', 'Injection', 'Sanitize'],
+				categories: ['AI'],
+				subcategories: {
+					AI: ['Agents', 'Miscellaneous', 'Root Nodes'],
+				},
+				resources: {
+					primaryDocumentation: [
+						{
+							url: 'https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.guardrails/',
+						},
+					],
+				},
+			},
+		};
 
-	async execute(this: IExecuteFunctions): Promise<INodeExecutionData[][]> {
-		const items = this.getInputData();
-		const operation = this.getNodeParameter('operation', 0) as 'classify' | 'sanitize';
-		const model = operation === 'classify' ? await getChatModel.call(this) : null;
+		const nodeVersions: IVersionedNodeType['nodeVersions'] = {
+			1: new GuardrailsV1(baseDescription),
+			2: new GuardrailsV2(baseDescription),
+		};
 
-		const failedItems: INodeExecutionData[] = [];
-		const passedItems: INodeExecutionData[] = [];
-		for (let i = 0; i < items.length; i++) {
-			try {
-				const responseData = await process.call(this, i, model);
-				if (responseData.passed) {
-					passedItems.push({
-						json: { guardrailsInput: responseData.guardrailsInput, ...responseData.passed },
-						pairedItem: { item: i },
-					});
-				}
-				if (responseData.failed) {
-					failedItems.push({
-						json: { guardrailsInput: responseData.guardrailsInput, ...responseData.failed },
-						pairedItem: { item: i },
-					});
-				}
-			} catch (error) {
-				if (this.continueOnFail()) {
-					failedItems.push({
-						json: { error: error.message, guardrailsInput: '' },
-						pairedItem: { item: i },
-					});
-				} else {
-					throw error;
-				}
-			}
-		}
-
-		if (operation === 'classify') {
-			return [passedItems, failedItems];
-		}
-
-		return [passedItems];
+		super(nodeVersions, baseDescription);
 	}
 }

packages/@n8n/nodes-langchain/nodes/Guardrails/actions/execute.ts

@@ -0,0 +1,49 @@
+import type { IExecuteFunctions, INodeExecutionData } from 'n8n-workflow';
+
+import { process } from './process';
+import type { GuardrailsOptions } from './types';
+import { hasLLMGuardrails } from '../helpers/configureNodeInputs';
+import { getChatModel } from '../helpers/model';
+
+export async function execute(this: IExecuteFunctions): Promise<INodeExecutionData[][]> {
+	const items = this.getInputData();
+	const operation = this.getNodeParameter('operation', 0) as 'classify' | 'sanitize';
+	const model = hasLLMGuardrails(this.getNodeParameter('guardrails', 0) as GuardrailsOptions)
+		? await getChatModel.call(this)
+		: null;
+
+	const failedItems: INodeExecutionData[] = [];
+	const passedItems: INodeExecutionData[] = [];
+	for (let i = 0; i < items.length; i++) {
+		try {
+			const responseData = await process.call(this, i, model);
+			if (responseData.passed) {
+				passedItems.push({
+					json: { guardrailsInput: responseData.guardrailsInput, ...responseData.passed },
+					pairedItem: { item: i },
+				});
+			}
+			if (responseData.failed) {
+				failedItems.push({
+					json: { guardrailsInput: responseData.guardrailsInput, ...responseData.failed },
+					pairedItem: { item: i },
+				});
+			}
+		} catch (error) {
+			if (this.continueOnFail()) {
+				failedItems.push({
+					json: { error: error.message, guardrailsInput: '' },
+					pairedItem: { item: i },
+				});
+			} else {
+				throw error;
+			}
+		}
+	}
+
+	if (operation === 'classify') {
+		return [passedItems, failedItems];
+	}
+
+	return [passedItems];
+}

packages/@n8n/nodes-langchain/nodes/Guardrails/actions/process.ts

@@ -80,6 +80,13 @@ export async function process(
 		input: [],
 	};
 
+	const checkModelAvailable = (model: BaseChatModel | null): model is BaseChatModel => {
+		if (!model) {
+			throw new NodeOperationError(this.getNode(), 'Chat Model is required');
+		}
+		return true;
+	};
+
 	if (guardrails.pii?.value) {
 		const { entities } = guardrails.pii.value;
 		stageGuardrails.preflight.push({
@@ -121,18 +128,14 @@ export async function process(
 	}
 
 	if (operation === 'classify') {
-		if (!model) {
-			throw new NodeOperationError(this.getNode(), 'Chat Model is required for classify operation');
-		}
-
 		if (guardrails.keywords) {
 			stageGuardrails.input.push({
 				name: 'keywords',
 				check: createKeywordsCheckFn({ keywords: splitByComma(guardrails.keywords) }),
 			});
 		}
 
-		if (guardrails.jailbreak?.value) {
+		if (guardrails.jailbreak?.value && checkModelAvailable(model)) {
 			const { prompt, threshold } = guardrails.jailbreak.value;
 			stageGuardrails.input.push({
 				name: 'jailbreak',
@@ -145,7 +148,7 @@ export async function process(
 			});
 		}
 
-		if (guardrails.nsfw?.value) {
+		if (guardrails.nsfw?.value && checkModelAvailable(model)) {
 			const { prompt, threshold } = guardrails.nsfw.value;
 			stageGuardrails.input.push({
 				name: 'nsfw',
@@ -158,7 +161,7 @@ export async function process(
 			});
 		}
 
-		if (guardrails.topicalAlignment?.value) {
+		if (guardrails.topicalAlignment?.value && checkModelAvailable(model)) {
 			const { prompt, threshold } = guardrails.topicalAlignment.value;
 			stageGuardrails.input.push({
 				name: 'topicalAlignment',
@@ -171,7 +174,7 @@ export async function process(
 			});
 		}
 
-		if (guardrails.custom?.guardrail) {
+		if (guardrails.custom?.guardrail && checkModelAvailable(model)) {
 			for (const customGuardrail of guardrails.custom.guardrail) {
 				const { prompt, threshold, name } = customGuardrail;
 				stageGuardrails.input.push({