feat(AI Agent Tool Node): Add Agent Tool (#17108)

packages/@n8n/nodes-langchain/nodes/agents/Agent/Agent.node.ts

@@ -45,6 +45,7 @@ export class Agent extends VersionedNodeType {
 			2: new AgentV2(baseDescription),
 			2.1: new AgentV2(baseDescription),
 			2.2: new AgentV2(baseDescription),
+			// IMPORTANT Reminder to update AgentTool
 		};
 
 		super(nodeVersions, baseDescription);

packages/@n8n/nodes-langchain/nodes/agents/Agent/AgentTool.node.ts

@@ -0,0 +1,34 @@
+import type { INodeTypeBaseDescription, IVersionedNodeType } from 'n8n-workflow';
+import { VersionedNodeType } from 'n8n-workflow';
+
+import { AgentToolV2 } from './V2/AgentToolV2.node';
+
+export class AgentTool extends VersionedNodeType {
+	constructor() {
+		const baseDescription: INodeTypeBaseDescription = {
+			displayName: 'AI Agent Tool',
+			name: 'agentTool',
+			icon: 'fa:robot',
+			iconColor: 'black',
+			group: ['transform'],
+			description: 'Generates an action plan and executes it. Can use external tools.',
+			codex: {
+				alias: ['LangChain', 'Chat', 'Conversational', 'Plan and Execute', 'ReAct', 'Tools'],
+				categories: ['AI'],
+				subcategories: {
+					AI: ['Tools'],
+					Tools: ['Other Tools'],
+				},
+			},
+			defaultVersion: 2.2,
+		};
+
+		const nodeVersions: IVersionedNodeType['nodeVersions'] = {
+			// Should have the same versioning as Agent node
+			// because internal agent logic often checks for node version
+			2.2: new AgentToolV2(baseDescription),
+		};
+
+		super(nodeVersions, baseDescription);
+	}
+}

packages/@n8n/nodes-langchain/nodes/agents/Agent/V2/AgentToolV2.node.ts

@@ -0,0 +1,90 @@
+import { NodeConnectionTypes } from 'n8n-workflow';
+import type {
+	IExecuteFunctions,
+	INodeExecutionData,
+	INodeType,
+	INodeTypeDescription,
+	INodeTypeBaseDescription,
+	ISupplyDataFunctions,
+} from 'n8n-workflow';
+
+import { textInput, toolDescription } from '@utils/descriptions';
+
+import { getInputs } from './utils';
+import { getToolsAgentProperties } from '../agents/ToolsAgent/V2/description';
+import { toolsAgentExecute } from '../agents/ToolsAgent/V2/execute';
+
+export class AgentToolV2 implements INodeType {
+	description: INodeTypeDescription;
+	constructor(baseDescription: INodeTypeBaseDescription) {
+		this.description = {
+			...baseDescription,
+			version: [2.2],
+			defaults: {
+				name: 'AI Agent Tool',
+				color: '#404040',
+			},
+			inputs: `={{
+				((hasOutputParser, needsFallback) => {
+					${getInputs.toString()};
+					return getInputs(false, hasOutputParser, needsFallback)
+				})($parameter.hasOutputParser === undefined || $parameter.hasOutputParser === true, $parameter.needsFallback !== undefined && $parameter.needsFallback === true)
+			}}`,
+			outputs: [NodeConnectionTypes.AiTool],
+			properties: [
+				toolDescription,
+				{
+					...textInput,
+				},
+				{
+					displayName: 'Require Specific Output Format',
+					name: 'hasOutputParser',
+					type: 'boolean',
+					default: false,
+					noDataExpression: true,
+				},
+				{
+					displayName: `Connect an <a data-action='openSelectiveNodeCreator' data-action-parameter-connectiontype='${NodeConnectionTypes.AiOutputParser}'>output parser</a> on the canvas to specify the output format you require`,
+					name: 'notice',
+					type: 'notice',
+					default: '',
+					displayOptions: {
+						show: {
+							hasOutputParser: [true],
+						},
+					},
+				},
+				{
+					displayName: 'Enable Fallback Model',
+					name: 'needsFallback',
+					type: 'boolean',
+					default: false,
+					noDataExpression: true,
+					displayOptions: {
+						show: {
+							'@version': [{ _cnd: { gte: 2.1 } }],
+						},
+					},
+				},
+				{
+					displayName:
+						'Connect an additional language model on the canvas to use it as a fallback if the main model fails',
+					name: 'fallbackNotice',
+					type: 'notice',
+					default: '',
+					displayOptions: {
+						show: {
+							needsFallback: [true],
+						},
+					},
+				},
+				...getToolsAgentProperties({ withStreaming: false }),
+			],
+		};
+	}
+
+	// Automatically wrapped as a tool
+	async execute(this: IExecuteFunctions | ISupplyDataFunctions): Promise<INodeExecutionData[][]> {
+		return await toolsAgentExecute.call(this);
+	}
+}

packages/@n8n/nodes-langchain/nodes/agents/Agent/V2/AgentV2.node.ts

@@ -1,104 +1,18 @@
 import { NodeConnectionTypes } from 'n8n-workflow';
 import type {
-	INodeInputConfiguration,
-	INodeInputFilter,
 	IExecuteFunctions,
 	INodeExecutionData,
 	INodeType,
 	INodeTypeDescription,
-	NodeConnectionType,
 	INodeTypeBaseDescription,
 } from 'n8n-workflow';
 
 import { promptTypeOptions, textFromPreviousNode, textInput } from '@utils/descriptions';
 
-import { toolsAgentProperties } from '../agents/ToolsAgent/V2/description';
+import { getInputs } from './utils';
+import { getToolsAgentProperties } from '../agents/ToolsAgent/V2/description';
 import { toolsAgentExecute } from '../agents/ToolsAgent/V2/execute';
 
-// Function used in the inputs expression to figure out which inputs to
-// display based on the agent type
-function getInputs(
-	hasOutputParser?: boolean,
-	needsFallback?: boolean,
-): Array<NodeConnectionType | INodeInputConfiguration> {
-	interface SpecialInput {
-		type: NodeConnectionType;
-		filter?: INodeInputFilter;
-		displayName: string;
-		required?: boolean;
-	}
-
-	const getInputData = (
-		inputs: SpecialInput[],
-	): Array<NodeConnectionType | INodeInputConfiguration> => {
-		return inputs.map(({ type, filter, displayName, required }) => {
-			const input: INodeInputConfiguration = {
-				type,
-				displayName,
-				required,
-				maxConnections: ['ai_languageModel', 'ai_memory', 'ai_outputParser'].includes(type)
-					? 1
-					: undefined,
-			};
-
-			if (filter) {
-				input.filter = filter;
-			}
-
-			return input;
-		});
-	};
-
-	let specialInputs: SpecialInput[] = [
-		{
-			type: 'ai_languageModel',
-			displayName: 'Chat Model',
-			required: true,
-			filter: {
-				excludedNodes: [
-					'@n8n/n8n-nodes-langchain.lmCohere',
-					'@n8n/n8n-nodes-langchain.lmOllama',
-					'n8n/n8n-nodes-langchain.lmOpenAi',
-					'@n8n/n8n-nodes-langchain.lmOpenHuggingFaceInference',
-				],
-			},
-		},
-		{
-			type: 'ai_languageModel',
-			displayName: 'Fallback Model',
-			required: true,
-			filter: {
-				excludedNodes: [
-					'@n8n/n8n-nodes-langchain.lmCohere',
-					'@n8n/n8n-nodes-langchain.lmOllama',
-					'n8n/n8n-nodes-langchain.lmOpenAi',
-					'@n8n/n8n-nodes-langchain.lmOpenHuggingFaceInference',
-				],
-			},
-		},
-		{
-			displayName: 'Memory',
-			type: 'ai_memory',
-		},
-		{
-			displayName: 'Tool',
-			type: 'ai_tool',
-		},
-		{
-			displayName: 'Output Parser',
-			type: 'ai_outputParser',
-		},
-	];
-
-	if (hasOutputParser === false) {
-		specialInputs = specialInputs.filter((input) => input.type !== 'ai_outputParser');
-	}
-	if (needsFallback === false) {
-		specialInputs = specialInputs.filter((input) => input.displayName !== 'Fallback Model');
-	}
-	return ['main', ...getInputData(specialInputs)];
-}
-
 export class AgentV2 implements INodeType {
 	description: INodeTypeDescription;
 
@@ -113,7 +27,7 @@ export class AgentV2 implements INodeType {
 			inputs: `={{
 				((hasOutputParser, needsFallback) => {
 					${getInputs.toString()};
-					return getInputs(hasOutputParser, needsFallback)
+					return getInputs(true, hasOutputParser, needsFallback);
 				})($parameter.hasOutputParser === undefined || $parameter.hasOutputParser === true, $parameter.needsFallback !== undefined && $parameter.needsFallback === true)
 			}}`,
 			outputs: [NodeConnectionTypes.Main],
@@ -184,7 +98,7 @@ export class AgentV2 implements INodeType {
 						},
 					},
 				},
-				...toolsAgentProperties,
+				...getToolsAgentProperties({ withStreaming: true }),
 			],
 			hints: [
 				{

packages/@n8n/nodes-langchain/nodes/agents/Agent/V2/utils.ts

@@ -0,0 +1,95 @@
+// Function used in the inputs expression to figure out which inputs to
+
+import {
+	type INodeInputConfiguration,
+	type INodeInputFilter,
+	type NodeConnectionType,
+} from 'n8n-workflow';
+
+// display based on the agent type
+export function getInputs(
+	hasMainInput?: boolean,
+	hasOutputParser?: boolean,
+	needsFallback?: boolean,
+): Array<NodeConnectionType | INodeInputConfiguration> {
+	interface SpecialInput {
+		type: NodeConnectionType;
+		filter?: INodeInputFilter;
+		displayName: string;
+		required?: boolean;
+	}
+
+	const getInputData = (
+		inputs: SpecialInput[],
+	): Array<NodeConnectionType | INodeInputConfiguration> => {
+		return inputs.map(({ type, filter, displayName, required }) => {
+			const input: INodeInputConfiguration = {
+				type,
+				displayName,
+				required,
+				maxConnections: ['ai_languageModel', 'ai_memory', 'ai_outputParser'].includes(type)
+					? 1
+					: undefined,
+			};
+
+			if (filter) {
+				input.filter = filter;
+			}
+
+			return input;
+		});
+	};
+
+	let specialInputs: SpecialInput[] = [
+		{
+			type: 'ai_languageModel',
+			displayName: 'Chat Model',
+			required: true,
+			filter: {
+				excludedNodes: [
+					'@n8n/n8n-nodes-langchain.lmCohere',
+					'@n8n/n8n-nodes-langchain.lmOllama',
+					'n8n/n8n-nodes-langchain.lmOpenAi',
+					'@n8n/n8n-nodes-langchain.lmOpenHuggingFaceInference',
+				],
+			},
+		},
+		{
+			type: 'ai_languageModel',
+			displayName: 'Fallback Model',
+			required: true,
+			filter: {
+				excludedNodes: [
+					'@n8n/n8n-nodes-langchain.lmCohere',
+					'@n8n/n8n-nodes-langchain.lmOllama',
+					'n8n/n8n-nodes-langchain.lmOpenAi',
+					'@n8n/n8n-nodes-langchain.lmOpenHuggingFaceInference',
+				],
+			},
+		},
+		{
+			displayName: 'Memory',
+			type: 'ai_memory',
+		},
+		{
+			displayName: 'Tool',
+			type: 'ai_tool',
+		},
+		{
+			displayName: 'Output Parser',
+			type: 'ai_outputParser',
+		},
+	];
+
+	if (hasOutputParser === false) {
+		specialInputs = specialInputs.filter((input) => input.type !== 'ai_outputParser');
+	}
+	if (needsFallback === false) {
+		specialInputs = specialInputs.filter((input) => input.displayName !== 'Fallback Model');
+	}
+
+	// Note cannot use NodeConnectionType.Main
+	// otherwise expression won't evaluate correctly on the FE
+	const mainInputs = hasMainInput ? ['main' as NodeConnectionType] : [];
+	return [...mainInputs, ...getInputData(specialInputs)];
+}

packages/@n8n/nodes-langchain/nodes/agents/Agent/agents/ToolsAgent/V2/description.ts

@@ -4,7 +4,17 @@ import { getBatchingOptionFields } from '@utils/sharedFields';
 
 import { commonOptions } from '../options';
 
-export const toolsAgentProperties: INodeProperties[] = [
+const enableStreaminOption: INodeProperties = {
+	displayName: 'Enable Streaming',
+	name: 'enableStreaming',
+	type: 'boolean',
+	default: true,
+	description: 'Whether this agent will stream the response in real-time as it generates text',
+};
+
+export const getToolsAgentProperties = ({
+	withStreaming,
+}: { withStreaming: boolean }): INodeProperties[] => [
 	{
 		displayName: 'Options',
 		name: 'options',
@@ -14,14 +24,7 @@ export const toolsAgentProperties: INodeProperties[] = [
 		options: [
 			...commonOptions,
 			getBatchingOptionFields(undefined, 1),
-			{
+			...(withStreaming ? [enableStreaminOption] : []),
-				displayName: 'Enable Streaming',
-				name: 'enableStreaming',
-				type: 'boolean',
-				default: true,
-				description:
-					'Whether this agent will stream the response in real-time as it generates text',
-			},
 		],
 		displayOptions: {
 			hide: {

packages/@n8n/nodes-langchain/nodes/agents/Agent/agents/ToolsAgent/V2/execute.ts

@@ -13,7 +13,7 @@ import type { BaseChatMemory } from 'langchain/memory';
 import type { DynamicStructuredTool, Tool } from 'langchain/tools';
 import omit from 'lodash/omit';
 import { jsonParse, NodeOperationError, sleep } from 'n8n-workflow';
-import type { IExecuteFunctions, INodeExecutionData } from 'n8n-workflow';
+import type { IExecuteFunctions, INodeExecutionData, ISupplyDataFunctions } from 'n8n-workflow';
 import assert from 'node:assert';
 
 import { getPromptInputByType } from '@utils/helpers';
@@ -167,9 +167,13 @@ async function processEventStream(
  * creates the agent, and processes each input item. The error handling for each item is also
  * managed here based on the node's continueOnFail setting.
  *
+ * @param this Execute context. SupplyDataContext is passed when agent is as a tool
+ *
  * @returns The array of execution data for all processed items
  */
-export async function toolsAgentExecute(this: IExecuteFunctions): Promise<INodeExecutionData[][]> {
+export async function toolsAgentExecute(
+	this: IExecuteFunctions | ISupplyDataFunctions,
+): Promise<INodeExecutionData[][]> {
 	this.logger.debug('Executing Tools Agent V2');
 
 	const returnData: INodeExecutionData[] = [];
@@ -247,9 +251,14 @@ export async function toolsAgentExecute(this: IExecuteFunctions): Promise<INodeE
 			const executeOptions = { signal: this.getExecutionCancelSignal() };
 
 			// Check if streaming is actually available
-			const isStreamingAvailable = this.isStreaming();
+			const isStreamingAvailable = 'isStreaming' in this ? this.isStreaming?.() : undefined;
 
-			if (enableStreaming && isStreamingAvailable && this.getNode().typeVersion >= 2.1) {
+			if (
+				'isStreaming' in this &&
+				enableStreaming &&
+				isStreamingAvailable &&
+				this.getNode().typeVersion >= 2.1
+			) {
 				const chatHistory = await memory?.chatHistory.getMessages();
 				const eventStream = executor.streamEvents(
 					{

packages/@n8n/nodes-langchain/nodes/agents/Agent/agents/ToolsAgent/common.ts

@@ -7,7 +7,7 @@ import type { ToolsAgentAction } from 'langchain/dist/agents/tool_calling/output
 import type { BaseChatMemory } from 'langchain/memory';
 import { DynamicStructuredTool, type Tool } from 'langchain/tools';
 import { BINARY_ENCODING, jsonParse, NodeConnectionTypes, NodeOperationError } from 'n8n-workflow';
-import type { IExecuteFunctions } from 'n8n-workflow';
+import type { IExecuteFunctions, ISupplyDataFunctions } from 'n8n-workflow';
 import type { ZodObject } from 'zod';
 import { z } from 'zod';
 
@@ -42,7 +42,7 @@ export function getOutputParserSchema(
  * @returns A HumanMessage containing the binary image messages.
  */
 export async function extractBinaryMessages(
-	ctx: IExecuteFunctions,
+	ctx: IExecuteFunctions | ISupplyDataFunctions,
 	itemIndex: number,
 ): Promise<HumanMessage> {
 	const binaryData = ctx.getInputData()?.[itemIndex]?.binary ?? {};
@@ -263,7 +263,7 @@ export const getAgentStepsParser =
  * @returns The validated chat model
  */
 export async function getChatModel(
-	ctx: IExecuteFunctions,
+	ctx: IExecuteFunctions | ISupplyDataFunctions,
 	index: number = 0,
 ): Promise<BaseChatModel | undefined> {
 	const connectedModels = await ctx.getInputConnectionData(NodeConnectionTypes.AiLanguageModel, 0);
@@ -297,7 +297,7 @@ export async function getChatModel(
  * @returns The connected memory (if any)
  */
 export async function getOptionalMemory(
-	ctx: IExecuteFunctions,
+	ctx: IExecuteFunctions | ISupplyDataFunctions,
 ): Promise<BaseChatMemory | undefined> {
 	return (await ctx.getInputConnectionData(NodeConnectionTypes.AiMemory, 0)) as
 		| BaseChatMemory
@@ -313,7 +313,7 @@ export async function getOptionalMemory(
  * @returns The array of connected tools
  */
 export async function getTools(
-	ctx: IExecuteFunctions,
+	ctx: IExecuteFunctions | ISupplyDataFunctions,
 	outputParser?: N8nOutputParser,
 ): Promise<Array<DynamicStructuredTool | Tool>> {
 	const tools = (await getConnectedTools(ctx, true, false)) as Array<DynamicStructuredTool | Tool>;
@@ -343,7 +343,7 @@ export async function getTools(
  * @returns The array of prompt messages
  */
 export async function prepareMessages(
-	ctx: IExecuteFunctions,
+	ctx: IExecuteFunctions | ISupplyDataFunctions,
 	itemIndex: number,
 	options: {
 		systemMessage?: string;

packages/@n8n/nodes-langchain/nodes/agents/Agent/test/ToolsAgent/ToolsAgentV2.test.ts

@@ -2,7 +2,7 @@ import type { BaseChatModel } from '@langchain/core/language_models/chat_models'
 import { mock } from 'jest-mock-extended';
 import { AgentExecutor } from 'langchain/agents';
 import type { Tool } from 'langchain/tools';
-import type { IExecuteFunctions, INode } from 'n8n-workflow';
+import type { ISupplyDataFunctions, IExecuteFunctions, INode } from 'n8n-workflow';
 
 import * as helpers from '../../../../../utils/helpers';
 import * as outputParserModule from '../../../../../utils/output_parsers/N8nOutputParser';
@@ -620,4 +620,60 @@ describe('toolsAgentExecute', () => {
 			expect(result[0][0].json.output).toBe('Regular response');
 		});
 	});
+
+	it('should process items if SupplyDataContext is passed and isStreaming is not set', async () => {
+		const mockSupplyDataContext = mock<ISupplyDataFunctions>();
+
+		// @ts-expect-error isStreaming is not supported by SupplyDataFunctions, but mock object still resolves it
+		mockSupplyDataContext.isStreaming = undefined;
+
+		mockSupplyDataContext.logger = {
+			debug: jest.fn(),
+			info: jest.fn(),
+			warn: jest.fn(),
+			error: jest.fn(),
+		};
+
+		const mockNode = mock<INode>();
+		mockNode.typeVersion = 2.2; // version where streaming is supported
+		mockSupplyDataContext.getNode.mockReturnValue(mockNode);
+		mockSupplyDataContext.getInputData.mockReturnValue([{ json: { text: 'test input 1' } }]);
+
+		const mockModel = mock<BaseChatModel>();
+		mockModel.bindTools = jest.fn();
+		mockModel.lc_namespace = ['chat_models'];
+		mockSupplyDataContext.getInputConnectionData.mockResolvedValue(mockModel);
+
+		const mockTools = [mock<Tool>()];
+		jest.spyOn(helpers, 'getConnectedTools').mockResolvedValue(mockTools);
+
+		// Mock getNodeParameter to return default values
+		mockSupplyDataContext.getNodeParameter.mockImplementation((param, _i, defaultValue) => {
+			if (param === 'enableStreaming') return true;
+			if (param === 'text') return 'test input';
+			if (param === 'needsFallback') return false;
+			if (param === 'options.batching.batchSize') return defaultValue;
+			if (param === 'options.batching.delayBetweenBatches') return defaultValue;
+			if (param === 'options')
+				return {
+					systemMessage: 'You are a helpful assistant',
+					maxIterations: 10,
+					returnIntermediateSteps: false,
+					passthroughBinaryImages: true,
+				};
+			return defaultValue;
+		});
+
+		const mockExecutor = {
+			invoke: jest.fn().mockResolvedValueOnce({ output: { text: 'success 1' } }),
+		};
+
+		jest.spyOn(AgentExecutor, 'fromAgentAndTools').mockReturnValue(mockExecutor as any);
+
+		const result = await toolsAgentExecute.call(mockSupplyDataContext);
+
+		expect(mockExecutor.invoke).toHaveBeenCalledTimes(1);
+		expect(result[0]).toHaveLength(1);
+		expect(result[0][0].json).toEqual({ output: { text: 'success 1' } });
+	});
 });

packages/@n8n/nodes-langchain/nodes/agents/Agent/test/utils.test.ts

@@ -6,6 +6,7 @@ import { z } from 'zod';
 
 import type { ZodObjectAny } from '../../../../types/types';
 import { checkForStructuredTools } from '../agents/utils';
+import { getInputs } from '../V2/utils';
 
 describe('checkForStructuredTools', () => {
 	let mockNode: INode;
@@ -105,3 +106,172 @@ describe('checkForStructuredTools', () => {
 		});
 	});
 });
+
+describe('getInputs', () => {
+	it('should include all inputs when no flags are set to false', () => {
+		const inputs = getInputs(true, true, true);
+		expect(inputs).toEqual([
+			'main',
+			{
+				type: 'ai_languageModel',
+				displayName: 'Chat Model',
+				required: true,
+				maxConnections: 1,
+				filter: {
+					excludedNodes: [
+						'@n8n/n8n-nodes-langchain.lmCohere',
+						'@n8n/n8n-nodes-langchain.lmOllama',
+						'n8n/n8n-nodes-langchain.lmOpenAi',
+						'@n8n/n8n-nodes-langchain.lmOpenHuggingFaceInference',
+					],
+				},
+			},
+			{
+				type: 'ai_languageModel',
+				displayName: 'Fallback Model',
+				required: true,
+				maxConnections: 1,
+				filter: {
+					excludedNodes: [
+						'@n8n/n8n-nodes-langchain.lmCohere',
+						'@n8n/n8n-nodes-langchain.lmOllama',
+						'n8n/n8n-nodes-langchain.lmOpenAi',
+						'@n8n/n8n-nodes-langchain.lmOpenHuggingFaceInference',
+					],
+				},
+			},
+			{
+				type: 'ai_memory',
+				displayName: 'Memory',
+				maxConnections: 1,
+			},
+			{
+				type: 'ai_tool',
+				displayName: 'Tool',
+			},
+			{
+				type: 'ai_outputParser',
+				displayName: 'Output Parser',
+				maxConnections: 1,
+			},
+		]);
+	});
+
+	it('should exclude Output Parser when hasOutputParser is false', () => {
+		const inputs = getInputs(true, false, true);
+		expect(inputs).toEqual([
+			'main',
+			{
+				type: 'ai_languageModel',
+				displayName: 'Chat Model',
+				required: true,
+				maxConnections: 1,
+				filter: {
+					excludedNodes: [
+						'@n8n/n8n-nodes-langchain.lmCohere',
+						'@n8n/n8n-nodes-langchain.lmOllama',
+						'n8n/n8n-nodes-langchain.lmOpenAi',
+						'@n8n/n8n-nodes-langchain.lmOpenHuggingFaceInference',
+					],
+				},
+			},
+			{
+				type: 'ai_languageModel',
+				displayName: 'Fallback Model',
+				required: true,
+				maxConnections: 1,
+				filter: {
+					excludedNodes: [
+						'@n8n/n8n-nodes-langchain.lmCohere',
+						'@n8n/n8n-nodes-langchain.lmOllama',
+						'n8n/n8n-nodes-langchain.lmOpenAi',
+						'@n8n/n8n-nodes-langchain.lmOpenHuggingFaceInference',
+					],
+				},
+			},
+			{
+				type: 'ai_memory',
+				displayName: 'Memory',
+				maxConnections: 1,
+			},
+			{
+				type: 'ai_tool',
+				displayName: 'Tool',
+			},
+		]);
+	});
+
+	it('should exclude Fallback Model when needsFallback is false', () => {
+		const inputs = getInputs(true, true, false);
+		expect(inputs).toEqual([
+			'main',
+			{
+				type: 'ai_languageModel',
+				displayName: 'Chat Model',
+				required: true,
+				maxConnections: 1,
+				filter: {
+					excludedNodes: [
+						'@n8n/n8n-nodes-langchain.lmCohere',
+						'@n8n/n8n-nodes-langchain.lmOllama',
+						'n8n/n8n-nodes-langchain.lmOpenAi',
+						'@n8n/n8n-nodes-langchain.lmOpenHuggingFaceInference',
+					],
+				},
+			},
+			{
+				type: 'ai_memory',
+				displayName: 'Memory',
+				maxConnections: 1,
+			},
+			{
+				type: 'ai_tool',
+				displayName: 'Tool',
+			},
+			{
+				type: 'ai_outputParser',
+				displayName: 'Output Parser',
+				maxConnections: 1,
+			},
+		]);
+	});
+
+	it('should include main input when hasMainInput is true', () => {
+		const inputs = getInputs(true, true, true);
+		expect(inputs[0]).toBe('main');
+	});
+
+	it('should exclude main input when hasMainInput is false', () => {
+		const inputs = getInputs(false, true, true);
+		expect(inputs).not.toContain('main');
+	});
+
+	it('should handle all flags set to false', () => {
+		const inputs = getInputs(false, false, false);
+		expect(inputs).toEqual([
+			{
+				type: 'ai_languageModel',
+				displayName: 'Chat Model',
+				required: true,
+				maxConnections: 1,
+				filter: {
+					excludedNodes: [
+						'@n8n/n8n-nodes-langchain.lmCohere',
+						'@n8n/n8n-nodes-langchain.lmOllama',
+						'n8n/n8n-nodes-langchain.lmOpenAi',
+						'@n8n/n8n-nodes-langchain.lmOpenHuggingFaceInference',
+					],
+				},
+			},
+			{
+				type: 'ai_memory',
+				displayName: 'Memory',
+				maxConnections: 1,
+			},
+			{
+				type: 'ai_tool',
+				displayName: 'Tool',
+			},
+		]);
+	});
+});

packages/@n8n/nodes-langchain/package.json

@@ -50,6 +50,7 @@
     "nodes": [
       "dist/nodes/vendors/OpenAi/OpenAi.node.js",
       "dist/nodes/agents/Agent/Agent.node.js",
+      "dist/nodes/agents/Agent/AgentTool.node.js",
       "dist/nodes/agents/OpenAiAssistant/OpenAiAssistant.node.js",
       "dist/nodes/chains/ChainSummarization/ChainSummarization.node.js",
       "dist/nodes/chains/ChainLLM/ChainLlm.node.js",

packages/@n8n/nodes-langchain/utils/descriptions.ts

@@ -143,3 +143,14 @@ export const textFromPreviousNode: INodeProperties = {
 	},
 	disabledOptions: { show: { promptType: ['auto'] } },
 };
+
+export const toolDescription: INodeProperties = {
+	displayName: 'Description',
+	name: 'toolDescription',
+	type: 'string',
+	default: 'AI Agent that can call other tools',
+	required: true,
+	typeOptions: { rows: 2 },
+	description:
+		'Explain to the LLM what this tool does, a good, specific description would allow LLMs to produce expected results much more often',
+};

packages/@n8n/nodes-langchain/utils/helpers.ts

@@ -75,16 +75,16 @@ export function isToolsInstance(model: unknown): model is Tool {
 }
 
 export function getPromptInputByType(options: {
-	ctx: IExecuteFunctions;
+	ctx: IExecuteFunctions | ISupplyDataFunctions;
 	i: number;
 	promptTypeKey: string;
 	inputKey: string;
 }) {
 	const { ctx, i, promptTypeKey, inputKey } = options;
-	const prompt = ctx.getNodeParameter(promptTypeKey, i) as string;
+	const promptType = ctx.getNodeParameter(promptTypeKey, i, 'define') as string;
 
 	let input;
-	if (prompt === 'auto') {
+	if (promptType === 'auto') {
 		input = ctx.evaluateExpression('{{ $json["chatInput"] }}', i) as string;
 	} else {
 		input = ctx.getNodeParameter(inputKey, i) as string;
@@ -186,7 +186,7 @@ export function escapeSingleCurlyBrackets(text?: string): string | undefined {
 }
 
 export const getConnectedTools = async (
-	ctx: IExecuteFunctions | IWebhookFunctions,
+	ctx: IExecuteFunctions | IWebhookFunctions | ISupplyDataFunctions,
 	enforceUniqueNames: boolean,
 	convertStructuredTool: boolean = true,
 	escapeCurlyBrackets: boolean = false,

packages/@n8n/nodes-langchain/utils/output_parsers/N8nOutputParser.ts

@@ -1,4 +1,4 @@
-import type { IExecuteFunctions } from 'n8n-workflow';
+import type { IExecuteFunctions, ISupplyDataFunctions } from 'n8n-workflow';
 import { NodeConnectionTypes } from 'n8n-workflow';
 
 import { N8nItemListOutputParser } from './N8nItemListOutputParser';
@@ -13,7 +13,7 @@ export type N8nOutputParser =
 export { N8nOutputFixingParser, N8nItemListOutputParser, N8nStructuredOutputParser };
 
 export async function getOptionalOutputParser(
-	ctx: IExecuteFunctions,
+	ctx: IExecuteFunctions | ISupplyDataFunctions,
 	index: number = 0,
 ): Promise<N8nOutputParser | undefined> {
 	let outputParser: N8nOutputParser | undefined;