fix(AI Agent Node): Fix tools agent when using memory and Anthropic models

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

@@ -1,20 +1,20 @@
 import { BINARY_ENCODING, NodeConnectionType, NodeOperationError } from 'n8n-workflow';
 import type { IExecuteFunctions, INodeExecutionData } from 'n8n-workflow';
 
-import type { AgentAction, AgentFinish, AgentStep } from 'langchain/agents';
+import type { AgentAction, AgentFinish } from 'langchain/agents';
 import { AgentExecutor, createToolCallingAgent } from 'langchain/agents';
 import type { BaseChatMemory } from '@langchain/community/memory/chat_memory';
 import type { BaseMessagePromptTemplateLike } from '@langchain/core/prompts';
 import { ChatPromptTemplate } from '@langchain/core/prompts';
 import { omit } from 'lodash';
 import type { Tool } from '@langchain/core/tools';
 import { DynamicStructuredTool } from '@langchain/core/tools';
-import { RunnableSequence } from '@langchain/core/runnables';
 import type { ZodObject } from 'zod';
 import { z } from 'zod';
 import type { BaseOutputParser, StructuredOutputParser } from '@langchain/core/output_parsers';
 import { OutputFixingParser } from 'langchain/output_parsers';
 import { HumanMessage } from '@langchain/core/messages';
+import { RunnableSequence } from '@langchain/core/runnables';
 import {
 	isChatInstance,
 	getPromptInputByType,
@@ -93,7 +93,43 @@ export async function toolsAgentExecute(this: IExecuteFunctions): Promise<INodeE
 	const tools = (await getConnectedTools(this, true, false)) as Array<DynamicStructuredTool | Tool>;
 	const outputParser = (await getOptionalOutputParsers(this))?.[0];
 	let structuredOutputParserTool: DynamicStructuredTool | undefined;
+	/**
+	 * Handles the agent text output and transforms it in case of multi-output.
+	 *
+	 * @param steps - The agent finish or agent action steps.
+	 * @returns The modified agent finish steps or the original steps.
+	 */
+	function handleAgentFinishOutput(steps: AgentFinish | AgentAction[]) {
+		// Check if the steps contain multiple outputs
+		type AgentMultiOutputFinish = AgentFinish & {
+			returnValues: { output: Array<{ text: string; type: string; index: number }> };
+		};
+		const agentFinishSteps = steps as AgentMultiOutputFinish | AgentFinish;
+
+		if (agentFinishSteps.returnValues) {
+			const isMultiOutput = Array.isArray(agentFinishSteps.returnValues?.output);
+			if (isMultiOutput) {
+				// Define the type for each item in the multi-output array
+				type MultiOutputItem = { index: number; type: string; text: string };
+				const multiOutputSteps = agentFinishSteps.returnValues.output as MultiOutputItem[];
+
+				// Check if all items in the multi-output array are of type 'text'
+				const isTextOnly = (multiOutputSteps ?? []).every((output) => output.type === 'text');
+
+				if (isTextOnly) {
+					// If all items are of type 'text', merge them into a single string
+					agentFinishSteps.returnValues.output = multiOutputSteps
+						.map((output) => output.text)
+						.join('\n')
+						.trim();
+				}
+				return agentFinishSteps;
+			}
+		}
 
+		// If the steps do not contain multiple outputs, return them as is
+		return steps;
+	}
 	async function agentStepsParser(
 		steps: AgentFinish | AgentAction[],
 	): Promise<AgentFinish | AgentAction[]> {
@@ -113,20 +149,7 @@ export async function toolsAgentExecute(this: IExecuteFunctions): Promise<INodeE
 			}
 		}
 
-		// If the steps are an AgentFinish and the outputParser is defined it must mean that the LLM didn't use `format_final_response` tool so we will parse the output manually
-		if (outputParser && typeof steps === 'object' && (steps as AgentFinish).returnValues) {
-			const finalResponse = (steps as AgentFinish).returnValues;
-			const returnValues = (await outputParser.parse(finalResponse as unknown as string)) as Record<
-				string,
-				unknown
-			>;
-
-			return {
-				returnValues,
-				log: 'Final response formatted',
-			};
-		}
-		return steps;
+		return handleAgentFinishOutput(steps);
 	}
 
 	if (outputParser) {
@@ -172,9 +195,7 @@ export async function toolsAgentExecute(this: IExecuteFunctions): Promise<INodeE
 	});
 	agent.streamRunnable = false;
 
-	const runnableAgent = RunnableSequence.from<{
-		steps: AgentStep[];
-	}>([agent, agentStepsParser]);
+	const runnableAgent = RunnableSequence.from([agent, agentStepsParser]);
 
 	const executor = AgentExecutor.fromAgentAndTools({
 		agent: runnableAgent,
@@ -196,7 +217,7 @@ export async function toolsAgentExecute(this: IExecuteFunctions): Promise<INodeE
 			});
 
 			if (input === undefined) {
-				throw new NodeOperationError(this.getNode(), 'The ‘text parameter is empty.');
+				throw new NodeOperationError(this.getNode(), 'The ‘text‘ parameter is empty.');
 			}
 
 			// OpenAI doesn't allow empty tools array so we will provide a more user-friendly error message

packages/@n8n/nodes-langchain/nodes/embeddings/EmbeddingsOllama/EmbeddingsOllama.node.ts

@@ -6,7 +6,7 @@ import {
 	type INodeTypeDescription,
 	type SupplyData,
 } from 'n8n-workflow';
-import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama';
+import { OllamaEmbeddings } from '@langchain/ollama';
 import { logWrapper } from '../../../utils/logWrapper';
 import { getConnectionHintNoticeField } from '../../../utils/sharedFields';
 import { ollamaDescription, ollamaModel } from '../../llms/LMOllama/description';

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

@@ -137,17 +137,17 @@
     "@google-cloud/resource-manager": "5.3.0",
     "@google/generative-ai": "0.11.4",
     "@huggingface/inference": "2.7.0",
-    "@langchain/anthropic": "0.2.9",
+    "@langchain/anthropic": "0.2.15",
     "@langchain/cohere": "0.0.10",
-    "@langchain/community": "0.2.20",
-    "@langchain/core": "0.2.18",
-    "@langchain/google-genai": "0.0.23",
-    "@langchain/google-vertexai": "0.0.21",
-    "@langchain/groq": "0.0.15",
-    "@langchain/mistralai": "0.0.27",
-    "@langchain/ollama": "^0.0.2",
-    "@langchain/openai": "0.2.5",
-    "@langchain/pinecone": "0.0.8",
+    "@langchain/groq": "0.0.17",
+    "@langchain/mistralai": "0.0.28",
+    "@langchain/community": "0.2.28",
+    "@langchain/core": "0.2.27",
+    "@langchain/google-genai": "0.0.26",
+    "@langchain/google-vertexai": "0.0.26",
+    "@langchain/ollama": "^0.0.4",
+    "@langchain/openai": "0.2.7",
+    "@langchain/pinecone": "0.0.9",
     "@langchain/qdrant": "^0.0.5",
     "@langchain/redis": "0.0.5",
     "@langchain/textsplitters": "0.0.3",
@@ -156,7 +156,7 @@
     "@n8n/vm2": "3.9.25",
     "@pinecone-database/pinecone": "3.0.0",
     "@qdrant/js-client-rest": "1.9.0",
-    "@supabase/supabase-js": "2.43.4",
+    "@supabase/supabase-js": "2.45.1",
     "@types/pg": "^8.11.6",
     "@xata.io/client": "0.28.4",
     "basic-auth": "catalog:",
@@ -169,12 +169,12 @@
     "html-to-text": "9.0.5",
     "jsdom": "^23.0.1",
     "json-schema-to-zod": "2.1.0",
-    "langchain": "0.2.11",
+    "langchain": "0.2.16",
     "lodash": "catalog:",
     "mammoth": "1.7.2",
     "n8n-nodes-base": "workspace:*",
     "n8n-workflow": "workspace:*",
-    "openai": "4.53.0",
+    "openai": "4.56.0",
     "pdf-parse": "1.1.1",
     "pg": "8.12.0",
     "redis": "4.6.12",

packages/workflow/package.json

@@ -29,7 +29,7 @@
     "dist/**/*"
   ],
   "devDependencies": {
-    "@langchain/core": "^0.2.18",
+    "@langchain/core": "^0.2.27",
     "@types/deep-equal": "^1.0.1",
     "@types/express": "catalog:",
     "@types/jmespath": "^0.15.0",