feat(Sentiment Analysis Node): Implement Sentiment Analysis node

packages/@n8n/nodes-langchain/nodes/chains/SentimentAnalysis/SentimentAnalysis.node.ts

@@ -0,0 +1,230 @@
+import type {
+	IDataObject,
+	IExecuteFunctions,
+	INodeExecutionData,
+	INodeParameters,
+	INodeType,
+	INodeTypeDescription,
+} from 'n8n-workflow';
+
+import { NodeConnectionType } from 'n8n-workflow';
+
+import type { BaseLanguageModel } from '@langchain/core/language_models/base';
+import { HumanMessage } from '@langchain/core/messages';
+import { SystemMessagePromptTemplate, ChatPromptTemplate } from '@langchain/core/prompts';
+import { OutputFixingParser, StructuredOutputParser } from 'langchain/output_parsers';
+import { z } from 'zod';
+import { getTracingConfig } from '../../../utils/tracing';
+
+const DEFAULT_SYSTEM_PROMPT_TEMPLATE =
+	'You are highly intelligent and accurate sentiment analyzer. Analyze the sentiment of the provided text. Categorize it into one of the following: {categories}. Use the provided formatting instructions. Only output the JSON.';
+
+const DEFAULT_CATEGORIES = 'Positive, Neutral, Negative';
+const configuredOutputs = (parameters: INodeParameters, defaultCategories: string) => {
+	const options = (parameters?.options ?? {}) as IDataObject;
+	const categories = (options?.categories as string) ?? defaultCategories;
+	const categoriesArray = categories.split(',').map((cat) => cat.trim());
+
+	const ret = categoriesArray.map((cat) => ({ type: NodeConnectionType.Main, displayName: cat }));
+	return ret;
+};
+
+export class SentimentAnalysis implements INodeType {
+	description: INodeTypeDescription = {
+		displayName: 'Sentiment Analysis',
+		name: 'sentimentAnalysis',
+		icon: 'fa:balance-scale-left',
+		iconColor: 'black',
+		group: ['transform'],
+		version: 1,
+		description: 'Analyze the sentiment of your text',
+		codex: {
+			categories: ['AI'],
+			subcategories: {
+				AI: ['Chains', 'Root Nodes'],
+			},
+			resources: {
+				primaryDocumentation: [
+					{
+						url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainllm/',
+					},
+				],
+			},
+		},
+		defaults: {
+			name: 'Sentiment Analysis',
+		},
+		inputs: [
+			{ displayName: '', type: NodeConnectionType.Main },
+			{
+				displayName: 'Model',
+				maxConnections: 1,
+				type: NodeConnectionType.AiLanguageModel,
+				required: true,
+			},
+		],
+		outputs: `={{(${configuredOutputs})($parameter, "${DEFAULT_CATEGORIES}")}}`,
+		properties: [
+			{
+				displayName: 'Text to Analyze',
+				name: 'inputText',
+				type: 'string',
+				required: true,
+				default: '',
+				description: 'Use an expression to reference data in previous nodes or enter static text',
+				typeOptions: {
+					rows: 2,
+				},
+			},
+			{
+				displayName:
+					'Sentiment scores are LLM-generated estimates, not statistically rigorous measurements. They may be inconsistent across runs and should be used as rough indicators only.',
+				name: 'detailedResultsNotice',
+				type: 'notice',
+				default: '',
+				displayOptions: {
+					show: {
+						'/options.includeDetailedResults': [true],
+					},
+				},
+			},
+			{
+				displayName: 'Options',
+				name: 'options',
+				type: 'collection',
+				default: {},
+				placeholder: 'Add Option',
+				options: [
+					{
+						displayName: 'Sentiment Categories',
+						name: 'categories',
+						type: 'string',
+						default: DEFAULT_CATEGORIES,
+						description: 'A comma-separated list of categories to analyze',
+						noDataExpression: true,
+						typeOptions: {
+							rows: 2,
+						},
+					},
+					{
+						displayName: 'System Prompt Template',
+						name: 'systemPromptTemplate',
+						type: 'string',
+						default: DEFAULT_SYSTEM_PROMPT_TEMPLATE,
+						description: 'String to use directly as the system prompt template',
+						typeOptions: {
+							rows: 6,
+						},
+					},
+					{
+						displayName: 'Include Detailed Results',
+						name: 'includeDetailedResults',
+						type: 'boolean',
+						default: false,
+						description:
+							'Whether to include sentiment strength and confidence scores in the output',
+					},
+					{
+						displayName: 'Enable Auto-Fixing',
+						name: 'enableAutoFixing',
+						type: 'boolean',
+						default: true,
+						description: 'Whether to enable auto-fixing for the output parser',
+					},
+				],
+			},
+		],
+	};
+
+	async execute(this: IExecuteFunctions): Promise<INodeExecutionData[][]> {
+		const items = this.getInputData();
+
+		const llm = (await this.getInputConnectionData(
+			NodeConnectionType.AiLanguageModel,
+			0,
+		)) as BaseLanguageModel;
+
+		const returnData: INodeExecutionData[][] = [];
+
+		for (let itemIdx = 0; itemIdx < items.length; itemIdx++) {
+			const sentimentCategories = this.getNodeParameter(
+				'options.categories',
+				itemIdx,
+				DEFAULT_CATEGORIES,
+			) as string;
+
+			const categories = sentimentCategories.split(',').map((cat) => cat.trim());
+
+			// Initialize returnData with empty arrays for each category
+			if (returnData.length === 0) {
+				returnData.push(
+					...Array(categories.length)
+						.fill([])
+						.map(() => []),
+				);
+			}
+
+			const options = this.getNodeParameter('options', itemIdx, {}) as {
+				systemPromptTemplate?: string;
+				includeDetailedResults?: boolean;
+				enableAutoFixing?: boolean;
+			};
+
+			const schema = z.object({
+				sentiment: z.enum(categories as [string, ...string[]]),
+				strength: z
+					.number()
+					.min(0)
+					.max(1)
+					.describe('Strength score for sentiment in relation to the category'),
+				confidence: z.number().min(0).max(1),
+			});
+
+			const structuredParser = StructuredOutputParser.fromZodSchema(schema);
+
+			const parser = options.enableAutoFixing
+				? OutputFixingParser.fromLLM(llm, structuredParser)
+				: structuredParser;
+
+			const systemPromptTemplate = SystemMessagePromptTemplate.fromTemplate(
+				`${options.systemPromptTemplate ?? DEFAULT_SYSTEM_PROMPT_TEMPLATE}
+	{format_instructions}`,
+			);
+
+			const input = this.getNodeParameter('inputText', itemIdx) as string;
+			const inputPrompt = new HumanMessage(input);
+			const messages = [
+				await systemPromptTemplate.format({
+					categories: sentimentCategories,
+					format_instructions: parser.getFormatInstructions(),
+				}),
+				inputPrompt,
+			];
+
+			const prompt = ChatPromptTemplate.fromMessages(messages);
+			const chain = prompt.pipe(llm).pipe(parser).withConfig(getTracingConfig(this));
+
+			const output = await chain.invoke(messages);
+			const sentimentIndex = categories.findIndex(
+				(s) => s.toLowerCase() === output.sentiment.toLowerCase(),
+			);
+
+			if (sentimentIndex !== -1) {
+				const resultItem = { ...items[itemIdx] };
+				const sentimentAnalysis: IDataObject = {
+					category: output.sentiment,
+				};
+				if (options.includeDetailedResults) {
+					sentimentAnalysis.strength = output.strength;
+					sentimentAnalysis.confidence = output.confidence;
+				}
+				resultItem.json = {
+					...resultItem.json,
+					sentimentAnalysis,
+				};
+				returnData[sentimentIndex].push(resultItem);
+			}
+		}
+		return returnData;
+	}
+}

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

@@ -45,6 +45,7 @@
       "dist/nodes/chains/ChainSummarization/ChainSummarization.node.js",
       "dist/nodes/chains/ChainLLM/ChainLlm.node.js",
       "dist/nodes/chains/ChainRetrievalQA/ChainRetrievalQa.node.js",
+      "dist/nodes/chains/SentimentAnalysis/SentimentAnalysis.node.js",
       "dist/nodes/chains/TextClassifier/TextClassifier.node.js",
       "dist/nodes/code/Code.node.js",
       "dist/nodes/document_loaders/DocumentDefaultDataLoader/DocumentDefaultDataLoader.node.js",

packages/editor-ui/src/plugins/icons/index.ts

@@ -14,6 +14,7 @@ import {
 	faArrowDown,
 	faAt,
 	faBan,
+	faBalanceScaleLeft,
 	faBars,
 	faBolt,
 	faBook,
@@ -181,6 +182,7 @@ export const FontAwesomePlugin: Plugin = {
 		addIcon(faArrowDown);
 		addIcon(faAt);
 		addIcon(faBan);
+		addIcon(faBalanceScaleLeft);
 		addIcon(faBars);
 		addIcon(faBolt);
 		addIcon(faBook);