mirror of
https://github.com/Abdulazizzn/n8n-enterprise-unlocked.git
synced 2025-12-17 10:02:05 +00:00
fix(Sentiment Analysis Node): Fix problems with first sentiment output (#17233)
This commit is contained in:
Benjamin Schroth
@@ -0,0 +1,315 @@
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import type { BaseLanguageModel } from '@langchain/core/language_models/base';
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import { FakeListChatModel } from '@langchain/core/utils/testing';
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import { mock } from 'jest-mock-extended';
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import type { IExecuteFunctions, INode } from 'n8n-workflow';
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import { NodeOperationError } from 'n8n-workflow';
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import { SentimentAnalysis } from '../SentimentAnalysis.node';
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jest.mock('@utils/tracing', () => ({
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getTracingConfig: jest.fn().mockReturnValue({}),
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}));
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const createExecuteFunctionsMock = (
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parameters: any,
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fakeLlm: BaseLanguageModel,
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inputData = [{ json: { text: 'This is great!' } }],
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typeVersion = 1.1,
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) => {
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const mockExecuteFunctions = mock<IExecuteFunctions>();
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mockExecuteFunctions.getInputData.mockReturnValue(inputData);
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mockExecuteFunctions.getNode.mockReturnValue({
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name: 'Sentiment Analysis',
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typeVersion,
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parameters: {},
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} as INode);
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mockExecuteFunctions.getNodeParameter.mockImplementation((param, itemIndex, defaultValue) => {
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if (param === 'inputText') {
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return parameters.inputText || inputData[itemIndex]?.json?.text || 'Test text';
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}
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if (param === 'options.categories') {
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return parameters.categories || 'Positive, Neutral, Negative';
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}
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if (param === 'options') {
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return {
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systemPromptTemplate: parameters.systemPromptTemplate,
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includeDetailedResults: parameters.includeDetailedResults || false,
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enableAutoFixing:
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parameters.enableAutoFixing !== undefined ? parameters.enableAutoFixing : true,
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};
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}
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if (param === 'options.batching.batchSize') {
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return parameters.batchSize || 5;
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}
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if (param === 'options.batching.delayBetweenBatches') {
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return parameters.delayBetweenBatches || 0;
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}
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return defaultValue;
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});
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mockExecuteFunctions.getInputConnectionData.mockResolvedValue(fakeLlm);
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mockExecuteFunctions.continueOnFail.mockReturnValue(false);
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mockExecuteFunctions.helpers = {
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constructExecutionMetaData: jest.fn().mockImplementation((data, options) => {
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return data.map((item: any) => ({
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...item,
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pairedItem: { item: options?.itemData?.item || 0 },
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}));
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}),
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returnJsonArray: jest.fn().mockImplementation((data) => [{ json: data }]),
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} as any;
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return mockExecuteFunctions;
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};
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describe('SentimentAnalysis Node', () => {
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let node: SentimentAnalysis;
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beforeEach(() => {
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node = new SentimentAnalysis();
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jest.clearAllMocks();
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});
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describe('execute - basic functionality', () => {
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it('should analyze sentiment with default categories', async () => {
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const mockExecuteFunctions = createExecuteFunctionsMock(
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{ inputText: 'I love this product!' },
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new FakeListChatModel({
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responses: ['{"sentiment": "Positive", "strength": 0.9, "confidence": 0.95}'],
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}),
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);
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const result = await node.execute.call(mockExecuteFunctions);
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expect(result).toHaveLength(3); // 3 default categories
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expect(result[0]).toHaveLength(1); // Item goes to Positive category
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expect(result[0][0].json.sentimentAnalysis).toEqual({
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category: 'Positive',
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});
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});
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it('should analyze sentiment with custom categories', async () => {
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const mockExecuteFunctions = createExecuteFunctionsMock(
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{
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inputText: 'This is terrible!',
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categories: 'Happy, Sad, Angry',
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},
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new FakeListChatModel({
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responses: ['{"sentiment": "Angry", "strength": 0.8, "confidence": 0.9}'],
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}),
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);
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const result = await node.execute.call(mockExecuteFunctions);
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expect(result).toHaveLength(3); // 3 custom categories
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expect(result[2]).toHaveLength(1); // Item goes to Angry category (index 2)
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expect(result[2][0].json.sentimentAnalysis).toEqual({
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category: 'Angry',
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});
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});
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it('should include detailed results when enabled', async () => {
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const mockExecuteFunctions = createExecuteFunctionsMock(
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{
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inputText: 'I love this!',
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includeDetailedResults: true,
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},
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new FakeListChatModel({
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responses: ['{"sentiment": "Positive", "strength": 0.9, "confidence": 0.95}'],
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}),
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);
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const result = await node.execute.call(mockExecuteFunctions);
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expect(result[0][0].json.sentimentAnalysis).toEqual({
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category: 'Positive',
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strength: 0.9,
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confidence: 0.95,
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});
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});
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it('should handle multiple input items', async () => {
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const inputData = [
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{ json: { text: 'I love this!' } },
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{ json: { text: 'This is okay.' } },
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{ json: { text: 'I hate this!' } },
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];
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const mockExecuteFunctions = createExecuteFunctionsMock(
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{ inputText: '{{$json.text}}' },
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new FakeListChatModel({
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responses: [
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'{"sentiment": "Positive", "strength": 0.9, "confidence": 0.95}',
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'{"sentiment": "Neutral", "strength": 0.5, "confidence": 0.8}',
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'{"sentiment": "Negative", "strength": 0.9, "confidence": 0.9}',
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],
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}),
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inputData,
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);
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const result = await node.execute.call(mockExecuteFunctions);
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expect(result[0]).toHaveLength(1); // Positive
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expect(result[1]).toHaveLength(1); // Neutral
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expect(result[2]).toHaveLength(1); // Negative
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});
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});
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describe('execute - error handling', () => {
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it('should throw error when no categories provided', async () => {
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const mockExecuteFunctions = createExecuteFunctionsMock(
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{
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inputText: 'Test text',
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categories: '',
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},
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new FakeListChatModel({ responses: ['test'] }),
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);
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await expect(node.execute.call(mockExecuteFunctions)).rejects.toThrow(NodeOperationError);
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});
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it('should handle parsing errors with auto-fixing disabled', async () => {
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const mockExecuteFunctions = createExecuteFunctionsMock(
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{
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inputText: 'Test text',
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enableAutoFixing: false,
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},
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new FakeListChatModel({
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responses: ['Invalid JSON response'],
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}),
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);
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await expect(node.execute.call(mockExecuteFunctions)).rejects.toThrow(NodeOperationError);
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});
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it('should continue on failure when configured', async () => {
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const mockExecuteFunctions = createExecuteFunctionsMock(
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{
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inputText: 'Test text',
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enableAutoFixing: false,
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},
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new FakeListChatModel({
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responses: ['Invalid JSON response'],
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}),
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);
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mockExecuteFunctions.continueOnFail.mockReturnValue(true);
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const result = await node.execute.call(mockExecuteFunctions);
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expect(result[0]).toHaveLength(1);
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expect(result[0][0].json).toHaveProperty('error');
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});
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});
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describe('execute - batching (version 1.1+)', () => {
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it('should process items in batches with default settings', async () => {
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const inputData = [
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{ json: { text: 'Great!' } },
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{ json: { text: 'Okay.' } },
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{ json: { text: 'Bad!' } },
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];
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const mockExecuteFunctions = createExecuteFunctionsMock(
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{
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inputText: '{{$json.text}}',
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batchSize: 2,
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},
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new FakeListChatModel({
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responses: [
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'{"sentiment": "Positive", "strength": 0.9, "confidence": 0.95}',
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'{"sentiment": "Neutral", "strength": 0.5, "confidence": 0.8}',
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'{"sentiment": "Negative", "strength": 0.9, "confidence": 0.9}',
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],
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}),
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inputData,
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);
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const result = await node.execute.call(mockExecuteFunctions);
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expect(result[0]).toHaveLength(1); // Positive
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expect(result[1]).toHaveLength(1); // Neutral
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expect(result[2]).toHaveLength(1); // Negative
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});
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it('should handle errors in batch processing with continueOnFail', async () => {
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const inputData = [
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{ json: { text: 'Great!' } },
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{ json: { text: 'Invalid text' } },
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{ json: { text: 'Bad!' } },
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];
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const mockExecuteFunctions = createExecuteFunctionsMock(
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{
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inputText: '{{$json.text}}',
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batchSize: 2,
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enableAutoFixing: false,
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},
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new FakeListChatModel({
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responses: [
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'{"sentiment": "Positive", "strength": 0.9, "confidence": 0.95}',
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'Invalid JSON',
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'{"sentiment": "Negative", "strength": 0.9, "confidence": 0.9}',
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],
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}),
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inputData,
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);
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mockExecuteFunctions.continueOnFail.mockReturnValue(true);
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const result = await node.execute.call(mockExecuteFunctions);
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expect(result[0]).toHaveLength(2); // Positive and error item
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expect((result[0][0].json.sentimentAnalysis as any).category).toBe('Positive');
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expect(result[0][1].json).toHaveProperty('error');
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expect(result[2]).toHaveLength(1); // Negative
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});
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});
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describe('execute - sequential processing (version 1.0)', () => {
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it('should process items sequentially in older versions', async () => {
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const inputData = [{ json: { text: 'Great!' } }, { json: { text: 'Okay.' } }];
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const mockExecuteFunctions = createExecuteFunctionsMock(
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{ inputText: '{{$json.text}}' },
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new FakeListChatModel({
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responses: [
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'{"sentiment": "Positive", "strength": 0.9, "confidence": 0.95}',
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'{"sentiment": "Neutral", "strength": 0.5, "confidence": 0.8}',
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],
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}),
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inputData,
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1.0, // Older version
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);
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const result = await node.execute.call(mockExecuteFunctions);
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expect(result[0]).toHaveLength(1); // Positive
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expect(result[1]).toHaveLength(1); // Neutral
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});
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it('should handle errors in sequential processing', async () => {
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const mockExecuteFunctions = createExecuteFunctionsMock(
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{
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inputText: 'Test text',
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enableAutoFixing: false,
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},
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new FakeListChatModel({
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responses: ['Invalid JSON'],
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}),
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undefined,
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1.0,
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);
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mockExecuteFunctions.continueOnFail.mockReturnValue(true);
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const result = await node.execute.call(mockExecuteFunctions);
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expect(result[0]).toHaveLength(1);
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expect(result[0][0].json).toHaveProperty('error');
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});
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});
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});
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