first commit

packages/@n8n/nodes-langchain/nodes/chains/InformationExtractor/test/InformationExtraction.node.test.ts

@@ -0,0 +1,420 @@
+import type { BaseLanguageModel } from '@langchain/core/language_models/base';
+import { FakeListChatModel } from '@langchain/core/utils/testing';
+import { mock } from 'jest-mock-extended';
+import get from 'lodash/get';
+import type { IDataObject, IExecuteFunctions, INode } from 'n8n-workflow';
+
+import { makeZodSchemaFromAttributes } from '../helpers';
+import { InformationExtractor } from '../InformationExtractor.node';
+import type { AttributeDefinition } from '../types';
+
+const mockPersonAttributes: AttributeDefinition[] = [
+	{
+		name: 'name',
+		type: 'string',
+		description: 'The name of the person',
+		required: false,
+	},
+	{
+		name: 'age',
+		type: 'number',
+		description: 'The age of the person',
+		required: false,
+	},
+];
+
+const mockPersonAttributesRequired: AttributeDefinition[] = [
+	{
+		name: 'name',
+		type: 'string',
+		description: 'The name of the person',
+		required: true,
+	},
+	{
+		name: 'age',
+		type: 'number',
+		description: 'The age of the person',
+		required: true,
+	},
+];
+
+function formatFakeLlmResponse(object: Record<string, any>) {
+	return `\`\`\`json\n${JSON.stringify(object, null, 2)}\n\`\`\``;
+}
+
+const createExecuteFunctionsMock = (
+	parameters: IDataObject,
+	fakeLlm: BaseLanguageModel,
+	inputData = [{ json: {} }],
+) => {
+	const nodeParameters = parameters;
+
+	return {
+		getNodeParameter(parameter: string) {
+			return get(nodeParameters, parameter);
+		},
+		getNode() {
+			return {
+				typeVersion: 1.1,
+			};
+		},
+		getInputConnectionData() {
+			return fakeLlm;
+		},
+		getInputData() {
+			return inputData;
+		},
+		getWorkflow() {
+			return {
+				name: 'Test Workflow',
+			};
+		},
+		getExecutionId() {
+			return 'test_execution_id';
+		},
+		continueOnFail() {
+			return false;
+		},
+	} as unknown as IExecuteFunctions;
+};
+
+describe('InformationExtractor', () => {
+	describe('Schema Generation', () => {
+		it('should generate a schema from attribute descriptions with optional fields', async () => {
+			const schema = makeZodSchemaFromAttributes(mockPersonAttributes);
+
+			expect(schema.parse({ name: 'John', age: 30 })).toEqual({ name: 'John', age: 30 });
+			expect(schema.parse({ name: 'John' })).toEqual({ name: 'John' });
+			expect(schema.parse({ age: 30 })).toEqual({ age: 30 });
+		});
+	});
+
+	describe('Single Item Processing with JSON Schema from Example', () => {
+		it('should extract information using JSON schema from example - version 1.2 (required fields)', async () => {
+			const node = new InformationExtractor();
+			const inputData = [
+				{
+					json: { text: 'John lives in California and has visited Los Angeles and San Francisco' },
+				},
+			];
+
+			const mockExecuteFunctions = createExecuteFunctionsMock(
+				{
+					text: 'John lives in California and has visited Los Angeles and San Francisco',
+					schemaType: 'fromJson',
+					jsonSchemaExample: JSON.stringify({
+						state: 'California',
+						cities: ['Los Angeles', 'San Francisco'],
+					}),
+					options: {
+						systemPromptTemplate: '',
+					},
+				},
+				new FakeListChatModel({
+					responses: [
+						formatFakeLlmResponse({
+							state: 'California',
+							cities: ['Los Angeles', 'San Francisco'],
+						}),
+					],
+				}),
+				inputData,
+			);
+
+			// Mock version 1.2 to test required fields behavior
+			mockExecuteFunctions.getNode = () => mock<INode>({ typeVersion: 1.2 });
+
+			const response = await node.execute.call(mockExecuteFunctions);
+
+			expect(response).toEqual([
+				[
+					{
+						json: {
+							output: {
+								state: 'California',
+								cities: ['Los Angeles', 'San Francisco'],
+							},
+						},
+					},
+				],
+			]);
+		});
+
+		it('should extract information using JSON schema from example - version 1.1 (optional fields)', async () => {
+			const node = new InformationExtractor();
+			const inputData = [{ json: { text: 'John lives in California' } }];
+
+			const mockExecuteFunctions = createExecuteFunctionsMock(
+				{
+					text: 'John lives in California',
+					schemaType: 'fromJson',
+					jsonSchemaExample: JSON.stringify({
+						state: 'California',
+						cities: ['Los Angeles', 'San Francisco'],
+					}),
+					options: {
+						systemPromptTemplate: '',
+					},
+				},
+				new FakeListChatModel({
+					responses: [
+						formatFakeLlmResponse({
+							state: 'California',
+							// cities field missing - should be allowed in v1.1
+						}),
+					],
+				}),
+				inputData,
+			);
+
+			// Mock version 1.1 to test optional fields behavior
+			mockExecuteFunctions.getNode = () => mock<INode>({ typeVersion: 1.1 });
+
+			const response = await node.execute.call(mockExecuteFunctions);
+
+			expect(response).toEqual([
+				[
+					{
+						json: {
+							output: {
+								state: 'California',
+							},
+						},
+					},
+				],
+			]);
+		});
+
+		it('should throw error for incomplete model output in version 1.2 (required fields)', async () => {
+			const node = new InformationExtractor();
+			const inputData = [{ json: { text: 'John lives in California' } }];
+
+			const mockExecuteFunctions = createExecuteFunctionsMock(
+				{
+					text: 'John lives in California',
+					schemaType: 'fromJson',
+					jsonSchemaExample: JSON.stringify({
+						state: 'California',
+						cities: ['Los Angeles', 'San Francisco'],
+						zipCode: '90210',
+					}),
+					options: {
+						systemPromptTemplate: '',
+					},
+				},
+				new FakeListChatModel({
+					responses: [
+						formatFakeLlmResponse({
+							state: 'California',
+							// Missing cities and zipCode - should fail in v1.2 since all fields are required
+						}),
+					],
+				}),
+				inputData,
+			);
+
+			mockExecuteFunctions.getNode = () => mock<INode>({ typeVersion: 1.2 });
+
+			await expect(node.execute.call(mockExecuteFunctions)).rejects.toThrow();
+		});
+
+		it('should extract information using complex nested JSON schema from example', async () => {
+			const node = new InformationExtractor();
+			const inputData = [
+				{
+					json: {
+						text: 'John Doe works at Acme Corp as a Software Engineer with 5 years experience',
+					},
+				},
+			];
+
+			const complexSchema = {
+				person: {
+					name: 'John Doe',
+					company: {
+						name: 'Acme Corp',
+						position: 'Software Engineer',
+					},
+				},
+				experience: {
+					years: 5,
+					skills: ['JavaScript', 'TypeScript'],
+				},
+			};
+
+			const mockExecuteFunctions = createExecuteFunctionsMock(
+				{
+					text: 'John Doe works at Acme Corp as a Software Engineer with 5 years experience',
+					schemaType: 'fromJson',
+					jsonSchemaExample: JSON.stringify(complexSchema),
+					options: {
+						systemPromptTemplate: '',
+					},
+				},
+				new FakeListChatModel({
+					responses: [
+						formatFakeLlmResponse({
+							person: {
+								name: 'John Doe',
+								company: {
+									name: 'Acme Corp',
+									position: 'Software Engineer',
+								},
+							},
+							experience: {
+								years: 5,
+								skills: ['JavaScript', 'TypeScript'],
+							},
+						}),
+					],
+				}),
+				inputData,
+			);
+
+			mockExecuteFunctions.getNode = () => mock<INode>({ typeVersion: 1.2 });
+
+			const response = await node.execute.call(mockExecuteFunctions);
+
+			expect(response[0][0].json.output).toMatchObject({
+				person: {
+					name: 'John Doe',
+					company: {
+						name: 'Acme Corp',
+						position: 'Software Engineer',
+					},
+				},
+				experience: {
+					years: 5,
+					skills: expect.arrayContaining(['JavaScript', 'TypeScript']),
+				},
+			});
+		});
+	});
+
+	describe('Batch Processing', () => {
+		it('should process multiple items in batches', async () => {
+			const node = new InformationExtractor();
+			const inputData = [
+				{ json: { text: 'John is 30 years old' } },
+				{ json: { text: 'Alice is 25 years old' } },
+				{ json: { text: 'Bob is 40 years old' } },
+			];
+
+			const response = await node.execute.call(
+				createExecuteFunctionsMock(
+					{
+						text: 'John is 30 years old',
+						attributes: {
+							attributes: mockPersonAttributes,
+						},
+						options: {
+							batching: {
+								batchSize: 2,
+								delayBetweenBatches: 0,
+							},
+						},
+						schemaType: 'fromAttributes',
+					},
+					new FakeListChatModel({
+						responses: [
+							formatFakeLlmResponse({ name: 'John', age: 30 }),
+							formatFakeLlmResponse({ name: 'Alice', age: 25 }),
+							formatFakeLlmResponse({ name: 'Bob', age: 40 }),
+						],
+					}),
+					inputData,
+				),
+			);
+
+			expect(response).toEqual([
+				[
+					{ json: { output: { name: 'John', age: 30 } } },
+					{ json: { output: { name: 'Alice', age: 25 } } },
+					{ json: { output: { name: 'Bob', age: 40 } } },
+				],
+			]);
+		});
+
+		it('should handle errors in batch processing', async () => {
+			const node = new InformationExtractor();
+			const inputData = [
+				{ json: { text: 'John is 30 years old' } },
+				{ json: { text: 'Invalid text' } },
+				{ json: { text: 'Bob is 40 years old' } },
+			];
+
+			const mockExecuteFunctions = createExecuteFunctionsMock(
+				{
+					text: 'John is 30 years old',
+					attributes: {
+						attributes: mockPersonAttributesRequired,
+					},
+					options: {
+						batching: {
+							batchSize: 2,
+							delayBetweenBatches: 0,
+						},
+					},
+					schemaType: 'fromAttributes',
+				},
+				new FakeListChatModel({
+					responses: [
+						formatFakeLlmResponse({ name: 'John', age: 30 }),
+						formatFakeLlmResponse({ name: 'Invalid' }), // Missing required age
+						formatFakeLlmResponse({ name: 'Invalid' }), // Missing required age on retry
+						formatFakeLlmResponse({ name: 'Bob', age: 40 }),
+					],
+				}),
+				inputData,
+			);
+
+			mockExecuteFunctions.continueOnFail = () => true;
+
+			const response = await node.execute.call(mockExecuteFunctions);
+
+			expect(response[0]).toHaveLength(3);
+			expect(response[0][0]).toEqual({ json: { output: { name: 'John', age: 30 } } });
+			expect(response[0][1]).toEqual({
+				json: { error: expect.stringContaining('Failed to parse') },
+				pairedItem: { item: 1 },
+			});
+			expect(response[0][2]).toEqual({ json: { output: { name: 'Bob', age: 40 } } });
+		});
+
+		it('should throw error if batch processing fails and continueOnFail is false', async () => {
+			const node = new InformationExtractor();
+			const inputData = [
+				{ json: { text: 'John is 30 years old' } },
+				{ json: { text: 'Invalid text' } },
+				{ json: { text: 'Bob is 40 years old' } },
+			];
+
+			const mockExecuteFunctions = createExecuteFunctionsMock(
+				{
+					text: 'John is 30 years old',
+					attributes: {
+						attributes: mockPersonAttributesRequired,
+					},
+					options: {
+						batching: {
+							batchSize: 2,
+							delayBetweenBatches: 0,
+						},
+					},
+					schemaType: 'fromAttributes',
+				},
+				new FakeListChatModel({
+					responses: [
+						formatFakeLlmResponse({ name: 'John', age: 30 }),
+						formatFakeLlmResponse({ name: 'Invalid' }), // Missing required age
+						formatFakeLlmResponse({ name: 'Invalid' }), // Missing required age on retry
+						formatFakeLlmResponse({ name: 'Bob', age: 40 }),
+					],
+				}),
+				inputData,
+			);
+
+			await expect(node.execute.call(mockExecuteFunctions)).rejects.toThrow('Failed to parse');
+		});
+	});
+});

packages/@n8n/nodes-langchain/nodes/chains/InformationExtractor/test/processItem.test.ts

@@ -0,0 +1,168 @@
+import { FakeLLM, FakeListChatModel } from '@langchain/core/utils/testing';
+import { OutputFixingParser, StructuredOutputParser } from '@langchain/classic/output_parsers';
+import { NodeOperationError } from 'n8n-workflow';
+
+import { makeZodSchemaFromAttributes } from '../helpers';
+import { processItem } from '../processItem';
+import type { AttributeDefinition } from '../types';
+
+jest.mock('@utils/tracing', () => ({
+	getTracingConfig: () => ({}),
+}));
+
+const mockPersonAttributes: AttributeDefinition[] = [
+	{
+		name: 'name',
+		type: 'string',
+		description: 'The name of the person',
+		required: false,
+	},
+	{
+		name: 'age',
+		type: 'number',
+		description: 'The age of the person',
+		required: false,
+	},
+];
+
+const mockPersonAttributesRequired: AttributeDefinition[] = [
+	{
+		name: 'name',
+		type: 'string',
+		description: 'The name of the person',
+		required: true,
+	},
+	{
+		name: 'age',
+		type: 'number',
+		description: 'The age of the person',
+		required: true,
+	},
+];
+
+function formatFakeLlmResponse(object: Record<string, any>) {
+	return `\`\`\`json\n${JSON.stringify(object, null, 2)}\n\`\`\``;
+}
+
+describe('processItem', () => {
+	it('should process a single item and return extracted attributes', async () => {
+		const mockExecuteFunctions = {
+			getNodeParameter: (param: string) => {
+				if (param === 'text') return 'John is 30 years old';
+				if (param === 'options') return {};
+				return undefined;
+			},
+			getNode: () => ({ typeVersion: 1.1 }),
+		};
+
+		const llm = new FakeLLM({ response: formatFakeLlmResponse({ name: 'John', age: 30 }) });
+		const parser = OutputFixingParser.fromLLM(
+			llm,
+			StructuredOutputParser.fromZodSchema(makeZodSchemaFromAttributes(mockPersonAttributes)),
+		);
+
+		const result = await processItem(mockExecuteFunctions as any, 0, llm, parser);
+
+		expect(result).toEqual({ name: 'John', age: 30 });
+	});
+
+	it('should throw error if input is undefined or empty', async () => {
+		const mockExecuteFunctions = {
+			getNodeParameter: (param: string, itemIndex: number) => {
+				if (param === 'text') {
+					if (itemIndex === 0) return undefined;
+					if (itemIndex === 1) return '';
+					if (itemIndex === 2) return ' ';
+					return null;
+				}
+				if (param === 'options') return {};
+				return undefined;
+			},
+			getNode: () => ({ typeVersion: 1.1 }),
+		};
+
+		const llm = new FakeLLM({ response: formatFakeLlmResponse({ name: 'John', age: 30 }) });
+		const parser = OutputFixingParser.fromLLM(
+			llm,
+			StructuredOutputParser.fromZodSchema(makeZodSchemaFromAttributes(mockPersonAttributes)),
+		);
+
+		for (let itemIndex = 0; itemIndex < 4; itemIndex++) {
+			await expect(
+				processItem(mockExecuteFunctions as any, itemIndex, llm, parser),
+			).rejects.toThrow(NodeOperationError);
+		}
+	});
+
+	it('should use custom system prompt template if provided', async () => {
+		const customTemplate = 'Custom template {format_instructions}';
+		const mockExecuteFunctions = {
+			getNodeParameter: (param: string) => {
+				if (param === 'text') return 'John is 30 years old';
+				if (param === 'options') return { systemPromptTemplate: customTemplate };
+				return undefined;
+			},
+			getNode: () => ({ typeVersion: 1.1 }),
+		};
+
+		const llm = new FakeLLM({ response: formatFakeLlmResponse({ name: 'John', age: 30 }) });
+		const parser = OutputFixingParser.fromLLM(
+			llm,
+			StructuredOutputParser.fromZodSchema(makeZodSchemaFromAttributes(mockPersonAttributes)),
+		);
+
+		const result = await processItem(mockExecuteFunctions as any, 0, llm, parser);
+
+		expect(result).toEqual({ name: 'John', age: 30 });
+	});
+
+	it('should handle curly braces in custom system prompt template', async () => {
+		const customTemplate = 'Extract JSON like this: {"name": "value"} from the text.';
+		const mockExecuteFunctions = {
+			getNodeParameter: (param: string) => {
+				if (param === 'text') return 'John is 30 years old';
+				if (param === 'options') return { systemPromptTemplate: customTemplate };
+				return undefined;
+			},
+			getNode: () => ({ typeVersion: 1.1 }),
+		};
+
+		const llm = new FakeLLM({ response: formatFakeLlmResponse({ name: 'John', age: 30 }) });
+		const parser = OutputFixingParser.fromLLM(
+			llm,
+			StructuredOutputParser.fromZodSchema(makeZodSchemaFromAttributes(mockPersonAttributes)),
+		);
+
+		const result = await processItem(mockExecuteFunctions as any, 0, llm, parser);
+
+		expect(result).toEqual({ name: 'John', age: 30 });
+	});
+
+	it('should handle retries when LLM returns invalid data', async () => {
+		const mockExecuteFunctions = {
+			getNodeParameter: (param: string) => {
+				if (param === 'text') return 'John is 30 years old';
+				if (param === 'options') return {};
+				return undefined;
+			},
+			getNode: () => ({ typeVersion: 1.1 }),
+		};
+
+		const llm = new FakeListChatModel({
+			responses: [
+				formatFakeLlmResponse({ name: 'John', age: '30' }), // Wrong type
+				formatFakeLlmResponse({ name: 'John', age: 30 }), // Correct type
+			],
+		});
+		const parser = OutputFixingParser.fromLLM(
+			llm,
+			StructuredOutputParser.fromZodSchema(
+				makeZodSchemaFromAttributes(mockPersonAttributesRequired),
+			),
+		);
+
+		const result = await processItem(mockExecuteFunctions as any, 0, llm, parser);
+
+		expect(result).toEqual({ name: 'John', age: 30 });
+	});
+});