feat(Information Extractor Node): Add new simplified AI-node for information extraction (#10149)

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

@@ -0,0 +1,308 @@
+import { jsonParse, NodeConnectionType, NodeOperationError } from 'n8n-workflow';
+import type {
+	INodeType,
+	INodeTypeDescription,
+	IExecuteFunctions,
+	INodeExecutionData,
+	INodePropertyOptions,
+} from 'n8n-workflow';
+import type { JSONSchema7 } from 'json-schema';
+import type { BaseLanguageModel } from '@langchain/core/language_models/base';
+import { ChatPromptTemplate, SystemMessagePromptTemplate } from '@langchain/core/prompts';
+import type { z } from 'zod';
+import { OutputFixingParser, StructuredOutputParser } from 'langchain/output_parsers';
+import { HumanMessage } from '@langchain/core/messages';
+import { generateSchema, getSandboxWithZod } from '../../../utils/schemaParsing';
+import {
+	inputSchemaField,
+	jsonSchemaExampleField,
+	schemaTypeField,
+} from '../../../utils/descriptions';
+import { getTracingConfig } from '../../../utils/tracing';
+import type { AttributeDefinition } from './types';
+import { makeZodSchemaFromAttributes } from './helpers';
+
+const SYSTEM_PROMPT_TEMPLATE = `You are an expert extraction algorithm.
+Only extract relevant information from the text.
+If you do not know the value of an attribute asked to extract, you may omit the attribute's value.`;
+
+export class InformationExtractor implements INodeType {
+	description: INodeTypeDescription = {
+		displayName: 'Information Extractor',
+		name: 'informationExtractor',
+		icon: 'fa:project-diagram',
+		iconColor: 'black',
+		group: ['transform'],
+		version: 1,
+		description: 'Extract information from text in a structured format',
+		codex: {
+			alias: ['NER', 'parse', 'parsing', 'JSON', 'data extraction', 'structured'],
+			categories: ['AI'],
+			subcategories: {
+				AI: ['Chains', 'Root Nodes'],
+			},
+			resources: {
+				primaryDocumentation: [
+					{
+						url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.information-extractor/',
+					},
+				],
+			},
+		},
+		defaults: {
+			name: 'Information Extractor',
+		},
+		inputs: [
+			{ displayName: '', type: NodeConnectionType.Main },
+			{
+				displayName: 'Model',
+				maxConnections: 1,
+				type: NodeConnectionType.AiLanguageModel,
+				required: true,
+			},
+		],
+		outputs: [NodeConnectionType.Main],
+		properties: [
+			{
+				displayName: 'Text',
+				name: 'text',
+				type: 'string',
+				default: '',
+				description: 'The text to extract information from',
+				typeOptions: {
+					rows: 2,
+				},
+			},
+			{
+				...schemaTypeField,
+				description: 'How to specify the schema for the desired output',
+				options: [
+					{
+						name: 'From Attribute Descriptions',
+						value: 'fromAttributes',
+						description:
+							'Extract specific attributes from the text based on types and descriptions',
+					} as INodePropertyOptions,
+					...(schemaTypeField.options as INodePropertyOptions[]),
+				],
+				default: 'fromAttributes',
+			},
+			{
+				...jsonSchemaExampleField,
+				default: `{
+	"state": "California",
+	"cities": ["Los Angeles", "San Francisco", "San Diego"]
+}`,
+			},
+			{
+				...inputSchemaField,
+				default: `{
+	"type": "object",
+	"properties": {
+		"state": {
+			"type": "string"
+		},
+		"cities": {
+			"type": "array",
+			"items": {
+				"type": "string"
+			}
+		}
+	}
+}`,
+			},
+			{
+				displayName:
+					'The schema has to be defined in the <a target="_blank" href="https://json-schema.org/">JSON Schema</a> format. Look at <a target="_blank" href="https://json-schema.org/learn/miscellaneous-examples.html">this</a> page for examples.',
+				name: 'notice',
+				type: 'notice',
+				default: '',
+				displayOptions: {
+					show: {
+						schemaType: ['manual'],
+					},
+				},
+			},
+			{
+				displayName: 'Attributes',
+				name: 'attributes',
+				placeholder: 'Add Attribute',
+				type: 'fixedCollection',
+				default: {},
+				displayOptions: {
+					show: {
+						schemaType: ['fromAttributes'],
+					},
+				},
+				typeOptions: {
+					multipleValues: true,
+				},
+				options: [
+					{
+						name: 'attributes',
+						displayName: 'Attribute List',
+						values: [
+							{
+								displayName: 'Name',
+								name: 'name',
+								type: 'string',
+								default: '',
+								description: 'Attribute to extract',
+								placeholder: 'e.g. company_name',
+								required: true,
+							},
+							{
+								displayName: 'Type',
+								name: 'type',
+								type: 'options',
+								description: 'Data type of the attribute',
+								required: true,
+								options: [
+									{
+										name: 'Boolean',
+										value: 'boolean',
+									},
+									{
+										name: 'Date',
+										value: 'date',
+									},
+									{
+										name: 'Number',
+										value: 'number',
+									},
+									{
+										name: 'String',
+										value: 'string',
+									},
+								],
+								default: 'string',
+							},
+							{
+								displayName: 'Description',
+								name: 'description',
+								type: 'string',
+								default: '',
+								description: 'Describe your attribute',
+								placeholder: 'Add description for the attribute',
+								required: true,
+							},
+							{
+								displayName: 'Required',
+								name: 'required',
+								type: 'boolean',
+								default: false,
+								description: 'Whether attribute is required',
+								required: true,
+							},
+						],
+					},
+				],
+			},
+			{
+				displayName: 'Options',
+				name: 'options',
+				type: 'collection',
+				default: {},
+				placeholder: 'Add Option',
+				options: [
+					{
+						displayName: 'System Prompt Template',
+						name: 'systemPromptTemplate',
+						type: 'string',
+						default: SYSTEM_PROMPT_TEMPLATE,
+						description: 'String to use directly as the system prompt template',
+						typeOptions: {
+							rows: 6,
+						},
+					},
+				],
+			},
+		],
+	};
+
+	async execute(this: IExecuteFunctions): Promise<INodeExecutionData[][]> {
+		const items = this.getInputData();
+
+		const llm = (await this.getInputConnectionData(
+			NodeConnectionType.AiLanguageModel,
+			0,
+		)) as BaseLanguageModel;
+
+		const schemaType = this.getNodeParameter('schemaType', 0, '') as
+			| 'fromAttributes'
+			| 'fromJson'
+			| 'manual';
+
+		let parser: OutputFixingParser<object>;
+
+		if (schemaType === 'fromAttributes') {
+			const attributes = this.getNodeParameter(
+				'attributes.attributes',
+				0,
+				[],
+			) as AttributeDefinition[];
+
+			if (attributes.length === 0) {
+				throw new NodeOperationError(this.getNode(), 'At least one attribute must be specified');
+			}
+
+			parser = OutputFixingParser.fromLLM(
+				llm,
+				StructuredOutputParser.fromZodSchema(makeZodSchemaFromAttributes(attributes)),
+			);
+		} else {
+			let jsonSchema: JSONSchema7;
+
+			if (schemaType === 'fromJson') {
+				const jsonExample = this.getNodeParameter('jsonSchemaExample', 0, '') as string;
+				jsonSchema = generateSchema(jsonExample);
+			} else {
+				const inputSchema = this.getNodeParameter('inputSchema', 0, '') as string;
+				jsonSchema = jsonParse<JSONSchema7>(inputSchema);
+			}
+
+			const zodSchemaSandbox = getSandboxWithZod(this, jsonSchema, 0);
+			const zodSchema = (await zodSchemaSandbox.runCode()) as z.ZodSchema<object>;
+
+			parser = OutputFixingParser.fromLLM(llm, StructuredOutputParser.fromZodSchema(zodSchema));
+		}
+
+		const resultData: INodeExecutionData[] = [];
+		for (let itemIndex = 0; itemIndex < items.length; itemIndex++) {
+			const input = this.getNodeParameter('text', itemIndex) as string;
+			const inputPrompt = new HumanMessage(input);
+
+			const options = this.getNodeParameter('options', itemIndex, {}) as {
+				systemPromptTemplate?: string;
+			};
+
+			const systemPromptTemplate = SystemMessagePromptTemplate.fromTemplate(
+				`${options.systemPromptTemplate ?? SYSTEM_PROMPT_TEMPLATE}
+{format_instructions}`,
+			);
+
+			const messages = [
+				await systemPromptTemplate.format({
+					format_instructions: parser.getFormatInstructions(),
+				}),
+				inputPrompt,
+			];
+			const prompt = ChatPromptTemplate.fromMessages(messages);
+			const chain = prompt.pipe(llm).pipe(parser).withConfig(getTracingConfig(this));
+
+			try {
+				const output = await chain.invoke(messages);
+				resultData.push({ json: { output } });
+			} catch (error) {
+				if (this.continueOnFail(error)) {
+					resultData.push({ json: { error: error.message }, pairedItem: { item: itemIndex } });
+					continue;
+				}
+
+				throw error;
+			}
+		}
+
+		return [resultData];
+	}
+}

packages/@n8n/nodes-langchain/nodes/chains/InformationExtractor/helpers.ts

@@ -0,0 +1,33 @@
+import { z } from 'zod';
+import type { AttributeDefinition } from './types';
+
+function makeAttributeSchema(attributeDefinition: AttributeDefinition, required: boolean = true) {
+	let schema: z.ZodTypeAny;
+
+	if (attributeDefinition.type === 'string') {
+		schema = z.string();
+	} else if (attributeDefinition.type === 'number') {
+		schema = z.number();
+	} else if (attributeDefinition.type === 'boolean') {
+		schema = z.boolean();
+	} else if (attributeDefinition.type === 'date') {
+		schema = z.string().date();
+	} else {
+		schema = z.unknown();
+	}
+
+	if (!required) {
+		schema = schema.optional();
+	}
+
+	return schema.describe(attributeDefinition.description);
+}
+
+export function makeZodSchemaFromAttributes(attributes: AttributeDefinition[]) {
+	const schemaEntries = attributes.map((attr) => [
+		attr.name,
+		makeAttributeSchema(attr, attr.required),
+	]);
+
+	return z.object(Object.fromEntries(schemaEntries));
+}

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

@@ -0,0 +1,218 @@
+import type { IDataObject, IExecuteFunctions } from 'n8n-workflow/src';
+import get from 'lodash/get';
+
+import { FakeLLM, FakeListChatModel } from '@langchain/core/utils/testing';
+import type { BaseLanguageModel } from '@langchain/core/language_models/base';
+import { InformationExtractor } from '../InformationExtractor.node';
+import { makeZodSchemaFromAttributes } from '../helpers';
+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) => {
+	const nodeParameters = parameters;
+
+	return {
+		getNodeParameter(parameter: string) {
+			return get(nodeParameters, parameter);
+		},
+		getNode() {
+			return {};
+		},
+		getInputConnectionData() {
+			return fakeLlm;
+		},
+		getInputData() {
+			return [{ json: {} }];
+		},
+		getWorkflow() {
+			return {
+				name: 'Test Workflow',
+			};
+		},
+		getExecutionId() {
+			return 'test_execution_id';
+		},
+		continueOnFail() {
+			return false;
+		},
+	} as unknown as IExecuteFunctions;
+};
+
+describe('InformationExtractor', () => {
+	describe('From Attribute Descriptions', () => {
+		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 });
+		});
+
+		it('should make a request to LLM and return the extracted attributes', async () => {
+			const node = new InformationExtractor();
+
+			const response = await node.execute.call(
+				createExecuteFunctionsMock(
+					{
+						text: 'John is 30 years old',
+						attributes: {
+							attributes: mockPersonAttributes,
+						},
+						options: {},
+						schemaType: 'fromAttributes',
+					},
+					new FakeLLM({ response: formatFakeLlmResponse({ name: 'John', age: 30 }) }),
+				),
+			);
+
+			expect(response).toEqual([[{ json: { output: { name: 'John', age: 30 } } }]]);
+		});
+
+		it('should not fail if LLM could not extract some attribute', async () => {
+			const node = new InformationExtractor();
+
+			const response = await node.execute.call(
+				createExecuteFunctionsMock(
+					{
+						text: 'John is 30 years old',
+						attributes: {
+							attributes: mockPersonAttributes,
+						},
+						options: {},
+						schemaType: 'fromAttributes',
+					},
+					new FakeLLM({ response: formatFakeLlmResponse({ name: 'John' }) }),
+				),
+			);
+
+			expect(response).toEqual([[{ json: { output: { name: 'John' } } }]]);
+		});
+
+		it('should fail if LLM could not extract some required attribute', async () => {
+			const node = new InformationExtractor();
+
+			try {
+				await node.execute.call(
+					createExecuteFunctionsMock(
+						{
+							text: 'John is 30 years old',
+							attributes: {
+								attributes: mockPersonAttributesRequired,
+							},
+							options: {},
+							schemaType: 'fromAttributes',
+						},
+						new FakeLLM({ response: formatFakeLlmResponse({ name: 'John' }) }),
+					),
+				);
+			} catch (error) {
+				expect(error.message).toContain('Failed to parse');
+			}
+		});
+
+		it('should fail if LLM extracted an attribute with the wrong type', async () => {
+			const node = new InformationExtractor();
+
+			try {
+				await node.execute.call(
+					createExecuteFunctionsMock(
+						{
+							text: 'John is 30 years old',
+							attributes: {
+								attributes: mockPersonAttributes,
+							},
+							options: {},
+							schemaType: 'fromAttributes',
+						},
+						new FakeLLM({ response: formatFakeLlmResponse({ name: 'John', age: '30' }) }),
+					),
+				);
+			} catch (error) {
+				expect(error.message).toContain('Failed to parse');
+			}
+		});
+
+		it('retries if LLM fails to extract some required attribute', async () => {
+			const node = new InformationExtractor();
+
+			const response = await node.execute.call(
+				createExecuteFunctionsMock(
+					{
+						text: 'John is 30 years old',
+						attributes: {
+							attributes: mockPersonAttributesRequired,
+						},
+						options: {},
+						schemaType: 'fromAttributes',
+					},
+					new FakeListChatModel({
+						responses: [
+							formatFakeLlmResponse({ name: 'John' }),
+							formatFakeLlmResponse({ name: 'John', age: 30 }),
+						],
+					}),
+				),
+			);
+
+			expect(response).toEqual([[{ json: { output: { name: 'John', age: 30 } } }]]);
+		});
+
+		it('retries if LLM extracted an attribute with a wrong type', async () => {
+			const node = new InformationExtractor();
+
+			const response = await node.execute.call(
+				createExecuteFunctionsMock(
+					{
+						text: 'John is 30 years old',
+						attributes: {
+							attributes: mockPersonAttributesRequired,
+						},
+						options: {},
+						schemaType: 'fromAttributes',
+					},
+					new FakeListChatModel({
+						responses: [
+							formatFakeLlmResponse({ name: 'John', age: '30' }),
+							formatFakeLlmResponse({ name: 'John', age: 30 }),
+						],
+					}),
+				),
+			);
+
+			expect(response).toEqual([[{ json: { output: { name: 'John', age: 30 } } }]]);
+		});
+	});
+});

packages/@n8n/nodes-langchain/nodes/chains/InformationExtractor/types.ts

@@ -0,0 +1,6 @@
+export interface AttributeDefinition {
+	name: string;
+	description: string;
+	type: 'string' | 'number' | 'boolean' | 'date';
+	required: boolean;
+}

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/InformationExtractor/InformationExtractor.node.js",
       "dist/nodes/chains/TextClassifier/TextClassifier.node.js",
       "dist/nodes/code/Code.node.js",
       "dist/nodes/document_loaders/DocumentDefaultDataLoader/DocumentDefaultDataLoader.node.js",