first commit

packages/@n8n/nodes-langchain/nodes/chains/ChainRetrievalQA/ChainRetrievalQa.node.ts

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+import { NodeConnectionTypes, parseErrorMetadata, sleep } from 'n8n-workflow';
+import {
+	type IExecuteFunctions,
+	type INodeExecutionData,
+	type INodeType,
+	type INodeTypeDescription,
+} from 'n8n-workflow';
+
+import {
+	promptTypeOptions,
+	promptTypeOptionsDeprecated,
+	textFromGuardrailsNode,
+	textFromPreviousNode,
+} from '@utils/descriptions';
+import { getBatchingOptionFields, getTemplateNoticeField } from '@n8n/ai-utilities';
+
+import { INPUT_TEMPLATE_KEY, LEGACY_INPUT_TEMPLATE_KEY, systemPromptOption } from './constants';
+import { processItem } from './processItem';
+
+export class ChainRetrievalQa implements INodeType {
+	description: INodeTypeDescription = {
+		displayName: 'Question and Answer Chain',
+		name: 'chainRetrievalQa',
+		icon: 'fa:link',
+		iconColor: 'black',
+		group: ['transform'],
+		version: [1, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7],
+		description: 'Answer questions about retrieved documents',
+		defaults: {
+			name: 'Question and Answer Chain',
+			color: '#909298',
+		},
+		codex: {
+			alias: ['LangChain'],
+			categories: ['AI'],
+			subcategories: {
+				AI: ['Chains', 'Root Nodes'],
+			},
+			resources: {
+				primaryDocumentation: [
+					{
+						url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainretrievalqa/',
+					},
+				],
+			},
+		},
+
+		inputs: [
+			NodeConnectionTypes.Main,
+			{
+				displayName: 'Model',
+				maxConnections: 1,
+				type: NodeConnectionTypes.AiLanguageModel,
+				required: true,
+			},
+			{
+				displayName: 'Retriever',
+				maxConnections: 1,
+				type: NodeConnectionTypes.AiRetriever,
+				required: true,
+			},
+		],
+		outputs: [NodeConnectionTypes.Main],
+		builderHint: {
+			inputs: {
+				ai_languageModel: { required: true },
+				ai_retriever: { required: true },
+			},
+		},
+		credentials: [],
+		properties: [
+			getTemplateNoticeField(1960),
+			{
+				displayName: 'Query',
+				name: 'query',
+				type: 'string',
+				required: true,
+				default: '={{ $json.input }}',
+				displayOptions: {
+					show: {
+						'@version': [1],
+					},
+				},
+			},
+			{
+				displayName: 'Query',
+				name: 'query',
+				type: 'string',
+				required: true,
+				default: '={{ $json.chat_input }}',
+				displayOptions: {
+					show: {
+						'@version': [1.1],
+					},
+				},
+			},
+			{
+				displayName: 'Query',
+				name: 'query',
+				type: 'string',
+				required: true,
+				default: '={{ $json.chatInput }}',
+				displayOptions: {
+					show: {
+						'@version': [1.2],
+					},
+				},
+			},
+			{
+				...promptTypeOptionsDeprecated,
+				displayOptions: {
+					hide: {
+						'@version': [{ _cnd: { lte: 1.2 } }, { _cnd: { gte: 1.7 } }],
+					},
+				},
+			},
+			{
+				...promptTypeOptions,
+				displayOptions: {
+					show: {
+						'@version': [{ _cnd: { gte: 1.7 } }],
+					},
+				},
+			},
+			{
+				...textFromGuardrailsNode,
+				displayOptions: {
+					show: { promptType: ['guardrails'], '@version': [{ _cnd: { gte: 1.4 } }] },
+				},
+			},
+			{
+				...textFromPreviousNode,
+				displayOptions: { show: { promptType: ['auto'], '@version': [{ _cnd: { gte: 1.4 } }] } },
+			},
+			{
+				displayName: 'Prompt (User Message)',
+				name: 'text',
+				type: 'string',
+				required: true,
+				default: '',
+				placeholder: 'e.g. Hello, how can you help me?',
+				typeOptions: {
+					rows: 2,
+				},
+				displayOptions: {
+					show: {
+						promptType: ['define'],
+					},
+				},
+			},
+			{
+				displayName: 'Options',
+				name: 'options',
+				type: 'collection',
+				default: {},
+				placeholder: 'Add Option',
+				options: [
+					{
+						...systemPromptOption,
+						description: `Template string used for the system prompt. This should include the variable \`{context}\` for the provided context. For text completion models, you should also include the variable \`{${LEGACY_INPUT_TEMPLATE_KEY}}\` for the user’s query.`,
+						displayOptions: {
+							show: {
+								'@version': [{ _cnd: { lt: 1.5 } }],
+							},
+						},
+					},
+					{
+						...systemPromptOption,
+						description: `Template string used for the system prompt. This should include the variable \`{context}\` for the provided context. For text completion models, you should also include the variable \`{${INPUT_TEMPLATE_KEY}}\` for the user’s query.`,
+						displayOptions: {
+							show: {
+								'@version': [{ _cnd: { gte: 1.5 } }],
+							},
+						},
+					},
+					getBatchingOptionFields({
+						show: {
+							'@version': [{ _cnd: { gte: 1.6 } }],
+						},
+					}),
+				],
+			},
+		],
+	};
+
+	async execute(this: IExecuteFunctions): Promise<INodeExecutionData[][]> {
+		this.logger.debug('Executing Retrieval QA Chain');
+
+		const items = this.getInputData();
+		const returnData: INodeExecutionData[] = [];
+		const batchSize = this.getNodeParameter('options.batching.batchSize', 0, 5) as number;
+		const delayBetweenBatches = this.getNodeParameter(
+			'options.batching.delayBetweenBatches',
+			0,
+			0,
+		) as number;
+
+		if (this.getNode().typeVersion >= 1.6 && batchSize >= 1) {
+			// Run in batches
+			for (let i = 0; i < items.length; i += batchSize) {
+				const batch = items.slice(i, i + batchSize);
+				const batchPromises = batch.map(async (_item, batchItemIndex) => {
+					return await processItem(this, i + batchItemIndex);
+				});
+
+				const batchResults = await Promise.allSettled(batchPromises);
+
+				batchResults.forEach((response, index) => {
+					if (response.status === 'rejected') {
+						const error = response.reason;
+						if (this.continueOnFail()) {
+							const metadata = parseErrorMetadata(error);
+							returnData.push({
+								json: { error: error.message },
+								pairedItem: { item: index },
+								metadata,
+							});
+							return;
+						} else {
+							throw error;
+						}
+					}
+					const output = response.value;
+					const answer = output.answer as string;
+					if (this.getNode().typeVersion >= 1.5) {
+						returnData.push({ json: { response: answer } });
+					} else {
+						// Legacy format for versions 1.4 and below is { text: string }
+						returnData.push({ json: { response: { text: answer } } });
+					}
+				});
+
+				// Add delay between batches if not the last batch
+				if (i + batchSize < items.length && delayBetweenBatches > 0) {
+					await sleep(delayBetweenBatches);
+				}
+			}
+		} else {
+			// Run for each item
+			for (let itemIndex = 0; itemIndex < items.length; itemIndex++) {
+				try {
+					const response = await processItem(this, itemIndex);
+					const answer = response.answer as string;
+					if (this.getNode().typeVersion >= 1.5) {
+						returnData.push({ json: { response: answer } });
+					} else {
+						// Legacy format for versions 1.4 and below is { text: string }
+						returnData.push({ json: { response: { text: answer } } });
+					}
+				} catch (error) {
+					if (this.continueOnFail()) {
+						const metadata = parseErrorMetadata(error);
+						returnData.push({
+							json: { error: error.message },
+							pairedItem: { item: itemIndex },
+							metadata,
+						});
+						continue;
+					}
+
+					throw error;
+				}
+			}
+		}
+		return [returnData];
+	}
+}