feat(Question and Answer Chain Node): Customize question and answer system prompt (#10385)

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

@@ -10,10 +10,21 @@ import {
 import { RetrievalQAChain } from 'langchain/chains';
 import type { BaseLanguageModel } from '@langchain/core/language_models/base';
 import type { BaseRetriever } from '@langchain/core/retrievers';
+import {
+	ChatPromptTemplate,
+	SystemMessagePromptTemplate,
+	HumanMessagePromptTemplate,
+	PromptTemplate,
+} from '@langchain/core/prompts';
 import { getTemplateNoticeField } from '../../../utils/sharedFields';
-import { getPromptInputByType } from '../../../utils/helpers';
+import { getPromptInputByType, isChatInstance } from '../../../utils/helpers';
 import { getTracingConfig } from '../../../utils/tracing';
 
+const SYSTEM_PROMPT_TEMPLATE = `Use the following pieces of context to answer the users question. 
+If you don't know the answer, just say that you don't know, don't try to make up an answer.
+----------------
+{context}`;
+
 export class ChainRetrievalQa implements INodeType {
 	description: INodeTypeDescription = {
 		displayName: 'Question and Answer Chain',
@@ -137,6 +148,26 @@ export class ChainRetrievalQa implements INodeType {
 					},
 				},
 			},
+			{
+				displayName: 'Options',
+				name: 'options',
+				type: 'collection',
+				default: {},
+				placeholder: 'Add Option',
+				options: [
+					{
+						displayName: 'System Prompt Template',
+						name: 'systemPromptTemplate',
+						type: 'string',
+						default: SYSTEM_PROMPT_TEMPLATE,
+						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 `{question}` for the user’s query.',
+						typeOptions: {
+							rows: 6,
+						},
+					},
+				],
+			},
 		],
 	};
 
@@ -154,7 +185,6 @@ export class ChainRetrievalQa implements INodeType {
 		)) as BaseRetriever;
 
 		const items = this.getInputData();
-		const chain = RetrievalQAChain.fromLLM(model, retriever);
 
 		const returnData: INodeExecutionData[] = [];
 
@@ -178,6 +208,35 @@ export class ChainRetrievalQa implements INodeType {
 					throw new NodeOperationError(this.getNode(), 'The ‘query‘ parameter is empty.');
 				}
 
+				const options = this.getNodeParameter('options', itemIndex, {}) as {
+					systemPromptTemplate?: string;
+				};
+
+				const chainParameters = {} as {
+					prompt?: PromptTemplate | ChatPromptTemplate;
+				};
+
+				if (options.systemPromptTemplate !== undefined) {
+					if (isChatInstance(model)) {
+						const messages = [
+							SystemMessagePromptTemplate.fromTemplate(options.systemPromptTemplate),
+							HumanMessagePromptTemplate.fromTemplate('{question}'),
+						];
+						const chatPromptTemplate = ChatPromptTemplate.fromMessages(messages);
+
+						chainParameters.prompt = chatPromptTemplate;
+					} else {
+						const completionPromptTemplate = new PromptTemplate({
+							template: options.systemPromptTemplate,
+							inputVariables: ['context', 'question'],
+						});
+
+						chainParameters.prompt = completionPromptTemplate;
+					}
+				}
+
+				const chain = RetrievalQAChain.fromLLM(model, retriever, chainParameters);
+
 				const response = await chain.withConfig(getTracingConfig(this)).invoke({ query });
 				returnData.push({ json: { response } });
 			} catch (error) {