refactor(Basic LLM Chain Node): Refactor Basic LLM Chain & add tests (#13850)

packages/@n8n/nodes-langchain/nodes/chains/ChainLLM/methods/chainExecutor.ts

@@ -0,0 +1,90 @@
+import type { BaseLanguageModel } from '@langchain/core/language_models/base';
+import { StringOutputParser } from '@langchain/core/output_parsers';
+import type { ChatPromptTemplate, PromptTemplate } from '@langchain/core/prompts';
+import type { IExecuteFunctions } from 'n8n-workflow';
+
+import { getTracingConfig } from '@utils/tracing';
+
+import { createPromptTemplate } from './promptUtils';
+import type { ChainExecutionParams } from './types';
+
+/**
+ * Creates a simple chain for LLMs without output parsers
+ */
+async function executeSimpleChain({
+	context,
+	llm,
+	query,
+	prompt,
+}: {
+	context: IExecuteFunctions;
+	llm: BaseLanguageModel;
+	query: string;
+	prompt: ChatPromptTemplate | PromptTemplate;
+}): Promise<string[]> {
+	const chain = prompt
+		.pipe(llm)
+		.pipe(new StringOutputParser())
+		.withConfig(getTracingConfig(context));
+
+	// Execute the chain
+	const response = await chain.invoke({
+		query,
+		signal: context.getExecutionCancelSignal(),
+	});
+
+	// Ensure response is always returned as an array
+	return [response];
+}
+
+/**
+ * Creates and executes an LLM chain with the given prompt and optional output parsers
+ */
+export async function executeChain({
+	context,
+	itemIndex,
+	query,
+	llm,
+	outputParser,
+	messages,
+}: ChainExecutionParams): Promise<unknown[]> {
+	// If no output parsers provided, use a simple chain with basic prompt template
+	if (!outputParser) {
+		const promptTemplate = await createPromptTemplate({
+			context,
+			itemIndex,
+			llm,
+			messages,
+			query,
+		});
+
+		return await executeSimpleChain({
+			context,
+			llm,
+			query,
+			prompt: promptTemplate,
+		});
+	}
+
+	const formatInstructions = outputParser.getFormatInstructions();
+
+	// Create a prompt template with format instructions
+	const promptWithInstructions = await createPromptTemplate({
+		context,
+		itemIndex,
+		llm,
+		messages,
+		formatInstructions,
+		query,
+	});
+
+	const chain = promptWithInstructions
+		.pipe(llm)
+		.pipe(outputParser)
+		.withConfig(getTracingConfig(context));
+	const response = await chain.invoke({ query }, { signal: context.getExecutionCancelSignal() });
+
+	// Ensure response is always returned as an array
+	// eslint-disable-next-line @typescript-eslint/no-unsafe-return
+	return Array.isArray(response) ? response : [response];
+}