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50 lines
1.5 KiB
TypeScript
50 lines
1.5 KiB
TypeScript
import type { BaseLanguageModel } from '@langchain/core/language_models/base';
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import { HumanMessage } from '@langchain/core/messages';
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import { ChatPromptTemplate, SystemMessagePromptTemplate } from '@langchain/core/prompts';
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import type { OutputFixingParser } from '@langchain/classic/output_parsers';
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import { NodeOperationError, type IExecuteFunctions } from 'n8n-workflow';
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import { getTracingConfig } from '@utils/tracing';
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import { SYSTEM_PROMPT_TEMPLATE } from './constants';
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export async function processItem(
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ctx: IExecuteFunctions,
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itemIndex: number,
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llm: BaseLanguageModel,
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parser: OutputFixingParser<object>,
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) {
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const input = ctx.getNodeParameter('text', itemIndex) as string;
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if (!input?.trim()) {
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throw new NodeOperationError(ctx.getNode(), `Text for item ${itemIndex} is not defined`, {
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itemIndex,
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});
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}
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const inputPrompt = new HumanMessage(input);
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const options = ctx.getNodeParameter('options', itemIndex, {}) as {
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systemPromptTemplate?: string;
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};
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const escapedTemplate = (options.systemPromptTemplate ?? SYSTEM_PROMPT_TEMPLATE).replace(
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/[{}]/g,
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(match) => match + match,
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);
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const systemPromptTemplate = SystemMessagePromptTemplate.fromTemplate(
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`${escapedTemplate}
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{format_instructions}`,
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);
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const messages = [
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await systemPromptTemplate.format({
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format_instructions: parser.getFormatInstructions(),
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}),
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inputPrompt,
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];
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const prompt = ChatPromptTemplate.fromMessages(messages);
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const chain = prompt.pipe(llm).pipe(parser).withConfig(getTracingConfig(ctx));
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return await chain.invoke(messages);
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}
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