n8n/packages/@n8n/nodes-langchain/nodes/llms/LMChatAnthropic/LmChatAnthropic.node.ts

/* eslint-disable n8n-nodes-base/node-dirname-against-convention */
import {
	NodeConnectionType,
	type IExecuteFunctions,
	type INodeType,
	type INodeTypeDescription,
	type SupplyData,
} from 'n8n-workflow';

import { ChatAnthropic } from 'langchain/chat_models/anthropic';
import { logWrapper } from '../../../utils/logWrapper';
import { getConnectionHintNoticeField } from '../../../utils/sharedFields';

export class LmChatAnthropic implements INodeType {
	description: INodeTypeDescription = {
		displayName: 'Anthropic Chat Model',
		// eslint-disable-next-line n8n-nodes-base/node-class-description-name-miscased
		name: 'lmChatAnthropic',
		icon: 'file:anthropic.svg',
		group: ['transform'],
		version: 1,
		description: 'Language Model Anthropic',
		defaults: {
			name: 'Anthropic Chat Model',
		},
		codex: {
			categories: ['AI'],
			subcategories: {
				AI: ['Language Models'],
			},
			resources: {
				primaryDocumentation: [
					{
						url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatanthropic/',
					},
				],
			},
		},
		// eslint-disable-next-line n8n-nodes-base/node-class-description-inputs-wrong-regular-node
		inputs: [],
		// eslint-disable-next-line n8n-nodes-base/node-class-description-outputs-wrong
		outputs: [NodeConnectionType.AiLanguageModel],
		outputNames: ['Model'],
		credentials: [
			{
				name: 'anthropicApi',
				required: true,
			},
		],
		properties: [
			getConnectionHintNoticeField([NodeConnectionType.AiChain, NodeConnectionType.AiChain]),
			{
				displayName: 'Model',
				name: 'model',
				type: 'options',
				options: [
					{
						name: 'Claude 2',
						value: 'claude-2',
					},
					{
						name: 'Claude 2.1',
						value: 'claude-2.1',
					},
					{
						name: 'Claude Instant 1.2',
						value: 'claude-instant-1.2',
					},
					{
						name: 'Claude Instant 1',
						value: 'claude-instant-1',
					},
				],
				description:
					'The model which will generate the completion. <a href="https://docs.anthropic.com/claude/reference/selecting-a-model">Learn more</a>.',
				default: 'claude-2',
			},
			{
				displayName: 'Options',
				name: 'options',
				placeholder: 'Add Option',
				description: 'Additional options to add',
				type: 'collection',
				default: {},
				options: [
					{
						displayName: 'Maximum Number of Tokens',
						name: 'maxTokensToSample',
						default: 32768,
						description: 'The maximum number of tokens to generate in the completion',
						type: 'number',
					},
					{
						displayName: 'Sampling Temperature',
						name: 'temperature',
						default: 0.7,
						typeOptions: { maxValue: 1, minValue: 0, numberPrecision: 1 },
						description:
							'Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.',
						type: 'number',
					},
					{
						displayName: 'Top K',
						name: 'topK',
						default: -1,
						typeOptions: { maxValue: 1, minValue: -1, numberPrecision: 1 },
						description:
							'Used to remove "long tail" low probability responses. Defaults to -1, which disables it.',
						type: 'number',
					},
					{
						displayName: 'Top P',
						name: 'topP',
						default: 1,
						typeOptions: { maxValue: 1, minValue: 0, numberPrecision: 1 },
						description:
							'Controls diversity via nucleus sampling: 0.5 means half of all likelihood-weighted options are considered. We generally recommend altering this or temperature but not both.',
						type: 'number',
					},
				],
			},
		],
	};

	async supplyData(this: IExecuteFunctions, itemIndex: number): Promise<SupplyData> {
		const credentials = await this.getCredentials('anthropicApi');

		const modelName = this.getNodeParameter('model', itemIndex) as string;
		const options = this.getNodeParameter('options', itemIndex, {}) as object;

		const model = new ChatAnthropic({
			anthropicApiKey: credentials.apiKey as string,
			modelName,
			...options,
		});

		return {
			response: logWrapper(model, this),
		};
	}
}