n8n/packages/@n8n/nodes-langchain/nodes/llms/LmChatOpenRouter/LmChatOpenRouter.node.ts

import { ChatOpenAI, type ClientOptions } from '@langchain/openai';
import {
	getProxyAgent,
	makeN8nLlmFailedAttemptHandler,
	N8nLlmTracing,
	getConnectionHintNoticeField,
} from '@n8n/ai-utilities';

import {
	NodeConnectionTypes,
	type INodeType,
	type INodeTypeDescription,
	type ISupplyDataFunctions,
	type SupplyData,
} from 'n8n-workflow';

import type { OpenAICompatibleCredential } from '../../../types/types';
import { openAiFailedAttemptHandler } from '../../vendors/OpenAi/helpers/error-handling';

interface OpenAIToolCall {
	function?: { arguments?: unknown };
}

interface OpenAIChoice {
	message?: { tool_calls?: OpenAIToolCall[] };
}

function isOpenAIResponseWithChoices(json: unknown): json is { choices: OpenAIChoice[] } {
	return (
		typeof json === 'object' &&
		json !== null &&
		'choices' in json &&
		Array.isArray((json as { choices: unknown }).choices)
	);
}

/**
 * Wraps fetch to fix empty tool call arguments in API responses.
 *
 * When Anthropic models are accessed through OpenRouter, tool calls for tools
 * with no parameters return empty string arguments ("") instead of "{}".
 * LangChain's parseToolCall does JSON.parse("") which throws, breaking the agent.
 * This wrapper normalizes empty arguments to "{}" before LangChain sees them.
 */
function createOpenRouterFetch(baseFetch: typeof globalThis.fetch): typeof globalThis.fetch {
	return async (input, init) => {
		const response = await baseFetch(input, init);

		const contentType = response.headers.get('content-type') ?? '';
		if (!contentType.includes('json')) return response;

		// Clone before reading, since .json() consumes the body. If no
		// modification is needed we return the clone with the original body intact.
		const clone = response.clone();
		const json: unknown = await response.json();

		if (!isOpenAIResponseWithChoices(json)) return clone;

		const isInvalidArgs = (args: unknown): boolean => typeof args !== 'string' || !args.trim();

		const toolCallsToFix = json.choices
			.flatMap((choice) => choice.message?.tool_calls ?? [])
			.filter((tc) => tc.function && isInvalidArgs(tc.function.arguments));

		if (toolCallsToFix.length === 0) return clone;

		for (const tc of toolCallsToFix) {
			if (!tc.function) continue;
			const { arguments: args } = tc.function;
			// Preserve already-parsed plain objects by stringifying them.
			// Arrays and other non-object types are not valid tool args, so default to '{}'.
			const isPlainObject = typeof args === 'object' && args !== null && !Array.isArray(args);
			tc.function.arguments = isPlainObject ? JSON.stringify(args) : '{}';
		}

		const body = JSON.stringify(json);
		return new Response(body, {
			status: response.status,
			statusText: response.statusText,
			headers: { 'content-type': contentType },
		});
	};
}

export class LmChatOpenRouter implements INodeType {
	description: INodeTypeDescription = {
		displayName: 'OpenRouter Chat Model',
		name: 'lmChatOpenRouter',
		icon: { light: 'file:openrouter.svg', dark: 'file:openrouter.dark.svg' },
		group: ['transform'],
		version: [1],
		description: 'For advanced usage with an AI chain',
		defaults: {
			name: 'OpenRouter Chat Model',
		},
		codex: {
			categories: ['AI'],
			subcategories: {
				AI: ['Language Models', 'Root Nodes'],
				'Language Models': ['Chat Models (Recommended)'],
			},
			resources: {
				primaryDocumentation: [
					{
						url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatopenrouter/',
					},
				],
			},
		},

		inputs: [],

		outputs: [NodeConnectionTypes.AiLanguageModel],
		outputNames: ['Model'],
		credentials: [
			{
				name: 'openRouterApi',
				required: true,
			},
		],
		requestDefaults: {
			ignoreHttpStatusErrors: true,
			baseURL: '={{ $credentials?.url }}',
		},
		properties: [
			getConnectionHintNoticeField([NodeConnectionTypes.AiChain, NodeConnectionTypes.AiAgent]),
			{
				displayName:
					'If using JSON response format, you must include word "json" in the prompt in your chain or agent. Also, make sure to select latest models released post November 2023.',
				name: 'notice',
				type: 'notice',
				default: '',
				displayOptions: {
					show: {
						'/options.responseFormat': ['json_object'],
					},
				},
			},
			{
				displayName: 'Model',
				name: 'model',
				type: 'options',
				description:
					'The model which will generate the completion. <a href="https://openrouter.ai/docs/models">Learn more</a>.',
				typeOptions: {
					loadOptions: {
						routing: {
							request: {
								method: 'GET',
								url: '/models',
							},
							output: {
								postReceive: [
									{
										type: 'rootProperty',
										properties: {
											property: 'data',
										},
									},
									{
										type: 'setKeyValue',
										properties: {
											name: '={{$responseItem.id}}',
											value: '={{$responseItem.id}}',
										},
									},
									{
										type: 'sort',
										properties: {
											key: 'name',
										},
									},
								],
							},
						},
					},
				},
				routing: {
					send: {
						type: 'body',
						property: 'model',
					},
				},
				default: 'openai/gpt-4.1-mini',
			},
			{
				displayName: 'Options',
				name: 'options',
				placeholder: 'Add Option',
				description: 'Additional options to add',
				type: 'collection',
				default: {},
				options: [
					{
						displayName: 'Frequency Penalty',
						name: 'frequencyPenalty',
						default: 0,
						typeOptions: { maxValue: 2, minValue: -2, numberPrecision: 1 },
						description:
							"Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim",
						type: 'number',
					},
					{
						displayName: 'Maximum Number of Tokens',
						name: 'maxTokens',
						default: -1,
						description:
							'The maximum number of tokens to generate in the completion. Most models have a context length of 2048 tokens (except for the newest models, which support 32,768).',
						type: 'number',
						typeOptions: {
							maxValue: 32768,
						},
					},
					{
						displayName: 'Response Format',
						name: 'responseFormat',
						default: 'text',
						type: 'options',
						options: [
							{
								name: 'Text',
								value: 'text',
								description: 'Regular text response',
							},
							{
								name: 'JSON',
								value: 'json_object',
								description:
									'Enables JSON mode, which should guarantee the message the model generates is valid JSON',
							},
						],
					},
					{
						displayName: 'Presence Penalty',
						name: 'presencePenalty',
						default: 0,
						typeOptions: { maxValue: 2, minValue: -2, numberPrecision: 1 },
						description:
							"Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics",
						type: 'number',
					},
					{
						displayName: 'Sampling Temperature',
						name: 'temperature',
						default: 0.7,
						typeOptions: { maxValue: 2, 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: 'Timeout',
						name: 'timeout',
						default: 360000,
						description: 'Maximum amount of time a request is allowed to take in milliseconds',
						type: 'number',
					},
					{
						displayName: 'Max Retries',
						name: 'maxRetries',
						default: 2,
						description: 'Maximum number of retries to attempt',
						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: ISupplyDataFunctions, itemIndex: number): Promise<SupplyData> {
		const credentials = await this.getCredentials<OpenAICompatibleCredential>('openRouterApi');

		const modelName = this.getNodeParameter('model', itemIndex) as string;

		const options = this.getNodeParameter('options', itemIndex, {}) as {
			frequencyPenalty?: number;
			maxTokens?: number;
			maxRetries: number;
			timeout: number;
			presencePenalty?: number;
			temperature?: number;
			topP?: number;
			responseFormat?: 'text' | 'json_object';
		};

		const timeout = options.timeout;
		const configuration: ClientOptions = {
			baseURL: credentials.url,
			fetch: createOpenRouterFetch(globalThis.fetch),
			fetchOptions: {
				dispatcher: getProxyAgent(credentials.url, {
					headersTimeout: timeout,
					bodyTimeout: timeout,
				}),
			},
		};

		const model = new ChatOpenAI({
			apiKey: credentials.apiKey,
			model: modelName,
			...options,
			timeout,
			maxRetries: options.maxRetries ?? 2,
			configuration,
			callbacks: [new N8nLlmTracing(this)],
			modelKwargs: options.responseFormat
				? {
						response_format: { type: options.responseFormat },
					}
				: undefined,
			onFailedAttempt: makeN8nLlmFailedAttemptHandler(this, openAiFailedAttemptHandler),
		});

		return {
			response: model,
		};
	}
}