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

import { loadChatOpenAi, loadN8nLlmTracing } from '../shared/langchainModules';
import { modelLoader } from '../shared/loadModels';
import { errorMessage, normalizeBaseUrl, parseExtraBody } from '../shared/teamorouter';

interface ChatModelOptions {
	temperature?: number;
	maxTokens?: number;
	topP?: number;
	forceJsonResponse?: boolean;
	serviceTier?: 'auto' | 'fast';
	extraBody?: unknown;
	timeout?: number;
	maxRetries?: number;
}

export class LmChatTeamRouter implements INodeType {
	description: INodeTypeDescription = {
		displayName: 'TeamoRouter Chat Model',
		name: 'lmChatTeamRouter',
		icon: 'file:teamorouter.svg',
		group: ['transform'],
		version: 1,
		description:
			'Chat model served by the TeamoRouter gateway (GPT, Claude, Gemini, DeepSeek, GLM, Grok, Kimi)',

		defaults: {
			name: 'TeamoRouter Chat Model',
		},

		codex: {
			categories: ['AI'],
			subcategories: {
				AI: ['Language Models', 'Root Nodes'],
				'Language Models': ['Chat Models (Recommended)'],
			},
			resources: {
				primaryDocumentation: [
					{
						url: 'https://git.itoservice.ru/dosnav/n8n-nodes-teamorouter',
					},
				],
			},
		},

		inputs: [],
		outputs: [NodeConnectionTypes.AiLanguageModel],
		outputNames: ['Model'],

		credentials: [
			{
				name: 'teamorouterApi',
				required: true,
			},
		],

		properties: [
			{
				displayName: 'Model',
				name: 'model',
				type: 'options',
				typeOptions: {
					loadOptionsMethod: 'getChatModels',
				},
				default: '',
				required: true,
				description:
					'Model ID to use. The list is read live from GET /v1/models. For an ID that is missing from the list, switch this field to expression mode and enter the ID.',
			},
			{
				displayName: 'Options',
				name: 'options',
				placeholder: 'Add Option',
				type: 'collection',
				default: {},
				options: [
					{
						displayName: 'Extra Body',
						name: 'extraBody',
						type: 'json',
						default: '',
						description:
							'Extra JSON properties to merge into the request body, e.g. {"top_k": 40}. Overrides the fields set by the options above.',
					},
					{
						displayName: 'Force JSON Response',
						name: 'forceJsonResponse',
						type: 'boolean',
						default: false,
						description:
							'Whether to request a JSON object from the model. The prompt must mention JSON.',
					},
					{
						displayName: 'Maximum Number of Tokens',
						name: 'maxTokens',
						type: 'number',
						default: -1,
						description: 'Maximum number of tokens to generate. -1 leaves it to the model.',
					},
					{
						displayName: 'Max Retries',
						name: 'maxRetries',
						type: 'number',
						default: 2,
						description: 'Maximum number of retries for failed requests',
					},
					{
						displayName: 'Sampling Temperature',
						name: 'temperature',
						type: 'number',
						default: 0.7,
						typeOptions: { maxValue: 2, minValue: 0, numberPrecision: 1 },
						description:
							'Controls randomness: lower values make the output more deterministic and repetitive',
					},
					{
						displayName: 'Service Tier',
						name: 'serviceTier',
						type: 'options',
						default: 'auto',
						options: [
							{ name: 'Auto', value: 'auto', description: 'Standard processing' },
							{
								name: 'Fast',
								value: 'fast',
								description: 'TeamoRouter Fast mode: up to 2.5x faster, billed at 2x the standard rate',
							},
						],
						description: 'Processing mode requested from TeamoRouter',
					},
					{
						displayName: 'Timeout',
						name: 'timeout',
						type: 'number',
						default: 600000,
						description:
							'Time to wait for an answer in milliseconds. TeamoRouter allows responses up to 600 seconds.',
					},
					{
						displayName: 'Top P',
						name: 'topP',
						type: 'number',
						default: 1,
						typeOptions: { maxValue: 1, minValue: 0, numberPrecision: 2 },
						description:
							'Controls diversity via nucleus sampling. Change this or the temperature, not both.',
					},
				],
			},
		],
	};

	methods = {
		loadOptions: {
			getChatModels: modelLoader('chat'),
		},
	};

	async supplyData(this: ISupplyDataFunctions, itemIndex: number): Promise<SupplyData> {
		const credentials = await this.getCredentials('teamorouterApi');
		const modelName = this.getNodeParameter('model', itemIndex) as string;
		if (typeof modelName !== 'string' || modelName === '') {
			throw new NodeOperationError(
				this.getNode(),
				'No model selected. Pick one from the list or switch the field to expression mode and enter the model ID.',
			);
		}

		const options = this.getNodeParameter('options', itemIndex, {}) as ChatModelOptions;

		const modelKwargs: Record<string, unknown> = {};
		if (options.forceJsonResponse === true) modelKwargs.response_format = { type: 'json_object' };
		if (options.serviceTier === 'fast') modelKwargs.service_tier = 'fast';
		Object.assign(modelKwargs, parseExtraBody(options.extraBody, this.getNode()));

		const config: Record<string, unknown> = {
			apiKey: credentials.apiKey,
			model: modelName,
			configuration: { baseURL: normalizeBaseUrl(credentials.baseUrl as string) },
			timeout: typeof options.timeout === 'number' && options.timeout > 0 ? options.timeout : 600000,
			maxRetries: typeof options.maxRetries === 'number' ? options.maxRetries : 2,
			// Keep the plain Chat Completions endpoint unless the installed LangChain decides otherwise
			// (it always uses the Responses API for "gpt-5.6*" and "codex" IDs, which TeamoRouter supports too).
			useResponsesApi: false,
		};
		if (typeof options.temperature === 'number') config.temperature = options.temperature;
		if (typeof options.topP === 'number') config.topP = options.topP;
		if (typeof options.maxTokens === 'number' && options.maxTokens > 0) {
			config.maxTokens = options.maxTokens;
		}
		if (Object.keys(modelKwargs).length > 0) config.modelKwargs = modelKwargs;

		let model: unknown;
		try {
			const ChatOpenAi = loadChatOpenAi();
			model = new ChatOpenAi(config);
		} catch (error) {
			throw new NodeOperationError(this.getNode(), errorMessage(error));
		}

		const tracing = loadN8nLlmTracing(this);
		if (tracing !== undefined) {
			(model as { callbacks?: unknown[] }).callbacks = [tracing];
		}

		return { response: model };
	}
}