/**
 * OpenAI-kompatible Chat-API (OpenAI, Azure OpenAI, Ollama, LM Studio, vLLM, …).
 *
 * Umgebung:
 *   LANGUAGE_COURSE_LLM_API_KEY  oder OPENAI_API_KEY
 *   LANGUAGE_COURSE_LLM_BASE_URL (optional, z. B. http://127.0.0.1:11434/v1 für Ollama)
 *   LANGUAGE_COURSE_LLM_MODEL      (optional, Default: gpt-4o-mini)
 */
import OpenAI from 'openai';

export function getLlmEnv() {
    const apiKey =
        process.env.LANGUAGE_COURSE_LLM_API_KEY ||
        process.env.OPENAI_API_KEY ||
        '';
    const baseURL = process.env.LANGUAGE_COURSE_LLM_BASE_URL || undefined;
    const model = process.env.LANGUAGE_COURSE_LLM_MODEL || 'gpt-4o-mini';
    return { apiKey, baseURL, model };
}

export function isLlmConfigured() {
    return Boolean(getLlmEnv().apiKey);
}

export function getOpenAiClient() {
    const { apiKey, baseURL } = getLlmEnv();
    if (!apiKey) return null;
    return new OpenAI({
        apiKey,
        baseURL,
    });
}

/**
 * @param {import('openai').ChatCompletionMessageParam[]} messages
 * @param {{ model?: string; temperature?: number; maxTokens?: number }} [opts]
 */
export async function chatComplete(messages, opts = {}) {
    const client = getOpenAiClient();
    if (!client) {
        throw new Error(
            'Kein LLM konfiguriert: LANGUAGE_COURSE_LLM_API_KEY oder OPENAI_API_KEY setzen (siehe README).'
        );
    }
    const { model, temperature = 0.6, maxTokens = 2048 } = opts;
    const m = model || getLlmEnv().model;
    const res = await client.chat.completions.create({
        model: m,
        messages,
        temperature,
        max_tokens: maxTokens,
    });
    const text = res.choices[0]?.message?.content?.trim() || '';
    if (!text) {
        throw new Error('Leere Antwort vom Modell.');
    }
    return text;
}