const { getEnv, UTILITY } = require ('@nexusai/shared')

const UTILITY_URL = getEnv('UTILITY_URL', UTILITY.DEFAULT_URL);
const UTILITY_MODEL = getEnv('UTILITY_MODEL', UTILITY.DEFAULT_MODEL);

// Background task inference (extraction/summarization).  Uses ollama's /api/chat
// so the model's own prompt template is server-side, no need for ChatML
async function utilityComplete({
    system,
    user,
    json = false,
    temperature,
    maxTokens
}) {
    const messages = [];
    if(system) messages.push({ role: 'system', content: system});
    messages.push ({role: 'user', content: user});
    
    const res = await fetch (`${UTILITY_URL}/api/chat`, {
        method: 'POST',
        headers: { 'Content-Type': 'application/json'},
        body: JSON.stringify({
            model: UTILITY_MODEL,
            messages,
            stream: false,
            ...(json && {format: 'json' }),
            options: {
                temperature: temperature ?? UTILITY.TEMPERATURE,
                num_predict: maxTokens ?? UTILITY.MAX_TOKENS,
            },
        }),
        signal: AbortSignal.timeout(UTILITY.TIMEOUT_MS),
    });

    if (!res.ok) throw new Error(`Utility backend responded ${res.status}`);
    const data = await res.json();

    return {
        text: (data.message?.content ?? '').trim(),
        model: data.model,
    }
}

module.exports = { utilityComplete};