// AI tags and descriptions through any OpenAI-compatible chat API: DeepSeek by
// default, or OpenRouter, OpenAI, or a local server such as Ollama or LM Studio.
// The API key stays on the server.

const PROVIDERS = {
  deepseek: { label: 'DeepSeek', baseUrl: 'https://api.deepseek.com', model: 'deepseek-flash', prices: { input: 0.3, output: 1.2 } },
  openrouter: { label: 'OpenRouter', baseUrl: 'https://openrouter.ai/api/v1', model: '' },
  openai: { label: 'OpenAI', baseUrl: 'https://api.openai.com/v1', model: '' },
  custom: { label: 'Other (OpenAI-compatible)', baseUrl: '', model: '' },
};

const SYSTEM_PROMPT = `You catalogue 3D-printable models in a maker's library. Reply with JSON only, shaped {"tags": ["..."], "description": "..."}.
tags: 3 to 8 short lowercase tags someone would search for: what the object is, what it's for, its theme or style, and print traits (print-in-place, articulated, multicolor, needs supports) only when evident. Prefer singular nouns. When a tag already used in the library fits, use it instead of a new synonym. Never use generic tags like "3d print", "model", "stl" or "3mf".
description: one or two plain sentences on what the object is and what it's for. Don't invent sizes, print settings or claims.`;

// Added to the prompt only when a run may rename models.
const NAME_PROMPT = `
Also include "name": the model's name as a clear title. If the current name already says clearly what the model is, return it exactly as it is. Otherwise write a short title-case name (under 60 characters) saying what it is, using the picture and details: drop file-name leftovers (underscores, stray spaces, version numbers like "v4", "final", file extensions), fix typos, and remove site boilerplate like "Free 3D Print Model - MakerWorld". Keep designer, character or product names that are part of what it is.`;

const GENERIC_TAGS = new Set([
  '3d print', '3d printing', '3d printed', '3d printable', '3d model', 'model', 'print', 'printable', 'file',
  'stl', '3mf', 'obj', 'step', 'stp', 'gcode',
]);

class AiError extends Error {
  constructor(message, status, kind = 'http') {
    super(message);
    this.status = status;
    this.kind = kind; // http | network | timeout
  }
}

const sleep = (ms) => new Promise((resolve) => setTimeout(resolve, ms));

// Settings values (ai_provider, ai_base_url, …) -> a client config, filling the
// gaps from the provider's preset.
function configFrom(values = {}) {
  const provider = PROVIDERS[values.ai_provider] ? values.ai_provider : 'deepseek';
  const preset = PROVIDERS[provider];
  const price = (value, fallback) => (value !== undefined && value !== null && value !== '' && Number.isFinite(Number(value))
    ? Number(value) : fallback ?? null);
  return {
    provider,
    label: preset.label,
    baseUrl: String(values.ai_base_url || preset.baseUrl || '').trim().replace(/\/+$/, ''),
    apiKey: values.ai_api_key || '',
    model: String(values.ai_model || preset.model || '').trim(),
    sendImages: values.ai_send_images !== 'false',
    prices: {
      input: price(values.ai_price_input, preset.prices && preset.prices.input),
      output: price(values.ai_price_output, preset.prices && preset.prices.output),
    },
  };
}

// What still needs filling in before AI can run, or null.
function missingConfig(config) {
  if (!config.baseUrl) return 'Add the API address in Settings → AI.';
  if (!config.model) return 'Choose a model in Settings → AI.';
  // Local servers (Ollama, LM Studio) usually don't need a key.
  if (!config.apiKey && config.provider !== 'custom') return 'Add your API key in Settings → AI.';
  return null;
}

// "120 × 80 × 40 mm" from the biggest file's bounding box, if known.
function modelSize(model) {
  const dims = (model.files || [])
    .map((f) => f.bbox && [f.bbox.x ?? f.bbox.width, f.bbox.y ?? f.bbox.depth, f.bbox.z ?? f.bbox.height].map(Number))
    .filter((d) => d && d.every((n) => Number.isFinite(n) && n > 0))
    .sort((a, b) => b[0] * b[1] * b[2] - a[0] * a[1] * a[2])[0];
  return dims ? `${dims.map((n) => Math.round(n)).join(' × ')} mm` : null;
}

function modelSummary(model, knownTags = []) {
  const lines = [`Name: ${model.name}`];
  const files = (model.files || []).map((f) => f.originalName).filter(Boolean);
  if (files.length) lines.push(`Files: ${files.slice(0, 30).join(', ')}`);
  if (model.entryNames && model.entryNames.length) lines.push(`Inside archives: ${model.entryNames.slice(0, 40).join(', ')}`);
  if (model.source_site) lines.push(`Source: ${model.source_site}${model.designer ? `, by ${model.designer.name}` : ''}`);
  const size = modelSize(model);
  if (size) lines.push(`Size: ${size}`);
  if (model.tags && model.tags.length) lines.push(`Tags so far: ${model.tags.join(', ')}`);
  if (model.description && model.description.trim()) lines.push(`Description so far: ${model.description.trim().slice(0, 800)}`);
  if (knownTags.length) lines.push(`Tags already used in this library: ${knownTags.join(', ')}`);
  return lines.join('\n');
}

function buildMessages(model, { image = null, knownTags = [], suggestName = false } = {}) {
  const text = modelSummary(model, knownTags);
  const content = image
    ? [{ type: 'text', text }, { type: 'image_url', image_url: { url: image } }]
    : text;
  return [{ role: 'system', content: SYSTEM_PROMPT + (suggestName ? NAME_PROMPT : '') }, { role: 'user', content }];
}

function normalizeTags(value) {
  const list = Array.isArray(value) ? value : typeof value === 'string' ? value.split(',') : [];
  const tags = [];
  for (const raw of list) {
    const tag = String(raw).toLowerCase()
      .replace(/^#+/, '')
      .replace(/[_\s]+/g, ' ')
      .replace(/[^\p{L}\p{N} +&'-]/gu, '')
      .trim()
      .slice(0, 40)
      .trim();
    if (tag && !GENERIC_TAGS.has(tag) && !tags.includes(tag)) tags.push(tag);
  }
  return tags.slice(0, 8);
}

const comparable = (s) => String(s || '').toLowerCase().replace(/[^\p{L}\p{N}]+/gu, '');

// A suggested name, tidied; null when there isn't one or it's the current name
// written differently.
function cleanName(value, currentName) {
  if (typeof value !== 'string') return null;
  const name = value
    .replace(/^["'“”‘’]+|["'“”‘’]+$/g, '')
    .replace(/\.(stl|3mf|obj|fbx|step|stp|3dm|gcode|zip|7z|rar)$/i, '')
    .replace(/\s+/g, ' ')
    .trim()
    .slice(0, 80)
    .trim();
  return name && comparable(name) !== comparable(currentName) ? name : null;
}

// The model's reply -> { tags, description, name }. Tolerates code fences or
// prose around the JSON. name is only read when { currentName } is given (the
// prompt asked for one).
function parseReply(content, options = {}) {
  const text = String(content || '');
  const start = text.indexOf('{');
  const end = text.lastIndexOf('}');
  let data = null;
  if (start >= 0 && end > start) {
    try { data = JSON.parse(text.slice(start, end + 1)); } catch { /* handled below */ }
  }
  if (!data || typeof data !== 'object') throw new Error('The AI reply wasn’t the JSON asked for');
  const tags = normalizeTags(data.tags);
  const description = typeof data.description === 'string' ? data.description.trim().slice(0, 600) : '';
  if (!tags.length && !description) throw new Error('The AI reply had no tags or description');
  const name = Object.prototype.hasOwnProperty.call(options, 'currentName') ? cleanName(data.name, options.currentName) : null;
  return { tags, description, name };
}

function usageOf(usage) {
  return {
    prompt: Math.max(0, Math.round(Number(usage && usage.prompt_tokens) || 0)),
    completion: Math.max(0, Math.round(Number(usage && usage.completion_tokens) || 0)),
  };
}

// US dollars: what the provider reports (OpenRouter), else tokens × your prices
// per million tokens, else null when prices aren't known.
function costOf(usage, prices) {
  if (usage && typeof usage.cost === 'number') return usage.cost;
  if (!prices || prices.input == null || prices.output == null) return null;
  const { prompt, completion } = usageOf(usage);
  return (prompt * prices.input + completion * prices.output) / 1e6;
}

async function chat(config, body, { timeoutMs = 90000 } = {}) {
  const headers = { 'Content-Type': 'application/json' };
  if (config.apiKey) headers.Authorization = `Bearer ${config.apiKey}`;
  if (config.provider === 'openrouter') headers['X-Title'] = 'Printhive';

  let res;
  try {
    res = await fetch(`${config.baseUrl}/chat/completions`, {
      method: 'POST', headers, body: JSON.stringify(body), signal: AbortSignal.timeout(timeoutMs),
    });
  } catch (err) {
    if (err.name === 'TimeoutError') throw new AiError('The AI service took too long to answer', 0, 'timeout');
    throw new AiError(`Couldn't reach ${config.baseUrl}: ${(err.cause && err.cause.message) || err.message}`, 0, 'network');
  }
  const text = await res.text();
  let data = null;
  try { data = JSON.parse(text); } catch { /* not JSON */ }
  const detail = (data && data.error && (data.error.message || data.error)) || (data && data.message);
  if (!res.ok) throw new AiError(`${res.status}: ${detail || text.slice(0, 200) || res.statusText}`, res.status);
  // OpenRouter can report an upstream failure inside a 200.
  if (data && data.error) throw new AiError(String(detail), Number(data.error.code) || 502);
  if (!data || !Array.isArray(data.choices) || !data.choices.length) {
    throw new AiError('The AI service sent back something unexpected', 502);
  }
  return data;
}

// Tags and a description for one model. Adapts to what the model supports: if it
// refuses JSON mode or images, the request is retried without them
// (imageRejected tells the caller to stop sending images). Rate limits and
// server errors are retried with backoff.
async function describeModel(config, model, { image = null, knownTags = [], suggestName = false } = {}) {
  let useImage = Boolean(image);
  let useJson = true;
  let imageRejected = false;
  for (let attempt = 0; ; attempt++) {
    const body = {
      model: config.model,
      messages: buildMessages(model, { image: useImage ? image : null, knownTags, suggestName }),
      temperature: 0.2,
      max_tokens: 800,
    };
    if (useJson) body.response_format = { type: 'json_object' };
    if (config.provider === 'openrouter') body.usage = { include: true };
    try {
      const data = await chat(config, body);
      const message = data.choices[0].message || {};
      return {
        ...parseReply(message.content, suggestName ? { currentName: model.name } : {}),
        usage: usageOf(data.usage),
        cost: costOf(data.usage, config.prices),
        imageUsed: useImage,
        imageRejected,
      };
    } catch (err) {
      if (!(err instanceof AiError) || attempt >= 5) throw err;
      if (err.status === 400 || err.status === 415 || err.status === 422) {
        if (useImage && /image|vision|multimodal|modalit|content.?part|content type/i.test(err.message)) {
          useImage = false; imageRejected = true; continue;
        }
        if (useJson) { useJson = false; continue; }
        if (useImage) { useImage = false; imageRejected = true; continue; }
        throw err;
      }
      if (err.status === 429 || err.status >= 500 || err.kind === 'timeout') {
        await sleep(Math.min(20000, 1500 * 2 ** attempt));
        continue;
      }
      throw err;
    }
  }
}

// Errors that will fail every request the same way, so a run stops instead of
// burning through the queue. null for errors worth moving past.
function fatalMessage(err) {
  if (!(err instanceof AiError)) return null;
  if (err.status === 401 || err.status === 403) return `Your API key was rejected (${err.message})`;
  if (err.status === 402) return `Your AI account is out of credit (${err.message})`;
  if (err.status === 404) return `The model or API address wasn't found (${err.message})`;
  if (err.kind === 'network') return err.message;
  return null;
}

// A rough cost for tagging `count` models, from typical token counts.
function estimate(count, config) {
  const prompt = count * (config.sendImages ? 1400 : 500);
  const completion = count * 120;
  const cost = costOf({ prompt_tokens: prompt, completion_tokens: completion }, config.prices);
  return { promptTokens: prompt, completionTokens: completion, cost };
}

module.exports = {
  PROVIDERS, AiError, configFrom, missingConfig, buildMessages, parseReply, normalizeTags,
  costOf, describeModel, fatalMessage, estimate,
};