import type { Plugin, PreviewServer, ViteDevServer } from "vite";
import { substances } from "../src/data/substances";
import https from "node:https";
import { URL } from "node:url";

type Env = Record<string, string | undefined>;

class UpstreamError extends Error {
  status: number;
  upstreamMessage?: string;
  constructor(status: number, message: string, upstreamMessage?: string) {
    super(message);
    this.status = status;
    this.upstreamMessage = upstreamMessage;
  }
}

function readBody(req: any): Promise<string> {
  return new Promise((resolve, reject) => {
    let data = "";
    req.on("data", (chunk: any) => {
      data += chunk;
    });
    req.on("end", () => resolve(data));
    req.on("error", reject);
  });
}

function sendJson(res: any, status: number, payload: unknown) {
  res.statusCode = status;
  res.setHeader("Content-Type", "application/json; charset=utf-8");
  res.end(JSON.stringify(payload));
}

function pickSubstances(substanceIds: string[]) {
  const uniqueIds = Array.from(new Set(substanceIds)).filter(Boolean);
  return uniqueIds
    .map((id) => substances.find((s) => s.id === id))
    .filter(Boolean);
}

function buildPrompt(args: {
  temperatureC: number;
  substances: Array<{
    id: string;
    name: string;
    formula: string;
    state: string;
    hazard: string;
    description: string;
  }>;
}) {
  const lines = args.substances.map((s) =>
    [
      `- id: ${s.id}`,
      `  nom: ${s.name}`,
      `  formule: ${s.formula}`,
      `  etat: ${s.state}`,
      `  danger: ${s.hazard}`,
      `  description: ${s.description}`,
    ].join("\n"),
  );

  const system =
    "Tu es un assistant de laboratoire de chimie. " +
    "Decris l'observation du melange en etant TRES CONCIS (MAXIMUM 2 a 3 phrases), en allant droit au but et en enlevant tous les details inutiles. Inclus les rappels de securite si necessaire. " +
    "Donne ensuite l'equation correspondante. " +
    "Termine avec une application pratique de ce melange dans la vie courante ou l'industrie (ex: 'ce melange sert a la fabrication de detergent'). " +
    "Important: Tu dois repondre UNIQUEMENT sous ce format textuel exact (sans markdown, sans blabla):\n" +
    "Observation: <tes 2 a 3 phrases ici>\n" +
    "Equation: <equation chimique avec -> ou -> ou →>\n" +
    "Application: <1 a 2 phrases sur l'utilite pratique>";

  const user =
    [
      "Contexte:",
      `- Temperature du milieu: ${args.temperatureC} degres Celsius`,
      `- Substances presentes (a melanger):`,
      ...lines,
      "",
      "Format attendu strictement: ",
      "Observation: <...>",
      "Equation: <...>",
      "Application: <...>"
    ].join("\n");

  return { system, user };
}

function countSentences(text: string) {
  // Heuristic: count sentence terminators.
  const matches = text.match(/[.!?](\s|$)/g);
  return matches ? matches.length : 0;
}

function normalizeOneParagraph(text: string) {
  return (text || "")
    .replace(/\s+/g, " ")
    .replace(/\u00a0/g, " ")
    .trim();
}

function validateObservation(args: {
  text: string;
  temperatureC: number;
  hasHazard: boolean;
}) {
  const t = args.text.trim();

  if (!/^Observation\s*:/i.test(t)) return { ok: false, reason: "Ne commence pas par Observation:" };
  if (!/Equation\s*:/i.test(t)) return { ok: false, reason: "equation manquante (Equation:)" };
  if (!/Application\s*:/i.test(t)) return { ok: false, reason: "application manquante (Application:)" };

  const parts = t.split(/Equation\s*:/i);
  const observation = parts[0].replace(/^Observation\s*:/i, '').trim();
  const lowerParts = parts[1].split(/Application\s*:/i);
  const equation = lowerParts[0].trim();
  const application = lowerParts[1] ? lowerParts[1].trim() : "";

  if (observation.length < 10) return { ok: false, reason: "observation trop courte" };
  const sentenceCount = countSentences(observation);
  if (sentenceCount > 5) return { ok: false, reason: `observation trop longue (${sentenceCount} phrases)` };
  if (equation.length < 2) return { ok: false, reason: "equation invalide" };
  if (application.length < 10) return { ok: false, reason: "application invalide ou trop courte" };

  if (args.hasHazard && !/secur|prud|attention|protection|danger|gants|lunettes|corros/i.test(observation)) {
    // on l'accepte tout de meme
  }

  return { ok: true, reason: null, parsed: { observation, equation, application } };
}

async function httpsPostJson(args: {
  url: string;
  headers: Record<string, string>;
  body: unknown;
}): Promise<{ status: number; statusText: string; text: string; json: any }> {
  const u = new URL(args.url);
  const bodyStr = JSON.stringify(args.body);

  return new Promise((resolve, reject) => {
    const req = https.request(
      {
        protocol: u.protocol,
        hostname: u.hostname,
        port: u.port ? Number(u.port) : undefined,
        path: `${u.pathname}${u.search}`,
        method: "POST",
        headers: {
          ...args.headers,
          "Content-Length": Buffer.byteLength(bodyStr).toString(),
        },
      },
      (res) => {
        let data = "";
        res.setEncoding("utf8");
        res.on("data", (chunk) => (data += chunk));
        res.on("end", () => {
          let parsed: any = null;
          try {
            parsed = data ? JSON.parse(data) : null;
          } catch {
            parsed = null;
          }
          resolve({
            status: res.statusCode || 0,
            statusText: res.statusMessage || "",
            text: data,
            json: parsed,
          });
        });
      },
    );

    req.on("error", reject);
    req.write(bodyStr);
    req.end();
  });
}

function extractResponsesText(data: any): string | null {
  if (typeof data?.output_text === "string" && data.output_text.trim()) {
    return data.output_text.trim();
  }

  const chunks: string[] = [];
  const outputs = Array.isArray(data?.output) ? data.output : [];
  for (const out of outputs) {
    // OpenAI Responses often returns items with type "message" and a content array.
    const content = Array.isArray(out?.content) ? out.content : [];
    for (const part of content) {
      if (part?.type === "output_text" && typeof part?.text === "string") chunks.push(part.text);
      if (part?.type === "text" && typeof part?.text === "string") chunks.push(part.text);
    }

    // Some providers nest content under message objects.
    const msgContent = Array.isArray(out?.message?.content) ? out.message.content : [];
    for (const part of msgContent) {
      if (part?.type === "output_text" && typeof part?.text === "string") chunks.push(part.text);
      if (part?.type === "text" && typeof part?.text === "string") chunks.push(part.text);
    }
  }

  const text = chunks.join("\n").trim();
  return text || null;
}

async function callGroqChatCompletionsText(args: {
  apiKey: string;
  model: string;
  system: string;
  user: string;
}) {
  let resp: { status: number; statusText: string; text: string; json: any };
  try {
    resp = await httpsPostJson({
      url: "https://api.groq.com/openai/v1/chat/completions",
      headers: {
        "Content-Type": "application/json",
        Authorization: `Bearer ${args.apiKey}`,
      },
      body: {
        model: args.model,
        messages: [
          { role: "system", content: args.system },
          { role: "user", content: args.user },
        ],
        temperature: 0.2,
        max_tokens: 350,
      },
    });
  } catch (e: any) {
    const code = e?.code ? String(e.code) : "NETWORK_ERROR";
    const msg = e?.message ? String(e.message) : "Network error";
    throw new UpstreamError(0, `Network error calling Groq: ${code} ${msg}`);
  }

  if (resp.status < 200 || resp.status >= 300) {
    const upstreamMessage = resp?.json?.error?.message || resp?.json?.message;
    const msg = upstreamMessage
      ? `Groq API error ${resp.status}: ${upstreamMessage}`
      : `Groq API error ${resp.status}: ${resp.statusText || "Unknown"}`;
    throw new UpstreamError(resp.status, msg, upstreamMessage);
  }

  const data = resp.json;
  if (!data || typeof data !== "object") {
    throw new UpstreamError(502, "Groq Chat Completions returned non-JSON response");
  }

  const choice = Array.isArray((data as any).choices) ? (data as any).choices[0] : undefined;
  const msg = choice?.message;

  // Standard OpenAI-compatible content.
  const content = msg?.content;
  if (typeof content === "string" && content.trim()) return content.trim();

  // Legacy completion-style field (some providers/models).
  const choiceText = choice?.text;
  if (typeof choiceText === "string" && choiceText.trim()) return choiceText.trim();

  // Sometimes providers include a delta even in non-stream mode.
  const deltaContent = choice?.delta?.content;
  if (typeof deltaContent === "string" && deltaContent.trim()) return deltaContent.trim();

  // Some providers can return content as an array of parts.
  if (Array.isArray(content)) {
    const parts = content
      .map((p: any) => (typeof p?.text === "string" ? p.text : ""))
      .filter(Boolean);
    const joined = parts.join("\n").trim();
    if (joined) return joined;
  }

  // Some providers return content as an object part (not array).
  if (content && typeof content === "object") {
    const objText = (content as any).text;
    if (typeof objText === "string" && objText.trim()) return objText.trim();
  }

  // Refusal format (treat as recoverable so the next model can be tried).
  const refusal = msg?.refusal;
  if (typeof refusal === "string" && refusal.trim()) {
    throw new UpstreamError(422, "Model refusal", refusal.trim());
  }

  // Some models put content into a "reasoning" field and leave content empty.
  // Treat as recoverable; the caller will try another model.
  const reasoning = msg?.reasoning;
  if (typeof reasoning === "string" && reasoning.trim()) {
    const candidate = normalizeOneParagraph(reasoning);
    if (/equation\s*:/i.test(candidate) && /application\s*:/i.test(candidate) && /(->|→)/.test(candidate)) {
      return candidate;
    }
    throw new UpstreamError(422, "Model returned reasoning without final content");
  }

  // Tool calls without text (recoverable, try next model).
  const toolCalls = msg?.tool_calls;
  if (Array.isArray(toolCalls) && toolCalls.length > 0) {
    const sample = JSON.stringify(toolCalls[0]).slice(0, 500);
    throw new UpstreamError(422, "Model returned tool_calls with no text", sample);
  }

  const keys = Object.keys(data).slice(0, 12).join(",");
  // Log a small sample for debugging without returning it to the client.
  try {
    console.error("[groq chat] empty content choice sample:", JSON.stringify(choice).slice(0, 900));
  } catch {
    // ignore
  }
  throw new UpstreamError(502, `Groq Chat Completions returned no message content (keys: ${keys})`);
}

async function callGroqChatCompletion(args: {
  apiKey: string;
  model: string;
  system: string;
  user: string;
}) {
  let resp: { status: number; statusText: string; text: string; json: any };
  try {
    resp = await httpsPostJson({
      url: "https://api.groq.com/openai/v1/responses",
      headers: {
        "Content-Type": "application/json",
        Authorization: `Bearer ${args.apiKey}`,
      },
      body: {
        model: args.model,
        instructions: args.system,
        input: args.user,
        temperature: 0.2,
        max_output_tokens: 350,
      },
    });
  } catch (e: any) {
    const code = e?.code ? String(e.code) : "NETWORK_ERROR";
    const msg = e?.message ? String(e.message) : "Network error";
    throw new UpstreamError(0, `Network error calling Groq: ${code} ${msg}`);
  }

  if (resp.status < 200 || resp.status >= 300) {
    const upstreamMessage = resp?.json?.error?.message || resp?.json?.message;
    const msg = upstreamMessage
      ? `Groq API error ${resp.status}: ${upstreamMessage}`
      : `Groq API error ${resp.status}: ${resp.statusText || "Unknown"}`;
    throw new UpstreamError(resp.status, msg, upstreamMessage);
  }

  const data: any = resp.json;
  const extracted = extractResponsesText(data);
  if (extracted) return extracted;

  // Some models/providers may not support Responses output_text cleanly; fallback to Chat Completions.
  try {
    return await callGroqChatCompletionsText(args);
  } catch (e) {
    // Preserve upstream errors for model fallback logic.
    throw e;
  }
}

function parseModelList(env: Env) {
  const rawList = (env.GROQ_MODELS || process.env.GROQ_MODELS || "").trim();
  const single = (env.GROQ_MODEL || process.env.GROQ_MODEL || "").trim();

  const fromList = rawList
    ? rawList
      .split(",")
      .map((s) => s.trim())
      .filter(Boolean)
    : [];

  const seed = fromList.length > 0 ? fromList : single ? [single] : [];
  const deduped: string[] = [];
  const seen = new Set<string>();
  for (const m of seed) {
    if (seen.has(m)) continue;
    seen.add(m);
    deduped.push(m);
  }
  return deduped;
}

function defaultModelList() {
  // Ordered fallback list (deduped).
  return [
    "openai/gpt-oss-120b",
    "llama-3.1-8b-instant",
    "llama-3.3-70b-versatile",
    "openai/gpt-oss-20b",
  ];
}

function filterGenerationModels(models: string[]) {
  // "safeguard" models often return refusals or reasoning-only payloads; avoid them for generation.
  const filtered = models.filter((m) => !/safeguard/i.test(m));
  return filtered.length > 0 ? filtered : models;
}

function shouldFallbackOnUpstreamError(err: UpstreamError) {
  // Do not fallback on auth errors: all models will fail the same way.
  if (err.status === 401 || err.status === 403) return false;

  // Rate limit / quota or temporary outages: try another model.
  if (err.status === 429) return true;
  if (err.status === 0) return true; // network error (might be transient)
  if (err.status >= 500 && err.status <= 599) return true;

  // Model unavailable / bad request: often model-specific.
  if (err.status === 400 || err.status === 404) return true;

  // Validation/refusal-type errors can be model-specific.
  if (err.status === 422) return true;

  return false;
}

function addRoutes(server: ViteDevServer | PreviewServer, env: Env) {
  server.middlewares.use("/api/ai/ping", async (req: any, res: any, next: any) => {
    if (req.method !== "GET") {
      res.statusCode = 405;
      res.setHeader("Allow", "GET");
      return res.end();
    }

    const apiKey = (env.GROQ_API_KEY || process.env.GROQ_API_KEY || "").trim();
    const configured = parseModelList(env);
    const models = configured.length > 0 ? configured : defaultModelList();
    const generationModels = filterGenerationModels(models);

    return sendJson(res, 200, {
      ok: true,
      hasGroqApiKey: !!apiKey && !apiKey.includes("your_groq_api_key_here"),
      groqApiKeyPrefix: apiKey ? apiKey.slice(0, 4) : null,
      models,
      generationModels,
      node: process.version,
    });
  });

  server.middlewares.use("/api/ai/mix", async (req: any, res: any, next: any) => {
    if (req.method !== "POST") {
      res.statusCode = 405;
      res.setHeader("Allow", "POST");
      return res.end();
    }

    const apiKey = (env.GROQ_API_KEY || process.env.GROQ_API_KEY || "").trim();
    if (!apiKey || apiKey.includes("your_groq_api_key_here")) {
      return sendJson(res, 500, {
        error: "GROQ_API_KEY manquant. Ajoute-le dans .env (ne le commit pas).",
      });
    }

    const triedModels: string[] = [];
    let lastModel: string | null = null;

    try {
      const body = await readBody(req);
      const parsed = body ? JSON.parse(body) : {};
      const substanceIds: string[] = Array.isArray(parsed?.substanceIds) ? parsed.substanceIds : [];
      const temperatureC = Number(parsed?.temperatureC);

      const providedSubstances: any[] = Array.isArray(parsed?.substances) ? parsed.substances : [];
      const picked = (providedSubstances.length >= 2 ? providedSubstances : pickSubstances(substanceIds)) as any[];
      if (picked.length < 2) {
        return sendJson(res, 400, { error: "substances/substanceIds doit contenir au moins 2 substances valides" });
      }

      const safeTemp = Number.isFinite(temperatureC) ? temperatureC : 20;
      const { system, user } = buildPrompt({
        temperatureC: safeTemp,
        substances: picked.map((s: any) => ({
          id: s.id,
          name: s.name,
          formula: s.formula,
          state: s.state,
          hazard: s.hazard,
          description: s.description,
        })),
      });

      const configured = parseModelList(env);
      const models = configured.length > 0 ? configured : defaultModelList();
      const generationModels = filterGenerationModels(models);

      let lastErr: unknown = null;
      const hasHazard = picked.some((s: any) => s.hazard && s.hazard !== "none");

      for (const model of generationModels) {
        triedModels.push(model);
        lastModel = model;
        let lastValidation: { ok: boolean; reason: string | null } | null = null;

        for (let attempt = 1; attempt <= 2; attempt++) {
          try {
            const attemptUser =
              attempt === 1
                ? user
                : `${user}\n\nLe texte precedent ne respecte pas les contraintes (${lastValidation?.reason || "incomplet"}). Regenerate en respectant STRICTEMENT le format attendu sans sauts de lignes et sans details.`;

            let text = await callGroqChatCompletion({ apiKey, model, system, user: attemptUser });
            text = normalizeOneParagraph(text);
            const v = validateObservation({ text, temperatureC: safeTemp, hasHazard });
            lastValidation = v as { ok: boolean; reason: string | null };
            if (v.ok) return sendJson(res, 200, { text: (v as any).parsed, modelUsed: model, triedModels });
          } catch (e: any) {
            lastErr = e;
            if (e instanceof UpstreamError) {
              if (!shouldFallbackOnUpstreamError(e)) throw e;
              // Upstream error: do not keep retrying the same model; try next.
              break;
            }
            throw e;
          }
        }

        // Model responded but didn't meet quality constraints twice: try next model.
        lastErr = lastErr || new UpstreamError(400, `Validation failed for model ${model}`, lastValidation?.reason || "validation failed");
      }

      // All models failed.
      if (lastErr instanceof UpstreamError) throw lastErr;
      throw new Error("All models failed");
    } catch (err: any) {
      const message = err?.message || "Erreur lors de la generation IA";

      // Avoid leaking secrets; log the error for debugging.
      console.error("[/api/ai/mix] error:", message);

      if (err instanceof UpstreamError) {
        if (err.status === 401 || err.status === 403) {
          return sendJson(res, 401, { error: "API key Groq invalide ou non autorisee" });
        }
        if (err.status === 429) {
          return sendJson(res, 429, { error: "Quota/limite Groq atteinte (429). Reessaye plus tard." });
        }

        // Pass through common client errors to make debugging actionable.
        if (err.status >= 400 && err.status < 500) {
          return sendJson(res, err.status, {
            error: message,
            triedModels,
            lastModel,
          });
        }

        return sendJson(res, 502, {
          error: "Erreur upstream Groq lors de la generation IA",
          details: message,
          triedModels,
          lastModel,
        });
      }

      // Local server-side error (ex: Node too old -> fetch undefined, JSON parse, etc.)
      return sendJson(res, 500, {
        error:
          "Erreur serveur /api/ai/mix (pas une reponse Groq). Verifie la console serveur et Node >= 18.",
        details: message,
        triedModels,
        lastModel,
      });
    }
  });
}

export function aiMixMiddleware(env: Env): Plugin {
  return {
    name: "ai-mix-middleware",
    configureServer(server) {
      addRoutes(server, env);
    },
    configurePreviewServer(server) {
      addRoutes(server, env);
    },
  };
}