/* ─── backend/utils/chatFreeEndpoint.js  (TOP-OF-FILE REPLACEMENT) ───────── */
import fs   from "fs/promises";
import path from "path";
import { fileURLToPath } from "url";

import { vectorSearch } from "./vectorSearch.js";

/* Resolve current directory ─────────────────────────────────────────────── */
const __filename = fileURLToPath(import.meta.url);
const __dirname  = path.dirname(__filename);

/* Directories ───────────────────────────────────────────────────────────── */
/*   repoRoot = “…/aptiva-dev1-app”               (one level up from backend/) */
const repoRoot   = path.resolve(__dirname, "..", "..");

/*   assetsDir = “…/aptiva-dev1-app/src/assets”   (where the JSONs live)     */
const assetsDir  = path.join(repoRoot, "src", "assets");

/*   FAQ SQLite DB (unchanged) */
const FAQ_PATH   = path.join(repoRoot, "backend", "user_profile.db");

/* Constants ─────────────────────────────────────────────────────────────── */
const FAQ_THRESHOLD = 0.80;
const HELP_TRIGGERS = ["help","error","bug","issue","login","password","support"];

/* Load tool manifests just once at boot ─────────────────────────────────── */
const BOT_TOOLS    = JSON.parse(
  await fs.readFile(path.join(assetsDir, "botTools.json"), "utf8")
);
const PAGE_TOOLMAP = JSON.parse(
  await fs.readFile(path.join(assetsDir, "pageToolMap.json"), "utf8")
);

/* ---------- helpers ---------- */
const classifyIntent = txt =>
  HELP_TRIGGERS.some(k => txt.toLowerCase().includes(k)) ? "support" : "guide";

const buildContext = (user = {}, page = "", intent = "guide") => {
  const { firstname = "User", career_situation = "planning" } = user;
  const mode = intent === "guide" ? "Aptiva Guide" : "Aptiva Support";
  return {
    system:
      `${mode} for page “${page}”. User: ${firstname}. Situation: ${career_situation}.` +
      (intent === "support"
        ? " Resolve issues quickly and end with: “Let me know if that fixed it.”"
        : "")
  };
};

const INTEREST_PLAYBOOK = `
### When the user is on **CareerExplorer** and no career tiles are visible
1. Explain there are two ways to begin:
   • Interest Inventory (7-minute, 60-question survey)  
   • Manual search (type a career in the “Search for Career” bar)
2. If the user chooses **Inventory**
   1. Tell them to click the green **“Start Interest Inventory”** button at the top of the page.  
   2. Explain the answer keys (A = Agree, U = Unsure, D = Dislike) and that each click advances to the next question.  
   3. Wait while the UI runs the survey. **Do NOT collect answers inside chat.**  
   4. When career tiles appear, say: “Great! Your matches are listed below. Click any blue tile for details.”
3. If the user chooses **Manual search**
   1. Tell them to click the **search bar** and type at least three letters.  
   2. After they pick a suggestion, remind them to click the blue tile to open its details.
4. **Never call \`getONetInterestQuestions\` or \`submitInterestInventory\` yourself.**
5. After tiles appear, you may call salary, projection, skills, or other data tools to answer follow-up questions.
`;

const CAREER_EXPLORER_FEATURES = `
### Aptiva Career Explorer — features you can (and should) guide the user to
• **Search bar** – type ≥3 letters, pick a suggestion, then click the blue tile.  
• **Interest Inventory** – green “Start Interest Inventory” button (60 Qs, 7 min).  
• **Blue career tile** – opens a modal with:
  • *Overview* tab (description & “Day-in-the-Life” tasks)  
  • *Salary* tab (regional & national percentiles)  
  • *Projections* tab (state + national growth)  
  • *AI Risk* tab (Aptiva’s proprietary impact level)  
• **Add to Comparison** button – builds a side-by-side table above the tiles.  
• **Filters** dropdowns – “Preparation Level” (Job Zone 1-5) and “Fit Level” (Best / Great / Good).  
• **Reload Career Suggestions** – re-runs your interest-based match with updated filters.  
• **Select for Education** – jumps to Educational Programs with the career’s CIP codes.  
• When users ask:
  • “Which is better?” → tell them to add both careers and open the comparison table.  
  • “What’s a day in the life?” → tell them to open the modal’s *Overview* tab.  
  • “How do I plan education?” → tell them to click *Select for Education*.  
• Use tools when numeric data is needed:
  • \`getSalaryData\`, \`getEconomicProjections\`, \`getAiRisk\`, \`getCareerDetails\`.  
• You may call \`addCareerToComparison\` or \`openCareerModal\`
  **only after the user has clearly asked you to do so** (e.g. “Yes, add it for me”).
  Always confirm first.
`;

/* ----------------------------------------------------------------------------
   FACTORY: registers POST /api/chat/free on the passed-in Express app
----------------------------------------------------------------------------- */
export default function chatFreeEndpoint(
  app,
  {
    openai,
    chatLimiter,
    userProfileDb,
    authenticateUser = (_req, _res, next) => next()
  }
) {
  /* -------- support-intent tool handlers now in scope -------- */
  const toolResolvers = {
    async clearLocalCache() { return { status: "ok" }; },

    async openTicket({ summary = "", user = {} }) {
      try {
        await userProfileDb.run(
          `INSERT INTO support_tickets (user_id, summary, created_at)
             VALUES (?,?,datetime('now'))`,
          [user.id || 0, summary]
        );
        return { ticket: "created" };
      } catch (err) {
        console.error("[openTicket] DB error:", err);
        return { ticket: "error" };
      }
    },

    async pingStatus() {
      try {
        await userProfileDb.get("SELECT 1");
        return { status: "healthy" };
      } catch {
        return { status: "db_error" };
      }
    },

        /*  NEW — forward any UI tool-call to the browser via SSE  */
         async __forwardUiTool(name, argsObj, res) {
  res.write(`__tool:${name}:${JSON.stringify(argsObj)}\n`);
       if (typeof res.flush === "function") res.flush();
       return { forwarded: true };
     },
  };

  /* --------------------  UI TOOLS (CareerExplorer only)  -------------------- */
const UI_TOOLS = [
  {
    type: "function",
    function: {
      name: "addCareerToComparison",
      description: "Add a career tile to the comparison table in Career Explorer",
      parameters: {
        type: "object",
        properties: { socCode: { type: "string" } },
        required: ["socCode"]
      }
    }
  },
  {
    type: "function",
    function: {
      name: "openCareerModal",
      description: "Open the Career-details modal for the given SOC code",
      parameters: {
        type: "object",
        properties: { socCode: { type: "string" } },
        required: ["socCode"]
      }
    }
  }
];


  const SUPPORT_TOOLS = [
 {
    type: "function",
    function: {
      name: "clearLocalCache",
      description: "Instruct front-end to purge its cache",
      parameters: { type: "object", properties: {} }
    }
  },
  {
    type: "function",
    function: {
      name: "openTicket",
      description: "Create a support ticket",
      parameters: {
        type: "object",
        properties: { summary: { type: "string" } },
        required: ["summary"]
      }
    }
  },
  {
    type: "function",
    function: {
      name: "pingStatus",
      description: "Ping DB/health",
      parameters: { type: "object", properties: {} }
    }
  }
];

  /* -----------------------------  ROUTE  ----------------------------- */
  app.post(
    "/api/chat/free",
    chatLimiter,
    authenticateUser,
    async (req, res) => {
      try {
        const { prompt = "", chatHistory = [], pageContext = "" } = req.body || {};
        if (!prompt.trim()) return res.status(400).json({ error: "Empty prompt" });

        /* ---------- 0️⃣  FAQ fast-path ---------- */
        let faqHit = null;
        try {
          const { data } = await openai.embeddings.create({
            model: "text-embedding-3-small",
            input: prompt
          });
          const hits = await vectorSearch(FAQ_PATH, data[0].embedding, 1);
          if (hits.length && hits[0].score >= FAQ_THRESHOLD) faqHit = hits[0];
        } catch { /* silently ignore if table/function missing */ }

        if (faqHit) return res.json({ answer: faqHit.answer });
        /* --------------------------------------- */

        const intent     = classifyIntent(prompt);
       let { system } = buildContext(req.user || {}, pageContext, intent);
       if (pageContext === "CareerExplorer") {
         system += INTEREST_PLAYBOOK + CAREER_EXPLORER_FEATURES;
       }

       /* ── Build tool list for this request ────────────────────── */
       let tools = intent === "support" ? [...SUPPORT_TOOLS] : [];
       const uiNamesForPage = PAGE_TOOLMAP[pageContext] || [];
       for (const def of BOT_TOOLS) {
         if (uiNamesForPage.includes(def.name)) {
           tools.push({ type: "function", function: def });
         }
       }
          const messages = [
            { role: "system", content: system },
            ...chatHistory,
            { role: "user",   content: prompt }
          ];

        const chatStream = await openai.chat.completions.create({
          model       : "gpt-4o-mini",
          stream      : true,
          messages,
          tools,
          tool_choice : tools.length ? "auto" : undefined
        });

               /* ── keep state while a tool call streams in ─────────────── */
        let pendingName  = null;   // addCareerToComparison
        let pendingArgs  = "";     // '{"socCode":"15-2051"}'

        for await (const part of chatStream) {
          const delta = part.choices?.[0]?.delta || {};

          /* 1️⃣  handle function / tool calls immediately */
          if (delta.tool_calls?.length) {
            const callObj = delta.tool_calls[0];
                      const fn        = callObj.function || {};
            if (fn.name)           pendingName = fn.name;          // keep first
            if (fn.arguments)      pendingArgs += fn.arguments;    // append

            // Try to parse the JSON only when it’s complete
            let args;
            try { args = JSON.parse(pendingArgs); } catch { continue; }
            /* run the resolver */
            let result;
                      if (toolResolvers[pendingName]) {
  result = await toolResolvers[pendingName]({ ...args, user: req.user }, res);
 } else {
  result = await toolResolvers.__forwardUiTool(pendingName, args, res);
 }
            /* feed the result back to the model so it can finish */
            const followStream = await openai.chat.completions.create({
              model: "gpt-4o-mini",
              stream: true,
              messages: [
                ...messages,
                { role: "assistant", tool_call_id: callObj.id, content: null },
                {
                  role: "tool",
                  tool_call_id: callObj.id,
                  content: JSON.stringify(result)
                }
              ]
            });

            /* stream the follow-up answer */
            for await (const follow of followStream) {
              const txt = follow.choices?.[0]?.delta?.content;
              if (txt) res.write(txt);
            }
            res.end();
            return;            // ✔ done
          }

           /* 2️⃣  normal text tokens */
        if (!delta.tool_calls && delta.content) {
          res.write(delta.content);   // SSE-safe
        }
      }                       // ← closes the for-await loop

      res.end();              // finished without tools
    } catch (err) {           // ← closes the try block above
      console.error("/api/chat/free error:", err);
  if (!res.headersSent) {
    res.status(500).json({ error: "Internal server error" });
  }
    }
  }                           // ← closes the async (req,res) => { … }
);                            // ← closes app.post(…)
}                             // ← closes export default chatFreeEndpoint