dev1/backend/utils/chatFreeEndpoint.js

/* ─── 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";
import { fuzzyCareerLookup } from "./fuzzyCareerLookup.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.”"
        : "")
  };
};

/** Returns a \n-joined bullet list of banner + page tasks */
const taskListForPage = (page = "", isPremium = false) => {
  const banner = (SUPPORT_TASKS.global_banner || [])
    // hide the “Upgrade” action for premium users
    .filter(t => isPremium || t.id !== "GN-07");

  const pageTasks = SUPPORT_TASKS[page] || [];
  return [...banner, ...pageTasks]
    .map(t => `• ${t.label}`)
    .join("\n");
};

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 **Interest Inventory**
   1. Tell them to open the Interest Inventory from the top by Clicking "Find Your Career" then "Interest Inventory".  
   2. Explain the answer keys (A = Agree, U = Unsure, D = Dislike); each click moves to the next question.  
   3. Wait while the UI runs the survey (do **not** collect answers in chat).  
   4. When the survey finishes, blue career tiles appear; tell them to click any tile to open its detail modal.
3. If the user chooses **Career Search**
3. If the user chooses **Manual search**
   1. Tell them to click the **search bar** and type at least three letters.  
   2. When the suggestion list appears, they should select the desired career.  
   3. A detail modal opens automatically — no blue tile in this flow.
4. After a modal is open, you can guide them to salary, projections, AI-risk, etc.
`;

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*.   
`;

const SUPPORT_TASKS = JSON.parse(
  await fs.readFile(
    path.join(repoRoot, "src", "ai", "agent_support_reference.json"),
    "utf8"
  )
);
/* ----------------------------------------------------------------------------
   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" };
      }
    },

  };

  
  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 {
         res.writeHead(200, {
          "Content-Type": "text/plain; charset=utf-8",
          "Cache-Control": "no-cache",
          Connection     : "keep-alive",
          "X-Accel-Buffering": "no"
        });
        res.flushHeaders?.();

        const sendChunk = (txt = "") => { res.write(txt); res.flush?.(); };

        const { prompt = "", chatHistory = [], pageContext = "", snapshot = {} } = 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);

      /* ---------- system-prompt scaffold ---------- */
        let { system } = buildContext(req.user || {}, pageContext, intent);

        /* 1) Add master playbooks per page (optional) */
        if (pageContext === "CareerExplorer") {
          system += INTEREST_PLAYBOOK + CAREER_EXPLORER_FEATURES;
        }

        /* 2) Append task catalogue so the bot can describe valid actions */
        const isPremium = req.user?.plan_type === "premium";
        system +=
          "\n\n### What the user can do on this screen\n" +
          taskListForPage(pageContext, isPremium) +
          "\n\n(Remember: do not click for the user; only explain the steps.)";

          const modalPayload = snapshot?.modalCtx;

          if (modalPayload) {
            const {
              socCode     = "n/a",
              title       = "n/a",
              aiRisk      = "n/a",
              salary      = {},
              projections = {},
              description = {},
              tasks       = []
            } = modalPayload;

            system +=
              `\n\n### Current career in focus\n` +
              `SOC: ${socCode} | Title: ${title}\n` +
              `AI-risk: ${aiRisk}\n` +
              `Median salary – regional: $${salary.regional ?? "n/a"}, ` +
              `national: $${salary.national ?? "n/a"}\n` +
              `Projections: ${JSON.stringify(projections)}` +
              `Description: ${description}\n` +
              `Key tasks: ${tasks.slice(0,5).join("; ")}\n`;
          }

       /* ── Build tool list for this request ────────────────────── */
      const tools = [...SUPPORT_TOOLS];   // guidance mode → support-only;
          let 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,
        });

for await (const part of chatStream) {
    const txt = part.choices?.[0]?.delta?.content;
    if (txt) sendChunk(txt);
  }

  // tell the front-end we are done and close the stream
  res.write("\n");
res.end();                                 
                        
              
    } catch (err) {           
      console.error("/api/chat/free error:", err);
  if (!res.headersSent) {
    res.status(500).json({ error: "Internal server error" });
  }
    }
  }                          
);               
}