pettalk/pettalk-server-new.ts

import express from "express";
import path from "path";
import { createServer as createViteServer } from "vite";
import { GoogleGenAI } from "@google/genai";
import { defaultMLProvider } from "./src/lib/mlProvider";
import { Pet } from "./src/types";
import { authMiddleware } from "./src/auth/middleware";
import authRouter from "./src/auth/routes";

async function startServer() {
  const app = express();
  const PORT = 3000;

  app.use(express.json({ limit: "10mb" }));

  // Auth middleware — protects /api/* except register, login, health
  app.use(authMiddleware);

  // Auth routes (register, login, me)
  app.use("/api", authRouter);

  // API Routes
  app.get("/api/health", (_req, res) => {
    res.json({ status: "ok", app: "PetTalk", timestamp: new Date().toISOString() });
  });

  /**
   * Analyze Pet Signal API endpoint.
   * Leverages Gemini API when GEMINI_API_KEY is available, or uses local ML Provider.
   */
  app.post("/api/analyze", async (req, res) => {
    try {
      const { pet, selectedZoneId, audio, video, customNote } = req.body as {
        pet: Pet;
        selectedZoneId?: string;
        audio?: any;
        video?: any;
        customNote?: string;
      };

      if (!pet) {
        return res.status(400).json({ error: "Pet profile is required for analysis." });
      }

      // Base ML prediction
      const baseResult = defaultMLProvider.combineSignals({
        pet,
        timeOfDay: new Date().toLocaleTimeString([], { hour: '2-digit', minute: '2-digit' }),
        selectedZoneId,
        audio,
        video,
        customNote
      });

      // If GEMINI_API_KEY is configured, enrich interpretation reasoning with Gemini
      if (process.env.GEMINI_API_KEY) {
        try {
          const ai = new GoogleGenAI({ apiKey: process.env.GEMINI_API_KEY });
          const zoneObj = pet.homeZones.find(z => z.id === selectedZoneId) || pet.homeZones[0];
          const zoneName = zoneObj ? zoneObj.name : "Home Area";

          const prompt = `You are a certified veterinary behaviorist and pet communication expert assisting a pet owner on PetTalk.
Pet Name: ${pet.name}
Species: ${pet.species}
Breed: ${pet.breed}
Age: ${pet.ageYears} years old
Personality: ${pet.personality.join(", ")}
Feeding Schedule: ${pet.feedingSchedule}
Current Home Zone: ${zoneName}
Acoustic Trait Detected: ${audio?.pitchVariation || 'rising pitch'} sound (${audio?.averageVolume ? Math.round(audio.averageVolume * 100) : 50}% volume)
Primary Predicted Intent: ${baseResult.primaryIntent.title} (${baseResult.primaryIntent.confidence}% confidence)

Write a short, empathetic, scientifically grounded "Why" reasoning breakdown (maximum 3 sentences).
Follow this STRICT honesty rule:
- Frame everything as a probabilistic likelihood based on sound, body language, routine, location, and owner feedback.
- NEVER claim pets speak English or that this is a literal translation.
- Maintain a warm, modern, intelligent tone.
- Do NOT make medical diagnoses or claims.`;

          const response = await ai.models.generateContent({
            model: "gemini-2.5-flash",
            contents: prompt
          });

          if (response.text) {
            baseResult.reasoning.summary = response.text.trim();
          }
        } catch (geminiErr) {
          console.warn("Gemini API enrichment skipped/failed, using ML provider output:", geminiErr);
        }
      }

      return res.json({ success: true, result: baseResult });
    } catch (err: any) {
      console.error("Error in /api/analyze:", err);
      return res.status(500).json({ error: "Failed to analyze pet signal", details: err?.message });
    }
  });

  /**
   * Train Pet Profile Feedback API endpoint
   */
  app.post("/api/train", (req, res) => {
    try {
      const { pet, feedback, correctedCategory } = req.body as {
        pet: Pet;
        feedback: 'confirmed' | 'corrected';
        correctedCategory?: string;
      };

      if (!pet || !feedback) {
        return res.status(400).json({ error: "Pet and feedback are required." });
      }

      const updatedPet = defaultMLProvider.trainPetProfile(pet, feedback, correctedCategory);
      return res.json({ success: true, pet: updatedPet });
    } catch (err: any) {
      return res.status(500).json({ error: "Failed to process training feedback" });
    }
  });

  // Vite development vs production setup
  if (process.env.NODE_ENV !== "production") {
    const vite = await createViteServer({
      server: { middlewareMode: true },
      appType: "spa",
    });
    app.use(vite.middlewares);
  } else {
    const distPath = path.join(process.cwd(), "dist");
    app.use(express.static(distPath));
    app.get("*", (_req, res) => {
      res.sendFile(path.join(distPath, "index.html"));
    });
  }

  app.listen(PORT, "0.0.0.0", () => {
    console.log(`PetTalk Server running on http://localhost:${PORT}`);
  });
}

startServer();