docs: enrich root README with full project plan details

- Add project plan context: team members, executive summary, schedule, risk management - Add project scope, deliverables, and classification table with symptoms - Add bibliography/references section from project plan - Centered header with logo, emoji-section navigation - Cleaner structure: Tentang → Tim → Ringkasan → Cakupan → Jadwal → Risiko → Arsitektur → Tech Stack → Memulai → Dokumentasi → Pustaka Co-Authored-By: Claude <noreply@anthropic.com>
fix(auth): use VITE_API_BASE_URL for Google OAuth redirect instead of window.location.origin
2026-06-16 00:25:47 +07:00 · 2026-06-16 00:23:46 +07:00 · 2026-06-16 00:23:18 +07:00 · 2026-06-15 23:49:47 +07:00 · 2026-06-15 23:17:46 +07:00 · 2026-06-15 23:00:30 +07:00
43 changed files with 3341 additions and 847 deletions
@@ -0,0 +1,25 @@
+<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 128 128" fill="none">
+  <!-- Background circle -->
+  <circle cx="64" cy="64" r="62" fill="#166534" stroke="#22c55e" stroke-width="3"/>
+  <circle cx="64" cy="64" r="56" fill="#15803d"/>
+
+  <!-- Corn leaf shape -->
+  <path d="M38 75 C32 55 30 35 45 22 C55 14 68 10 80 18 C85 22 90 26 95 30
+           C98 34 96 38 90 36 C84 34 78 32 72 34
+           C74 38 78 42 78 48 C78 56 72 62 64 64
+           C56 66 50 70 44 76 C42 78 38 80 38 75Z"
+        fill="#86efac" opacity="0.9"/>
+
+  <!-- Leaf vein -->
+  <path d="M46 56 C52 52 60 48 68 50" stroke="#166534" stroke-width="1.5" fill="none" opacity="0.6"/>
+  <path d="M50 62 C56 58 62 55 68 56" stroke="#166534" stroke-width="1.5" fill="none" opacity="0.6"/>
+
+  <!-- Magnifying glass / AI overlay -->
+  <circle cx="78" cy="68" r="18" fill="none" stroke="#fbbf24" stroke-width="3"/>
+  <line x1="91" y1="81" x2="98" y2="88" stroke="#fbbf24" stroke-width="3" stroke-linecap="round"/>
+
+  <!-- AI sparkle dots -->
+  <circle cx="70" cy="60" r="2" fill="#fbbf24"/>
+  <circle cx="82" cy="56" r="1.5" fill="#fbbf24"/>
+  <circle cx="76" cy="74" r="2" fill="#fbbf24"/>
+</svg>
@@ -18,7 +18,7 @@ on:
  workflow_dispatch:

 env:
-  VITE_API_BASE_URL: ${{ vars.VITE_API_BASE_URL || 'https://zeavisedu.asepharyana.tech' }}
+  VITE_API_BASE_URL: ${{ vars.VITE_API_BASE_URL || 'https://zeavisedu.asepharyana.my.id' }}

 jobs:
  build-apk:
@@ -40,6 +40,18 @@ jobs:
        with:
          bun-version: latest

+      - name: Cache Bun dependencies
+        uses: actions/cache@v4
+        with:
+          path: |
+            ~/.bun/install/cache
+            node_modules
+            apps/*/node_modules
+            packages/*/node_modules
+          key: ${{ runner.os }}-bun-${{ hashFiles('bun.lock', '**/package.json') }}
+          restore-keys: |
+            ${{ runner.os }}-bun-
+
      - name: Install dependencies
        run: bun install

@@ -52,7 +64,9 @@ jobs:
      - name: Setup Android SDK
        uses: android-actions/setup-android@v3
        with:
-          packages: 'platforms;android-36 build-tools;36.0.0 ndk;28.0.13004108'
+          packages: 'platforms;android-36 build-tools;36.0.0'
+      - name: Pin NDK version
+        run: echo "ANDROID_NDK_HOME=${ANDROID_SDK_ROOT}/ndk/$(ls ${ANDROID_SDK_ROOT}/ndk | sort -V | head -1)" >> $GITHUB_ENV

      - name: Setup Rust with Android targets
        uses: dtolnay/rust-toolchain@stable
@@ -74,6 +88,16 @@ jobs:
          restore-keys: |
            ${{ runner.os }}-cargo-android-

+      - name: Cache Gradle
+        uses: actions/cache@v4
+        with:
+          path: |
+            ~/.gradle/caches
+            ~/.gradle/wrapper
+          key: ${{ runner.os }}-gradle-android-${{ hashFiles('apps/tauri/Cargo.lock') }}
+          restore-keys: |
+            ${{ runner.os }}-gradle-android-
+
      - name: Install Tauri CLI
        run: cd apps/tauri && bun install

@@ -108,7 +132,13 @@ jobs:
          JAVA_HOME: ${{ env.JAVA_HOME_21_X64 }}
          ANDROID_HOME: ${{ env.ANDROID_SDK_ROOT }}
          NDK_HOME: ${{ env.ANDROID_NDK_HOME }}
-        run: bun tauri android init
+        run: |
+          rm -rf gen/android
+          bun tauri android init
+
+      - name: Patch AndroidManifest (CAMERA permission)
+        working-directory: apps/tauri
+        run: bash scripts/patch-android-manifest.sh

      - name: Build Tauri Android APK
        working-directory: apps/tauri
@@ -116,7 +146,7 @@ jobs:
          JAVA_HOME: ${{ env.JAVA_HOME_21_X64 }}
          ANDROID_HOME: ${{ env.ANDROID_SDK_ROOT }}
          NDK_HOME: ${{ env.ANDROID_NDK_HOME }}
-        run: bun tauri android build
+        run: bun tauri android build --apk

      - name: Decode keystore
        if: github.event_name != 'pull_request'
@@ -147,6 +177,7 @@ jobs:

      - name: Create Release and upload APK
        if: github.event_name != 'pull_request'
+        id: release
        uses: softprops/action-gh-release@v2
        with:
          tag_name: v${{ steps.version.outputs.version }}
@@ -177,8 +177,11 @@ jobs:
              cat << 'ENVEOF'
            DATABASE_URL=${{ secrets.DATABASE_URL }}
            SESSION_SECRET=${{ secrets.SESSION_SECRET }}
-            WEB_APP_URL=https://zeavisedu.asepharyana.tech
+            WEB_APP_URL=https://zeavisedu.asepharyana.my.id
            ML_SERVICE_URL=http://zeavis-ml:8000
+            GOOGLE_CLIENT_ID=${{ secrets.GOOGLE_CLIENT_ID }}
+            GOOGLE_CLIENT_SECRET=${{ secrets.GOOGLE_CLIENT_SECRET }}
+            GOOGLE_REDIRECT_URI=https://zeavisedu.asepharyana.my.id/api/v1/auth/google/callback
            ENVEOF
            } > .env

@@ -189,8 +192,17 @@ jobs:
            docker rm -f zeavis-web zeavis-api zeavis-ml zeavis-node-exporter 2>/dev/null || true
            docker compose pull
            docker compose up -d
+            # Wait for containers to be healthy (up to 60s)
+            wait_container() {
+              local name=$1
+              for i in $(seq 1 30); do
+                docker compose ps | grep -q "${name}.*Up" && return 0
+                sleep 2
+              done
+              return 1
+            }
+            wait_container zeavis-web || exit 1
+            wait_container zeavis-api || exit 1
+            wait_container zeavis-ml || exit 1
+            wait_container zeavis-node-exporter || echo "⚠️  node_exporter not running (non-fatal)"
            docker compose ps
-            docker compose ps | grep -q "zeavis-web.*Up" || exit 1
-            docker compose ps | grep -q "zeavis-api.*Up" || exit 1
-            docker compose ps | grep -q "zeavis-ml.*Up" || exit 1
-            docker compose ps | grep -q "zeavis-node-exporter.*Up" || echo "⚠️  node_exporter not running (non-fatal)"
@@ -1,6 +1,8 @@
-# Corn Leaf Disease Classification
+# Pipeline Machine Learning — ZeaVis Edu

-Pipeline lengkap untuk klasifikasi penyakit daun jagung menggunakan **EfficientNetV2B0**, mulai dari persiapan dataset, pelatihan di Google Colab, hingga ekspor model ke format **TFLite** dan **TensorFlow.js** untuk kebutuhan produksi.
+> Panduan lengkap: preprocessing dataset, pelatihan di Google Colab, ekspor model ke TFLite, TensorFlow.js, dan ONNX.
+
+← [Kembali ke README utama](../README.md)

 ---

@@ -391,3 +393,7 @@ export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python

 ### Sesi Colab terputus saat training
 **Solusi:** Gunakan callback `ModelCheckpoint` di notebook untuk menyimpan checkpoint secara berkala ke Google Drive, sehingga training bisa dilanjutkan dari checkpoint terakhir tanpa mengulang dari awal.
+
+---
+
+← [Kembali ke README utama](../README.md) &bull; [ML Service →](../apps/ml-service/README.md)
@@ -1,482 +1,277 @@
-# ZeaVis Edu
+<p align="center">
+  <br>
+  <img src=".github/assets/zeavis-logo.svg" alt="ZeaVis Edu" width="128"><br>
+  <h1 align="center">ZeaVis Edu</h1>
+  <p align="center">
+    <strong>Asisten Edukasi Interaktif untuk Deteksi Penyakit Daun Jagung</strong><br>
+    <em>Computer Vision &bull; EfficientNetV2B0 &bull; Transfer Learning</em>
+  </p>
+</p>

-ZeaVis Edu adalah aplikasi edukasi untuk membantu mengenali penyakit daun jagung melalui klasifikasi gambar berbasis machine learning. Repositori ini menggabungkan aplikasi web, API backend, layanan inferensi ML, serta pipeline pelatihan dan ekspor model EfficientNetV2B0.
+<p align="center">
+  <a href="#-tentang"><b>Tentang</b></a> &bull;
+  <a href="#-tim"><b>Tim</b></a> &bull;
+  <a href="#-ringkasan-eksekutif"><b>Ringkasan</b></a> &bull;
+  <a href="#-cakupan--deliverables"><b>Cakupan</b></a> &bull;
+  <a href="#-jadwal"><b>Jadwal</b></a> &bull;
+  <a href="#-tech-stack"><b>Tech Stack</b></a> &bull;
+  <a href="#-memulai"><b>Memulai</b></a> &bull;
+  <a href="#-dokumentasi"><b>Dokumentasi</b></a>
+</p>

-## Fitur Utama
+<br>

- Aplikasi web untuk pengalaman pengguna dan interaksi edukatif.
- API backend untuk status layanan, integrasi data, dan komunikasi dengan layanan ML.
- ML service berbasis Rust/Axum dengan ONNX Runtime untuk inferensi penyakit daun jagung dari gambar.
- Pipeline machine learning untuk preprocessing dataset, training di Google Colab, dan ekspor model produksi.
- Dukungan Docker untuk deployment web, API, dan ML service.
- Workspace monorepo berbasis Bun dan Moon untuk menjalankan task development, typecheck, dan build secara terpusat.
+---

-## Kelas Penyakit
+## 🌽 Tentang

-Model klasifikasi menargetkan empat label berbahasa Indonesia:
+**ZeaVis Edu** adalah aplikasi edukasi berbasis **Computer Vision** yang membantu petani, mahasiswa pertanian, dan penyuluh lapangan mengidentifikasi penyakit daun jagung secara mandiri — cukup dengan mengunggah foto daun jagung.

-| Label | Deskripsi |
+Proyek ini merupakan **Capstone Project** dalam program **Pijak × IBM SkillsBuild** dengan tema **"AI for Smart Education"**, dirancang untuk menjembatani kesenjangan antara pengetahuan teori pertanian dan kebutuhan praktis di lapangan.
+
+---
+
+## 👥 Tim
+
+| NPM | Nama | Learning Path | Peran |
+|---|---|---|---|
+| APC246D6Y0028 | **Asep Haryana Saputra** | Back-End | Arsitektur sistem, RESTful API, deployment Docker/Cloud, keamanan upload stream |
+| APC013D6X0081 | **Selly Supriyatin** | Front-End | UI/UX responsif, mekanisme unggah gambar, modul edukasi (rekomendasi obat & penanganan) |
+| APC013D6Y0091 | **Taufik Pathurrohman** | Machine Learning | Data Engineering — ekstraksi dataset, cleaning, augmentasi gambar |
+| APC414D6Y0138 | **Luhung Pandyaska Suyi** | Machine Learning | Model Architecture & Training — CNN, hyperparameter tuning |
+| APC013D6Y0269 | **Ardian** | Machine Learning | Model Evaluation & Deployment Prep — confusion matrix, konversi ke production-ready |
+
+---
+
+## 📋 Ringkasan Eksekutif
+
+### Masalah
+
+Data BPS menunjukkan penurunan luas panen jagung dari **2.764.366 Ha (2022)** menjadi **2.487.191 Ha (2023)**. Salah satu penyebab utamanya adalah penyakit daun seperti **Hawar Daun**, **Karat Daun**, dan **Bercak Daun Abu-abu** yang menyebabkan nekrosis dan menghambat fotosintesis.
+
+Petani sering kesulitan mengidentifikasi penyakit secara kasat mata dan memiliki **ketergantungan tinggi pada POPT** (Petugas Pengendali Organisme Pengganggu Tumbuhan) akibat minimnya media pembelajaran interaktif.
+
+### Solusi
+
+ZeaVis Edu menggunakan **Computer Vision** sebagai asisten edukasi interaktif:
+
+1. 📸 **Unggah** foto daun jagung yang diduga terinfeksi
+2. 🤖 **Deteksi otomatis** penyakit oleh model AI (EfficientNetV2B0)
+3. 📚 **Dapatkan** informasi detail penyakit, panduan pencegahan, dan rekomendasi obat secara mandiri
+
+### Metode Teknis
+
+| Komponen | Pilihan |
 |---|---|
-| Bercak Daun | Gray Leaf Spot |
-| Hawar Daun | Northern/Southern Leaf Blight |
-| Karat Daun | Common Rust |
-| Daun Sehat | Daun jagung tanpa gejala penyakit |
+| Arsitektur Model | **EfficientNetV2B0** — keseimbangan optimal antara akurasi dan efisiensi parameter |
+| Metode Pelatihan | **Transfer Learning** pada Google Colab (GPU T4) |
+| Sumber Dataset | Kaggle — [Corn Leaf Disease](https://www.kaggle.com/datasets/ndisan/corn-leaf-disease) |
+| Deployment | VPS dengan Docker, ONNX Runtime untuk inferensi real-time |

-## Struktur Proyek
+---

-```text
+## 🎯 Cakupan & Deliverables
+
+### Cakupan
+
+| ✅ Dalam Cakupan | ❌ Di Luar Cakupan |
+|---|---|
+| Klasifikasi 3 penyakit + 1 daun sehat | Penyakit pada batang atau buah jagung |
+| Deteksi berbasis unggah gambar daun | Prediksi tanpa input gambar |
+| Rekomendasi obat & penanganan | Diagnosis pengganti ahli/POPT |
+| Aplikasi web edukatif | Aplikasi mobile native |
+
+### 4 Kelas yang Diklasifikasikan
+
+| Label | Nama Ilmiah | Gejala |
+|---|---|---|
+| **Hawar Daun** | *Northern/Southern Leaf Blight* | Hawar coklat memanjang pada daun |
+| **Karat Daun** | *Common Rust* | Bintik coklat kemerahan berbentuk pustula |
+| **Bercak Daun** | *Gray Leaf Spot* | Bercak abu-abu memanjang |
+| **Daun Sehat** | — | Tanpa gejala penyakit |
+
+### Deliverables Proyek
+
+| No | Tahapan | Deskripsi |
+|---|---|---|
+| 1 | **Pengumpulan Data** | Dataset gambar 3 penyakit + 1 daun sehat dari Kaggle beserta pelabelan |
+| 2 | **Model ML** | Model Computer Vision terlatih di Google Colab, siap produksi |
+| 3 | **UI Antarmuka** | Front-End berbasis React + Vite dengan fitur unggah gambar |
+| 4 | **Back-End Integration** | API + ML Service untuk inferensi real-time via Docker |
+| 5 | **Prototipe Akhir** | Aplikasi web final dengan klasifikasi + modul edukasi (rekomendasi obat & penanganan) |
+
+---
+
+## 📅 Jadwal
+
+| Minggu | Tanggal | Fase | Aktivitas |
+|---|---|---|---|
+| **1** | 11–17 Mei 2026 | Inisiasi & Data | Spesifikasi teknis (Asep) • Dataset dari Kaggle + preprocessing (Taufik) • Wireframe UI/UX (Selly) |
+| **2** | 18–24 Mei 2026 | Training & Dev Awal | Implementasi EfficientNetV2B0 di Colab (Luhung) • Slicing UI ke React (Selly) • Setup server, database, routing API (Asep) |
+| **3** | 25–31 Mei 2026 | Evaluasi & Modul Edukasi | Evaluasi akurasi + konversi model ke ONNX/TFLite (Ardian) • Halaman edukasi obat & penanganan (Selly) • RESTful API untuk image upload & inferensi (Asep) |
+| **4** | 1–7 Juni 2026 | Integrasi & Testing | Integrasi penuh Front-End ↔ API ↔ Model ML • Pengujian end-to-end • Stress testing & error handling (Semua) |
+| **5** | 8–14 Juni 2026 | Deployment & Finalisasi | Deployment ke VPS (Asep) • Bug fixing & optimalisasi UI/UX (Selly) • Dokumentasi teknis & materi presentasi (Semua) |
+
+---
+
+## ⚠️ Manajemen Risiko
+
+| Risiko | Solusi |
+|---|---|
+| **Overfitting akibat imbalanced data** | Augmentasi tingkat lanjut (kecerahan, noise, rotasi) + confidence threshold < 75% → minta user foto ulang |
+| **Server downtime / latensi tinggi** | Batasan upload ≤ 5 MB + kompresi server-side + rate limiting + container Docker isolasi resource |
+| **Foto blur / objek bukan daun jagung** | Panduan visual (overlay) pada UI + validasi anomali + disclaimer "alat bantu edukasi, bukan pengganti POPT" |
+| **Bottleneck integrasi ML ↔ API ↔ UI** | API Contract ketat di minggu ke-1 + integrasi bertahap (CI) mulai minggu ke-3 |
+
+---
+
+## 🏗️ Arsitektur Proyek
+
+```
 .
 ├── apps/
-│   ├── api/              # Backend Elysia/Bun
-│   ├── ml-service/       # Layanan inferensi Rust/Axum + ONNX Runtime
-│   └── web/              # Frontend React + Vite
-├── Machine_Learning/     # Pipeline dataset, training, dan ekspor model
-├── packages/
-│   └── shared/           # Tipe dan utilitas bersama TypeScript
+│   ├── api/                  # Backend Elysia/Bun + Drizzle ORM + PostgreSQL
+│   ├── ml-service/           # Rust/Axum + ONNX Runtime inference service
+│   └── web/                  # Frontend React + Vite + Tailwind CSS
+├── Machine_Learning/         # Pipeline dataset, training Colab, ekspor model
+│   └── README.md             # ⤷ Panduan lengkap pipeline ML
+├── infra/
+│   └── README.md             # ⤷ Panduan deployment multi-VPS
+├── packages/shared/          # Tipe & utilitas TypeScript bersama
+├── telemetry/                # Submodule — Prometheus → ClickHouse pipeline
 ├── docker-compose.yml        # Konfigurasi deployment container
-├── package.json          # Script dan workspace root Bun
-└── README.md             # Dokumentasi utama proyek
+├── package.json              # Root workspace Bun + Moon
+└── README.md                 # ⤷ Anda di sini
 ```

-## Tech Stack
+| Komponen | Teknologi | Dokumentasi |
+|---|---|---|
+| Web Frontend | React, Vite, Tailwind, Zustand, TanStack Query | `apps/web/` |
+| API Backend | Bun, Elysia, Drizzle ORM, PostgreSQL | `apps/api/` |
+| ML Inference | Rust, Axum, ONNX Runtime | [`apps/ml-service/README.md`](apps/ml-service/README.md) |
+| ML Pipeline | Python, TensorFlow/Keras, EfficientNetV2B0 | [`Machine_Learning/README.md`](Machine_Learning/README.md) |
+| Infrastruktur | Docker, Coolify, Traefik, Tailscale | [`infra/README.md`](infra/README.md) |
+| Telemetry | Prometheus, ClickHouse, Vector, Vue 3 | `telemetry/` |
+
+---
+
+## 🛠️ Tech Stack

 ### Frontend
-
- React
- Vite
- TypeScript
- React Router
- TanStack Query
- Zustand
- Tailwind CSS
+React &bull; Vite &bull; TypeScript &bull; React Router &bull; TanStack Query &bull; Zustand &bull; Tailwind CSS

 ### Backend API
-
- Bun
- Elysia
- Drizzle ORM
- PostgreSQL
+Bun &bull; Elysia &bull; Drizzle ORM &bull; PostgreSQL &bull; prom-client

 ### Machine Learning
+Python &bull; TensorFlow/Keras &bull; EfficientNetV2B0 &bull; Google Colab (GPU T4)
+Rust &bull; Axum &bull; ONNX Runtime &bull; TFLite &bull; TensorFlow.js

- Python (preprocessing, training, export)
- TensorFlow/Keras
- EfficientNetV2B0
- Rust
- Axum
- ONNX Runtime
- TFLite
- TensorFlow.js
+### DevOps & Infrastruktur
+Docker &bull; Docker Compose &bull; Coolify &bull; Traefik &bull; Tailscale &bull; GitHub Actions (CI/CD)

-### Tooling & Deployment
+### Observabilitas
+Prometheus &bull; Metric Ingester (Go) &bull; Vector &bull; ClickHouse &bull; Query Proxy (Go) &bull; Telemetry UI (Vue 3)

- Bun workspaces
- Moon task runner
- Docker
- Docker Compose
- GitHub Container Registry
- Traefik labels untuk routing deployment
+---

-### Telemetry & Observability
+## 🚀 Memulai

- Prometheus — metric scraping & remote_write
- Metric Ingester (Go) — enrichment, filtering, aggregation
- Vector — buffering & backpressure
- ClickHouse — columnar analytical storage
- Query Proxy (Go) — read-only SQL proxy
- Telemetry UI (Vue 3) — metrics dashboard
- Semua service ZeaVis Edu (web, api, ml-service) mengekspos metrik Prometheus di `/metrics`
- Client-side Web Vitals (CLS, FCP, INP, LCP, TTFB) dikumpulkan di frontend
+### Prasyarat

-## Prasyarat
+- **Bun** — runtime & package manager
+- **Python 3.9–3.11** — pipeline ML
+- **Rust & Cargo** — `apps/ml-service`
+- **Docker & Docker Compose** — deployment & telemetry
+- **PostgreSQL** — backend API

-Untuk menjalankan seluruh project secara lokal, siapkan:
-
- Bun
- Python 3.9–3.11 untuk pipeline ML
- Rust dan Cargo untuk `apps/ml-service`
- Docker dan Docker Compose jika ingin menjalankan/deploy via container
- PostgreSQL jika fitur backend yang membutuhkan database digunakan
- File model `Machine_Learning/model/model.onnx` untuk inferensi ML lokal
-
-## Instalasi Root Workspace
-
-Jalankan dari root repository:
+### Instalasi

 ```bash
+git clone https://github.com/ATLAS-PJK-GM007/ZeaVis-Edu.git
+cd ZeaVis-Edu
 bun install
 ```

-## Menjalankan Project Lokal
-
-### Menjalankan Semua Task Development
+### Menjalankan Development

 ```bash
-bun run dev
+bun run dev                # Semua service (web + api)
+cd apps/web && bun run dev # Hanya frontend
+cd apps/api && bun run start # Hanya backend API
+cd apps/ml-service && cargo run  # Hanya ML service (port 8000)
 ```

-Script ini menjalankan task `dev` melalui Moon untuk workspace yang tersedia.
+### Environment Variables

-### Type Check
+Salin `.env.example` ke `.env` dan isi:

-```bash
-bun run typecheck
-```
-
-### Build Produksi
-
-```bash
-bun run build
-```
-
-## Menjalankan Service Secara Terpisah
-
-### Web App
-
-```bash
-cd apps/web
-bun run dev
-```
-
-Secara default Vite akan menjalankan server development dan menampilkan URL lokal di terminal.
-
-### API Backend
-
-```bash
-cd apps/api
-bun run start
-```
-
-API membaca konfigurasi dari file `.env` di root repository melalui script Bun.
-
-Script lain yang tersedia:
-
-```bash
-bun run db:generate
-bun run db:migrate
-bun run db:seed
-bun run typecheck
-```
-
-### ML Service
-
-```bash
-cd apps/ml-service
-cargo run
-```
-
-Default path model adalah:
-
-```text
-../../Machine_Learning/model/model.onnx
-```
-
-Jika model berada di lokasi lain, gunakan environment variable `MODEL_PATH`:
-
-```bash
-MODEL_PATH=/path/to/model.onnx cargo run
-```
-
-**Port Configuration:**
-
- **Default (tanpa .env):** Service mendengarkan di `http://localhost:8000`
- **Local development (dengan .env.example):** Service mendengarkan di `http://localhost:8001`
-  ```bash
-  cd apps/ml-service
-  source .env.example
-  cargo run
-  ```
- **Docker container:** Service mendengarkan di port `8000`
-
-Lihat `apps/ml-service/README.md` untuk detail lengkap tentang konfigurasi port dan contoh curl.
-
-## Docker Deployment
-
-File `docker-compose.yml` di root menyiapkan tiga service produksi:
-
- `web` untuk frontend
- `api` untuk backend
- `ml` untuk layanan inferensi machine learning
-
-Konfigurasi compose menggunakan image dari GitHub Container Registry:
-
-```text
-ghcr.io/${GITHUB_REPOSITORY:-mytheclipse/zeavis-edu}/web:main
-ghcr.io/${GITHUB_REPOSITORY:-mytheclipse/zeavis-edu}/api:main
-ghcr.io/${GITHUB_REPOSITORY:-mytheclipse/zeavis-edu}/ml:main
-```
-
-Compose juga mengasumsikan network eksternal bernama `app-shared-net` dan routing Traefik untuk domain produksi. Service `ml` berjalan pada port `8000` di dalam container.
-
-Contoh menjalankan compose setelah environment dan network siap:
-
-```bash
-docker compose up -d
-```
-
-## Telemetry Stack
-
-Proyek ini menyertakan pipeline telemetry metric sebagai git submodule di `telemetry/`. Pipeline mengalirkan metrik dari seluruh service ZeaVis Edu ke ClickHouse untuk analisis dan visualisasi jangka panjang.
-
-### Arsitektur (Production)
-
-Di production, aplikasi dan telemetry berjalan di **VPS terpisah** dan terhubung via **Tailscale** (mesh VPN). Prometheus di VPS telemetry melakukan scrape ke service ZeaVis Edu melalui IP Tailscale masing-masing.
-
-```mermaid
-flowchart LR
-    subgraph VPS1["VPS — ZeaVis Edu (App)"]
-        W[Web / React<br/>api-zeavisedu.asepharyana.id]
-        A[API / Elysia<br/>:3000]
-        M[ML Service / Axum<br/>:8000]
-    end
-
-    subgraph VPS2["VPS — Telemetry Stack"]
-        P[Prometheus<br/>:9090]
-        MI[Metric Ingester<br/>:9091]
-        V[Vector<br/>:9001]
-        CH[ClickHouse<br/>:8123]
-        QP[Query Proxy<br/>:9092]
-        TUI[Telemetry UI<br/>:8181]
-    end
-
-    P -.->|"scrape via Tailscale IP<br/>100.x.x.a:3000/metrics"| A
-    P -.->|"scrape via Tailscale IP<br/>100.x.x.a:8000/metrics"| M
-    P -->|remote_write| MI
-    MI --> V
-    V --> CH
-    QP --> CH
-    TUI --> QP
-```
-
-Setiap service ZeaVis Edu mengekspos endpoint `/metrics` dalam format Prometheus text:
-
-| Service               | Endpoint           | Port (lokal) |
-|-----------------------|--------------------|--------------|
-| Web (Vite dev)        | `GET /metrics`     | 5173         |
-| API (Elysia)          | `GET /metrics`     | 3000         |
-| ML Service (Axum)     | `GET /metrics`     | 8000         |
-
-Prometheus di VPS telemetry melakukan **scrape langsung** ke API dan ML service melalui IP Tailscale mereka, bukan melalui domain publik. Konfigurasi target ada di `telemetry/prometheus/targets/zeavis-edu.json` — isi dengan IP Tailscale dari service yang dituju.
-
-Lihat [`METRICS.md`](./METRICS.md) untuk daftar lengkap metrik yang diekspos.
-
-### Service Telemetry
-
-| # | Service | Peran | Port |
-|---|---------|------|------|
-| 1 | **Prometheus** | Metric scraping & remote_write | 9090 |
-| 2 | **Metric Ingester** | Enrichment, filtering, aggregation | 9091 |
-| 3 | **Vector** | Buffering, backpressure, retry | 9001 |
-| 4 | **ClickHouse** | Columnar analytical storage | 8123 / 9000 |
-| 5 | **Query Proxy** | Read-only SQL proxy, tenant isolation | 9092 |
-| 6 | **Telemetry UI** | Vue 3 metrics dashboard | 8181 |
-
-### Arsitektur (Local Dev)
-
-Untuk development lokal di satu mesin, telemetry dan app bisa jalan bareng di satu Docker host. Prometheus bisa scrape service lewat Docker network yang sama.
-
-```bash
-# Setup network
-docker network create app-shared-net
-
-# Build & start telemetry (dengan network sharing)
-make telemetry-up-local
-```
-
-### Menjalankan Telemetry Stack
-
-Semua operasi telemetry dijalankan dari **root proyek** melalui Makefile:
-
-```bash
-# Build komponen telemetry (metric-ingester + telemetry-ui)
-make telemetry-build
-
-# Start semua service telemetry (mode produksi, via Tailscale)
-make telemetry-up
-
-# Start semua service telemetry (mode lokal — port langsung terbuka)
-make telemetry-up-local
-
-# Cek status kesehatan semua service
-make telemetry-status
-
-# Lihat log (semua service, atau filter dengan s=)
-make telemetry-logs
-make telemetry-logs s=metric-ingester
-
-# Restart service tertentu
-make telemetry-restart s=prometheus
-
-# Kirim test metric
-make telemetry-test-metric
-
-# Stop semua service
-make telemetry-down
-```
-
-Untuk development lokal:
-
-```bash
-# Setup network jika belum ada
-docker network create telemetry-net
-docker network create app-shared-net
-
-# Build & start
-make telemetry-build
-make telemetry-up-local
-
-# Buka dashboard di http://localhost:8181
-```
-
-### Prometheus Auto-Discovery
-
-Prometheus menggunakan `file_sd_configs` untuk menemukan target secara dinamis. Cukup letakkan file JSON di `telemetry/prometheus/targets/` dan Prometheus akan otomatis mendeteksinya dalam 15 detik — tanpa restart.
-
-File template sudah tersedia di [`telemetry/prometheus/targets/zeavis-edu.json`](telemetry/prometheus/targets/zeavis-edu.json). **Sebelum production, isi `__CHANGE_ME__` dengan IP Tailscale masing-masing service:**
-
-```json
-[
-  { "targets": ["100.x.x.a:3000"], "labels": { "service": "zeavis-api", "component": "backend", "env": "production" } },
-  { "targets": ["100.x.x.a:8000"],  "labels": { "service": "zeavis-ml", "component": "inference", "env": "production" } }
-]
-```
-
-> **Catatan:** Aplikasi ZeaVis Edu mengekspose port Docker-nya (`:3000`, `:8000`) langsung ke host via `docker-compose.yml`. Pastikan port-port tersebut terbuka di network Tailscale (biasanya iptables Tailscale mengizinkan koneksi ke port localhost).
-
-### Environment Variables Telemetry
-
-| Variable | Default | Deskripsi |
-|----------|---------|-----------|
-| `CLICKHOUSE_USER` | `telemetry` | User ClickHouse |
-| `CLICKHOUSE_PASSWORD` | `telemetry` | Password ClickHouse |
-
-## Workflow Machine Learning
-
-Detail lengkap tersedia di [`Machine_Learning/README.md`](Machine_Learning/README.md). Ringkasnya:
-
-1. Unduh `dataset_1.zip`, `dataset_2.zip`, dan `dataset_3.zip` lalu letakkan di `Machine_Learning/`.
-2. Jalankan preprocessing lokal:
-
-   ```bash
-   cd Machine_Learning
-   python preprocessing.py
-   ```
-
-3. Upload `dataset.zip` ke Google Drive.
-4. Jalankan `notebook.ipynb` di Google Colab dengan GPU.
-5. Download model terbaik sebagai `best_model/best_model.keras`.
-6. Ekspor model produksi:
-
-   ```bash
-   python save_model.py
-   ```
-
-7. Konversi TensorFlow.js via CLI:
-
-   ```bash
-   export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python
-   tensorflowjs_converter \
-     --input_format=tf_saved_model \
-     --output_format=tfjs_graph_model \
-     --signature_name=serving_default \
-     --saved_model_tags=serve \
-     model/saved_model \
-     model/tfjs_model
-   ```
-
-Output utama pipeline ML:
-
-| Path | Kegunaan |
+| Variable | Keterangan |
 |---|---|
-| `Machine_Learning/dataset.zip` | Dataset siap upload ke Colab |
-| `Machine_Learning/best_model/best_model.keras` | Model Keras hasil training |
-| `Machine_Learning/model/saved_model/` | TensorFlow SavedModel |
-| `Machine_Learning/model/model.tflite` | Model untuk mobile/TFLite |
-| `Machine_Learning/model/model.onnx` | Model untuk Rust ONNX Runtime |
-| `Machine_Learning/model/tfjs_model/` | Model untuk TensorFlow.js |
+| `DATABASE_URL` | URL koneksi PostgreSQL |
+| `SESSION_SECRET` | Secret untuk session auth |
+| `WEB_APP_URL` | URL frontend (untuk CORS) |
+| `ML_SERVICE_URL` | URL layanan inferensi ML |

-## Artifact Lokal dan Generated Files
+### Pipeline ML (Ringkasan)

-Beberapa file tidak tersedia di fresh clone karena berukuran besar, dihasilkan lokal, atau berasal dari sumber eksternal:
+1. Unduh 3 dataset ZIP → letakkan di `Machine_Learning/`
+2. `python preprocessing.py` — gabungkan & bersihkan dataset
+3. Upload `dataset.zip` ke Google Drive
+4. Jalankan `notebook.ipynb` di Google Colab (GPU T4)
+5. Download `best_model.keras`
+6. `python save_model.py` → TFLite + SavedModel
+7. Konversi ke TFJS & ONNX

- `Machine_Learning/dataset_1.zip`
- `Machine_Learning/dataset_2.zip`
- `Machine_Learning/dataset_3.zip`
- `Machine_Learning/dataset/`
- `Machine_Learning/dataset.zip`
- `Machine_Learning/best_model/best_model.keras`
- `Machine_Learning/model/saved_model/`
- `Machine_Learning/model/model.tflite`
- `Machine_Learning/model/model.onnx`
- `Machine_Learning/model/tfjs_model/`
+> 📖 **Panduan lengkap:** [`Machine_Learning/README.md`](Machine_Learning/README.md)

-## Environment Variable Penting
-
-| Variable | Digunakan oleh | Keterangan |
-|---|---|---|
-| `DATABASE_URL` | API | URL koneksi PostgreSQL untuk Drizzle |
-| `API_PORT` | API | Port backend produksi |
-| `WEB_APP_URL` | API | URL frontend untuk konfigurasi CORS/integrasi |
-| `ML_SERVICE_URL` | API | URL layanan ML |
-| `MODEL_PATH` | ML Service | Lokasi file model ONNX, default `../../Machine_Learning/model/model.onnx` |
-| `MODEL_INPUT_SIZE` | ML Service | Ukuran input model, default produksi `224` |
-
-## Troubleshooting
-
-### `bun run dev` gagal karena dependency belum tersedia
-
-Jalankan ulang instalasi dari root repository:
+### Deployment

 ```bash
-bun install
+docker compose up -d       # App services
+make telemetry-up          # Telemetry stack
 ```

-### API membutuhkan database
+> 📖 **Panduan infrastruktur:** [`infra/README.md`](infra/README.md)

-Pastikan `DATABASE_URL` tersedia di `.env` root dan PostgreSQL dapat diakses oleh aplikasi.
+---

-### ML service gagal memuat model
+## 📚 Dokumentasi

-Pastikan file model tersedia di path default:
+| Dokumen | Isi |
+|---|---|
+| [`Machine_Learning/README.md`](Machine_Learning/README.md) | Pipeline ML lengkap — preprocessing, training Colab, ekspor TFLite/TFJS/ONNX |
+| [`apps/ml-service/README.md`](apps/ml-service/README.md) | ML Inference Service — setup, endpoint API, konfigurasi |
+| [`infra/README.md`](infra/README.md) | Arsitektur multi-VPS — diagram, GitHub Secrets, port, metrics flow |
+| [`METRICS.md`](METRICS.md) | Daftar lengkap metrik Prometheus |
+| `telemetry/` (submodule) | Source code telemetry stack |

-```text
-Machine_Learning/model/model.onnx
-```
+---

-Atau set path khusus:
+## 🔧 Troubleshooting

-```bash
-MODEL_PATH=/path/to/model.onnx cargo run
-```
+| Masalah | Solusi |
+|---|---|
+| `bun install` gagal | `bun --version` — pastikan ≥ 1.x |
+| API perlu database | Isi `DATABASE_URL` di root `.env` |
+| ML service gagal muat model | `ls Machine_Learning/model/model.onnx` — jalankan pipeline ML jika belum ada |
+| Docker Compose gagal | `docker network create app-shared-net` |
+| Konversi TFJS gagal | `export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python` |

-### Docker Compose gagal karena network tidak ditemukan
+---

-`docker-compose.yml` menggunakan network eksternal `app-shared-net`. Buat network tersebut jika belum ada:
+## 📖 Daftar Pustaka

-```bash
-docker network create app-shared-net
-```
+1. Prayogi, A. et al. *"Klasifikasi Penyakit Daun Jagung Menggunakan CNN"* — [SISTEMATIS](https://ejournal.rizaniamedia.com/index.php/sistematis/article/view/87/49)
+2. Nugroho, A. et al. *"Deteksi Penyakit Daun Jagung dengan Deep Learning"* — [MIND Journal](https://ejurnal.itenas.ac.id/index.php/mindjournal/article/view/14032/4209)
+3. Ramadhan, F. et al. *"Identifikasi Penyakit Jagung Berbasis Citra Digital"* — [Informa](https://www.informa.poltekindonusa.ac.id/index.php/informa/article/view/199/170)
+4. Corteva Agriscience. *"Kenali Ragam Jenis Penyakit Jagung dan Cara Mengatasinya"* — [corteva.com](https://www.corteva.com/id/berita/Kenali-Ragam-Jenis-Penyakit-Jagung-dan-Cara-Mengatasinya.html)

-### Konversi TensorFlow.js gagal karena konflik protobuf
+---

-Jalankan konversi melalui CLI dan set environment variable berikut:
-
-```bash
-export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python
-```
-
-## Pengembangan
-
-Alur umum pengembangan:
-
-1. Install dependency dengan `bun install`.
-2. Jalankan service yang dibutuhkan secara lokal.
-3. Jalankan `bun run typecheck` sebelum membuat commit.
-4. Jalankan `bun run build` untuk memverifikasi build produksi.
-5. Untuk perubahan ML, ikuti dokumentasi detail di `Machine_Learning/README.md`.
-6. Untuk perubahan ML service, cek juga `apps/ml-service/README.md`.
-
-## Dokumentasi Terkait
-
- [`Machine_Learning/README.md`](Machine_Learning/README.md) — panduan lengkap dataset, training, dan ekspor model.
- [`apps/ml-service/README.md`](apps/ml-service/README.md) — panduan menjalankan dan memverifikasi layanan inferensi ML.
+<p align="center">
+  <sub>
+    Capstone Project • Pijak × IBM SkillsBuild • AI for Smart Education<br>
+    © 2026 ZeaVis Edu Team
+  </sub>
+</p>
@@ -4,8 +4,9 @@ WORKDIR /app
 COPY package.json bun.lock bunfig.toml tsconfig.base.json ./
 COPY apps/api/package.json apps/api/package.json
 COPY apps/web/package.json apps/web/package.json
+COPY apps/tauri/package.json apps/tauri/package.json
 COPY packages/shared/package.json packages/shared/package.json
-RUN bun install --frozen-lockfile --production
+RUN bun install --production

 FROM oven/bun:1.3.14 AS runner
 WORKDIR /app
@@ -13,7 +14,9 @@ ENV NODE_ENV=production
 ENV API_PORT=3000

 COPY --from=deps /app/node_modules ./node_modules
-COPY package.json bun.lock bunfig.toml tsconfig.base.json ./
+COPY --from=deps /app/apps/api/node_modules apps/api/node_modules
+COPY --from=deps /app/bun.lock ./bun.lock
+COPY package.json bunfig.toml tsconfig.base.json ./
 COPY apps/api apps/api
 COPY packages/shared packages/shared

@@ -8,6 +8,13 @@ const googleOAuthEnabled = Boolean(
 );

 const webAppUrl = Bun.env.WEB_APP_URL ?? 'http://localhost:5173';
+const allowedOrigins = [
+  webAppUrl,
+  'https://tauri.localhost',
+  'http://tauri.localhost',
+  'tauri://localhost',
+  'http://localhost:5173',
+];
 const secureCookies = Bun.env.SECURE_COOKIES === 'true' || webAppUrl.startsWith('https://');

 export const env = {
@@ -24,6 +31,7 @@ export const env = {
  googleClientSecret: Bun.env.GOOGLE_CLIENT_SECRET,
  googleRedirectUri: Bun.env.GOOGLE_REDIRECT_URI,
  webAppUrl,
+  allowedOrigins,
  secureCookies,
 };

@@ -17,7 +17,7 @@ assertRequiredEnv();

 const app = new Elysia()
  .use(cors({
-    origin: env.webAppUrl,
+    origin: env.allowedOrigins,
    credentials: true,
  }))
  .use(metricsRoutes)
@@ -28,14 +28,26 @@ function hashToken(token: string) {
  return createHash('sha256').update(`${env.sessionSecret}:${token}`).digest('hex');
 }

-export function createSessionCookie(token: string) {
+function isSecureRequest(headers?: { get(name: string): string | null }) {
+  if (env.secureCookies) return true;
+  // Detect HTTPS behind proxy (X-Forwarded-Proto)
+  const proto = headers?.get('x-forwarded-proto');
+  if (proto === 'https') return true;
+  return false;
+}
+
+function buildSameSite(headers?: { get(name: string): string | null }) {
+  return isSecureRequest(headers) ? 'SameSite=None; Secure' : 'SameSite=Lax';
+}
+
+export function createSessionCookie(token: string, headers?: { get(name: string): string | null }) {
  const maxAge = 60 * 60 * 24 * 30;
-  const sameSite = env.secureCookies ? 'SameSite=None; Secure' : 'SameSite=Lax';
+  const sameSite = buildSameSite(headers);
  return `${sessionCookieName}=${token}; HttpOnly; Path=/; ${sameSite}; Max-Age=${maxAge}`;
 }

-export function clearSessionCookie() {
-  const sameSite = env.secureCookies ? 'SameSite=None; Secure' : 'SameSite=Lax';
+export function clearSessionCookie(headers?: { get(name: string): string | null }) {
+  const sameSite = buildSameSite(headers);
  return `${sessionCookieName}=; HttpOnly; Path=/; ${sameSite}; Max-Age=0`;
 }

@@ -49,6 +61,19 @@ export function readSessionToken(cookieHeader: string | null | undefined) {
  return decodeURIComponent(sessionCookie.slice(sessionCookieName.length + 1));
 }

+/**
+ * Extract bearer token from Authorization header.
+ * Used as fallback when cookies are blocked (e.g. Android WebView third-party blocking).
+ */
+export function readBearerToken(headers?: { get(name: string): string | null }) {
+  if (!headers) return null;
+  const auth = headers.get('authorization');
+  if (!auth) return null;
+  const parts = auth.split(' ');
+  if (parts.length !== 2 || parts[0] !== 'Bearer') return null;
+  return parts[1];
+}
+
 export async function createSession(userId: string) {
  const db = createDbClient();
  const token = randomBytes(32).toString('base64url');
@@ -71,8 +96,12 @@ export async function deleteSession(token: string | null) {
  await db.delete(sessions).where(eq(sessions.tokenHash, hashToken(token)));
 }

-export async function getCurrentUser(cookieHeader: string | null | undefined): Promise<CurrentUser | null> {
-  const token = readSessionToken(cookieHeader);
+export async function getCurrentUser(
+  cookieHeader: string | null | undefined,
+  headers?: { get(name: string): string | null },
+): Promise<CurrentUser | null> {
+  // Try cookie first, then Authorization header (for Android WebView where 3rd-party cookies are blocked)
+  const token = readSessionToken(cookieHeader) ?? readBearerToken(headers);
  if (!token) return null;

  const db = createDbClient();
@@ -18,6 +18,86 @@ import {
 import { env } from '../config/env';
 import { authCounter } from '../lib/telemetry';

+// ── Google OAuth Helpers ──────────────────────────────────────────────
+
+interface GoogleTokenResponse {
+  access_token: string;
+  id_token: string;
+}
+
+interface GoogleIdPayload {
+  sub: string;
+  email: string;
+  email_verified: boolean;
+  name: string;
+  picture?: string;
+}
+
+async function exchangeGoogleCode(code: string): Promise<GoogleTokenResponse> {
+  const res = await fetch('https://oauth2.googleapis.com/token', {
+    method: 'POST',
+    headers: { 'Content-Type': 'application/x-www-form-urlencoded' },
+    body: new URLSearchParams({
+      code,
+      client_id: env.googleClientId!,
+      client_secret: env.googleClientSecret!,
+      redirect_uri: env.googleRedirectUri!,
+      grant_type: 'authorization_code',
+    }),
+  });
+
+  if (!res.ok) {
+    const err = await res.text();
+    throw new Error(`Google token exchange failed: ${res.status} ${err}`);
+  }
+
+  return res.json() as Promise<GoogleTokenResponse>;
+}
+
+function decodeGoogleIdToken(idToken: string): GoogleIdPayload {
+  const parts = idToken.split('.');
+  if (parts.length !== 3) {
+    throw new Error('Invalid id_token format');
+  }
+  const payload = Buffer.from(parts[1], 'base64url').toString('utf-8');
+  return JSON.parse(payload);
+}
+
+/**
+ * Render a page for the Android system browser that redirects back to the
+ * Tauri app via a custom scheme (zeavisedu://). The app's AndroidManifest
+ * must register an intent filter for this scheme.
+ */
+function renderTauriDeepLinkPage(targetUrl: string): Response {
+  // Rewrite https://... to zeavisedu://... for the custom scheme
+  const deepLink = targetUrl.replace(/^https?:\/\//, 'zeavisedu://');
+  const html = `<!DOCTYPE html>
+<html><head><meta charset="utf-8"><meta name="viewport" content="width=device-width,initial-scale=1">
+<title>Kembali ke ZeaVis Edu</title></head>
+<body style="font-family:sans-serif;display:flex;align-items:center;justify-content:center;min-height:100vh;margin:0;background:#f0fdf4">
+<div style="text-align:center;padding:2rem">
+<p style="color:#166534;font-size:1.1rem;margin-bottom:1.5rem">Login berhasil!<br>Kembali ke aplikasi...</p>
+<a href="${deepLink.replace(/"/g, '&quot;')}" style="display:inline-block;background:#16a34a;color:white;padding:0.75rem 2rem;border-radius:0.5rem;text-decoration:none;font-weight:600;font-size:1rem">Buka ZeaVis Edu</a>
+<p style="color:#6b7280;font-size:0.8rem;margin-top:1rem">Jika tombol tidak berfungsi, salin URL ini:<br><code style="word-break:break-all;font-size:0.75rem">${deepLink.replace(/</g, '&lt;')}</code></p>
+</div>
+<script>window.location.href=${JSON.stringify(deepLink)};</script>
+</body></html>`;
+  return new Response(html, {
+    status: 200,
+    headers: { 'Content-Type': 'text/html;charset=utf-8' },
+  });
+}
+
+function resolvePlatform(stateRaw: string | undefined): string {
+  try {
+    if (stateRaw) {
+      const parsed = JSON.parse(Buffer.from(stateRaw, 'base64url').toString('utf-8'));
+      return parsed.platform ?? 'web';
+    }
+  } catch { /* ignore */ }
+  return 'web';
+}
+
 function normalizeEmail(email: unknown) {
  return typeof email === 'string' ? email.trim().toLowerCase() : '';
 }
@@ -32,13 +112,13 @@ function validatePassword(password: unknown) {

 export const authRoutes = new Elysia({ prefix: '/api/v1/auth' })
  .get('/me', async ({ request }) => {
-    const user = await getCurrentUser(request.headers.get('cookie'));
+    const user = await getCurrentUser(request.headers.get('cookie'), request.headers);
    return {
      user,
      features: getAuthFeatures(),
    };
  })
-  .post('/register', async ({ body, set }) => {
+  .post('/register', async ({ body, set, request }) => {
    const req = body as Partial<RegisterRequest> | undefined;
    const email = normalizeEmail(req?.email);
    const name = normalizeName(req?.name);
@@ -62,7 +142,7 @@ export const authRoutes = new Elysia({ prefix: '/api/v1/auth' })

      const user = inserted[0];
      const token = await createSession(user.id);
-      set.headers['Set-Cookie'] = createSessionCookie(token);
+      set.headers['Set-Cookie'] = createSessionCookie(token, request.headers);

      authCounter.labels('register', 'true').inc();

@@ -73,13 +153,14 @@ export const authRoutes = new Elysia({ prefix: '/api/v1/auth' })
          name: user.name,
          role: 'user' as const,
        },
+        token,
        features: getAuthFeatures(),
      };
    } catch (error) {
      return serviceUnavailable('Database unavailable');
    }
  })
-  .post('/login', async ({ body, set }) => {
+  .post('/login', async ({ body, set, request }) => {
    const req = body as Partial<AuthRequest> | undefined;
    const email = normalizeEmail(req?.email);

@@ -98,7 +179,7 @@ export const authRoutes = new Elysia({ prefix: '/api/v1/auth' })
      }

      const token = await createSession(user.id);
-      set.headers['Set-Cookie'] = createSessionCookie(token);
+      set.headers['Set-Cookie'] = createSessionCookie(token, request.headers);

      authCounter.labels('login', 'true').inc();

@@ -109,6 +190,7 @@ export const authRoutes = new Elysia({ prefix: '/api/v1/auth' })
          name: user.name,
          role: user.role === 'expert' ? 'expert' as const : 'user' as const,
        },
+        token,
        features: getAuthFeatures(),
      };
    } catch (error) {
@@ -116,16 +198,20 @@ export const authRoutes = new Elysia({ prefix: '/api/v1/auth' })
    }
  })
  .post('/logout', async ({ request, set }) => {
-    await deleteSession(readSessionToken(request.headers.get('cookie')));
-    set.headers['Set-Cookie'] = clearSessionCookie();
+    const cookieHeader = request.headers.get('cookie');
+    await deleteSession(readSessionToken(cookieHeader));
+    set.headers['Set-Cookie'] = clearSessionCookie(request.headers);
    return { ok: true };
  })
-  .get('/google', ({ set }) => {
+  .get('/google', ({ query, set }) => {
    if (!env.googleOAuthEnabled) {
      set.status = 404;
      return { error: 'Google OAuth is not configured' };
    }

+    const platform = (query as Record<string, string>).platform ?? 'web';
+    const state = Buffer.from(JSON.stringify({ platform })).toString('base64url');
+
    const params = new URLSearchParams({
      client_id: env.googleClientId!,
      redirect_uri: env.googleRedirectUri!,
@@ -133,15 +219,96 @@ export const authRoutes = new Elysia({ prefix: '/api/v1/auth' })
      scope: 'openid email profile',
      access_type: 'offline',
      prompt: 'select_account',
+      state,
    });

-    set.redirect = `https://accounts.google.com/o/oauth2/v2/auth?${params.toString()}`;
+    set.status = 302;
+    set.headers['Location'] = `https://accounts.google.com/o/oauth2/v2/auth?${params.toString()}`;
  })
-  .get('/google/callback', ({ set }) => {
+  .get('/google/callback', async ({ query, set, request }) => {
    if (!env.googleOAuthEnabled) {
      set.status = 404;
      return { error: 'Google OAuth is not configured' };
    }

-    set.redirect = `${env.webAppUrl}/login?oauth=not-implemented`;
+    const q = query as Record<string, string>;
+    const code = q.code;
+    const error = q.error;
+    const platform = resolvePlatform(q.state);
+
+    // User denied or Google returned an error
+    const makeErrorUrl = (msg: string) =>
+      `${env.webAppUrl}/login?error=${encodeURIComponent(msg)}`;
+
+    if (error || !code) {
+      const url = makeErrorUrl(error ?? 'missing_code');
+      if (platform === 'tauri') return renderTauriDeepLinkPage(url);
+      set.status = 302;
+      set.headers['Location'] = url;
+      return;
+    }
+
+    // Exchange authorization code for tokens
+    let idPayload: GoogleIdPayload;
+    try {
+      const tokens = await exchangeGoogleCode(code);
+      idPayload = decodeGoogleIdToken(tokens.id_token);
+    } catch (err) {
+      const msg = err instanceof Error ? err.message : 'Google auth failed';
+      const url = makeErrorUrl(msg);
+      if (platform === 'tauri') return renderTauriDeepLinkPage(url);
+      set.status = 302;
+      set.headers['Location'] = url;
+      return;
+    }
+
+    // Validate email
+    if (!idPayload.email_verified || !idPayload.email) {
+      const url = makeErrorUrl('Email not verified by Google');
+      if (platform === 'tauri') return renderTauriDeepLinkPage(url);
+      set.status = 302;
+      set.headers['Location'] = url;
+      return;
+    }
+
+    const googleId = idPayload.sub;
+    const email = idPayload.email.trim().toLowerCase();
+    const name = idPayload.name?.trim() ?? email.split('@')[0];
+
+    try {
+      const db = createDbClient();
+
+      let user = await db.select().from(users).where(eq(users.googleId, googleId)).limit(1).then(r => r[0] ?? null);
+
+      if (!user) {
+        user = await db.select().from(users).where(eq(users.email, email)).limit(1).then(r => r[0] ?? null);
+        if (user) {
+          await db.update(users).set({ googleId }).where(eq(users.id, user.id));
+        }
+      }
+
+      if (!user) {
+        const inserted = await db
+          .insert(users)
+          .values({ email, name, googleId, role: 'user' })
+          .returning();
+        user = inserted[0];
+        authCounter.labels('register', 'true').inc();
+      }
+
+      const token = await createSession(user.id);
+      set.headers['Set-Cookie'] = createSessionCookie(token, request.headers);
+
+      authCounter.labels('login', 'true').inc();
+
+      const successUrl = `${env.webAppUrl}/login?token=${encodeURIComponent(token)}`;
+      if (platform === 'tauri') return renderTauriDeepLinkPage(successUrl);
+      set.status = 302;
+      set.headers['Location'] = successUrl;
+    } catch (err) {
+      const url = makeErrorUrl('Database unavailable');
+      if (platform === 'tauri') return renderTauriDeepLinkPage(url);
+      set.status = 302;
+      set.headers['Location'] = url;
+    }
  });
@@ -13,7 +13,7 @@ export const dashboardRoutes = new Elysia({ prefix: '/api/v1' })
  .get('/dashboard/summary', async ({ request }) => {
    try {
      const db = createDbClient();
-      const user = await getCurrentUser(request.headers.get('cookie'));
+      const user = await getCurrentUser(request.headers.get('cookie'), request.headers);

      const diseases = await db.select().from(diseaseCatalog).orderBy(diseaseCatalog.displayOrder);
      const manualRows = await db.select().from(manualClassifications).orderBy(desc(manualClassifications.createdAt)).limit(1);
@@ -175,7 +175,7 @@ function getFileFromBody(body: unknown): File | null {

 export const diagnosisRoutes = new Elysia({ prefix: '/api/v1' })
  .post('/diagnoses', async ({ body, request }) => {
-    const user = await getCurrentUser(request.headers.get('cookie'));
+    const user = await getCurrentUser(request.headers.get('cookie'), request.headers);
    if (!user) return unauthorized('Authentication required');

    const file = getFileFromBody(body);
@@ -251,7 +251,7 @@ export const diagnosisRoutes = new Elysia({ prefix: '/api/v1' })
    }
  })
  .get('/diagnoses', async ({ request }) => {
-    const user = await getCurrentUser(request.headers.get('cookie'));
+    const user = await getCurrentUser(request.headers.get('cookie'), request.headers);
    if (!user) return unauthorized('Authentication required');

    try {
@@ -270,7 +270,7 @@ export const diagnosisRoutes = new Elysia({ prefix: '/api/v1' })
    }
  })
  .get('/diagnoses/:id', async ({ params, request }) => {
-    const user = await getCurrentUser(request.headers.get('cookie'));
+    const user = await getCurrentUser(request.headers.get('cookie'), request.headers);
    if (!user) return unauthorized('Authentication required');

    try {
@@ -16,7 +16,7 @@ function isDiagnosisRecordOrNull(record: unknown): record is DiagnosisRecord {

 export const expertRoutes = new Elysia({ prefix: '/api/v1/expert' })
  .get('/reviews', async ({ request }) => {
-    const user = await getCurrentUser(request.headers.get('cookie'));
+    const user = await getCurrentUser(request.headers.get('cookie'), request.headers);
    if (!user) return unauthorized('Authentication required');
    if (user.role !== 'expert') return forbidden('Expert role required');

@@ -36,7 +36,7 @@ export const expertRoutes = new Elysia({ prefix: '/api/v1/expert' })
    }
  })
  .post('/reviews/:diagnosisId', async ({ params, body, request }) => {
-    const user = await getCurrentUser(request.headers.get('cookie'));
+    const user = await getCurrentUser(request.headers.get('cookie'), request.headers);
    if (!user) return unauthorized('Authentication required');
    if (user.role !== 'expert') return forbidden('Expert role required');

@@ -1,8 +1,25 @@
-# ML Service — Rust Axum ONNX Runtime
+# ML Inference Service — ZeaVis Edu

-Layanan inferensi machine learning berbasis Rust dengan Axum web framework dan ONNX Runtime untuk klasifikasi penyakit daun jagung. Service ini menyediakan endpoint HTTP untuk prediksi real-time dengan performa tinggi dan konsumsi resource minimal.
+> Layanan inferensi machine learning berbasis Rust/Axum + ONNX Runtime untuk klasifikasi penyakit daun jagung.

-## Fitur
+← [Kembali ke README utama](../../README.md)
+
+---
+
+## Daftar Isi
+
+1. [Fitur](#1-fitur)
+2. [Prasyarat & Instalasi](#2-prasyarat--instalasi)
+3. [Menjalankan Service](#3-menjalankan-service)
+4. [Environment Variables](#4-environment-variables)
+5. [Endpoint API](#5-endpoint-api)
+6. [Verifikasi & Testing](#6-verifikasi--testing)
+7. [Docker Deployment](#7-docker-deployment)
+8. [Troubleshooting](#8-troubleshooting)
+
+---
+
+## 1. Fitur

 - **Framework:** Axum (async Rust web framework)
 - **Runtime Inferensi:** ONNX Runtime untuk kompatibilitas lintas platform
@@ -10,15 +27,13 @@ Layanan inferensi machine learning berbasis Rust dengan Axum web framework dan O
 - **Endpoint:** Health check, metadata, dan prediksi gambar
 - **Multipart Upload:** Dukungan upload gambar langsung via HTTP POST

-## Prasyarat
+---
+
+## 2. Prasyarat & Instalasi

 - Rust 1.70+ dan Cargo
 - Model ONNX di `../../Machine_Learning/model/model.onnx` (atau path custom via `MODEL_PATH`)

-## Instalasi & Setup
-
-### Instalasi Dependensi
-
 Dependensi Rust sudah terdaftar di `Cargo.toml`. Cargo akan mengunduh dan mengkompilasi otomatis saat pertama kali build.

 ```bash
@@ -27,75 +42,58 @@ cargo build

 Output build lokal berada di `target/` dan direktori tersebut diabaikan oleh Git.

-## Menjalankan Service Lokal
+---
+
+## 3. Menjalankan Service

 Semua perintah di bawah dijalankan dari direktori `apps/ml-service`.

-### Opsi 1: Default (Port 8000, Model dari Machine_Learning/)
+### Opsi 1: Default (Port 8000)

 ```bash
-cd apps/ml-service
 cargo run
 ```

-Service akan mencari model di path default dan mendengarkan di `http://localhost:8000`:
+Service akan mencari model di path default:
 ```
 ../../Machine_Learning/model/model.onnx
 ```

 ### Opsi 2: Local Development dengan .env.example (Port 8001)

-Untuk development lokal dengan port 8001 (sesuai `.env.example`):
-
 ```bash
-cd apps/ml-service
 source .env.example
 cargo run
 ```

-Service akan mendengarkan di `http://localhost:8001` karena `ML_SERVICE_PORT=8001` di `.env.example`.
-
-### Opsi 3: Custom Model Path
-
-Jika model berada di lokasi lain, gunakan environment variable `MODEL_PATH`:
+### Opsi 3: Custom Model Path & Port

 ```bash
-cd apps/ml-service
-MODEL_PATH=/path/to/model.onnx cargo run
-```
-
-Atau kombinasikan dengan port custom:
-
-```bash
-cd apps/ml-service
 ML_SERVICE_PORT=9000 MODEL_PATH=/path/to/model.onnx cargo run
 ```

-## Environment Variables
+---
+
+## 4. Environment Variables

 | Variable | Default | Keterangan |
 |---|---|---|
 | `ML_SERVICE_HOST` | `0.0.0.0` | Bind address |
-| `ML_SERVICE_PORT` | `8000` | Bind port (override untuk local dev dengan `.env.example`) |
+| `ML_SERVICE_PORT` | `8000` | Bind port |
 | `MODEL_PATH` | `../../Machine_Learning/model/model.onnx` | Path ke file model ONNX |
-| `MODEL_INPUT_SIZE` | `224` | Ukuran input gambar (224x224 untuk EfficientNetV2B0) |
+| `MODEL_INPUT_SIZE` | `224` | Ukuran input gambar (224×224 untuk EfficientNetV2B0) |
 | `RUST_LOG` | `info` | Level logging (debug, info, warn, error) |

-## Endpoint API
+---

-### 1. Health Check
+## 5. Endpoint API
+
+### Health Check

-**Default (port 8000):**
 ```bash
 curl http://localhost:8000/health
 ```

-**Local dev dengan .env.example (port 8001):**
-```bash
-curl http://localhost:8001/health
-```
-
-**Response:**
 ```json
 {
  "status": "ok",
@@ -103,19 +101,12 @@ curl http://localhost:8001/health
 }
 ```

-### 2. Metadata
+### Metadata

-**Default (port 8000):**
 ```bash
 curl http://localhost:8000/metadata
 ```

-**Local dev dengan .env.example (port 8001):**
-```bash
-curl http://localhost:8001/metadata
-```
-
-**Response:**
 ```json
 {
  "service_name": "zeavis-ml-service",
@@ -123,32 +114,19 @@ curl http://localhost:8001/metadata
  "model_path": "../../Machine_Learning/model/model.onnx",
  "model_loaded": true,
  "input_size": 224,
-  "labels": [
-    "Bercak Daun",
-    "Daun Sehat",
-    "Karat Daun",
-    "Hawar Daun"
-  ]
+  "labels": ["Bercak Daun", "Daun Sehat", "Karat Daun", "Hawar Daun"]
 }
 ```

-### 3. Prediksi
+### Prediksi

 Upload gambar daun jagung untuk klasifikasi:

-**Default (port 8000):**
 ```bash
 curl -X POST http://localhost:8000/predict \
  -F "file=@/path/to/corn-leaf.jpg"
 ```

-**Local dev dengan .env.example (port 8001):**
-```bash
-curl -X POST http://localhost:8001/predict \
-  -F "file=@/path/to/corn-leaf.jpg"
-```
-
-**Response:**
 ```json
 {
  "label": "Daun Sehat",
@@ -162,120 +140,45 @@ curl -X POST http://localhost:8001/predict \
 }
 ```

-## Verifikasi & Testing
+---
+
+## 6. Verifikasi & Testing

 ### Build Produksi

 ```bash
 cargo build --release
+# Binary di target/release/zeavis-ml-service
 ```

-Output binary akan tersedia di `target/release/zeavis-ml-service`.
-
 ### Menjalankan Tests

 ```bash
 cargo test
 ```

-Tests mencakup validasi loading model, preprocessing gambar, dan output prediksi.
+### Verifikasi Manual (default port 8000)

-### Verifikasi Manual
+```bash
+# 1. Start service
+cargo run

-#### Dengan default port 8000:
+# 2. Health check
+curl http://localhost:8000/health

-1. Jalankan service:
-   ```bash
-   cargo run
-   ```
+# 3. Metadata
+curl http://localhost:8000/metadata

-2. Di terminal lain, test health endpoint:
-   ```bash
-   curl http://localhost:8000/health
-   ```
-
-3. Test metadata:
-   ```bash
-   curl http://localhost:8000/metadata
-   ```
-
-4. Test prediksi dengan gambar sample:
-   ```bash
-   curl -X POST http://localhost:8000/predict \
+# 4. Prediksi
+curl -X POST http://localhost:8000/predict \
  -F "file=@../../Machine_Learning/dataset/Daun\ Sehat/sample.jpg"
-   ```
-
-#### Dengan local dev port 8001 (.env.example):
-
-1. Jalankan service dengan .env.example:
-   ```bash
-   source .env.example
-   cargo run
-   ```
-
-2. Di terminal lain, test health endpoint:
-   ```bash
-   curl http://localhost:8001/health
-   ```
-
-3. Test metadata:
-   ```bash
-   curl http://localhost:8001/metadata
-   ```
-
-4. Test prediksi dengan gambar sample:
-   ```bash
-   curl -X POST http://localhost:8001/predict \
-     -F "file=@../../Machine_Learning/dataset/Daun\ Sehat/sample.jpg"
-   ```
-
-## Troubleshooting
-
-### Model tidak ditemukan
-
-**Error:** `Failed to load model: No such file or directory`
-
-**Solusi:** Pastikan file model tersedia di path yang benar:
-```bash
-ls -la ../../Machine_Learning/model/model.onnx
 ```

-Atau set path custom:
-```bash
-MODEL_PATH=/absolute/path/to/model.onnx cargo run
-```
+---

-### Port sudah digunakan
+## 7. Docker Deployment

-**Error:** `Address already in use`
-
-**Solusi:** Service menggunakan port 8000 secara default. Jika port sudah digunakan, ubah dengan environment variable:
-
-```bash
-ML_SERVICE_PORT=9000 cargo run
-```
-
-Atau jika menggunakan `.env.example` (port 8001), pastikan tidak ada service lain di port tersebut:
-
-```bash
-lsof -i :8001
-```
-
-### ONNX Runtime tidak kompatibel
-
-**Error:** `ONNX Runtime initialization failed`
-
-**Solusi:** Pastikan ONNX Runtime binary kompatibel dengan sistem operasi. Cargo akan mengunduh binary yang sesuai otomatis. Jika masalah persisten, coba rebuild:
-```bash
-cargo clean
-cargo build
-```
-
-## Deployment
-
-### Docker
-
-Service dapat di-deploy via Docker. Jalankan build dari root repository karena Dockerfile menyalin source service dan artifact ONNX dari beberapa direktori repo.
+Service dapat di-deploy via Docker. Build dari root repository karena Dockerfile menyalin source service dan artifact ONNX dari beberapa direktori repo.

 ```bash
 docker build -f apps/ml-service/Dockerfile -t zeavis-ml-service .
@@ -284,11 +187,42 @@ docker run -p 8000:8000 zeavis-ml-service

 Pastikan `Machine_Learning/model/model.onnx` sudah dibuat sebelum build image.

-### Docker Compose
+---

-Lihat `docker-compose.yml` di root repository untuk deployment lengkap dengan web, API, dan ML service.
+## 8. Troubleshooting

-## Dokumentasi Terkait
+### Model tidak ditemukan

- [`Machine_Learning/README.md`](../../Machine_Learning/README.md) — Panduan training dan ekspor model ONNX
- [`README.md`](../../README.md) — Dokumentasi proyek utama
+**Error:** `Failed to load model: No such file or directory`
+
+**Solusi:**
+```bash
+ls -la ../../Machine_Learning/model/model.onnx
+# Atau set path custom:
+MODEL_PATH=/absolute/path/to/model.onnx cargo run
+```
+
+### Port sudah digunakan
+
+**Error:** `Address already in use`
+
+**Solusi:**
+```bash
+ML_SERVICE_PORT=9000 cargo run
+# Cek port yang digunakan:
+lsof -i :8000
+```
+
+### ONNX Runtime tidak kompatibel
+
+**Error:** `ONNX Runtime initialization failed`
+
+**Solusi:** Pastikan binary ONNX Runtime kompatibel dengan sistem operasi. Jika masalah persisten:
+```bash
+cargo clean
+cargo build
+```
+
+---
+
+← [Kembali ke README utama](../../README.md) &bull; [Pipeline ML →](../../Machine_Learning/README.md) &bull; [Infra →](../../infra/README.md)
@@ -0,0 +1,3 @@
+# Default ignored files
+/shelf/
+/workspace.xml
@@ -0,0 +1,13 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="DeviceTable">
+    <option name="columnSorters">
+      <list>
+        <ColumnSorterState>
+          <option name="column" value="Name" />
+          <option name="order" value="ASCENDING" />
+        </ColumnSorterState>
+      </list>
+    </option>
+  </component>
+</project>
@@ -0,0 +1,17 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="DiscordProjectSettings">
+    <option name="show" value="ASK" />
+    <option name="description" value="" />
+    <option name="applicationTheme" value="default" />
+    <option name="iconsTheme" value="default" />
+    <option name="button1Title" value="" />
+    <option name="button1Url" value="" />
+    <option name="button2Title" value="" />
+    <option name="button2Url" value="" />
+    <option name="customApplicationId" value="" />
+  </component>
+  <component name="ProjectRootManager" version="2">
+    <output url="file://$PROJECT_DIR$/out" />
+  </component>
+</project>
@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/tauri.iml" filepath="$PROJECT_DIR$/.idea/tauri.iml" />
+    </modules>
+  </component>
+</project>
@@ -0,0 +1,9 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="JAVA_MODULE" version="4">
+  <component name="NewModuleRootManager" inherit-compiler-output="true">
+    <exclude-output />
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>
@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$/../.." vcs="Git" />
+  </component>
+</project>
@@ -12,5 +12,7 @@ tauri-build = { version = "2", features = [] }

 [dependencies]
 tauri = { version = "2", default-features = false, features = ["wry", "common-controls-v6", "dynamic-acl", "x11", "dbus", "custom-protocol"] }
+tauri-plugin-opener = "2"
+tauri-plugin-deep-link = "2"
 serde = { version = "1", features = ["derive"] }
 serde_json = "1"
@@ -3,6 +3,9 @@
  "description": "Capability for the main window",
  "windows": ["main"],
  "permissions": [
-    "core:default"
+    "core:default",
+    "opener:default",
+    "opener:allow-open-url",
+    "deep-link:default"
  ]
 }
@@ -0,0 +1,45 @@
+#!/usr/bin/env bash
+# Patches the generated AndroidManifest.xml with:
+# 1. CAMERA permission
+# 2. Deep link intent filter (zeavisedu:// scheme) for Google OAuth return
+# Run after `tauri android init` to apply.
+set -euo pipefail
+
+MANIFEST="gen/android/app/src/main/AndroidManifest.xml"
+
+if [ ! -f "$MANIFEST" ]; then
+  echo "ERROR: $MANIFEST not found. Run 'tauri android init' first." >&2
+  exit 1
+fi
+
+# ── CAMERA permission ──────────────────────────────────────────────────
+
+if ! grep -q 'android.permission.CAMERA' "$MANIFEST"; then
+  echo "Adding CAMERA permission to AndroidManifest.xml..."
+  sed -i 's|<uses-permission android:name="android.permission.INTERNET" />|<uses-permission android:name="android.permission.INTERNET" />\n    <uses-permission android:name="android.permission.CAMERA" />\n    <uses-feature android:name="android.hardware.camera" android:required="false" />\n    <uses-feature android:name="android.hardware.camera.autofocus" android:required="false" />|' "$MANIFEST"
+else
+  echo "CAMERA permission already present."
+fi
+
+# ── Deep link intent filter ────────────────────────────────────────────
+# Allows the app to receive zeavisedu:// scheme URLs from the system browser
+# (used after Google OAuth completes in external browser on Android)
+
+DEEP_LINK_FILTER='<!-- Deep link for Google OAuth return from system browser -->\
+        <intent-filter android:autoVerify="true">\
+            <action android:name="android.intent.action.VIEW" />\
+            <category android:name="android.intent.category.DEFAULT" />\
+            <category android:name="android.intent.category.BROWSABLE" />\
+            <data android:scheme="zeavisedu" />\
+        </intent-filter>'
+
+if grep -q 'android:scheme="zeavisedu"' "$MANIFEST"; then
+  echo "Deep link intent filter already present."
+else
+  echo "Adding deep link intent filter to AndroidManifest.xml..."
+  # Insert before the closing </activity> tag of MainActivity
+  sed -i "s|</activity>|${DEEP_LINK_FILTER}\n        </activity>|" "$MANIFEST"
+  echo "Deep link intent filter added."
+fi
+
+echo "AndroidManifest patched successfully."
@@ -1,6 +1,8 @@
 #[cfg_attr(mobile, tauri::mobile_entry_point)]
 pub fn run() {
    tauri::Builder::default()
+        .plugin(tauri_plugin_opener::init())
+        .plugin(tauri_plugin_deep_link::init())
        .run(tauri::generate_context!())
        .expect("error while running tauri application");
 }
@@ -5,7 +5,8 @@ COPY package.json bun.lock bunfig.toml tsconfig.base.json ./
 COPY packages/shared/package.json packages/shared/package.json
 COPY apps/web/package.json apps/web/package.json
 COPY apps/api/package.json apps/api/package.json
-RUN bun install --frozen-lockfile
+COPY apps/tauri/package.json apps/tauri/package.json
+RUN bun install

 COPY packages/shared packages/shared
 COPY apps/web apps/web
@@ -22,6 +22,7 @@
    "react-router-dom": "^7.15.1",
    "recharts": "3.8.1",
    "tailwind-merge": "^3.6.0",
+    "tailwindcss": "^4.3.1",
    "web-vitals": "5.3.0",
    "zustand": "^5.0.13"
  },
@@ -1,9 +1,10 @@
-import { FormEvent, useState } from 'react';
+import { FormEvent, useState, useCallback } from 'react';
 import { Eye, EyeOff } from 'lucide-react';
 import { Button } from '@/components/ui/button';
 import { Card, CardContent, CardDescription, CardHeader, CardTitle } from '@/components/ui/card';
 import { Input } from '@/components/ui/input';
 import { Label } from '@/components/ui/label';
+import { isTauri, openUrl } from '@/lib/tauri';

 type AuthFormProps = {
  mode: 'login' | 'register';
@@ -25,6 +26,16 @@ export function AuthForm({ mode, isSubmitting, error, googleOAuthEnabled, onSubm
    await onSubmit({ name, email, password });
  }

+  const handleGoogleLogin = useCallback(async (e: React.MouseEvent) => {
+    e.preventDefault();
+    const platform = isTauri() ? 'tauri' : 'web';
+    // Use API base URL, not window.location.origin — on Tauri Android
+    // the origin is http://tauri.localhost which is not the API server.
+    const apiBase = import.meta.env.VITE_API_BASE_URL || window.location.origin;
+    const googleUrl = `${apiBase}/api/v1/auth/google?platform=${platform}`;
+    await openUrl(googleUrl);
+  }, []);
+
  return (
    <Card className="mx-auto w-full max-w-md">
      <CardHeader>
@@ -75,8 +86,15 @@ export function AuthForm({ mode, isSubmitting, error, googleOAuthEnabled, onSubm
          </Button>
        </form>
        {googleOAuthEnabled && (
-          <Button className="mt-3 w-full" variant="outline" asChild>
-            <a href="/api/v1/auth/google">Masuk dengan Google</a>
+          <Button className="mt-3 w-full flex items-center justify-center gap-2.5" variant="outline" onClick={handleGoogleLogin} type="button">
+            <svg viewBox="0 0 24 24" className="h-5 w-5" aria-hidden="true">
+              <path fill="#4285F4" d="M22.56 12.25c0-.78-.07-1.53-.2-2.25H12v4.26h5.92a5.06 5.06 0 0 1-2.2 3.32v2.77h3.57c2.08-1.92 3.28-4.74 3.28-8.1z" />
+              <path fill="#34A853" d="M12 23c2.97 0 5.46-.98 7.28-2.66l-3.57-2.77c-.98.66-2.23 1.06-3.71 1.06-2.86 0-5.29-1.93-6.16-4.53H2.18v2.84C3.99 20.53 7.7 23 12 23z" />
+              <path fill="#FBBC05" d="M5.84 14.09c-.22-.66-.35-1.36-.35-2.09s.13-1.43.35-2.09V7.07H2.18C1.43 8.55 1 10.22 1 12s.43 3.45 1.18 4.93l2.85-2.22.81-.62z" />
+              <path fill="#EA4335" d="M12 5.38c1.62 0 3.06.56 4.21 1.64l3.15-3.15C17.45 2.09 14.97 1 12 1 7.7 1 3.99 3.47 2.18 7.07l3.66 2.84c.87-2.6 3.3-4.53 6.16-4.53z" />
+              <path fill="none" d="M1 1h22v22H1z" />
+            </svg>
+            Masuk dengan Google
          </Button>
        )}
      </CardContent>
@@ -10,27 +10,32 @@ type AuthGuardProps = {
 };

 export function AuthGuard({ children, requireExpert = false }: AuthGuardProps) {
+  const user = useAuthStore((state) => state.user);
  const setUser = useAuthStore((state) => state.setUser);
  const query = useQuery({
    queryKey: ['auth', 'me'],
    queryFn: () => apiClient.getMe(),
+    staleTime: 30_000,
  });

  useEffect(() => {
-    if (query.data) {
+    if (query.data?.user) {
      setUser(query.data.user);
    }
  }, [query.data, setUser]);

-  if (query.isLoading) {
+  // Tunjukkan loading hanya jika belum ada user di store
+  if (query.isLoading && !user) {
    return <main className="min-h-screen p-8 text-center text-muted-foreground">Memeriksa sesi...</main>;
  }

-  if (!query.data?.user) {
+  // Cek store dulu, baru query — mencegah redirect saat refetch background
+  const currentUser = query.data?.user ?? user;
+  if (!currentUser) {
    return <Navigate to="/login" replace />;
  }

-  if (requireExpert && query.data.user.role !== 'expert') {
+  if (requireExpert && currentUser.role !== 'expert') {
    return <Navigate to="/dashboard" replace />;
  }

@@ -9,10 +9,11 @@ export function AuthInitializer() {
    queryKey: ['auth', 'me'],
    queryFn: () => apiClient.getMe(),
    retry: false,
+    staleTime: 30_000,
  });

  useEffect(() => {
-    if (query.data) {
+    if (query.data?.user) {
      setUser(query.data.user);
    }
  }, [query.data, setUser]);
@@ -0,0 +1,202 @@
+import { useRef, useState, useCallback, useEffect } from "react";
+import { SwitchCamera, CameraOff, Aperture } from "lucide-react";
+import { Button } from "@/components/ui/button";
+
+interface CameraCaptureProps {
+  onCapture: (file: File) => void;
+  onClose: () => void;
+}
+
+type FacingMode = "environment" | "user";
+
+export function CameraCapture({ onCapture, onClose }: CameraCaptureProps) {
+  const videoRef = useRef<HTMLVideoElement | null>(null);
+  const streamRef = useRef<MediaStream | null>(null);
+  const canvasRef = useRef<HTMLCanvasElement | null>(null);
+  const [facingMode, setFacingMode] = useState<FacingMode>("environment");
+  const [status, setStatus] = useState<"loading" | "ready" | "error" | "denied">("loading");
+  const [errorMsg, setErrorMsg] = useState<string>("");
+
+  const stopStream = useCallback(() => {
+    if (streamRef.current) {
+      streamRef.current.getTracks().forEach((t) => t.stop());
+      streamRef.current = null;
+    }
+  }, []);
+
+  const startCamera = useCallback(
+    async (mode: FacingMode) => {
+      stopStream();
+      setStatus("loading");
+      setErrorMsg("");
+
+      try {
+        const stream = await navigator.mediaDevices.getUserMedia({
+          video: {
+            facingMode: mode,
+            width: { ideal: 1920 },
+            height: { ideal: 1080 },
+          },
+          audio: false,
+        });
+
+        streamRef.current = stream;
+        if (videoRef.current) {
+          videoRef.current.srcObject = stream;
+          await videoRef.current.play();
+        }
+        setStatus("ready");
+      } catch (err: unknown) {
+        const e = err as DOMException;
+        if (e.name === "NotAllowedError" || e.name === "PermissionDeniedError") {
+          setStatus("denied");
+          setErrorMsg("Izin kamera ditolak. Buka pengaturan untuk mengizinkan akses kamera.");
+        } else if (e.name === "NotFoundError") {
+          setStatus("error");
+          setErrorMsg("Kamera tidak ditemukan pada perangkat ini.");
+        } else if (e.name === "NotReadableError") {
+          setStatus("error");
+          setErrorMsg("Kamera sedang digunakan oleh aplikasi lain.");
+        } else {
+          setStatus("error");
+          setErrorMsg(`Gagal mengakses kamera: ${e.message}`);
+        }
+      }
+    },
+    [stopStream],
+  );
+
+  // Start camera on mount
+  useEffect(() => {
+    startCamera(facingMode);
+    return () => stopStream();
+  }, []); // eslint-disable-line react-hooks/exhaustive-deps
+
+  const toggleFacing = () => {
+    const next = facingMode === "environment" ? "user" : "environment";
+    setFacingMode(next);
+    startCamera(next);
+  };
+
+  const handleCapture = () => {
+    const video = videoRef.current;
+    const canvas = canvasRef.current;
+    if (!video || !canvas) return;
+
+    const vw = video.videoWidth;
+    const vh = video.videoHeight;
+    canvas.width = vw;
+    canvas.height = vh;
+
+    const ctx = canvas.getContext("2d");
+    if (!ctx) return;
+
+    ctx.drawImage(video, 0, 0, vw, vh);
+    canvas.toBlob(
+      (blob) => {
+        if (!blob) return;
+        const file = new File([blob], `camera-${Date.now()}.jpg`, {
+          type: "image/jpeg",
+        });
+        stopStream();
+        onCapture(file);
+      },
+      "image/jpeg",
+      0.92,
+    );
+  };
+
+  return (
+    <div className="flex flex-col items-center gap-3 w-full">
+      {/* Viewfinder */}
+      <div className="relative w-full rounded-xl overflow-hidden bg-black aspect-[4/3] max-h-[420px]">
+        {status === "loading" && (
+          <div className="absolute inset-0 flex items-center justify-center bg-black/80 text-white">
+            <div className="flex flex-col items-center gap-2">
+              <div className="h-8 w-8 border-2 border-white border-t-transparent rounded-full animate-spin" />
+              <span className="text-sm">Membuka kamera...</span>
+            </div>
+          </div>
+        )}
+
+        {(status === "error" || status === "denied") && (
+          <div className="absolute inset-0 flex items-center justify-center bg-black/90 text-white p-6">
+            <div className="flex flex-col items-center gap-3 text-center">
+              <CameraOff className="text-red-400" size={40} />
+              <p className="text-sm text-red-300">{errorMsg}</p>
+              <Button
+                variant="outline"
+                className="h-9 px-3 text-sm text-white border-white/30 hover:bg-white/10"
+                onClick={() => startCamera(facingMode)}
+              >
+                Coba Lagi
+              </Button>
+            </div>
+          </div>
+        )}
+
+        <video
+          ref={videoRef}
+          autoPlay
+          playsInline
+          muted
+          className={`w-full h-full object-cover ${status === "ready" ? "opacity-100" : "opacity-0"}`}
+        />
+
+        {/* Scan area overlay */}
+        {status === "ready" && (
+          <div className="absolute inset-0 flex items-center justify-center pointer-events-none">
+            <div className="absolute inset-0 bg-black/20" />
+            <div
+              className="relative flex items-center justify-center"
+              style={{ width: "70%", height: "75%" }}
+            >
+              <div className="absolute top-0 left-0 w-6 h-6 border-t-2 border-l-2 border-lime-300" />
+              <div className="absolute top-0 right-0 w-6 h-6 border-t-2 border-r-2 border-lime-300" />
+              <div className="absolute bottom-0 left-0 w-6 h-6 border-b-2 border-l-2 border-lime-300" />
+              <div className="absolute bottom-0 right-0 w-6 h-6 border-b-2 border-r-2 border-lime-300" />
+              <div className="text-white text-center flex flex-col gap-1">
+                <span className="text-xs font-semibold tracking-widest">
+                  AREA SCAN
+                </span>
+              </div>
+            </div>
+          </div>
+        )}
+      </div>
+
+      {/* Controls */}
+      <div className="flex items-center justify-center gap-4 w-full">
+        <Button
+          variant="outline"
+          className="rounded-full h-12 w-12 p-0"
+          onClick={onClose}
+          title="Tutup kamera"
+        >
+          <CameraOff size={20} />
+        </Button>
+
+        <Button
+          className="rounded-full h-16 w-16 p-0 bg-white border-4 border-green-500 hover:bg-green-50"
+          onClick={handleCapture}
+          disabled={status !== "ready"}
+          title="Ambil foto"
+        >
+          <Aperture className="text-green-600" size={32} />
+        </Button>
+
+        <Button
+          variant="outline"
+          className="rounded-full h-12 w-12 p-0"
+          onClick={toggleFacing}
+          title="Ganti kamera"
+        >
+          <SwitchCamera size={20} />
+        </Button>
+      </div>
+
+      {/* Hidden canvas for capture */}
+      <canvas ref={canvasRef} className="hidden" />
+    </div>
+  );
+}
@@ -9,12 +9,13 @@ import {
  RefreshCcw,
  FlaskConical,
  CheckCircle2,
+  Camera,
 } from "lucide-react";
 import { RiskBadge } from "@/components/risk-badge";

 type Props = {
  imageUrl: string;
-  confidence: number; // contoh: 0.95
+  confidence: number;
  diseaseName: string;
  scientificName: string;
  riskLevel: string;
@@ -41,8 +42,8 @@ export function DiagnosisResultView({

  const getRiskLevelKey = (level: string): "low" | "medium" | "high" => {
    const normalized = level.toLowerCase();
-    if (normalized.includes("rendah")) return "low";
-    if (normalized.includes("tinggi")) return "high";
+    if (normalized.includes("rendah") || normalized === "low") return "low";
+    if (normalized.includes("tinggi") || normalized === "high") return "high";
    return "medium";
  };

@@ -62,10 +63,8 @@ export function DiagnosisResultView({
            alt="Daun yang dianalisis"
            className="w-full h-48 md:h-64 object-cover rounded-xl"
          />
-          <div className="mt-3 flex items-center gap-2 text-slate-500 text-sm px-1">
-            <span className="w-4 h-4 bg-slate-200 rounded flex items-center justify-center text-[10px]">
-              📷
-            </span>
+          <div className="mt-3 flex items-center gap-2 text-slate-500 text-md px-1">
+            <Camera className="w-5 h-5 text-gray-500" />
            Gambar yang dianalisis
          </div>
        </div>
@@ -86,18 +85,35 @@ export function DiagnosisResultView({
          <div className="space-y-2 mb-4">
            <div className="flex justify-between text-sm font-bold text-slate-700">
              <span>Tingkat Keyakinan AI</span>
-              <span className="text-emerald-600">{confidencePercent}%</span>
+              <span
+                className={
+                  confidencePercent >= 75
+                    ? "text-emerald-600"
+                    : "text-amber-500"
+                }
+              >
+                {confidencePercent}%
+              </span>
            </div>
            <div className="w-full bg-slate-200 rounded-full h-2.5 overflow-hidden">
              <div
-                className="bg-emerald-500 h-2.5 rounded-full transition-all duration-1000"
+                className={`h-2.5 rounded-full transition-all duration-1000 ${
+                  confidencePercent >= 75 ? "bg-emerald-500" : "bg-amber-500"
+                }`}
                style={{ width: `${confidencePercent}%` }}
              ></div>
            </div>
+            {confidencePercent >= 75 ? (
              <p className="text-[11px] text-emerald-600 flex items-center gap-1 font-medium">
-              <CheckCircle2 className="w-3 h-3" /> Di atas ambang batas minimum
-              (75%)
+                <CheckCircle2 className="w-3 h-3" /> Di atas ambang batas
+                minimum (75%)
              </p>
+            ) : (
+              <p className="text-[11px] text-amber-600 flex items-center gap-1 font-medium">
+                <AlertTriangle className="w-3 h-3" /> Di bawah ambang batas
+                minimum (75%)
+              </p>
+            )}
          </div>

          <div className="flex items-center gap-3 pt-4 border-t border-amber-200/50">
@@ -14,7 +14,29 @@ import type {
 } from '@zeavis/shared';
 import { recordApiCall } from './telemetry';

-const apiBaseUrl = import.meta.env.VITE_API_BASE_URL ?? '';
+const apiBaseUrl = import.meta.env.VITE_API_BASE_URL ?? 'https://zeavisedu.asepharyana.my.id';
+
+const AUTH_TOKEN_KEY = 'zeavis_auth_token';
+
+function getAuthToken(): string | null {
+  try {
+    return localStorage.getItem(AUTH_TOKEN_KEY);
+  } catch {
+    return null;
+  }
+}
+
+export function setAuthToken(token: string | null) {
+  try {
+    if (token) {
+      localStorage.setItem(AUTH_TOKEN_KEY, token);
+    } else {
+      localStorage.removeItem(AUTH_TOKEN_KEY);
+    }
+  } catch {
+    // localStorage may throw in private browsing
+  }
+}

 export interface ApiError extends Error {
  status: number;
@@ -24,10 +46,21 @@ export interface ApiError extends Error {
 async function fetchApi<T>(endpoint: string, options?: RequestInit): Promise<T> {
  const start = performance.now();
  const url = `${apiBaseUrl}${endpoint}`;
+  const token = getAuthToken();
+  const headers = new Headers(options?.headers);
+
+  if (token) {
+    headers.set('Authorization', `Bearer ${token}`);
+  }
+
+  if (options?.body && !options.method) {
+    // auto-set Content-Type for JSON bodies
+  }
+
  const response = await fetch(url, {
    credentials: 'include',
    ...options,
-    headers: options?.headers,
+    headers,
  });

  const duration = performance.now() - start;
@@ -93,23 +126,29 @@ export const apiClient = {
  },

  async register(payload: RegisterRequest): Promise<AuthResponse> {
-    return fetchApi('/api/v1/auth/register', {
+    const result = await fetchApi<AuthResponse>('/api/v1/auth/register', {
      method: 'POST',
      headers: { 'Content-Type': 'application/json' },
      body: JSON.stringify(payload),
    });
+    if (result.token) setAuthToken(result.token);
+    return result;
  },

  async login(payload: AuthRequest): Promise<AuthResponse> {
-    return fetchApi('/api/v1/auth/login', {
+    const result = await fetchApi<AuthResponse>('/api/v1/auth/login', {
      method: 'POST',
      headers: { 'Content-Type': 'application/json' },
      body: JSON.stringify(payload),
    });
+    if (result.token) setAuthToken(result.token);
+    return result;
  },

  async logout(): Promise<{ ok: boolean }> {
-    return fetchApi('/api/v1/auth/logout', { method: 'POST' });
+    const result = await fetchApi<{ ok: boolean }>('/api/v1/auth/logout', { method: 'POST' });
+    setAuthToken(null);
+    return result;
  },

  // Disease catalog methods
@@ -0,0 +1,25 @@
+/**
+ * Lightweight Tauri environment detection and utilities.
+ * Avoids importing @tauri-apps/api at module level so the web build
+ * doesn't bundle Tauri internals.
+ */
+
+let _isTauri: boolean | null = null;
+
+export function isTauri(): boolean {
+  if (_isTauri !== null) return _isTauri;
+  _isTauri =
+    typeof window !== 'undefined' &&
+    '__TAURI_INTERNALS__' in window;
+  return _isTauri;
+}
+
+export async function openUrl(url: string): Promise<void> {
+  if (!isTauri()) {
+    window.location.href = url;
+    return;
+  }
+  // Lazy-import Tauri opener only in Tauri context
+  const { openUrl: tauriOpenUrl } = await import('@tauri-apps/plugin-opener');
+  await tauriOpenUrl(url);
+}
@@ -71,11 +71,7 @@ export function DiagnosisDetailPage() {
            Hasil deteksi AI dan panduan edukasi
          </p>
        </div>
-        <Button
-          asChild
-          variant="outline"
-          className="border-[#214B11] text-[#214B11] hover:bg-[#214B11] hover:text-white"
-        >
+        <Button asChild variant="outline">
          <Link to="/diagnoses">Kembali ke Riwayat</Link>
        </Button>
      </div>
@@ -1,15 +1,48 @@
-import { useState } from "react";
+import { useState, useEffect, useRef } from "react";
 import { Link, useNavigate } from "react-router-dom";
 import { useMutation, useQuery, useQueryClient } from "@tanstack/react-query";
 import { AuthForm } from "@/components/auth-form";
-import { apiClient } from "@/lib/api-client";
+import { apiClient, setAuthToken } from "@/lib/api-client";
 import { useAuthStore } from "@/store/auth-store";

+function getUrlParam(name: string): string | null {
+  return new URLSearchParams(window.location.search).get(name);
+}
+
 export function LoginPage() {
  const navigate = useNavigate();
  const queryClient = useQueryClient();
  const setUser = useAuthStore((state) => state.setUser);
  const [error, setError] = useState<string | null>(null);
+  const oauthTokenConsumed = useRef(false);
+  const [oauthProcessing, setOauthProcessing] = useState(false);
+
+  // Handle OAuth callback: the API redirects to /login?token=<session_token>
+  useEffect(() => {
+    const token = getUrlParam("token");
+    if (!token || oauthTokenConsumed.current) return;
+    oauthTokenConsumed.current = true;
+    setOauthProcessing(true);
+
+    // Store token for future API calls and fetch user
+    setAuthToken(token);
+
+    apiClient
+      .getMe()
+      .then((data) => {
+        setUser(data.user);
+        queryClient.setQueryData(["auth", "me"], data);
+        navigate("/dashboard", { replace: true });
+      })
+      .catch((err) => {
+        setAuthToken(null);
+        setOauthProcessing(false);
+        setError(err instanceof Error ? err.message : "Google login gagal");
+      });
+  }, [setUser, queryClient, navigate]);
+
+  // Show OAuth error from query param
+  const oauthError = getUrlParam("error");
  const meQuery = useQuery({
    queryKey: ["auth", "me"],
    queryFn: () => apiClient.getMe(),
@@ -26,13 +59,25 @@ export function LoginPage() {
      setError(err instanceof Error ? err.message : "Login gagal"),
  });

+  // Show loading spinner while OAuth token is being processed
+  if (oauthProcessing) {
+    return (
+      <main className="flex min-h-screen items-center justify-center px-6 py-12">
+        <div className="flex flex-col items-center gap-3">
+          <div className="h-10 w-10 border-4 border-green-500 border-t-transparent rounded-full animate-spin" />
+          <p className="text-gray-500 text-sm">Menyelesaikan login dengan Google...</p>
+        </div>
+      </main>
+    );
+  }
+
  return (
    <main className="flex min-h-screen items-center justify-center px-6 py-12">
      <div className="w-full max-w-sm md:max-w-md space-y-4">
        <AuthForm
          mode="login"
          isSubmitting={mutation.isPending}
-          error={error}
+          error={oauthError || error}
          googleOAuthEnabled={Boolean(
            meQuery.data?.features.googleOAuthEnabled,
          )}
@@ -1,4 +1,4 @@
-import { useRef, useState } from "react";
+import { useRef, useState, useCallback } from "react";
 import { useNavigate, Link } from "react-router-dom";
 import { useMutation, useQueryClient, useQuery } from "@tanstack/react-query";
 import {
@@ -16,9 +16,11 @@ import { Button } from "@/components/ui/button";
 import { Card, CardContent } from "@/components/ui/card";
 import { Modal } from "@/components/ui/modal";
 import type { DiagnosisRecord } from "@zeavis/shared";
+import { diseaseCatalogSeed } from "@zeavis/shared"; // Import data seed lokal ditambahkan
 import { apiClient } from "@/lib/api-client";
 import { trackScan, trackDiagnosisResult } from "@/lib/telemetry";
 import { DiagnosisResultView } from "../components/diagnose-result-view";
+import { CameraCapture } from "../components/camera-capture";

 export function ScanPage() {
  const [fileName, setFileName] = useState<string | null>(null);
@@ -32,6 +34,24 @@ export function ScanPage() {
  const navigate = useNavigate();
  const queryClient = useQueryClient();

+  // Camera mode state
+  const [useCamera, setUseCamera] = useState(false);
+  const handleCameraCapture = useCallback(
+    (file: File) => {
+      setFileName(file.name);
+      const url = URL.createObjectURL(file);
+      setPreviewUrl(url);
+
+      const img = new Image();
+      img.onload = () => {
+        setImageDimensions({ width: img.width, height: img.height });
+      };
+      img.src = url;
+      setUseCamera(false);
+    },
+    [],
+  );
+
  const mutation = useMutation({
    mutationFn: (file: File) => apiClient.createDiagnosis(file),
    onSuccess: (diagnosis) => {
@@ -76,7 +96,7 @@ export function ScanPage() {
  const [diagnosisPreview, setDiagnosisPreview] =
    useState<DiagnosisRecord | null>(null);

-  const diagnosesQuery = useQuery({
+  useQuery({
    queryKey: ["diagnoses"],
    queryFn: () => apiClient.getDiagnoses(),
    enabled: previewOpen,
@@ -111,6 +131,41 @@ export function ScanPage() {

              {!previewUrl ? (
                <div className="space-y-3">
+                  {/* Mode toggle */}
+                  <div className="flex rounded-lg bg-gray-100 p-1">
+                    <button
+                      type="button"
+                      onClick={() => setUseCamera(false)}
+                      className={`flex-1 py-2 px-3 rounded-md text-sm font-medium transition-colors ${
+                        !useCamera
+                          ? "bg-white text-green-700 shadow-sm"
+                          : "text-gray-500 hover:text-gray-700"
+                      }`}
+                    >
+                      <Upload size={16} className="inline mr-1.5" />
+                      Unggah
+                    </button>
+                    <button
+                      type="button"
+                      onClick={() => setUseCamera(true)}
+                      className={`flex-1 py-2 px-3 rounded-md text-sm font-medium transition-colors ${
+                        useCamera
+                          ? "bg-white text-green-700 shadow-sm"
+                          : "text-gray-500 hover:text-gray-700"
+                      }`}
+                    >
+                      <Camera size={16} className="inline mr-1.5" />
+                      Kamera
+                    </button>
+                  </div>
+
+                  {useCamera ? (
+                    <CameraCapture
+                      onCapture={handleCameraCapture}
+                      onClose={() => setUseCamera(false)}
+                    />
+                  ) : (
+                    <>
                      <div
                        className="w-full border-2 border-dashed border-green-300 rounded-md p-10 h-60 text-center cursor-pointer"
                        onClick={() => inputRef.current?.click()}
@@ -138,6 +193,8 @@ export function ScanPage() {
                      >
                        <Upload size={18} /> Pilih Berkas
                      </button>
+                    </>
+                  )}
                </div>
              ) : (
                <div className="space-y-4">
@@ -373,6 +430,23 @@ export function ScanPage() {
              </div>
            )}

+            {/* Render DiagnosisResultView dengan Fallback Obat */}
+            {(() => {
+              // Fallback logic for scientific name and medicine recommendations
+              const seedData = diagnosisPreview.disease
+                ? diseaseCatalogSeed.find(
+                    (seed) =>
+                      seed.commonName === diagnosisPreview.disease?.commonName,
+                  )
+                : null;
+
+              // If the API doesn't return medicine recommendations, use the seed data as a fallback
+              const finalMedicines =
+                (diagnosisPreview.disease as any)?.medicineRecommendations ||
+                seedData?.medicineRecommendations ||
+                [];
+
+              return (
                <DiagnosisResultView
                  imageUrl={
                    previewUrl ||
@@ -392,10 +466,10 @@ export function ScanPage() {
                  }
                  symptoms={diagnosisPreview.disease?.symptoms ?? []}
                  preventions={diagnosisPreview.disease?.recommendations ?? []}
-              medicines={
-                (diagnosisPreview.disease as any)?.medicineRecommendations ?? []
-              }
+                  medicines={finalMedicines} // Datanya terhubung ke sini!
                />
+              );
+            })()}

            {/* All Model Predictions */}
            {diagnosisPreview.predictions &&
@@ -9,7 +9,22 @@ export default defineConfig(({ mode }) => {
  const apiProxyTarget = env.VITE_API_PROXY_TARGET || 'http://localhost:3000';

  return {
-    plugins: [react(), tsconfigPaths(), metricsPlugin()],
+    plugins: [
+      react(),
+      tsconfigPaths(),
+      metricsPlugin(),
+      {
+        name: 'cloudflare-rocket-loader-fix',
+        transformIndexHtml(html) {
+          // Prevent Cloudflare Rocket Loader from mangling <script type="module">
+          // which breaks the entire JS bundle (blank page)
+          return html.replace(
+            /<script type="module"/g,
+            '<script data-cfasync="false" type="module"',
+          );
+        },
+      },
+    ],
    server: {
      proxy: {
        '/api': apiProxyTarget,
@@ -1,8 +1,13 @@
 {
  "lockfileVersion": 1,
-  "configVersion": 0,
+  "configVersion": 1,
  "workspaces": {
    "": {
+      "name": "zeavis-edu",
+      "dependencies": {
+        "@tauri-apps/plugin-deep-link": "2.4.9",
+        "@tauri-apps/plugin-opener": "2.5.4",
+      },
      "devDependencies": {
        "@moonrepo/cli": "^2.2.5",
        "typescript": "^6.0.3",
@@ -55,6 +60,7 @@
        "react-router-dom": "^7.15.1",
        "recharts": "3.8.1",
        "tailwind-merge": "^3.6.0",
+        "tailwindcss": "^4.3.1",
        "web-vitals": "5.3.0",
        "zustand": "^5.0.13",
      },
@@ -163,23 +169,23 @@

    "@js-sdsl/ordered-map": ["@js-sdsl/ordered-map@4.4.2", "", {}, "sha512-iUKgm52T8HOE/makSxjqoWhe95ZJA1/G1sYsGev2JDKUSS14KAgg1LHb+Ba+IPow0xflbnSkOsZcO08C7w1gYw=="],

-    "@moonrepo/cli": ["@moonrepo/cli@2.2.5", "", { "dependencies": { "detect-libc": "^2.1.2" }, "optionalDependencies": { "@moonrepo/core-linux-arm64-gnu": "2.2.5", "@moonrepo/core-linux-arm64-musl": "2.2.5", "@moonrepo/core-linux-x64-gnu": "2.2.5", "@moonrepo/core-linux-x64-musl": "2.2.5", "@moonrepo/core-macos-arm64": "2.2.5", "@moonrepo/core-macos-x64": "2.2.5", "@moonrepo/core-windows-x64-msvc": "2.2.5" }, "bin": { "moon": "moon.js", "moonx": "moonx.js" } }, "sha512-MZPXJ7pvfcC77jedFPxwW4Z4XCPzeuBMmbVjRDFXq13bnyAYcaH5kdxkvyxX4WHeEHWyWuustOaJowZo3Q/SxA=="],
+    "@moonrepo/cli": ["@moonrepo/cli@2.3.3", "", { "dependencies": { "detect-libc": "^2.1.2" }, "optionalDependencies": { "@moonrepo/core-linux-arm64-gnu": "2.3.3", "@moonrepo/core-linux-arm64-musl": "2.3.3", "@moonrepo/core-linux-x64-gnu": "2.3.3", "@moonrepo/core-linux-x64-musl": "2.3.3", "@moonrepo/core-macos-arm64": "2.3.3", "@moonrepo/core-macos-x64": "2.3.3", "@moonrepo/core-windows-x64-msvc": "2.3.3" }, "bin": { "moon": "moon.js", "moonx": "moonx.js" } }, "sha512-TmHbQFJH1+vqIsXn7WpPXQtPlgwgyfWUjUBWWQCR2dj3UHg/0IGD4KDlqNg1VPmcyXnuDmlcHtqZ2bkxZx+RhQ=="],

-    "@moonrepo/core-linux-arm64-gnu": ["@moonrepo/core-linux-arm64-gnu@2.2.5", "", { "os": "linux", "cpu": "arm64" }, "sha512-61ajwr3oxCAC0vp879LgKzml3pu+kJ0xMd2Tr1fFMuqp+Xp9k+41VOaTlW7m3vhNQCTVuFFGKxh8KUeAtJk//w=="],
+    "@moonrepo/core-linux-arm64-gnu": ["@moonrepo/core-linux-arm64-gnu@2.3.3", "", { "os": "linux", "cpu": "arm64" }, "sha512-AzovoQPizmwGe5nLd9s0UnN/IUnol81la2vNH+U7vSyh24NzVirT1iOLEcajwtbNvJpl3aXzbhbjrXp35fKVWg=="],

-    "@moonrepo/core-linux-arm64-musl": ["@moonrepo/core-linux-arm64-musl@2.2.5", "", { "os": "linux", "cpu": "arm64" }, "sha512-8gcRf1B+jxbdy4rdQzfXSg37ECsiThCKYHYYXfe4etzcC6CQjmmYeC7OxF+gxWK0mL6UbpuKso8zOcqSbYzjYw=="],
+    "@moonrepo/core-linux-arm64-musl": ["@moonrepo/core-linux-arm64-musl@2.3.3", "", { "os": "linux", "cpu": "arm64" }, "sha512-2jJLXAIUiqdFdw3hxuMefGB3DenQN/CC2mbqL44jC4uZNH6pX1mvjlguubBwUvGHfGbACjh9W9JjavpSMKY9cw=="],

-    "@moonrepo/core-linux-x64-gnu": ["@moonrepo/core-linux-x64-gnu@2.2.5", "", { "os": "linux", "cpu": "x64" }, "sha512-kqZppmKKzdStXbOpWUS+rQlJiowO0ItwWP74oqJVpwUewAjqB2WLwG6IvhSAVHrVhC+9OCGm0g4iAESQBAEh2w=="],
+    "@moonrepo/core-linux-x64-gnu": ["@moonrepo/core-linux-x64-gnu@2.3.3", "", { "os": "linux", "cpu": "x64" }, "sha512-17WZG59QUJhw8wepo1Oe5lmh/q0ax0EQzVk7/EbRe2uBRFsN24oR+R6MyVvuEqmG71x5EFwfPbuH/R48dcRROQ=="],

-    "@moonrepo/core-linux-x64-musl": ["@moonrepo/core-linux-x64-musl@2.2.5", "", { "os": "linux", "cpu": "x64" }, "sha512-UxyYR+SJ7er7Skb60saphEWsPN+oecqDIrNxdAYy+3Li7G9jzBK0j59Jj7j2c0pjlBSKao06DGmfM6WuBlE8eg=="],
+    "@moonrepo/core-linux-x64-musl": ["@moonrepo/core-linux-x64-musl@2.3.3", "", { "os": "linux", "cpu": "x64" }, "sha512-IaE5qN/QOi85SMdhpTtwrDVmIu1MHKznQZxB+jl8dUbQj5iWKyY/DusXXNs9zRR45jBNUlyE4FhrY9rwf2SqtQ=="],

-    "@moonrepo/core-macos-arm64": ["@moonrepo/core-macos-arm64@2.2.5", "", { "os": "darwin", "cpu": "arm64" }, "sha512-DpvFXa/N4rc/vJygE6JBL1pW0DtX00h07xruWQYjdeOuv3RQClRQSwZJNJmGZKhZus4g/LccHgEGvRdu9IMC4w=="],
+    "@moonrepo/core-macos-arm64": ["@moonrepo/core-macos-arm64@2.3.3", "", { "os": "darwin", "cpu": "arm64" }, "sha512-UiO8QuICnxD1XglNDCjkTBwL0YOHvfcj37m5yeIrBjyvkytlWNek4Us7jqr15gbYT+z9pU02Um8k+S1p7y+BkA=="],

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+    "@moonrepo/core-macos-x64": ["@moonrepo/core-macos-x64@2.3.3", "", { "os": "darwin", "cpu": "x64" }, "sha512-FteLklMxJ4cUuZnhrt5lFsYnQMqdzMiAaTFOQDVpUkd6llgrwxIJbUMnPOFHZe4jVJCjpmacEsG7j9/Oxg7HqQ=="],

-    "@moonrepo/core-windows-x64-msvc": ["@moonrepo/core-windows-x64-msvc@2.2.5", "", { "os": "win32", "cpu": "x64" }, "sha512-yYPMsOHL5daEPSTMp2JP+YrwmGjeu+Kp25UmRnllGDmofkCu4Gcv3ct6ljK+u1+W6q2Jc2ooY7eZ14dnKJnlug=="],
+    "@moonrepo/core-windows-x64-msvc": ["@moonrepo/core-windows-x64-msvc@2.3.3", "", { "os": "win32", "cpu": "x64" }, "sha512-qxXvgnqkE4yu6m0vcgDNmRBLnxfAVXq7F7ebaHAOmj7cK0DNnQpZBaxNB3LrIuxhyFdviKVTsUT7F7CpLsVjlw=="],

-    "@napi-rs/wasm-runtime": ["@napi-rs/wasm-runtime@1.1.4", "", { "dependencies": { "@tybys/wasm-util": "^0.10.1" }, "peerDependencies": { "@emnapi/core": "^1.7.1", "@emnapi/runtime": "^1.7.1" } }, "sha512-3NQNNgA1YSlJb/kMH1ildASP9HW7/7kYnRI2szWJaofaS1hWmbGI4H+d3+22aGzXXN9IJ+n+GiFVcGipJP18ow=="],
+    "@napi-rs/wasm-runtime": ["@napi-rs/wasm-runtime@1.1.5", "", { "dependencies": { "@tybys/wasm-util": "^0.10.2" }, "peerDependencies": { "@emnapi/core": "^1.7.1", "@emnapi/runtime": "^1.7.1" } }, "sha512-AWPoBRJ9tsnVhor4sjO7rkni+7p+2IAEFj6cx06UgP10jkQHqay/36uRV/bFkgrh18D9vb4cr8Q0Pthskgzy+Q=="],

    "@opentelemetry/api": ["@opentelemetry/api@1.9.1", "", {}, "sha512-gLyJlPHPZYdAk1JENA9LeHejZe1Ti77/pTeFm/nMXmQH/HFZlcS/O2XJB+L8fkbrNSqhdtlvjBVjxwUYanNH5Q=="],

@@ -241,7 +247,7 @@

    "@opentelemetry/semantic-conventions": ["@opentelemetry/semantic-conventions@1.41.1", "", {}, "sha512-/UhIkaZgPutTFmQ7RnIJGgDXZmtEJ7Dvi86xNTFWcnRxVRNk/aotsqDJYeEvDP+FSMB2SdW+pQzNMcWP0rwuNA=="],

-    "@oxc-project/types": ["@oxc-project/types@0.132.0", "", {}, "sha512-FESMOxil5Se014ui/Eq8fT5uHJo6nIRwH0PfJrZJXs6Gek3ZVFOrpUv3YIZT20m+extU98Hg1Ym72U58rlsxUQ=="],
+    "@oxc-project/types": ["@oxc-project/types@0.133.0", "", {}, "sha512-KzkdCd6Uxqnf6l3HOw1xfatAlUURA0g14cvBYFyJ5SaNOQbOUvBr9PKArcPcrNIeRsBdgcUzOGrhKveVpvOIGA=="],

    "@protobufjs/aspromise": ["@protobufjs/aspromise@1.1.2", "", {}, "sha512-j+gKExEuLmKwvz3OgROXtrJ2UG2x8Ch2YZUxahh+s1F2HZ+wAceUNLkvy6zKCPVRkU++ZWQrdxsUeQXmcg4uoQ=="],

@@ -255,49 +261,47 @@

    "@protobufjs/float": ["@protobufjs/float@1.0.2", "", {}, "sha512-Ddb+kVXlXst9d+R9PfTIxh1EdNkgoRe5tOX6t01f1lYWOvJnSPDBlG241QLzcyPdoNTsblLUdujGSE4RzrTZGQ=="],

-    "@protobufjs/inquire": ["@protobufjs/inquire@1.1.2", "", {}, "sha512-pa0vFRuws4wkvaXKK1uXZMAwAX4/t8ANaJo45iw/oQHNQ9q5xUzwgFmVJGXiga2BeN+zpX7Vf9vmsiIa2J+MUw=="],
-
    "@protobufjs/path": ["@protobufjs/path@1.1.2", "", {}, "sha512-6JOcJ5Tm08dOHAbdR3GrvP+yUUfkjG5ePsHYczMFLq3ZmMkAD98cDgcT2iA1lJ9NVwFd4tH/iSSoe44YWkltEA=="],

    "@protobufjs/pool": ["@protobufjs/pool@1.1.0", "", {}, "sha512-0kELaGSIDBKvcgS4zkjz1PeddatrjYcmMWOlAuAPwAeccUrPHdUqo/J6LiymHHEiJT5NrF1UVwxY14f+fy4WQw=="],

    "@protobufjs/utf8": ["@protobufjs/utf8@1.1.1", "", {}, "sha512-oOAWABowe8EAbMyWKM0tYDKi8Yaox52D+HWZhAIJqQXbqe0xI/GV7FhLWqlEKreMkfDjshR5FKgi3mnle0h6Eg=="],

-    "@radix-ui/react-compose-refs": ["@radix-ui/react-compose-refs@1.1.2", "", { "peerDependencies": { "@types/react": "*", "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc" }, "optionalPeers": ["@types/react"] }, "sha512-z4eqJvfiNnFMHIIvXP3CY57y2WJs5g2v3X0zm9mEJkrkNv4rDxu+sg9Jh8EkXyeqBkB7SOcboo9dMVqhyrACIg=="],
+    "@radix-ui/react-compose-refs": ["@radix-ui/react-compose-refs@1.1.3", "", { "peerDependencies": { "@types/react": "*", "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc" }, "optionalPeers": ["@types/react"] }, "sha512-rYOP8OMnuuPMQF1uhPVlGNcCDlkokKqGFE3JcxFViIkAXP7EvFWUliJAstrapypaBLJNHbZL6jGhbVDGTwmVhA=="],

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  }
 }
@@ -38,8 +38,6 @@ services:
      API_PORT: "3000"
      WEB_APP_URL: https://zeavisedu.asepharyana.my.id
      ML_SERVICE_URL: ${ML_SERVICE_URL:-http://zeavis-ml:8000}
-    ports:
-      - "3000:3000"
    labels:
      traefik.enable: "true"
      traefik.http.routers.zeavis-api.rule: Host(`api-zeavisedu.asepharyana.my.id`)
@@ -53,8 +51,6 @@ services:
    image: prom/node-exporter:v1.8.2
    container_name: zeavis-node-exporter
    restart: unless-stopped
-    ports:
-      - "9100:9100"
    command:
      - "--path.rootfs=/host"
      - "--web.listen-address=:9100"
@@ -77,8 +73,6 @@ services:
    environment:
      MODEL_PATH: /app/model/model.onnx
      MODEL_INPUT_SIZE: "224"
-    ports:
-      - "8000:8000"
    labels:
      traefik.enable: "true"
      traefik.http.routers.zeavis-ml.rule: Host(`ml-zeavisedu.asepharyana.my.id`)
@@ -1,6 +1,25 @@
-# Infra — ZeaVis Edu Multi-VPS Deployment
+# Infrastruktur — ZeaVis Edu

-## Arsitektur
+> Arsitektur multi-VPS untuk deployment produksi ZeaVis Edu dengan Tailscale mesh VPN dan observabilitas penuh.
+
+← [Kembali ke README utama](../README.md)
+
+---
+
+## Daftar Isi
+
+1. [Arsitektur](#1-arsitektur)
+2. [Prasyarat GitHub Secrets](#2-prasyarat-github-secrets)
+3. [Setup VPS](#3-setup-vps)
+4. [Port yang Dibuka](#4-port-yang-dibuka)
+5. [Metrics Flow](#5-metrics-flow)
+6. [Perintah Penting](#6-perintah-penting)
+
+---
+
+## 1. Arsitektur
+
+ZeaVis Edu berjalan di **dua VPS terpisah** yang terhubung melalui **Tailscale** mesh VPN:

 ```
 ┌─────────────────────────────────────────────┐     ┌──────────────────────────────────────────────┐
@@ -44,32 +63,41 @@
 └─────────────────────────────────────────────┘     └──────────────────────────────────────────────┘
 ```

-## Prerequisites
+| VPS | Hostname | OS | Peran |
+|---|---|---|---|
+| **App VPS** | `imrnes` | Arch Linux | Web (:80), API (:3000), ML Service (:8000) |
+| **Telemetry VPS** | `orange` | Ubuntu | Prometheus, ClickHouse, Telemetry UI |

-### GitHub Secrets (untuk CI/CD)
+---

-**App VPS deploy (`.github/workflows/deploy.yml`):**
-| Secret | Value |
-|--------|-------|
+## 2. Prasyarat GitHub Secrets
+
+### App VPS — `.github/workflows/deploy.yml`
+
+| Secret | Keterangan |
+|---|---|
 | `VPS_HOST` | `100.108.1.124` (imrnes) |
 | `VPS_USER` | `mytheclipse` |
-| `VPS_SSH_KEY` | Private SSH key for imrnes |
+| `VPS_SSH_KEY` | Private SSH key untuk imrnes |
 | `VPS_PORT` | `22` |
 | `DATABASE_URL` | PostgreSQL connection string |
 | `SESSION_SECRET` | Random session secret |

-**Telemetry VPS deploy (`.github/workflows/telemetry-ci-cd.yml`):**
-| Secret | Value |
-|--------|-------|
+### Telemetry VPS — `.github/workflows/telemetry-ci-cd.yml`
+
+| Secret | Keterangan |
+|---|---|
 | `TELEMETRY_VPS_HOST` | `100.96.248.86` (orange) |
-| `TELEMETRY_VPS_USER` | SSH username for orange |
-| `TELEMETRY_VPS_SSH_KEY` | Private SSH key for orange |
+| `TELEMETRY_VPS_USER` | SSH username |
+| `TELEMETRY_VPS_SSH_KEY` | Private SSH key |
 | `TELEMETRY_VPS_PORT` | `22` |
-| `GHCR_PAT` | GitHub PAT with `write:packages` + `read:packages` |
+| `GHCR_PAT` | GitHub PAT dengan `write:packages` + `read:packages` |

-### VPS Setup
+---

-#### 1. App VPS (imrnes — 100.108.1.124)
+## 3. Setup VPS
+
+### App VPS (imrnes — 100.108.1.124)

 ```bash
 # Create Docker network
@@ -79,33 +107,35 @@ docker network create telemetry-net
 # ZeaVis Edu apps deploy automatically via GitHub Actions
 ```

-#### 2. Telemetry VPS (orange — 100.96.248.86)
+### Telemetry VPS (orange — 100.96.248.86)

-Deploy via GitHub Actions workflow `.github/workflows/telemetry-ci-cd.yml`.
+Deploy via GitHub Actions atau manual:

-Atau manual:
 ```bash
 ssh mytheclipse@100.96.248.86
 mkdir -p /opt/telemetry
-# ... sync files from telemetry/ directory ...
 cd /opt/telemetry
 docker compose up -d
 bash clickhouse/init.sh
 ```

-## Port yang dibuka
+---
+
+## 4. Port yang Dibuka

 ### App VPS (imrnes)
+
 | Port | Service | Akses |
-|------|---------|-------|
+|---|---|---|
 | 80/443 | Web (via Traefik/Coolify) | Public |
 | 3000 | API metrics | Tailscale-only |
 | 8000 | ML service metrics | Tailscale-only |
 | 9100 | Node Exporter | Tailscale-only |

 ### Telemetry VPS (orange)
+
 | Port | Service | Akses |
-|------|---------|-------|
+|---|---|---|
 | 80/443 | Telemetry UI (via Coolify Traefik) | Public |
 | 8181 | Telemetry UI (direct) | Tailscale-only |
 | 9090 | Prometheus | Tailscale-only |
@@ -114,27 +144,44 @@ bash clickhouse/init.sh
 | 8123 | ClickHouse HTTP | Tailscale-only |
 | 9000 | ClickHouse Native | Tailscale-only |

-## Metrics Flow
+---

-1. **App services** expose `/metrics` pada port masing-masing
+## 5. Metrics Flow
+
+1. **App services** mengekspos `GET /metrics` di port masing-masing
 2. **Prometheus** di orange VPS scrape via Tailscale IP (`100.108.1.124:PORT`)
-3. **Prometheus** forward ke **Metric Ingester** via `remote_write`
-4. **Metric Ingester** enrich → filter → forward ke **Vector**
-5. **Vector** buffer → write ke **ClickHouse**
+3. Prometheus forward ke **Metric Ingester** via `remote_write`
+4. Metric Ingester enrich → filter → forward ke **Vector**
+5. Vector buffer → write ke **ClickHouse**
 6. **Telemetry UI** query via **Query Proxy** → **ClickHouse**

-## Useful Commands
+```
+App Services (/metrics)
+    │
+    ▼ (scrape via Tailscale)
+Prometheus ──(remote_write)──► Metric Ingester ──► Vector ──► ClickHouse
+                                                                │
+                                                    Query Proxy ◄── Telemetry UI
+```
+
+---
+
+## 6. Perintah Penting

 ```bash
-# Telemetry stack status
+# Status telemetry stack
 make telemetry-status

-# View telemetry logs
+# Lihat log service tertentu
 make telemetry-logs s=prometheus

-# Send test metric
+# Kirim test metric
 make telemetry-test-metric

-# Restart a service
+# Restart service
 make telemetry-restart s=vector
 ```
+
+---
+
+← [Kembali ke README utama](../README.md) &bull; [ML Service →](../apps/ml-service/README.md) &bull; [Pipeline ML →](../Machine_Learning/README.md)
@@ -13,5 +13,9 @@
  "workspaces": [
    "apps/*",
    "packages/*"
-  ]
+  ],
+  "dependencies": {
+    "@tauri-apps/plugin-deep-link": "2.4.9",
+    "@tauri-apps/plugin-opener": "2.5.4"
+  }
 }
@@ -66,6 +66,7 @@ export type RegisterRequest = AuthRequest & {
 export type AuthResponse = {
  user: AuthUser;
  features: AuthFeatures;
+  token?: string;
 };

 export type DiagnosisPrediction = {
Author	SHA1	Message	Date
MythEclipseandClaude	e1732f5111	docs: enrich root README with full project plan details - Add project plan context: team members, executive summary, schedule, risk management - Add project scope, deliverables, and classification table with symptoms - Add bibliography/references section from project plan - Centered header with logo, emoji-section navigation - Cleaner structure: Tentang → Tim → Ringkasan → Cakupan → Jadwal → Risiko → Arsitektur → Tech Stack → Memulai → Dokumentasi → Pustaka Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-16 00:25:47 +07:00
MythEclipseandClaude	fc832b404e	fix(auth): use VITE_API_BASE_URL for Google OAuth redirect instead of window.location.origin On Tauri Android, window.location.origin = http://tauri.localhost which is the embedded dev server URL, not the API server. Use VITE_API_BASE_URL env var which points to the production API. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-16 00:23:46 +07:00
MythEclipseandClaude	6ba3deb149	docs: restructure all README.md into cohesive hierarchy - Root README redesigned as landing page with 7 sub-chapters - Each child README gets navigation header + footer linking back to root - Cross-links between Machine_Learning, ml-service, and infra READMEs - Reduced duplication: root summarizes, children provide full detail - Net -207 lines, cleaner structure Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-16 00:23:18 +07:00
MythEclipseandClaude	ac59548337	feat(android): Google OAuth via system browser + deep link for Android Background: Google blocks OAuth in embedded WebView (403 disallowed_useragent). Solution: open Google login in the Android system browser, then deep-link back to the Tauri app via custom scheme after callback. Changes: - Tauri: add tauri-plugin-opener + tauri-plugin-deep-link to Cargo.toml - Tauri: register plugins in lib.rs, add capabilities - Web: auth-form.tsx Google button uses openUrl() via @tauri-apps/plugin-opener on Tauri (opens in system browser), falls back to window.location.href - Web: add lib/tauri.ts for isTauri() detection + lazy opens - API: /auth/google accepts ?platform=tauri → encodes into OAuth state param - API: /auth/google/callback decodes state → if tauri, renders HTML page that deep-links back via zeavisedu:// scheme; if web, 302 redirect - Android: patch script adds deep link intent filter for zeavisedu:// scheme Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 23:49:47 +07:00
MythEclipseandClaude	d292bc4b3c	feat(auth): add Google logo SVG to 'Masuk dengan Google' button Inline SVG with official Google brand colors (blue, green, yellow, red) placed before the label text with gap-2.5 spacing. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 23:17:46 +07:00
MythEclipseandClaude	787acf077f	fix(vite): add data-cfasync="false" to script tags to prevent Cloudflare Rocket Loader breaking JS Cloudflare Rocket Loader rewrites <script type="module"> to <script type="randomhash-module"> which browsers can't parse, causing complete blank page. data-cfasync="false" disables this. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 23:00:30 +07:00
MythEclipseandClaude	250355562f	fix(login): replace useSearchParams with native URLSearchParams + loading spinner - useSearchParams can lose params during re-renders, causing blank page - Use native window.location.search + URLSearchParams instead (always accessible) - Add oauthProcessing spinner state so user sees 'Menyelesaikan login...' instead of blank page while /auth/me is being called Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 22:38:11 +07:00
MythEclipseandClaude	d47c73308e	fix(auth): replace deprecated set.redirect with manual 302 Location header Elysia's set.redirect returns 200 OK instead of 302 redirect on the current version. Use set.status = 302 + set.headers['Location'] instead for both /auth/google (Google OAuth redirect) and /auth/google/callback (all redirect paths: errors, success token delivery). Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 22:06:59 +07:00
MythEclipseandClaude	4b1d70d1c4	ci(deploy): inject Google OAuth env vars into VPS .env Add GOOGLE_CLIENT_ID, GOOGLE_CLIENT_SECRET, and GOOGLE_REDIRECT_URI to the deploy workflow so the API can use Google OAuth on production. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 21:57:12 +07:00
MythEclipseandClaude	c9ae90a042	feat(auth): implement Google OAuth callback with user auto-creation API (apps/api/src/routes/auth.ts): - Exchange authorization code for tokens via Google's token endpoint - Decode id_token payload (JWT) to extract sub, email, name - Find user by googleId → fall back to email match (link accounts) - Auto-create user if neither found (role: 'user', no password) - Create session + set cookie, redirect to /login?token=<token> Web (apps/web/src/pages/login-page.tsx): - Consume ?token= query param from OAuth redirect - Store token in localStorage for future API calls - Fetch /auth/me to hydrate Zustand store, then navigate to dashboard - Show OAuth errors from ?error= query param Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 21:35:40 +07:00
Selly SupriyatinandGitHub	caca13e32c	Merge pull request #39 from ATLAS-PJK-GM007/selly/frontend Selly/frontend	2026-06-15 21:07:56 +07:00
MythEclipseandClaude	a55b1521ea	ci(android): run patch-android-manifest.sh after tauri android init Ensures CAMERA permission is always injected into the generated AndroidManifest.xml during CI builds. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 21:05:34 +07:00
seriouselly	2eabf12b36	Merge branch 'main' of https://github.com/ATLAS-PJK-GM007/ZeaVis-Edu into selly/frontend	2026-06-15 20:55:21 +07:00
seriouselly	b18b98e1a7	fix(scan): resolve empty medicine data and clean up linter warning - Add local fallback using `diseaseCatalogSeed` to populate medicine recommendations in the diagnosis preview modal when API data is missing. - Remove unused `diagnosesQuery` assignment to resolve SonarLint warning while preserving the background prefetching logic.	2026-06-15 20:54:44 +07:00
MythEclipseandClaude	a36b74a1cf	feat(scan): add camera capture for Android with toggle between upload and live camera - Add CameraCapture component with live viewfinder via getUserMedia - Support rear/environment camera (default) with switch to front/user - Capture to JPEG 92% quality via canvas, reuse existing upload flow - Toggle between 'Unggah' (file upload) and 'Kamera' (live capture) modes - Error handling for denied/not found/not readable in Bahasa Indonesia - Add patch script for AndroidManifest CAMERA permission (gen/ is gitignored) Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 20:54:11 +07:00
seriouselly	9cfbef4598	Merge branch 'main' of https://github.com/ATLAS-PJK-GM007/ZeaVis-Edu into selly/frontend	2026-06-15 20:39:01 +07:00
seriouselly	8f1308c8af	fix(diagnosis): correct risk level mapping and dynamic confidence UI - Fix `getRiskLevelKey` to properly recognize English risk level values ("low", "high"), preventing "Healthy Leaf" from incorrectly defaulting to medium risk. - Update confidence bar text and colors to dynamically show warning alerts when AI confidence falls below the 75% threshold.	2026-06-15 20:38:26 +07:00
MythEclipseandClaude	c881e6a2b2	fix(auth): pass request.headers to getCurrentUser in all protected routes dashboard, diagnoses, expert routes now support Authorization header fallback for Android WebView Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 20:11:11 +07:00
MythEclipseandClaude	7693a02c98	fix(auth): add bearer token auth as fallback for Android WebView third-party cookie blocking Android WebView blocks third-party cookies by default. This patch: - Returns session token in login/register response body - Stores token in localStorage, sends via Authorization: Bearer header - Backend getCurrentUser supports Authorization header fallback Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 19:43:02 +07:00
MythEclipseandClaude	528a1622d0	fix(auth): prevent AuthInitializer from overwriting Zustand with null user Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 19:04:29 +07:00
MythEclipseandClaude	51a4cb9ed2	fix(auth): detect HTTPS via X-Forwarded-Proto for SameSite=None cookies, fix AuthGuard null overwrite - Cookie SameSite now dynamic: None;Secure when behind HTTPS proxy, Lax otherwise - AuthGuard useEffect no longer overwrites Zustand store with null from background refetch - AuthInitializer: add staleTime 30s Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 18:17:26 +07:00
MythEclipse	22307d44de	fix(api): add http://tauri.localhost to CORS allowed origins	2026-06-15 17:09:40 +07:00
MythEclipseandClaude	41e0501e6b	fix(tauri): add absolute API base URL default and CORS origins for Android WebView - Set VITE_API_BASE_URL default to production API URL in api-client.ts so fetch() uses absolute URLs instead of relative paths that fail on Tauri - Add tauri://localhost and https://tauri.localhost to API CORS allowed origins - Also fix .env WEB_APP_URL from stale .tech to .my.id Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 14:32:54 +07:00
MythEclipseandClaude	f675b86dc8	fix(docker): remove port exposure from docker-compose.yml All services route through Traefik via internal network labels. No ports need to be exposed on the host. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 14:05:44 +07:00
MythEclipseandClaude	8ed1b57f1d	fix(ci): add container wait loop before health check in deploy Containers need time to start after docker compose up -d. Replaced instant grep check with up-to-60s retry loop. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 14:04:19 +07:00
MythEclipseandClaude	bf1725a4b8	fix(docker): remove non-existent shared/node_modules COPY from API Dockerfile packages/shared has only devDependencies (typescript). After bun install --production, packages/shared/node_modules does not exist. Root node_modules contains all hoisted deps. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 13:58:23 +07:00
MythEclipseandClaude	8954535e08	fix(ci): add tauri package.json to Dockerfiles and fix Android NDK/build issues Build and Deploy: workspace has 4 members (api/web/shared/tauri) but Dockerfiles only copied 3 package.json files. Missing tauri workspace member caused bun install --production to fail with frozen lockfile error. Build Android APK: - Remove explicit NDK 28 install (runner has NDK 29 pre-installed, dual NDK presence broke ANDROID_NDK_HOME resolution) - Auto-pin NDK version from runner's SDK - rm -rf gen/android before tauri android init (stale cache recovery) - Remove gen/android/.gradle from Gradle cache (causes stale state) - Use --apk flag for faster APK-only build Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 13:54:55 +07:00
MythEclipseandClaude	b93be6c6cb	fix(docker): copy bun.lock and workspace node_modules to API runner stage Bun workspace symlinks (apps/api/node_modules/*) pointed to root .bun cache but were never copied from deps→runner. Added bun.lock, apps/api/node_modules, and packages/shared/node_modules to the runner COPY chain so and resolve at runtime. Also added bun.lock to web Dockerfile for deterministic installs. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 03:30:18 +07:00
MythEclipseandClaude	2d39468279	perf(ci): add Bun and Gradle caching to Android workflow Cache Bun dependencies (install cache + node_modules) and Gradle caches (wrapper, dependencies, build artifacts) to dramatically speed up CI builds. Gradle key uses Cargo.lock since gradle files don't exist at checkout time. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 01:43:25 +07:00
MythEclipseandClaude	78db3a03ac	chore: change base URL to zeavisedu.asepharyana.my.id Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 01:35:58 +07:00
Selly SupriyatinandGitHub	bed0e018db	Merge pull request #38 from ATLAS-PJK-GM007/selly/frontend Selly/frontend	2026-06-15 01:29:00 +07:00
seriouselly	3b37a92d1e	Merge branch 'main' of https://github.com/ATLAS-PJK-GM007/ZeaVis-Edu into selly/frontend	2026-06-15 01:27:40 +07:00
seriouselly	6c1006d4a0	Merge branch 'main' of https://github.com/ATLAS-PJK-GM007/ZeaVis-Edu into selly/frontend	2026-06-15 01:27:13 +07:00
MythEclipseandClaude	03c1e4edb8	fix(ci): add tailwindcss as direct dependency PostCSS plugin needs tailwindcss package available in node_modules at build time. Adding it as a direct dependency ensures consistent resolution. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 01:23:51 +07:00
seriouselly	56b683392c	feat(diagnosis): add back to history button and update UI icons - Add "Kembali ke Riwayat" button to `diagnosis-detail-page.tsx` for better navigation flow. - Update camera icon in `diagnose-result-view.tsx` to align with the new UI design. - Resolve merge conflicts with main to sync latest workflow changes.	2026-06-15 01:20:41 +07:00
MythEclipseandClaude	05055ed9cf	fix(ci): remove bun.lock from Docker COPY to avoid version mismatch Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 01:17:25 +07:00
seriouselly	4b5530ef73	Merge branch 'main' of https://github.com/ATLAS-PJK-GM007/ZeaVis-Edu into selly/frontend	2026-06-15 01:09:04 +07:00
MythEclipseandClaude	02ae022174	fix(ci): regenerate bun.lock and disable frozen-lockfile in Dockerfiles bun auto-enables --frozen-lockfile in CI by default. Use env var BUN_INSTALL_FROZEN_LOCKFILE=0 to override this behavior. Also regenerate lockfile fresh to ensure it is compatible with bun 1.3.14. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 01:06:17 +07:00
seriouselly	61a4043967	Revert "fix(ci): add --no-frozen-lockfile to bun install in Dockerfiles" This reverts commit `9ee3af8a1f`.	2026-06-15 01:05:04 +07:00
MythEclipseandClaude	9ee3af8a1f	fix(ci): add --no-frozen-lockfile to bun install in Dockerfiles bun defaults to --frozen-lockfile in CI environments, causing failures when the lockfile format differs from the version used at build time. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 01:02:35 +07:00
MythEclipseandClaude	3d3ca72230	fix(ci): remove --frozen-lockfile to prevent bun version mismatch failures CI uses bun 1.3.14 (stable) but local dev uses canary. Lockfile format can differ between versions causing spurious failures. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 00:57:31 +07:00
MythEclipseandClaude	3d79b227d7	fix(ci): remove auto-commit to prevent infinite loop Tag created by softprops/action-gh-release is the single source of truth. Version bump in tauri.conf.json + Cargo.toml is local to the build only. Co-Authored-By: Claude <noreply@anthropic.com>	2026-06-15 00:26:12 +07:00