Galbay Predictor

Financial Behavior Coach berbasis Big Data untuk Gen Z Indonesia

Repositori ini berisi pipeline scraping 7 sumber data, paket dataset terkurasi, ringkasan visual, dan aplikasi web Flask interaktif untuk final project mata kuliah Analisis Keputusan Bisnis.

Ringkasan

Galbay Predictor adalah proyek analisis perilaku finansial Gen Z berbasis 602.675 data publik multi-source. Backbone datanya tetap 599.000 review Google Play Store dari 53 aplikasi fintech Indonesia, sedangkan OJK/media, forum, blog, YouTube, Threads, dan Google Trends dipakai sebagai konteks pendukung, bukan bobot yang setara.

Repositori ini disusun untuk dua kebutuhan:

anggota tim yang perlu mengambil dataset besar dengan alur yang jelas;
reviewer yang ingin cepat memahami apa yang benar-benar kuat dari proyek ini: data besar, insight perilaku, batas model, lalu demo tools turunannya.

Cara Membaca Project Ini

Data-first: nilai utama proyek ada pada pemetaan sinyal distress finansial dari dataset publik besar.
Play Store-dominant: label “multi-source” benar, tetapi volumenya tetap sangat didominasi review aplikasi di Google Play Store.
Prototype-aware: beberapa tool di web bersifat rule-based decision support, bukan model ML generatif penuh.
Demo-focused: chatbot, Galbay Score, dan simulator DC diposisikan sebagai alat bantu orientasi untuk demo, bukan diagnosis finansial formal.

Highlights

602.675 item dari 7 sumber, dengan 599.000 review Google Play Store sebagai sumber volume utama
58.120 review relevan (9,7% dari total) yang mengandung sinyal galbay/distress
11 kategori distress untuk membaca pola gagal bayar, tekanan DC, bunga/biaya, dan perilaku impulsif
Model Multinomial Naive Bayes untuk klasifikasi sentimen/relevansi pada review terpilih
Dashboard insight yang memisahkan data-driven insight, rule-based support, dan demo interaction
Tool inti:
- Galbay Score — pembacaan awal risiko berbasis pola perilaku yang ditemukan di data publik
- Debt Planner — simulasi snowball vs avalanche untuk strategi bayar
- Hadapi Tekanan DC — simulator respons penagihan bercabang multi-turn
Tool pendukung:
- Pinjol Checker
- Emergency Runway Calculator
- 30-Day Action Plan
- Recovery Roadmap 30/60/90
Chat assistant rule-based dengan intent routing, fallback klarifikasi, dan navigasi ke tool yang relevan
Distribusi data memakai DVC + Google Drive agar anggota tim bisa dvc pull setelah setup OAuth sekali

🆕 What's New (Round 8-13)

Round	Highlight	Commits
Round 8	Multi-source 7 platform (599K Play + 3.6K pendukung)	7 commits
Round 8	BMC v2.0 dengan 9 blok data-driven	1 commit
Round 9	Galbay Score Quiz (public, 6 pertanyaan)	1 commit
Round 10	Topnav reorder (Produk + Galbay Score)	1 commit
Round 10	Chatbot markdown renderer (XSS-safe)	1 commit
Round 10	Theme polish (microinteractions, scroll reveal)	1 commit
Round 10	Data expansion (blogs 506 → 2.142)	1 commit
Round 10	3 NEW TOOLS: DC Simulator + Runway + 30-Day Plan	1 commit
Round 11	Privacy + Terms pages (UU PDP)	1 commit
Round 11	Multi-source analysis dashboard (charts)	1 commit
Round 12	Bug fixes (chart labels, footer links, spacing)	1 commit
Round 13	DC Simulator v2 (multi-turn, 3-5 exchanges)	1 commit
Round 13	Chatbot FAQ 38 → 60+ intents	1 commit
Round 13	Free/Premium rate limits (10 chat/day, 1 DC/day)	1 commit
Round 13	Advanced modeling metrics (per-category + learning curve)	1 commit
Round 13	SWOT analysis di kesimpulan page	1 commit

Demo

# 1. Install
pip install -r requirements.txt

# 2. Set up environment
copy .env.example .env
# Fill in GDRIVE_CLIENT_ID + GDRIVE_CLIENT_SECRET

# 3. Pull dataset (~180MB)
python scripts/setup_dvc_gdrive.py
dvc pull

# 4. Run
python run.py
# → http://localhost:5000

Live demo publik:

Galbay Predictor on Hugging Face Spaces

Demo login (no setup needed):

demo@galbay.id / demo123 — Free tier (10 chat/day, 1 DC/day)
premium@galbay.id / demo123 — Premium tier (unlimited all features)

Deploy Gratis ke Hugging Face Spaces

Repo ini sekarang sudah disiapkan untuk Hugging Face Docker Space dalam mode public demo stateless.

Runtime deploy memakai requirements-runtime.txt, bukan dependency scraping penuh.
Container dijalankan lewat gunicorn pada port 7860.
Dataset besar tidak ditarik via DVC saat runtime.
Register, waitlist, Google OAuth, dan penyimpanan lokal dimatikan pada deploy gratis.

Langkah ringkas:

Buat Space baru dengan SDK Docker.
Copy isi HF_SPACE_README.md menjadi README.md di repo Space.
Tambahkan SECRET_KEY di Settings > Variables and secrets.
Push source ke repo Space.
Login memakai akun demo:
- demo@galbay.id / demo123
- premium@galbay.id / demo123

URL deploy aktif saat ini:

https://adan11-galbay-predictor.hf.space

Panduan lengkap ada di DEPLOY_HF.md.

Tech Stack

Layer	Tools
Backend	Flask 3.0, Python 3.12, Blueprint multi-page
Frontend	Vanilla JS, Chart.js 4.4, custom percentLabel plugin, IntersectionObserver
Auth	Hybrid Google OAuth (authlib) + demo login + JSON storage + usage tracking
Data	Pandas, NumPy, scikit-learn, DVC + Google Drive
Scraping	BeautifulSoup, Playwright (Kaskus SPA), requests, yt-dlp (YouTube)
NLP	Rule-based assistant (intent routing, synonym, typo tolerance, clarification fallback, markdown render)
Testing	pytest, 342 tests passing

Gambaran Dataset

Komponen	Nilai
Total multi-source	602.675 item dari 7 platform
Sumber utama	Google Play Store (599K review, backbone insight)
Sumber sekunder	OJK + media, Forum, Blog, YouTube, Threads, Google Trends
Aplikasi fintech	53 app Indonesia (paylater, pinjol, e-wallet, bank digital, dll)
Periode Play Store	2015-10-02 s/d 2026-06-23
Ulasan relevan galbay	58.120 (9,7% dari total)
Sinyal distress	13.827 ulasan (23,8% dari relevan)
Severity tinggi	865 ulasan (target intervensi utama)
Distribusi	DVC + Google Drive (~200MB)

Multi-Source Breakdown

Catatan penting: label multi-source dipakai karena memang ada 7 sumber, tetapi pembacaan utama project tetap harus dibaca sebagai Play Store-dominant dataset with supporting context.

Source	Items	%	Icon
Google Play Store	599.000	99,1%	📱
Blog Indonesia	2.142	0,4%	📝
YouTube (yt-dlp)	1.614 (283 vids + 1.331 komentar)	0,3%	▶️
Google Trends	786	0,1%	📈
Forum (Kaskus)	244	<0,1%	💬
Threads (Meta)	231	<0,1%	🧵
OJK + Media	160	<0,1%	📰

Rincian Sumber Data

Sumber utama (Google Play Store)

Dataset utama berasal dari review Google Play Store untuk 53 aplikasi fintech Indonesia (10 kategori).

Kategori aplikasi yang dicakup

Kategori	Aplikasi
`paylater`	Kredivo, Indodana, Akulaku, Atome, Kredito, Shopee Paylater, Tokopedia Paylater
`ecommerce`	Shopee, Tokopedia, Lazada, Bukalapak, Tiket.com, Traveloka
`ewallet`	DANA, Flip, GoPay, Gojek, LinkAja, OVO, Sakuku, ShopeePay, Blu by BCA
`pinjol`	AdaKami, Adapundi, BantuSaku, Cairin, Easycash, Finmas, Home Credit, Indosaku, JULO, KTA Kilat, KrediOne, Kredit Pintar, Maupinjam, PinjamUang, Pinjam Yuk, RupiahCepat, Singa Fintech, Tunaiku, UATAS, DanaCepat
`bank_digital`	Bank Jago, SeaBank, blu by BCA Digital, Jenius, Allo Bank, LINE Bank
`mobile_banking`	BRImo, Livin' by Mandiri, BCA Mobile, BNI Mobile, CIMB Niaga, Danamon
`p2p_lending`	KoinWorks, Amartha, Investree, Modalku, TaniFund, Akseleran
`investasi`	Bibit, Ajaib, Stockbit, Pluang, Bareksa, IPOT
`aggregator`	Cermati, Lifepal, Roojai
`kartu_kredit`	Honest
`koperasi`	Artha Niaga

Sumber pendukung (Non-Play)

OJK + Media — 160 artikel (siaran pers, info terkini, liputan Kompas/Detik/CNBC)
Forum (Kaskus + Reddit) — 244 threads diskusi utang, galbay, negosiasi
Blog Indonesia — 2.142 posts (Medium, Hipwee, Kumparan, Brilio, CNBC, Kompas, Detik, dll)
YouTube (yt-dlp) — 283 video + 1.331 komentar (review app, simulasi DC, recovery)
Threads (Meta) — 231 posts Gen Z (FOMO, self reward, bahasa natural)
Google Trends — 786 time-series 5 tahun (20 keyword grup)

Lokasi dan File Data

Lokasi	Isi
`data/raw/`	data mentah hasil scraping (60+ file JSON, multi-source)
`data/processed/`	data olahan utama (9 CSV: per-source + multi_source_combined)
`data/sample/`	sample kecil yang ikut tersimpan di repo
`data/site/`	output dashboard (data.js + PNG charts)
`data/pinjol_database.json`	database 50+ app pinjol legal + ilegal

File utama untuk analisis

File	Fungsi
`data/processed/play_reviews_clean.csv`	ulasan Google Play (599K baris, kolom: query, app_name, category, score, content, date, is_relevant)
`data/processed/ojk_media_articles.csv`	OJK + media (160 artikel)
`data/processed/forum_threads.csv`	Kaskus + Reddit (244 threads)
`data/processed/blogs_id_posts.csv`	Blog Indonesia (2.142 posts)
`data/processed/youtube_videos.csv`	YouTube videos (283)
`data/processed/youtube_comments.csv`	YouTube comments (1.331)
`data/processed/threads_posts.csv`	Threads (231)
`data/processed/google_trends.csv`	Google Trends (786 time-series)
`data/processed/multi_source_combined.csv`	Combined (104K sampled dari 7 sources)
`data/site/data.js`	semua stats untuk dashboard (window.GALBAY_DATA)
`data/site/assets/*.png`	5 chart PNG (confusion_matrix, distress_trend, top_neg_words, multi_source_breakdown, severity_distribution)

Arsitektur Aplikasi Web

app/
├── __init__.py        # Flask app factory
├── main.py            # 5 dashboard routes + 9 API endpoints + 3 tool endpoints
├── api.py             # Skor Risiko, Simulasi, Pinjol Checker, Debt Planner,
│                      # Recovery Roadmap, Chatbot v3 (60+ intents),
│                      # DC Simulator (multi-turn), Emergency Runway, 30-Day Plan,
│                      # Rate limits, 8 module FAQ
├── auth.py            # User model + Google OAuth + demo login + decorators + usage tracking
├── templates/
│   ├── index.html              # Landing page (vibrant redesign + featured tools)
│   ├── login.html              # 2-column login (Masuk/Daftar tabs)
│   ├── privacy.html            # UU PDP compliant Privacy
│   ├── terms.html              # Syarat & Ketentuan
│   ├── dashboard/
│   │   ├── base.html           # Topbar + chatbot widget + privacy/terms footer
│   │   ├── ringkasan.html      # Executive summary + KPI + multi-source stats
│   │   ├── analisis.html       # Per-category + multi-source + learning curve + CV folds
│   │   ├── solusi.html         # Inovasi + BMC 9 blok + Risk mitigation
│   │   ├── kesimpulan.html     # Key findings + SWOT Analysis
│   │   ├── produk.html         # 6 game-changer tools + pricing + premium
│   │   ├── dc_simulator.html   # Multi-turn DC Chat Simulator
│   │   ├── galbay_score.html   # Galbay Score Quiz
│   │   └── galbay_score_result.html  # Score result with recommendations
└── static/
    ├── css/style.css           # Dual theme (purple dark/light) + DC simulator + quiz + tools
    ├── js/
    │   ├── main.js             # Chart init + 20+ chart functions + scroll-reveal integration
    │   ├── produk.js           # Skor Risiko + Pinjol + Planner + Roadmap + Runway + 30-Day
    │   ├── chatbot.js          # AI Coach widget v3 (60+ intents, markdown, 429 handling)
    │   ├── data.js             # 602K multi-source data + per-category + learning curve
    │   ├── scroll-reveal.js    # IntersectionObserver + chart re-init on visible
    │   ├── theme.js            # Dark/light toggle
    │   └── quiz.js             # Galbay Score Quiz logic
    └── img/                    # Logo + favicon

API Endpoints

Endpoint	Method	Fungsi	Auth
`/api/health`	GET	health check	No
`/api/score`	POST	hitung Skor Risiko Galbay (rule-based)	No
`/api/simulate`	POST	simulasi cicilan dengan bunga flat	No
`/api/check-pinjol`	POST	cek status legal/ilegal pinjol	No
`/api/debt-planner`	POST	snowball vs avalanche + timeline	No
`/api/recovery-roadmap`	POST	generate 30/60/90 hari plan	No
`/api/chat`	POST	Assistant rule-based untuk FAQ + navigasi tool	Rate-limit 10/day free
`/api/waitlist`	POST	daftar waitlist premium	No
`/api/usage`	GET	current usage (rate limit tracking)	Auto
`/galbay-score`	GET/POST	Galbay Score Quiz (6 pertanyaan)	No
`/tools/dc-simulator`	GET/POST	DC Chat Simulator (multi-turn)	Rate-limit 1/day free
`/tools/emergency-runway`	POST	hitung emergency runway	No
`/tools/30-day-plan`	POST	generate 30-Day Action Plan	No

Galbay AI Coach v3 (Chatbot)

Phase 3 NLP-like dengan 60+ intents across 8 modul:

Module	Topik	Intents
M1 Galbay Basics	Pengertian galbay, skor, simulasi, financial coach	6
M2 Pinjol	Legal/ilegal, OJK, bunga wajar, registered check	8
M3 Debt Strategy	Snowball, Avalanche, negosiasi, konsolidasi	7
M4 DC Negotiation	DC agresif, telpon malam, datang ke rumah, palsu	8
M5 Recovery	30/60/90 hari, telat 7/30, tanpa kerja, nabung	7
M6 Legal Rights	UU PDP, ITE, OJK, SLIK, pembelaan pengadilan	7
M7 App Recommendation	blu/jago/seabank, kartu kredit vs paylater, dll	9
M8 Mental Health	Stress, krisis, konseling, dukungan keluarga	9
+ default	smart fallback dengan top-3 closest	1

Smart features:

🔤 Synonym resolution — "pinjol" matches "pinjaman online", "online", "p2p"
🔍 Typo tolerance — "snowbol" → snowball via difflib (>= 0.8 ratio)
🎯 Multi-intent — returns top 3 secondary intents for follow-up
💚 Sentiment detection — curious/stressed/crisis/grateful/positive
⏰ Time-based greeting — pagi/siang/sore/malam
📍 Context-aware — page-specific tips (ringkasan/produk/solusi)
🆘 Crisis helpline — auto-suggest Sejiwa 119 ext 8 untuk self-harm
🧠 Markdown rendering — full support untuk bold, italic, list, links
🎨 Contextual Quick Replies — 8 default + 9 category chips
🚨 Smart fallback — when conf < 0.1, suggest top 3 closest intent

Modeling & Analysis

Model Performance

Metric	Score
Algorithm	Multinomial Naive Bayes (from scratch)
Accuracy	0.858
Precision	0.903
Recall	0.815
F1-Score	0.857
Macro F1	0.858
5-Fold CV Accuracy	0.860 ± 0.003
5-Fold CV Macro F1	0.860 ± 0.003
Vocab	4.446 kata

Per-Category Performance (Top 8)

Category	N Test	F1 Negatif	Predicted POS	Actual POS
kartu_kredit	542	0.86	75.7%	78.9%
pinjol	4421	0.85	49.2%	53.6%
paylater	689	0.82	49.2%	53.8%
bank_digital	712	0.81	60.9%	65.7%
p2p_lending	487	0.80	58.1%	61.7%
ewallet	823	0.79	38.2%	44.8%
ecommerce	298	0.75	26.4%	32.9%
mobile_banking	312	0.74	23.0%	31.4%

Premium Tier + Rate Limits

Fitur	Free	Premium
Skor Risiko, Simulasi, Pinjol Checker	✅	✅ + alerts
Recovery Roadmap	Preview	Full + save
Debt Planner	1x/hari	✅ unlimited
Galbay AI Coach	10 pesan/hari	✅ unlimited
DC Chat Simulator	1 attempt/hari	✅ unlimited
Save history	3	✅ unlimited
Export PDF	❌	✅
Laporan Bulanan	❌	✅

Pricing: Rp 49rb/bln atau Rp 399rb/tahun (diskon 50% tahun pertama).

Tools & Pages

Page	URL	Description
Landing	`/`	Hero + Featured Tools + Why Us + 7 source cards
Login	`/login`	Google OAuth + demo login
Galbay Score Quiz	`/galbay-score`	Public, 6 pertanyaan, scoring 0-100
Dashboard Ringkasan	`/dashboard/ringkasan`	Executive summary + 4 KPI + charts
Dashboard Analisis	`/dashboard/analisis`	Multi-source + per-category + learning curve + CV folds
Dashboard Solusi	`/dashboard/solusi`	Inovasi + BMC 9 blok + Risk mitigation
Dashboard Kesimpulan	`/dashboard/kesimpulan`	Key findings + SWOT Analysis
Dashboard Produk	`/dashboard/produk`	6 tools + pricing + premium
DC Chat Simulator	`/tools/dc-simulator`	Multi-turn conversation (3-5 exchanges)
Privacy	`/privacy`	UU PDP compliant
Terms	`/terms`	Syarat & ketentuan

Cara Mengambil Project dan Dataset

1. Clone repository

git clone https://github.com/addaan1/Final-Project-AKB.git
cd Final-Project-AKB

2. Buat dan aktifkan virtual environment

python -m venv .venv
.\.venv\Scripts\Activate.ps1

3. Install dependency

pip install -r requirements.txt

4. Siapkan konfigurasi DVC Google Drive

copy .env.example .env

Isi minimal field berikut di .env:

GDRIVE_CLIENT_ID=your-client-id.apps.googleusercontent.com
GDRIVE_CLIENT_SECRET=your-client-secret

Lalu jalankan:

python scripts/setup_dvc_gdrive.py

5. Ambil dataset besar dengan DVC

dvc pull

Yang akan dipulihkan otomatis: data/raw/, data/processed/, data/site/.

6. Jalankan aplikasi

python run.py

Buka http://localhost:5000.

Testing

# Run all tests
pytest tests/

# Run specific file
pytest tests/test_chatbot.py -v

342 tests passing:

test_api.py — API logic (scoring, simulasi, pinjol, debt planner, recovery, chatbot, DC, runway)
test_auth.py — User model, OAuth, login, upgrade
test_chatbot.py — FAQ NLP v3 (60+ intents, synonyms, typos, multi-intent, sentiment, crisis)
test_game_changers.py — Pinjol Checker, Debt Planner, Recovery Roadmap
test_routes.py — Dashboard routes + auth integration
test_produk.py, test_simulasi.py, test_smoke.py — integration tests
test_sentiment.py, test_sentiment_model.py, test_behavior_analysis.py — modeling

Struktur Project

app/             aplikasi Flask (main.py, api.py, auth.py)
scraper/         pipeline pengumpulan data (10+ scrapers)
processing/      pembentukan CSV, sentiment, chart, dan SQLite
data/raw/        data mentah (60+ file JSON, multi-source)
data/processed/  output analisis terkurasi (9 CSV multi-source)
data/site/       output dashboard (data.js + PNG charts)
docs/            dokumen pendukung + API docs + business plan
tests/           342 unit & integration tests
assets/          chart PNGs untuk laporan

Alur Kolaborasi

Branch	Fungsi
`main`	branch utama yang stabil dan siap dipresentasikan
`scraping`	branch untuk pengolahan data, scraping, dan dataset
`fullstack`	branch untuk pengembangan aplikasi web + UI/UX (currently synced with main)
`feat/multi-source-700k`	branch eksperimen multi-source 600K+ (merged ke main via PR #9)

Alur kerja yang disarankan:

kerjakan perubahan di branch yang sesuai;
sinkronkan branch dengan main sebelum lanjut kerja besar;
validasi hasil secara lokal (pytest tests/);
push branch ke GitHub;
buka pull request ke main;
merge setelah perubahan siap.

Catatan tentang DVC

Konfigurasi DVC adalah jalur utama untuk mengambil dataset besar tim. Folder Google Drive tetap dipakai sebagai remote storage di belakang DVC, tetapi anggota tim seharusnya tidak perlu mengunduh dataset secara manual bila setup DVC sudah benar.

Pada alur ini:

setiap anggota tim tetap harus punya akses ke folder Google Drive;
.dvc/config.local bersifat lokal dan tidak boleh di-commit;
python scripts/setup_dvc_gdrive.py akan menulis konfigurasi OAuth lokal untuk mesin masing-masing;
dvc pull pertama biasanya akan membuka login atau consent Google di browser.

Demo Login (Tanpa Setup)

Untuk coba aplikasi tanpa setup DVC/OAuth, pakai akun demo:

demo@galbay.id / demo123 — Free tier (10 chat/day, 1 DC/day)
premium@galbay.id / demo123 — Premium tier (semua fitur terbuka, unlimited)

SWOT Analysis (Round 13)

💪 Strengths

Data 602K dari 7 sumber (paling kaya di niche)
Model Multinomial NB F1 0,857, CV stabil ±0,003
6 tools interaktif (DC Simulator, Runway, 30-Day Plan, dll)
Privacy-first (no data keuangan pribadi dikumpulkan)

⚠️ Weaknesses

Fitur masih rule-based, belum pakai LLM real-time
Premium tier belum fully implemented (no payment gateway)
6 source non-Play masih tipis (Twitter/TikTok blocked)
Onboarding mungkin terlalu panjang untuk Gen Z

🚀 Opportunities

Pasar Gen Z Indonesia ~70 juta, 60% pengguna fintech
OJK butuh tools edukasi (potential B2B partnership)
Bisa ekspansi ke SEA (Filipina, Vietnam: similar pain)
Premium tier Rp 49rb × 10K user = Rp 4,9M MRR potensial

🚧 Threats

Pesaing: aplikasi budgeting besar (Money Lover, Finansialku)
Bank digital sudah punya fitur serupa (Jenius, Jago)
Regulasi OJK untuk financial advisor (mungkin butuh lisensi)
Trust issue: scam di niche financial = sulit dapat user trust

Tim

Nama	NIM	Peran
Sahrul Adicandra Effendy	164231013	Big Data Engineer
Raihan Naufal Sauqi	164231107	Fullstack Engineer
Aflah Zein Japamel	164231085	Modeling Engineer
Muhammad Ilham Gustami	164231089	Fullstack Engineer
Mohammad Faizal Aprilianto	164231095	Big Data Engineer

Referensi Tambahan

data/README.md — struktur dan isi paket data
data/DOWNLOAD.md — panduan mengambil dataset besar
docs/API.md — dokumentasi API endpoints
docs/business_plan.md — konteks bisnis proyek
docs/bmc.md — Business Model Canvas 9 blok data-driven

Lisensi

MIT License. Lihat LICENSE.

Galbay Predictor — Membaca sinyal financial distress dari 602.675 item multi-source Indonesia.

🟣 Vibrant Purple Theme · 🤖 AI Coach v3 (60+ intents) · 🎮 6 Interaktif Tools · 🔐 Auth + Premium + Rate Limits

Name		Name	Last commit message	Last commit date
Latest commit History 14 Commits
.dvc		.dvc
app		app
assets		assets
data		data
docs		docs
models		models
notebooks		notebooks
processing		processing
scraper		scraper
scripts		scripts
tests		tests
.dockerignore		.dockerignore
.dvcignore		.dvcignore
.env.example		.env.example
.gitattributes		.gitattributes
.gitignore		.gitignore
DEPLOY_HF.md		DEPLOY_HF.md
Dockerfile		Dockerfile
HF_SPACE_README.md		HF_SPACE_README.md
README.md		README.md
README.txt		README.txt
config.py		config.py
dashboard.html		dashboard.html
data.js		data.js
index.html		index.html
requirements-runtime.txt		requirements-runtime.txt
requirements.txt		requirements.txt
run.py		run.py
script.js		script.js
style.css		style.css

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