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https://github.com/shawnkim1997/All-in-one-Financial-Analysis.git
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160 lines
6.9 KiB
Markdown
160 lines
6.9 KiB
Markdown
# ATLAS Terminal
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[](https://github.com/shawnkim1997/All-in-one-Financial-Analysis/actions/workflows/ci.yml)
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Institutional-style equity research terminal built with Next.js 14 and FastAPI.
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ATLAS Terminal brings market overview, quant research, valuation, technical analysis, macro monitoring, filings workflows, and printable institutional reports into one desktop-first interface.
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## What It Does
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- Multi-asset overview for equities, ETFs, commodities, crypto, FX, and macro signals
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- Quant research dashboards with F-Score, DuPont, anomalies, Sankey, and waterfall views
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- Valuation tooling including DCF, sensitivity, Monte Carlo, tornado, and reverse DCF
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- Technical analysis with candlesticks, moving averages, Bollinger Bands, RSI, MACD, and Fibonacci levels
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- Cross-market monitoring through macro, smart-money, yield/FX, earnings, news, filings, and portfolio pages
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- Institutional report generation with printable PDF-style layouts
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## Core Product Principle
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> LLMs handle text. Python handles numbers.
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Qualitative analysis, summarization, and narrative framing can be AI-assisted, while valuation logic, financial metrics, and quantitative workflows are computed deterministically in code.
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## Product Tour
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### Overview
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### Valuation
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### Technical Analysis
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### Institutional Report
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## Demo Assets
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- [Open recorded demo video](./docs/media/atlas-demo.mp4)
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- [Open report preview PDF](./docs/media/atlas-report-preview.pdf)
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You can also click the screenshot below to open the recorded walkthrough:
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[](./docs/media/atlas-demo.mp4)
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## Stack
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- Frontend: Next.js 14, React 18, TypeScript, Tailwind CSS, Recharts, Lightweight Charts
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- Frontend state: Zustand persistent terminal store, shared API hook, Playwright smoke tests
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- Backend: FastAPI, Python 3.12+, Pydantic, yfinance, yahooquery, FMP gateway scaffold, pandas, scipy
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- Data: SEC, DART, EDINET, FRED, OECD, DBnomics, Yahoo Finance
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- AI: Gemini for qualitative analysis only
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- Storage: SQLite by default
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## Key Pages
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- `/` overview dashboard
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- `/research` quant research workbench
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- `/valuation` DCF and scenario analysis
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- `/technical` chart-driven technical analysis
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- `/macro` macro and smart-money dashboard
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- `/filings` SEC, DART, and EDINET workflows
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- `/report` institutional report generator
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- `/portfolio` portfolio tracking and OCR import
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## Quick Start
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### Backend
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```bash
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pip install -r requirements.txt
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PYTHONPATH="." uvicorn server.main:app --host 127.0.0.1 --port 8000
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```
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### Frontend
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```bash
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cd apps/web
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npm install
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npm run dev
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```
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### Verification
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```bash
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pytest tests -q
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cd apps/web
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npm run typecheck
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npm run build
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npm run e2e
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```
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### Local URLs
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- Frontend: [http://localhost:3000](http://localhost:3000)
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- Backend: [http://127.0.0.1:8000](http://127.0.0.1:8000)
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- API docs: [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)
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## Secure Credential Storage
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Server-side broker/API credentials are stored with envelope encryption. The master key must live in the environment and is never written to SQLite/PostgreSQL.
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Generate a local master key:
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```bash
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python -c "import secrets; print(secrets.token_urlsafe(32))"
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```
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Then set it in `.env`:
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```bash
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ATLAS_MASTER_KEY=your-generated-value
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```
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Credential tables:
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- `user_credentials`: encrypted provider blobs keyed by `user_id` and `provider`
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- `credential_access_log`: audit trail for store/status/delete/decrypt attempts
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Credential API:
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- `PUT /api/credentials/{provider}` stores a secret after envelope encryption
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- `GET /api/credentials/{provider}/status` returns only metadata, never the secret
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- `DELETE /api/credentials/{provider}` removes the encrypted credential
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## Recent Work
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- Phase 5 earnings-call delta: FMP transcript pair lookup, rule-based lemmatisation, bigram/trigram TF-IDF phrase ranking, finance-topic shift detection, tone shift scoring, and best-effort Claude/Gemini narrative on the Earnings page
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- Phase 4 peer comparison: gateway-backed peer discovery, parallel fundamentals matrix, percentile-colored valuation/quality cells, and backward-compatible `/api/market/peers/{ticker}` responses for overview/report flows
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- Phase 3 security hardening: AES-GCM envelope encryption, credential tables, credential access audit logs, and `ATLAS_MASTER_KEY` documentation for future KIS/IBKR key storage
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- v2 refactor foundation: baseline measurements in `docs/baseline-2026-04.md`, CI workflow, pytest smoke tests, and Playwright route smoke tests
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- Data Gateway scaffold: typed `DataGateway` contract, chained providers, TTL cache wrapper, provider metrics, and a flag-gated `/api/market/quote/{ticker}` migration path via `ATLAS_FLAG_GATEWAY=true`
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- Central terminal state: Zustand-backed `useTerminal` store for active symbol, page context, recent symbols, watchlist, currency, theme, layouts, and Copilot context
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- Copilot context injection: right rail chat now sends terminal context to `/api/copilot/chat` on every turn
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- Keyboard workflow: `Cmd/Ctrl+K` and `G` focus ticker search, `/` focuses Copilot, `W` adds the active symbol to watchlist, and `P/M/N` navigate Portfolio/Macro/News
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- Smarter ticker search: company-name and Korean aliases now resolve suggestions such as Berkshire Hathaway, SK hynix, Samsung Electronics, Toyota, Novo Nordisk, and common ETFs/commodities
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- Portfolio and FX reliability: exchange-aware Novo Nordisk EUR handling, faster FX/portfolio repeat loads, and cleaner local artifact ignore rules
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- Morgan Stanley-inspired redesign across the shell, overview, research, valuation, technical, macro, settings, and report flows
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- Shared chart palette and UI primitives for a more consistent desktop terminal experience
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- Research dashboard performance fixes for faster repeat loads and less blocking on page open
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- Improved macro failure states, report messaging, tooltip formatting, and chart legibility
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## Refactor Roadmap
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- Phase 0: Foundation safety net, baseline docs, CI, backend smoke tests, frontend e2e smoke tests
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- Phase 1: Data Gateway migration behind `ATLAS_FLAG_GATEWAY`, starting with low-risk quote data before wider overview/profile routes
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- Phase 2: Global terminal state through Zustand, Copilot context, and keyboard-first terminal navigation
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- Next phases: encrypted credential vault, peer comparison, earnings-call delta analysis, and smaller institutional feature gaps
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## Why This Project
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ATLAS Terminal started as an attempt to build a personal Bloomberg-lite for retail investing workflows: high information density, clean narrative structure, and a hard separation between AI-generated language and deterministic financial computation.
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It is currently optimized as a desktop-first personal research environment rather than a SaaS product.
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