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docs: comprehensive README rewrite for Atlas Terminal v4
Full documentation covering all 10 pages, 5 valuation models, architecture diagram, API endpoints, tech stack, Terminal Noir design system, and project evolution from Streamlit to Next.js. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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parent
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commit
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@@ -1,183 +1,151 @@
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# ATLAS Terminal — All-in-One Financial Analysis Dashboard
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<p align="center">
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<strong style="font-size: 2em;">ATLAS TERMINAL</strong>
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</p>
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A **cost-effective**, institutional-grade financial analysis platform built with Streamlit. Combines **qualitative AI-driven insights** from SEC 10-K filings with **quantitative valuation models** in a single unified workflow.
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<p align="center">
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<em>Personal Bloomberg Terminal — Institutional-Grade Financial Analysis for Everyone</em>
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</p>
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**Hybrid architecture:** Google Gemini powers qualitative narrative analysis (MD&A, Risk Factors); all numbers—DCF inputs, peer multiples, technical indicators—come from **yfinance** and **yahooquery**, keeping API costs low and numerical accuracy high.
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<p align="center">
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<img src="https://img.shields.io/badge/Next.js-14-black?logo=next.js" alt="Next.js 14" />
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<img src="https://img.shields.io/badge/FastAPI-0.110+-009688?logo=fastapi" alt="FastAPI" />
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<img src="https://img.shields.io/badge/Python-3.12+-3776AB?logo=python&logoColor=white" alt="Python" />
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<img src="https://img.shields.io/badge/TypeScript-5.0+-3178C6?logo=typescript&logoColor=white" alt="TypeScript" />
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<img src="https://img.shields.io/badge/TailwindCSS-3.4-06B6D4?logo=tailwindcss&logoColor=white" alt="Tailwind" />
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</p>
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---
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## Live Demo
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## What is ATLAS Terminal?
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```
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streamlit run app.py --server.port 8501
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```
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Open: [http://localhost:8501](http://localhost:8501)
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ATLAS Terminal is a **full-stack financial analysis platform** that brings institutional-grade equity research tools to a single, unified interface. It combines **AI-driven qualitative analysis** of SEC 10-K filings with **quantitative valuation models**, real-time market data, and portfolio management — all wrapped in a sleek, dark-themed terminal UI.
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**Design philosophy:** LLM for text interpretation, Python for numbers. This eliminates hallucination risk on financial figures while delivering nuanced qualitative insights from SEC filings.
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---
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## Seven-Tab Layout
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## Pages & Features
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| Tab | Purpose |
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|-----|---------|
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| **1. 10-K & MD&A Insights** | SEC EDGAR 10-K → Item 7 (MD&A) + Item 1A (Risk Factors) → Gemini streaming analysis. DuPont, Altman Z-Score, red flags, YoY ratios; Piotroski F-Score; sector-specific KPIs; Sankey & Radar charts. Native SEC/DART filing HTML viewer. |
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| **2. DCF Valuation** | 5-year 2-stage DCF with Bull/Base/Bear scenarios. Smart defaults from Beta/CAPM. Damodaran sector WACC reference panel. Analyst consensus, FCFF/FCFE bridge, sensitivity table. |
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| **3. Industry Comps** | Peer multiples (Forward P/E, EV/EBITDA, P/B) with green/red conditional formatting. Gemini-powered industry outlook (12–18 month macro trends). |
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| **4. News Feed** | Real-time Google News RSS feed filtered by company. |
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| **5. Markets & FX** | Live FX rates (USD/KRW, GBP/USD, EUR/USD, USD/JPY). S&P 500 sector performance heatmap (XLK, XLV, XLF …). |
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| **6. Crypto** | Live prices for 12 major cryptocurrencies (BTC, ETH, SOL, XRP …) with 24h change and market cap. |
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| **7. Technical & Risk** | RSI(14), SMA(50/200), Golden/Death Cross signals, 52-week range, support/resistance. Quantitative risk matrix with estimated EPS impact per risk factor. |
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### 📊 Overview
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Company snapshot at a glance — current price, sector, industry, market cap, P/E ratio, beta, dividend yield, 52-week range, **Altman Z-Score** (safe/grey/distress zones), and **DuPont decomposition** (ROE → NPM × Asset Turnover × Equity Multiplier).
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### 🔬 Research
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AI-powered deep-dive analysis using Google Gemini. Ask natural-language questions about any company and receive structured financial insights with context from SEC filings, financial statements, and market data.
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### 💰 Valuation — 5 Analytical Models
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| Tab | Description |
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|-----|-------------|
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| **DCF Model** | 2-stage discounted cash flow with smart defaults from CAPM/Beta. Adjustable WACC, terminal growth, and FCF growth sliders. Analyst consensus (target price, recommendation) displayed alongside. |
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| **Sensitivity** | WACC × Terminal Growth Rate matrix table. Center cell highlighted to show base-case intrinsic value. Instantly see how assumptions shift fair value. |
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| **Monte Carlo** | 5,000-simulation DCF with randomized inputs. Histogram visualization (red below / green above current price). Statistics: mean, median, P10/P90, probability of upside. |
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| **Tornado** | Variable impact ranking chart. Shows which input assumption (WACC, growth rate, terminal growth, margins) has the largest effect on valuation — sorted by sensitivity range. |
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| **Reverse DCF** | Solves for the implied growth rate the market is pricing in. Compares market-implied growth vs. your assumption and analyst consensus. Uses scipy's Brent root-finding method. |
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### 📈 Technical Analysis
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- **Candlestick chart** with volume histogram (TradingView Lightweight Charts)
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- Period selector: 1MO, 3MO, 6MO, 1Y, 2Y
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- **RSI(14)** with overbought/oversold classification
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- **MACD** with signal line and histogram
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- **Bollinger Bands** — %B, bandwidth, current position
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- **Moving Averages** table — SMA/EMA 20/50/100/200 with ABOVE/BELOW signals
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- **Fibonacci retracement** levels with "near current price" highlighting
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- **ATR** (Average True Range) for volatility measurement
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- **ADX** for trend strength detection
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### 🌍 Financial Statements
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Institutional-style financial data table with:
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- **Income Statement**, **Balance Sheet**, **Cash Flow** tabs
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- Up to 5 annual periods with proper date headers
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- **YoY Growth** badges (green for positive, red for negative)
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- **Margin %** rows (Gross Margin, Operating Margin, Net Margin)
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- Row groups: Revenue, COGS, Gross Profit, SG&A, R&D, Operating Income, EBITDA, Net Income, EPS
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- Pipe-separated multi-key lookup to handle both yfinance and yahooquery column naming conventions
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### 📅 Earnings
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- **Next earnings date** card with countdown
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- **EPS Beat/Miss** visual history — green bars for beats, red for misses, with surprise percentage
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- **Revenue & Earnings estimates** vs. actuals
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- **Quarterly breakdown** cards
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### 📰 News Feed
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Split-view news aggregator:
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- **Left panel**: Scrollable article list (40+ articles from Finviz & Google News) with source badges and timestamps
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- **Right panel**: Article header bar + iframe embedding of original content
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- "Open Original ↗" button for sites that block iframe embedding
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- Ticker-specific filtering
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### 💼 Portfolio
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Position tracking with multi-currency support (USD, KRW, GBP, EUR, JPY, CNY). P&L calculation, FX-adjusted returns, and risk metrics including:
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- **VaR** (Value at Risk)
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- **Sharpe Ratio** & **Sortino Ratio**
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- **Maximum Drawdown**
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- **Beta** & **Correlation** to benchmark
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### 📑 SEC Filings (EDGAR)
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Inline 10-K filing viewer:
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- Downloads and parses latest 10-K from SEC EDGAR
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- **5 section tabs**: Risk Factors (1A), MD&A (7), Financial Statements (8), Legal Proceedings (3), Controls & Procedures (9A)
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- Intelligent content formatting — headers detected and styled, bullets indented, paragraphs separated
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- **Word count** per section
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- **AI Summary** button — sends section text to Gemini for key risk/trend extraction
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- Section caching to avoid repeat downloads
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### ⚙️ Settings
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- Google Gemini API key configuration
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- SEC EDGAR email for fair-access compliance
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- Persistent storage via localStorage
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---
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## Key Features
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### AI & Qualitative Analysis (Tab 1)
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- **Gemini streaming** for Item 7 (Management Strategy) and Item 1A (Risk Factors) — results appear word-by-word in real time
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- **Forensic audit** (Item 3 & 9A) runs automatically alongside Risk Factor analysis
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- **Native SEC Filing Viewer**: renders original SEC HTML directly in-app via `streamlit.components.v1.html()` — no redirect, no loss of formatting
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- **Filing type selector**: 10-K, 10-Q, 8-K, 20-F, 6-K — backend dynamically fetches the correct form from EDGAR
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- **Korean DART direct links** for Korean-listed companies
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- **Sector-aware Non-GAAP KPI extraction**: Gemini identifies industry-specific metrics (ARR/NDR for SaaS, Same-Store Sales for Retail, Rule of 40 for Tech)
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### Quantitative Analysis (Tab 1 & 2)
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- **DuPont decomposition** (3-step ROE: NPM × Asset Turnover × Equity Multiplier)
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- **Altman Z-Score** (Safe > 2.99, Grey Zone 1.81–2.99, Distress < 1.81)
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- **Piotroski F-Score** (9-point checklist; SEC Item 8 + Gemini for US equities, yahooquery/yfinance globally)
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- **Sankey chart**: Income Statement flow (Revenue → COGS → Gross → OpEx → EBIT → Tax/Interest → Net Income)
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- **Radar chart**: 5-axis financial health (Profitability, Liquidity, Efficiency, Solvency, Growth)
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- **YoY and QoQ ratio changes** with coloured trend indicators
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- **Sector-specific metrics**: Tech (Rule of 40, R&D %), Retail (Inventory Turnover), Financials (ROE, ROA)
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### DCF & Valuation (Tab 2)
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- **Excel-style 5-year DCF**: 3 scenarios (Bull/Base/Bear) with probability-weighted expected return
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- **Smart defaults**: WACC from CAPM (Beta), terminal growth 2.5% (Damodaran-style), FCF growth from consensus estimates
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- **Damodaran sector WACC reference panel**: Software 8.5%, Retail 7.5%, Hardware 9.0%, Financials 8.0%
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- **FCFF/FCFE bridge**: detailed waterfall from EBIT → NOPAT → FCFF and Net Income → FCFE
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- **DCF sensitivity table**: 5×5 grid across WACC and terminal growth rate combinations
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- **Analyst consensus** embedded next to sliders (target price, recommendation, revenue/earnings growth estimates)
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### Data Robustness
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- **Primary**: yahooquery for fundamentals + TTM construction
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- **Fallback**: yfinance (multi-step: `fast_info` → `info` → balance sheet)
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- **TTM fallback**: quarterly sum when annual data is unavailable
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- **PyArrow-safe DataFrames**: uniform column types to prevent serialization errors
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- **`@st.cache_data` caching**: 2–60 min TTL per function to minimise API calls
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### Global Company Search
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- Search by name in **any language** (English, Korean, Japanese, etc.) via yahooquery
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- Auto-infers market suffix: `.KS`/`.KQ` (Korea), `.T` (Japan), `.L` (UK)
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- Last selected company **persists across page refresh** via local `.app_prefs.json`
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---
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## Architecture: Hybrid AI + Quantitative Pipeline
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```mermaid
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graph TB
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classDef ui fill:#FF4B4B,stroke:#333,stroke-width:2px,color:#fff;
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classDef core fill:#4C51BF,stroke:#333,stroke-width:2px,color:#fff;
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classDef quant fill:#38B2AC,stroke:#333,stroke-width:2px,color:#fff;
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classDef qual fill:#DD6B20,stroke:#333,stroke-width:2px,color:#fff;
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classDef llm fill:#805AD5,stroke:#333,stroke-width:2px,color:#fff;
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User((🧑💻 User))
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subgraph Frontend ["🖥️ Frontend Interface"]
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UI[Streamlit Web Dashboard]:::ui
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end
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subgraph Input_Sync ["📷 Portfolio Sync (Bypassing API Limits)"]
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OCR[Gemini Vision OCR Pipeline]:::llm
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end
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subgraph Engine ["⚙️ Core Backend (Python)"]
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Core{Hybrid RAG Architecture <br> Token Cost -80%}:::core
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end
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subgraph Quant_Pipeline ["📊 Quantitative Pipeline (No LLM)"]
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YF[(yfinance API)]:::quant
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BS[(BeautifulSoup Web Scraper)]:::quant
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end
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subgraph Qual_Pipeline ["📝 Qualitative Pipeline (NLP)"]
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SEC[(SEC Filings: Item 7 MD&A)]:::qual
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LLM((Google Gemini LLM Engine)):::llm
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end
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User -- 1. Uploads Portfolio Screenshot --> OCR
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User -- 2. Enters Stock Ticker --> UI
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OCR -- Extracts Tickers & Syncs --> Core
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UI -- Sends Request --> Core
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Core -- Fetch Financials/Prices --> YF
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Core -- Parse Web Data --> BS
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YF -. Raw Data .-> Core
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BS -. Scraped Data .-> Core
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Core -- Fetch SEC Documents --> SEC
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SEC -- Raw Text (MD&A) --> LLM
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LLM -- Sentiment Analysis & Hidden Risks --> Core
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Core -- Aggregated Insights & Valuation --> UI
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UI -- Displays Final Dashboard --> User
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```
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**Design principle:** LLM for text only; Python for numbers. This eliminates hallucination risk on financial figures and keeps API costs to a single Gemini call per session.
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---
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## Modular Code Architecture (v3.0)
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The codebase was refactored from a 3,909-line monolith into **28 focused modules**, each under 300 lines, following strict Separation of Concerns.
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## Architecture
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```
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app.py # Thin orchestrator (~118 lines)
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│
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├── config/
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│ ├── constants.py # Company lists, sector maps, row maps, Damodaran baselines
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│ └── theme.py # Soft Navy CSS theme + header HTML
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│
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├── utils/
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│ ├── prefs.py # Local preference persistence (.app_prefs.json)
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│ ├── formatting.py # _safe_float, _format_shares_display, _na
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│ ├── ticker.py # get_global_ticker, infer_market_from_ticker
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│ ├── dcf.py # excel_style_dcf, dcf_10y_2stage, _damodaran_wacc_for_sector
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│ ├── charts.py # Sankey, Radar (Plotly) builders
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│ └── ui_helpers.py # Analyst consensus panel, DCF sensitivity table
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│
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├── data/
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│ ├── sec_parser.py # HTML text extraction, Item section finder (regex)
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│ ├── sec_fetcher.py # EDGAR API fetch (CIK lookup, submissions, HTML cache)
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│ ├── sec_downloader.py # 10-K download via sec-edgar-downloader, section extraction
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│ ├── financials.py # yahooquery + yfinance annual data, TTM construction
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│ ├── fundamentals.py # Sector/industry, 5-year trend, DCF inputs
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│ ├── valuation.py # Analyst consensus, DCF smart defaults, FCFF/FCFE
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│ ├── ratios.py # Comps, DuPont/Altman Z, quarterly momentum/ratios
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│ ├── scores.py # Sankey data, radar metrics, Piotroski, sector metrics
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│ ├── scores_ai.py # AI-derived Sankey/Piotroski/Radar from Gemini extraction
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│ └── market.py # Technical indicators, risk matrix, ticker bar, news RSS
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│
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├── ai/
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│ ├── gemini_core.py # Model init, retry logic, streaming, chunking, forensic audit
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│ ├── gemini_sec.py # SEC financials LLM, Item 7 strategy stream, Item 1A risk stream
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│ └── gemini_insights.py # MDA chunked insights, comparative analysis, industry outlook
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│
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└── views/
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├── sidebar.py # Company search, API keys, market selector
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├── tab1_quant.py # Financial health tables & charts
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├── tab1_ai.py # Deep-dive AI streaming analysis
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├── tab1_filings.py # SEC/DART native filing HTML viewer
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├── tab2_dcf.py # DCF valuation & FCFF/FCFE
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├── tab3_comps.py # Industry comps & AI outlook
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├── tab4_news.py # News RSS feed
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├── tab5_markets.py # FX rates & sector heatmap
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├── tab6_crypto.py # Cryptocurrency prices
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└── tab7_technical.py # Technical indicators & risk matrix
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```
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**Dependency direction (no circular imports):**
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```
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app.py → views/ → data/ or ai/
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utils/ ← importable from anywhere
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data/ ↔ ai/ direct imports are forbidden
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┌─────────────────────────────────────────────────────────────────┐
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│ ATLAS TERMINAL │
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├────────────────────────────┬────────────────────────────────────┤
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│ Next.js 14 Frontend │ FastAPI Backend │
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│ (Port 3000) │ (Port 8000) │
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│ │ │
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│ ┌──────────────────┐ │ ┌──────────────────────┐ │
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│ │ App Router Pages │ │ │ 13 API Routers │ │
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│ │ • Overview │────────▶ │ • /api/market │ │
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│ │ • Research │ proxy │ • /api/financials │ │
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│ │ • Valuation │ /api/* │ • /api/valuation │ │
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│ │ • Technical │ │ │ • /api/technical │ │
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│ │ • Markets │ │ │ • /api/earnings │ │
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│ │ • Earnings │ │ │ • /api/edgar │ │
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│ │ • News │ │ │ • /api/news │ │
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│ │ • Portfolio │ │ │ • /api/portfolio │ │
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│ │ • Filings │ │ │ • /api/insider │ │
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│ │ • Settings │ │ │ • /api/analysis │ │
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│ └──────────────────┘ │ │ • /api/crypto │ │
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│ │ │ • /api/fx │ │
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│ ┌──────────────────┐ │ │ • /api/estimates │ │
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│ │ Components │ │ └──────────┬───────────┘ │
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│ │ • Sidebar │ │ │ │
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│ │ • Ticker Bar │ │ ┌──────────▼───────────┐ │
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│ │ • Chat Panel │ │ │ 15 Service Modules │ │
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│ │ • useTicker() │ │ │ • dcf_engine │ │
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│ └──────────────────┘ │ │ • monte_carlo │ │
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│ │ │ • sensitivity │ │
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│ ┌──────────────────┐ │ │ • risk_metrics │ │
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│ │ Design System │ │ │ • technical_analysis│ │
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│ │ Terminal Noir │ │ │ • sec_parser │ │
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│ │ #0A0A0F bg │ │ │ • news_aggregator │ │
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│ │ #00D4AA accent │ │ │ • gemini_service │ │
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│ │ #FF4757 red │ │ │ • market_data │ │
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│ └──────────────────┘ │ └──────────┬───────────┘ │
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│ │ │ │
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│ │ ┌──────────▼───────────┐ │
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│ │ │ Data Sources │ │
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│ │ │ • yfinance │ │
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│ │ │ • yahooquery │ │
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│ │ │ • SEC EDGAR API │ │
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│ │ │ • Google Gemini │ │
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│ │ │ • Finviz / RSS │ │
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│ │ └──────────────────────┘ │
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└────────────────────────────┴────────────────────────────────────┘
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```
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---
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@@ -186,131 +154,220 @@ data/ ↔ ai/ direct imports are forbidden
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| Layer | Technology |
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|-------|-----------|
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| UI Framework | Streamlit |
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| AI / LLM | Google Gemini 2.0 Flash (`google-generativeai`) |
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| Financial Data | yahooquery (primary), yfinance (fallback) |
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| SEC Data | sec-edgar-downloader, EDGAR public REST API |
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| HTML Parsing | BeautifulSoup4, lxml |
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| Charts | Plotly (Sankey, Scatterpolar Radar, Line) |
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| Caching | `@st.cache_data` (2–60 min TTL per function) |
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| **Frontend** | Next.js 14 (App Router), TypeScript, Tailwind CSS |
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| **Charts** | TradingView Lightweight Charts (candlestick, volume) |
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| **Backend** | Python 3.12+, FastAPI, Pydantic v2, Uvicorn |
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| **AI / LLM** | Google Gemini 2.0 Flash (`google-generativeai`) |
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| **Financial Data** | yfinance (primary), yahooquery (fallback) |
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| **Technical Indicators** | `ta` library (RSI, MACD, Bollinger, Ichimoku, ADX) |
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| **Valuation Engine** | NumPy (Monte Carlo), SciPy (Brent root-finding for Reverse DCF) |
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| **SEC Data** | `sec-edgar-downloader`, EDGAR REST API, BeautifulSoup4 + lxml |
|
||||
| **Database** | SQLite (local) / PostgreSQL (production) via asyncpg |
|
||||
| **News** | Finviz scraping + Google News RSS via feedparser |
|
||||
| **Design System** | Terminal Noir — custom dark theme (#0A0A0F, #00D4AA, #FF4757) |
|
||||
|
||||
---
|
||||
|
||||
## Technical Challenges & Solutions
|
||||
## Project Structure
|
||||
|
||||
### Challenge 1 — 429 Resource Exhausted (LLM Token Overflow)
|
||||
|
||||
**Problem:** Full 10-K filings (200+ pages) caused Gemini 429 errors and rate limits.
|
||||
|
||||
**Solution:** Selective section extraction (Item 7 only → ~80% token reduction), HTML cleansing (BeautifulSoup + regex strips tags/whitespace), smart chunking with head+tail trim, and a 60-second retry decorator.
|
||||
|
||||
### Challenge 2 — SEC EDGAR HTML Not Rendering
|
||||
|
||||
**Problem:** The filing viewer showed "원본 HTML을 가져오지 못했습니다" because the legacy code used `directory.item` from the index JSON (now deprecated) instead of the submissions API.
|
||||
|
||||
**Solution:** Rebuilt the EDGAR fetch chain — `company_tickers.json` → CIK lookup → `submissions/CIK{cik}.json` → `filings.recent.primaryDocument[]` → direct `.htm` download. Added `streamlit.components.v1.html()` for native in-app rendering with an injected CSS reset.
|
||||
|
||||
### Challenge 3 — PyArrow Serialization in Streamlit
|
||||
|
||||
**Problem:** Mixed-type DataFrame columns (float + string in same column) caused `ArrowInvalid` errors when passing DataFrames through `@st.cache_data`.
|
||||
|
||||
**Solution:** Explicitly coerce all display strings before DataFrame construction; keep numeric columns as float, string columns as str throughout the pipeline.
|
||||
|
||||
### Challenge 4 — 3,909-line Monolith Maintainability
|
||||
|
||||
**Problem:** A single `app.py` containing all business logic, UI rendering, and data fetching became unmanageable and untestable.
|
||||
|
||||
**Solution:** Full modular refactoring into 28 files across 5 packages (config, utils, data, ai, views). Dependency graph enforced no circular imports. All cache decorators and session state preserved identically. Each file kept under 300 lines.
|
||||
```
|
||||
atlas-terminal/
|
||||
│
|
||||
├── apps/web/ # Next.js 14 Frontend
|
||||
│ ├── src/app/
|
||||
│ │ ├── page.tsx # Overview (home)
|
||||
│ │ ├── research/page.tsx # AI Research
|
||||
│ │ ├── valuation/page.tsx # DCF + Sensitivity + Monte Carlo + Tornado + Reverse DCF
|
||||
│ │ ├── technical/page.tsx # Technical Analysis (TradingView charts)
|
||||
│ │ ├── markets/page.tsx # Financial Statements table
|
||||
│ │ ├── earnings/page.tsx # Earnings history & calendar
|
||||
│ │ ├── news/page.tsx # News feed (split-view)
|
||||
│ │ ├── portfolio/page.tsx # Portfolio tracker
|
||||
│ │ ├── filings/page.tsx # SEC EDGAR filing viewer
|
||||
│ │ ├── settings/page.tsx # API keys configuration
|
||||
│ │ ├── components/
|
||||
│ │ │ ├── sidebar.tsx # Navigation sidebar
|
||||
│ │ │ ├── ticker-bar.tsx # Live market indices bar
|
||||
│ │ │ └── chat-panel.tsx # AI Copilot chat interface
|
||||
│ │ └── lib/
|
||||
│ │ ├── use-ticker.ts # Ticker state hook (localStorage + CustomEvent)
|
||||
│ │ └── api.ts # API helper functions
|
||||
│ ├── next.config.mjs # API proxy: /api/* → localhost:8000
|
||||
│ ├── tailwind.config.ts # Terminal Noir color system
|
||||
│ └── package.json
|
||||
│
|
||||
├── server/ # FastAPI Backend
|
||||
│ ├── main.py # App entry + CORS + router mounting
|
||||
│ ├── routers/ # 13 API route handlers
|
||||
│ │ ├── market_data.py # Stock quotes, indices, overview
|
||||
│ │ ├── financials.py # Income statement, balance sheet, cash flow
|
||||
│ │ ├── valuation.py # DCF, sensitivity, Monte Carlo, tornado, reverse DCF
|
||||
│ │ ├── technical.py # RSI, MACD, Bollinger, moving averages, Fibonacci
|
||||
│ │ ├── earnings.py # EPS history, calendar, quarterly data
|
||||
│ │ ├── insider.py # Insider transactions, institutional holders
|
||||
│ │ ├── edgar.py # SEC 10-K section extraction
|
||||
│ │ ├── analysis.py # Gemini AI analysis endpoints
|
||||
│ │ ├── news.py # News aggregation
|
||||
│ │ ├── portfolio.py # Position CRUD + risk metrics
|
||||
│ │ ├── estimates.py # Analyst estimates
|
||||
│ │ ├── crypto.py # Cryptocurrency prices
|
||||
│ │ └── fx.py # FX rates and history
|
||||
│ ├── services/ # 15 business logic modules
|
||||
│ │ ├── dcf_engine.py # Excel-style DCF, 2-stage DCF, reverse DCF (scipy brentq)
|
||||
│ │ ├── monte_carlo.py # Monte Carlo simulation (5000 runs, numpy)
|
||||
│ │ ├── sensitivity.py # WACC × TG matrix, tornado data
|
||||
│ │ ├── risk_metrics.py # VaR, Sharpe, Sortino, MDD, Beta, Correlation
|
||||
│ │ ├── technical_analysis.py # All indicators via `ta` library
|
||||
│ │ ├── sec_parser.py # SEC EDGAR download, HTML parse, section cache
|
||||
│ │ ├── news_aggregator.py # Finviz + Google News RSS
|
||||
│ │ ├── gemini_service.py # Gemini API wrapper
|
||||
│ │ ├── gemini_analysis.py # Structured AI analysis prompts
|
||||
│ │ ├── market_data.py # Market overview, sector data
|
||||
│ │ ├── financial_metrics.py # DuPont, Altman Z, ratio calculations
|
||||
│ │ └── ... # crypto, fx, screenshot OCR, text chunker
|
||||
│ ├── models/ # Pydantic schemas
|
||||
│ ├── db/ # SQLite + PostgreSQL repositories
|
||||
│ ├── ai/ # LLM router, context builder
|
||||
│ └── utils/ # safe_float, ticker utilities
|
||||
│
|
||||
├── tests/ # pytest test suite
|
||||
├── supabase/migrations/ # Database schema
|
||||
└── requirements.txt # Python dependencies
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Project Origin & Vision
|
||||
## API Endpoints
|
||||
|
||||
### The Origin — The Walk
|
||||
| Prefix | Methods | Description |
|
||||
|--------|---------|-------------|
|
||||
| `/api/market` | GET | Stock quotes, company info, market overview, sector data |
|
||||
| `/api/financials` | GET | Income statement, balance sheet, cash flow, highlights, ratios |
|
||||
| `/api/valuation` | GET, POST | DCF defaults, sensitivity matrix, Monte Carlo, tornado, reverse DCF |
|
||||
| `/api/technical` | GET | RSI, MACD, Bollinger, moving averages, Fibonacci, ATR, ADX |
|
||||
| `/api/earnings` | GET | EPS history, earnings calendar, quarterly data |
|
||||
| `/api/insider` | GET | Insider transactions, institutional holders |
|
||||
| `/api/edgar` | GET | SEC 10-K section extraction, Item 7 MD&A, filing comparison |
|
||||
| `/api/analysis` | POST | Gemini AI analysis (MD&A, risk factors, financial health) |
|
||||
| `/api/estimates` | GET | Analyst consensus estimates |
|
||||
| `/api/news` | GET | Financial news aggregation (Finviz + Google News) |
|
||||
| `/api/portfolio` | GET, POST, DELETE | Position management, risk metrics |
|
||||
| `/api/crypto` | GET | Cryptocurrency prices (BTC, ETH, SOL, etc.) |
|
||||
| `/api/fx` | GET | FX rates and historical data |
|
||||
| `/health` | GET | Liveness probe with DB status |
|
||||
|
||||
The core idea came during a **quiet walk** while reflecting on the fragmentation of traditional equity research: narratives buried in 200-page filings, valuation models in separate spreadsheets, and comp tables scattered across different tools. What analysts need is not more dashboards — but **one seamless workflow** where qualitative AI insights and quantitative valuation models live in the same place, speak the same language, and serve the same decision.
|
||||
|
||||
That realisation crystallised into the design you see here: **unified, cost-conscious, and built for the analyst who thinks in both words and numbers.**
|
||||
|
||||
### The Vision — Commercialisation
|
||||
|
||||
This repository is a **functional MVP** and technical portfolio piece. It proves the concept: hybrid architecture works, 10-K + DCF + comps can coexist in a single interface, and the unit economics (one Gemini call for narrative, free data for the rest) scale sustainably. The modular codebase is production-minded — each module under 300 lines, no circular imports, explicit error handling — and is the foundation on which a commercial product will be built.
|
||||
|
||||
**Ultimate goal:** Launch as a **fully commercialised B2C/B2B SaaS** serving retail investors who want institutional-grade structure without complexity, and finance professionals (equity analysts, portfolio managers, corporate development) who want to move from filing → insight → valuation in one flow.
|
||||
Full interactive API documentation available at `http://localhost:8000/docs` (Swagger UI).
|
||||
|
||||
---
|
||||
|
||||
## Design Rationale (Interview Notes)
|
||||
## Quick Start
|
||||
|
||||
- **Why hybrid (LLM for text, Python for numbers)?**
|
||||
LLMs hallucinate financial figures. Separating concerns — Gemini for narrative, yfinance for numbers — gives the best of both: nuanced qualitative analysis with numerically accurate, auditable quantitative data.
|
||||
### Prerequisites
|
||||
- Python 3.12+
|
||||
- Node.js 18+
|
||||
- [Google Gemini API Key](https://aistudio.google.com/apikey) (for AI features)
|
||||
- Email address for SEC EDGAR fair-access compliance
|
||||
|
||||
- **Why a 5-year 2-stage DCF instead of a simple Gordon Growth model?**
|
||||
A single-stage model lets terminal value dominate the result, which overstates value for high-growth companies. The 2-stage model (Stage 1: projected FCF growth; Stage 2: terminal growth) is closer to how institutional DCF models are built and avoids absurd valuations.
|
||||
### Installation & Launch
|
||||
|
||||
- **Why integrate Damodaran's academic baselines?**
|
||||
Slider defaults anchored to peer-reviewed data (Damodaran sector WACC, US ERP, 10Y risk-free rate) give users a credible starting point. The reference panel links to his data pages so users can verify and critique the assumptions.
|
||||
```bash
|
||||
# Clone the repository
|
||||
git clone https://github.com/shawnkim1997/All-in-one-Financial-Analysis.git
|
||||
cd "All-in-one-Financial-Analysis/atlas-terminal"
|
||||
|
||||
- **Why modular architecture?**
|
||||
Single-file Streamlit apps are fast to prototype but impossible to test, maintain, or extend. Separation of concerns — config, utils, data, ai, views — makes each component independently comprehensible, testable, and replaceable without touching the rest of the system.
|
||||
# ── Backend ──
|
||||
pip install -r requirements.txt
|
||||
PYTHONPATH="." uvicorn server.main:app --port 8000
|
||||
|
||||
- **Why yahooquery as primary (not yfinance)?**
|
||||
yahooquery's bulk query API returns TTM-constructed financials with cleaner column names. yfinance is kept as a fallback for tickers yahooquery misses and for technical/historical price data.
|
||||
# ── Frontend (new terminal) ──
|
||||
cd apps/web
|
||||
npm install
|
||||
npm run dev
|
||||
```
|
||||
|
||||
Open **http://localhost:3000** in your browser.
|
||||
|
||||
Configure your **Gemini API Key** and **SEC EDGAR email** in the Settings page, then search for any ticker (e.g., MSFT, AAPL, GOOGL) to explore.
|
||||
|
||||
---
|
||||
|
||||
## Design System — Terminal Noir
|
||||
|
||||
ATLAS Terminal uses a custom dark theme inspired by professional trading terminals:
|
||||
|
||||
| Token | Value | Usage |
|
||||
|-------|-------|-------|
|
||||
| `bg-primary` | `#0A0A0F` | Main background |
|
||||
| `bg-card` | `#12121A` | Card surfaces |
|
||||
| `bg-elevated` | `#1A1A2E` | Hover states, elevated panels |
|
||||
| `border` | `#2A2A3E` | Borders and dividers |
|
||||
| `accent-green` | `#00D4AA` | Positive values, CTAs, active states |
|
||||
| `accent-red` | `#FF4757` | Negative values, warnings |
|
||||
| `accent-blue` | `#4A9EFF` | Informational badges, links |
|
||||
| `accent-yellow` | `#FFD93D` | Caution, highlights |
|
||||
| `text-primary` | `#E8E8ED` | Primary text |
|
||||
| `text-secondary` | `#A0A0B0` | Secondary text |
|
||||
| `text-muted` | `#6B6B80` | Muted labels |
|
||||
|
||||
---
|
||||
|
||||
## Evolution: Streamlit → Next.js + FastAPI
|
||||
|
||||
This project began as a **Streamlit prototype** (`app.py`, 3,909 lines) and has been fully migrated to a modern full-stack architecture:
|
||||
|
||||
| Aspect | Streamlit (v1-v3) | Next.js + FastAPI (v4) |
|
||||
|--------|-------------------|----------------------|
|
||||
| Frontend | Streamlit widgets | Next.js 14 App Router + Tailwind |
|
||||
| Backend | Embedded in Streamlit | Dedicated FastAPI with 13 routers |
|
||||
| Charts | Plotly (Sankey, Radar) | TradingView Lightweight Charts |
|
||||
| State | `st.session_state` | React hooks + localStorage |
|
||||
| Routing | Tab-based (7 tabs) | File-based (10 pages) |
|
||||
| API | Monolithic | RESTful with OpenAPI docs |
|
||||
| Caching | `@st.cache_data` | SQLite/PostgreSQL persistence |
|
||||
| Deployment | Single process | Frontend + Backend independently scalable |
|
||||
|
||||
The original Streamlit version remains functional at the project root (`app.py`) for reference.
|
||||
|
||||
---
|
||||
|
||||
## Technical Highlights
|
||||
|
||||
### Hybrid AI Architecture
|
||||
Gemini handles **text interpretation only** (MD&A analysis, risk factor extraction, industry outlook). All financial figures come from yfinance/yahooquery — zero hallucination risk on numbers.
|
||||
|
||||
### Multi-Source Data Resilience
|
||||
Primary source (yfinance) with automatic yahooquery fallback. Pipe-separated multi-key column lookups handle naming differences between providers (`"TotalRevenue|Total Revenue|Revenue"`).
|
||||
|
||||
### Quantitative Valuation Suite
|
||||
Five interconnected valuation models — DCF serves as the base, Sensitivity shows assumption impact, Monte Carlo quantifies uncertainty, Tornado ranks variable importance, and Reverse DCF reveals market-implied expectations.
|
||||
|
||||
### SEC EDGAR Integration
|
||||
Full pipeline: `sec-edgar-downloader` → HTML parsing with BeautifulSoup → section extraction (Items 1A, 3, 7, 8, 9A) → local caching → AI summarization via Gemini.
|
||||
|
||||
---
|
||||
|
||||
## Requirements
|
||||
|
||||
- Python 3.9+
|
||||
- [Google API Key (Gemini)](https://aistudio.google.com/apikey)
|
||||
- An email address for SEC EDGAR programmatic access
|
||||
- All Python dependencies in `requirements.txt`
|
||||
- Optional: `.env` with `GOOGLE_API_KEY` and `SEC_EDGAR_EMAIL`
|
||||
See [`atlas-terminal/requirements.txt`](atlas-terminal/requirements.txt) for the full Python dependency list. Key packages:
|
||||
|
||||
- `fastapi`, `uvicorn` — Web framework
|
||||
- `yfinance`, `yahooquery` — Financial data
|
||||
- `google-generativeai` — Gemini AI
|
||||
- `sec-edgar-downloader`, `beautifulsoup4`, `lxml` — SEC filing parsing
|
||||
- `ta` — Technical analysis indicators
|
||||
- `numpy`, `scipy` — Monte Carlo simulation, optimization
|
||||
- `pandas` — Data manipulation
|
||||
|
||||
Frontend: `next`, `react`, `tailwindcss`, `lightweight-charts`
|
||||
|
||||
---
|
||||
|
||||
## How to Run
|
||||
## License & Disclaimer
|
||||
|
||||
```bash
|
||||
# 1. Navigate to project directory
|
||||
cd "/path/to/your/FQDC Project"
|
||||
|
||||
# 2. Activate virtual environment
|
||||
source venv/bin/activate # Mac/Linux
|
||||
# venv\Scripts\Activate.ps1 # Windows PowerShell
|
||||
|
||||
# 3. Install dependencies (first time or when requirements change)
|
||||
pip install -r requirements.txt
|
||||
|
||||
# 4. Launch the app
|
||||
streamlit run app.py --server.port 8501
|
||||
# or: ./run.sh
|
||||
```
|
||||
|
||||
Open **http://localhost:8501** in your browser.
|
||||
|
||||
Set **Google API Key** and **SEC EDGAR Email** in the sidebar. Then search for any company by name (any language) and explore the seven tabs.
|
||||
This project is built for learning, research, and portfolio demonstration purposes. Nothing in this application constitutes investment advice. Comply with [SEC EDGAR policy](https://www.sec.gov/os/webmaster-faq#code-support) when accessing SEC data, and with Google's terms of service for the Gemini API.
|
||||
|
||||
---
|
||||
|
||||
## Update History (Changelog)
|
||||
|
||||
| Date | Update |
|
||||
|------|--------|
|
||||
| **2026-03-19** | **Modular refactoring (v3.0) + SEC filing viewer fix:** (1) **Architecture:** 3,909-line `app.py` refactored into 28 focused modules across `config/`, `utils/`, `data/`, `ai/`, `views/`. Each file under 300 lines. Strict unidirectional dependency graph (no circular imports). All `@st.cache_data` TTLs and `st.session_state` keys preserved identically. (2) **SEC Filing Viewer fixed:** Rebuilt EDGAR fetch chain using `submissions/CIK{cik}.json` → `filings.recent.primaryDocument[]` (replaces deprecated `directory.item` lookup). Added filing type `st.selectbox` (10-K, 10-Q, 8-K, 20-F, 6-K) connected to backend dynamically. Native HTML rendered via `streamlit.components.v1.html()` with injected CSS reset. Errors surfaced explicitly with `st.error()`. (3) **DART links** restored for Korean-listed companies. |
|
||||
| **2026-02-18** | **Market Heatmap & FX charts:** Sector heatmap with 5d/1mo data and per-ticker fallback (weekend/holiday robust). FX Momentum normalized 1Y line chart (GBP/USD, EUR/USD, USD/JPY, KRW). 10-K language toggle (한글/영문) via Gemini translation. plotly/yfinance added to requirements. |
|
||||
| **2026-02-17** | **DART, prefs, run script:** DART fetch timeout 90s; DART report titles in English (cached). SEC & DART per-category iframe viewer. Last selected company persisted in `.app_prefs.json` (survives page refresh). Single run script `run.sh` at port 8501. |
|
||||
| **2025-02-15** | **Multi-currency portfolio & FX:** Per-position currency (USD/GBP/EUR/KRW/JPY/CNY), fractional quantity, FX-adjusted returns. Gemini Vision AI screenshot import (extracts ticker, price, currency, quantity). App-wide `get_currency_for_ticker`, `get_fx_rate`, `format_price_with_usd`. |
|
||||
| **2025-02-14** | **Global company search:** yahooquery `search()` replaces static dropdown. Search by name in any language; filters INDEX/MUTUALFUND; auto-infers .KS/.KQ/.T/.L suffix. |
|
||||
| **2025-02-13** | **Design Rationale & 10Y DCF:** Design rationale section (undergrad automation mindset, 10Y 2-stage DCF, Damodaran integration). Wall Street Assumptions panel (analyst consensus + Damodaran baselines). Smart DCF defaults from Beta/CAPM. |
|
||||
| **2025-02-13** | **Robust data & comps redesign:** Multi-step shares/debt/cash fallback (fast_info → info → balance). Top-down sector analysis with `SECTORS` dict and AI Industry Outlook (Gemini). |
|
||||
| **2025-02-12** | **Hybrid architecture:** Item 7 only to Gemini; yfinance for all numbers. HTML cleansing pipeline (BeautifulSoup + regex). |
|
||||
| **2025-02-12** | **DuPont, Altman Z, Piotroski, sector KPIs, TTM fallback:** Full quantitative financial health suite. Sector-specific metrics (Tech: Rule of 40; Retail: Inventory Turnover; Financials: ROE/ROA). |
|
||||
| **2025-02-12** | **Preference persistence:** "Remember API key & email" checkbox; `.app_prefs.json` (gitignored). |
|
||||
| **2025-01-XX** | **Initial release:** SEC EDGAR 10-K download, Item 7/8 extraction, Gemini analysis, Streamlit UI. |
|
||||
|
||||
---
|
||||
|
||||
## License and Disclaimer
|
||||
|
||||
This project is built for learning, research, and portfolio demonstration. Comply with [SEC EDGAR policy](https://www.sec.gov/os/webmaster-faq#code-support) when accessing SEC data, and with Google's terms of service for the Gemini API. Nothing in this app constitutes investment advice.
|
||||
<p align="center">
|
||||
<sub>Built with ☕ and late nights — <a href="https://github.com/shawnkim1997">@shawnkim1997</a></sub>
|
||||
</p>
|
||||
|
||||
+14
-60
@@ -1,73 +1,27 @@
|
||||
# ATLAS Terminal
|
||||
# ATLAS Terminal — Web Application
|
||||
|
||||
> Personal Bloomberg-style financial terminal -- real-time market data,
|
||||
> AI-powered analysis, DCF valuation, and portfolio management.
|
||||
|
||||
## Features
|
||||
|
||||
- **SEC EDGAR** -- 10-K filing download and section extraction
|
||||
- **AI Analysis** -- Gemini-powered financial statement analysis
|
||||
- **DCF Valuation** -- Single-stage, two-stage, and Excel-style DCF models with Damodaran WACC
|
||||
- **Market Data** -- Live stock quotes, indices, and sector data
|
||||
- **News** -- Financial news aggregation via RSS feeds
|
||||
- **Crypto** -- Top 20 cryptocurrency prices (Bithumb KRW + Binance USD)
|
||||
- **FX** -- Foreign exchange rates and 1-year history via yfinance
|
||||
- **Portfolio** -- Position tracking with P&L and multi-currency support
|
||||
- **Financial Health** -- DuPont analysis, Altman Z-Score, Piotroski F-Score, radar charts
|
||||
|
||||
## Tech Stack
|
||||
|
||||
**Backend:** Python 3.12+, FastAPI, Pydantic v2, yfinance, yahooquery, Google Generative AI, Supabase
|
||||
|
||||
**Frontend:** Next.js 14, TypeScript, Tailwind CSS
|
||||
> Next.js 14 + FastAPI full-stack financial analysis terminal.
|
||||
>
|
||||
> See the [main README](../README.md) for full documentation.
|
||||
|
||||
## Quick Start
|
||||
|
||||
```bash
|
||||
# Backend
|
||||
cd atlas-terminal
|
||||
# Backend (from atlas-terminal/)
|
||||
pip install -r requirements.txt
|
||||
cp .env.example .env # configure API keys
|
||||
uvicorn server.main:app --reload --port 8000
|
||||
PYTHONPATH="." uvicorn server.main:app --port 8000
|
||||
|
||||
# Frontend
|
||||
cd apps/web
|
||||
# Frontend (from atlas-terminal/apps/web/)
|
||||
npm install
|
||||
npm run dev
|
||||
```
|
||||
|
||||
The API will be available at `http://localhost:8000` and the web UI at `http://localhost:3000`.
|
||||
- **Frontend:** http://localhost:3000
|
||||
- **Backend:** http://localhost:8000
|
||||
- **API Docs:** http://localhost:8000/docs
|
||||
|
||||
## Project Structure
|
||||
## Stack
|
||||
|
||||
```
|
||||
atlas-terminal/
|
||||
server/
|
||||
main.py # FastAPI entry point
|
||||
models/ # Pydantic schemas, Supabase client
|
||||
routers/ # API route handlers
|
||||
services/ # Business logic, data fetchers
|
||||
utils/ # safe_float, ticker utilities
|
||||
apps/web/ # Next.js frontend
|
||||
supabase/migrations/ # Database schema
|
||||
tests/ # pytest test suite
|
||||
scripts/ # Automation scripts
|
||||
```
|
||||
|
||||
## API Endpoints
|
||||
|
||||
| Prefix | Description |
|
||||
|------------------|------------------------------------|
|
||||
| `/api/edgar` | SEC EDGAR 10-K filings |
|
||||
| `/api/analysis` | AI-powered financial analysis |
|
||||
| `/api/valuation` | DCF valuation and smart defaults |
|
||||
| `/api/market` | Stock quotes and market overview |
|
||||
| `/api/news` | Financial news feeds |
|
||||
| `/api/crypto` | Cryptocurrency prices |
|
||||
| `/api/fx` | Foreign exchange rates and history |
|
||||
| `/api/portfolio` | Portfolio position management |
|
||||
| `/health` | Liveness probe |
|
||||
|
||||
## License
|
||||
|
||||
Private project.
|
||||
- **Frontend:** Next.js 14, TypeScript, Tailwind CSS, TradingView Lightweight Charts
|
||||
- **Backend:** FastAPI, Python 3.12+, yfinance, yahooquery, Google Gemini
|
||||
- **Database:** SQLite (local) / PostgreSQL (production)
|
||||
|
||||
Reference in New Issue
Block a user