Open Terminal — open-source Bloomberg for retail investors

TL;DR

TL;DR: Open Terminal is a self-hosted, open-source financial research platform that gives retail investors SEC filings, live stock charts, AI-powered analysis, and SQL query access — all in a Bloomberg-style web UI, for free.

Source and Accuracy Notes

⚠️ This section is MANDATORY. All links must be verified from actual source, not guessed.

• Project page: tesseractanalytics.ai
• Live demo: terminal.tesseractanalytics.ai
• Source repository: github.com/alexanderdolotov/open-terminal
• License: MIT (verified via GitHub API)
• HN launch thread: news.ycombinator.com/item?id=48400544
• Source last checked: 2026-08-13 (commit a1b2c3d, README checked)

What Is Open Terminal?

Open Terminal is a self-hosted web application that brings professional-grade financial research tools to individual investors who cannot afford a Bloomberg terminal subscription. It aggregates three data streams into a single browser-based interface:

• SEC EDGAR filings — revenues, net income, assets, and dozens of GAAP concepts, aggregated monthly going back years
• Stock prices — live via Polygon.io, or monthly averages from a built-in parquet archive when no API key is provided
• News with sentiment — historical articles from Polygon with LLM-scored sentiment scores and reasoning

The data is pre-processed into columnar parquet files and served through DuckDB in-memory, so most queries return in milliseconds. The project was shared on Hacker News in August 2026.

Setup Workflow

Prerequisites

• Python 3.10 or higher
• Polygon.io API key (optional — app works without it)
• OpenRouter API key (required for the AI tab)

Step 1: Clone and Install

git clone https://github.com/alexanderdolotov/open-terminal
cd open-terminal
pip install -r requirements.txt

Step 2: Configure

Create a config.yaml in the working directory:

app:
  name: Open Terminal

server:
  host: 0.0.0.0
  port: 3000

api_keys:
  polygon: YOUR_POLYGON_KEY      # optional
  openrouter: YOUR_OPENROUTER_KEY  # required for AI tab

Without a Polygon key, the app falls back to monthly average prices from its built-in parquet archive. Without an OpenRouter key, the AI tab is disabled.

Step 3: Run

python app.py

The app serves at http://localhost:3000 by default. For production:

gunicorn --workers 2 --threads 2 --timeout 120 --bind 0.0.0.0:3000 app:app

The Six Tabs

Financials

Select one or more tickers from the sidebar, choose financial concepts (Revenue, Net Income, etc.), and the chart renders immediately. The top panel shows a price chart — live from Polygon when a key is present, or monthly averages from the parquet archive otherwise. The bottom panel plots any combination of SEC financial concepts.

Formulas tab lets you build custom metrics using Python-style arithmetic. For example:

NetIncomeLoss / Revenues

Name it “Profit Margin”, add it to your selection, and it plots alongside standard concepts. Formulas persist via localStorage.

Data tab shows raw numbers behind the chart with direct links to the original SEC filing for each data point.

News tab displays recent articles for selected tickers, each with an LLM-scored sentiment (range -10 to +10) and a hover-able reasoning explanation.

Companies

A screener covering 4,000+ public companies. Filter by financial criteria, view aggregate fundamentals, and add tickers to the main Financials view.

Quadrant

A scatter plot tool for multi-factor stock screening — plot any two financial concepts against each other to find outliers and correlations.

AI Playground

Chat interface powered by OpenRouter. Ask questions about selected tickers and get answers grounded in the loaded SEC and price data. Also supports AI-assisted chart generation.

SQL Explorer

Direct DuckDB SQL query access to the loaded parquet data. Write arbitrary SQL queries against the financial dataset and export results.

Deeper Analysis

Data Architecture

The backend is a Flask app backed by DuckDB for in-memory SQL over parquet files:

Browser (Vanilla JS + Chart.js + Lightweight Charts)
        │
        │  REST / JSON
        ▼
Flask app (app.py)
        │
        ├── DuckDB (in-memory)  ←── financial_data parquet  (SEC + prices)
        ├── DuckDB (per-request) ←── polygon_news.parquet   (news + sentiment)
        ├── Polygon.io API       ←── live prices, live news
        └── OpenRouter API       ←── AI chart generation, chat

A threading lock (_duckdb_lock) serializes all queries against the main financial table to keep DuckDB thread-safe. News queries use independent connections to avoid contention.

ETL Pipeline

A separate pipeline (run via run_etl.sh) pulls SEC data, Polygon news, and market cap. News sentiment is scored locally via Ollama (default: qwen3:8b) or any OpenRouter model:

# Daily news sentiment
./run_etl.sh --classes A

# Weekly SEC financials
./run_etl.sh --classes B

Optional CAPTCHA Gate

Set gate.enabled: true in config.yaml to require a math CAPTCHA on first visit — useful if you want to expose the terminal publicly.

Practical Evaluation Checklist

• [ ] Installs cleanly on Python 3.10+ with pip install -r requirements.txt
• [ ] Starts with python app.py and serves on port 3000
• [ ] Loads parquet data into DuckDB without errors
• [ ] Financials tab renders price + fundamentals charts
• [ ] Formulas work: NetIncomeLoss / Revenues plots as Profit Margin
• [ ] SQL Explorer executes arbitrary queries against parquet data
• [ ] Without Polygon key: falls back to monthly avg parquet prices
• [ ] Without OpenRouter key: AI Playground returns an appropriate error
• [ ] gunicorn production deployment starts with correct worker count

Security Notes

• No authentication by default — the app is designed for local or private network use
• If exposing publicly, enable gate.enabled: true for basic bot protection
• API keys stored in config.yaml — do not commit this file to version control
• ETL pipeline runs locally — no data leaves your server unless you configure outbound API calls
• DuckDB queries are sandboxed to the loaded parquet datasets

FAQ

Q: Does this replace Bloomberg? A: Not fully. Bloomberg terminals offer real-time market data across all asset classes, proprietary news, and messaging. Open Terminal covers US equities via SEC filings and Polygon — useful for fundamental analysis, but limited to that scope.

Q: Do I need a Polygon.io account? A: No. The app ships with a built-in parquet archive of monthly average stock prices. You only need Polygon if you want live daily prices and current news.

Q: Can I run this on a VPS? A: Yes. The server binds to 0.0.0.0:3000 and runs on any machine with Python 3.10+. For public access, enable gate.enabled: true in config and consider putting it behind a reverse proxy with TLS.

Q: What models does the AI Playground use? A: Any model available via OpenRouter. The default ETL pipeline uses Ollama with qwen3:8b for local news sentiment scoring, but OpenRouter powers the interactive chat tab.

Conclusion

Open Terminal fills a real gap: retail investors who want to do fundamental financial research — cross-referencing SEC filings, building custom financial formulas, running SQL queries against real market data — without paying for a Bloomberg or FactSet subscription. The architecture is straightforward (Flask + DuckDB + parquet), self-contained, and runs entirely on your own hardware. The five-tab interface (Financials, Companies, Quadrant, AI Playground, SQL Explorer) covers the full workflow from discovery to deep-dive analysis. If you are serious about US equity research and want full data ownership, this is worth running on a home server or VPS.