Trading Journal AI

A trading journal that runs on your own machine. Import your broker's CSV and it rebuilds your round-trip trades, tracks the numbers that matter (win rate, profit factor, expectancy, drawdown, MFE/MAE, exit efficiency), and, if you want it to, uses Claude to read your trading diary and grade your days on process.

• Your data stays on your computer. One SQLite file, no account, no telemetry.
• The numbers are not AI. Trade grouping, P&L, fees and statistics are plain code with tests. AI is an optional coaching layer on top.
• Stocks, options and futures, with partial fills, scale-ins and shorts grouped automatically.
• Thinkorswim and Interactive Brokers importers, plus a template for any other broker.
• Free and MIT licensed. No paid tier.

Quick start · Watch the walkthrough · Releases · Privacy

What this is not: Not financial advice. Not a signal service. Every screenshot below is the synthetic demo seed, not anyone's real trades.

Privacy and your data

Trading Journal AI is designed as a local-first application.

Your trading journal database, imported broker data, notes, and uploaded files are stored locally on your computer. Trading Journal AI does not require an account and does not include telemetry or analytics that send your usage data back to the project. The backend listens on localhost only.

What stays local

• Your trading database
• Imported broker CSV files
• Trade history and performance data
• Journal entries and notes
• Uploaded diary files and images
• Application settings

Optional external services

Some features use third-party APIs and are completely optional.

Claude / Anthropic

When you use AI analysis or the Brain assistant, the information required to answer your request may be sent to Anthropic's API. This can include trade information, journal context, or images you explicitly ask the AI to analyze.

The core journal, trade reconstruction, P&L calculations, reports, and statistics do not require Claude.

Market data (Alpaca)

If you add Alpaca keys, the trade chart asks Alpaca for price bars: the ticker and the date range, nothing about your trades or account.

API keys

API keys are configured locally and should never be committed to GitHub.

Do not share or commit:

• .env files
• API keys or secrets
• Local database files
• Raw broker statements containing personal information
• Screenshots containing account numbers or other sensitive financial information

The repository's .gitignore is configured to exclude common local data and credential files.

Deterministic calculations

AI is not used to calculate your trading results.

Trade reconstruction, P&L, commissions, statistics, and other core trading calculations are handled by deterministic application code. AI features are an optional analysis and coaching layer on top of those calculations.

What's inside

• Dashboard: your net P&L over a live equity curve (hover it for any day's running balance), every session in the period as a single strip you can scrub, measures against your own goals, the month beside your recent trades and open positions, and a tabbed breakdown by time of day, day of week and strategy
• Trade View: every trade with executions, playbook setup tags, MFE/MAE and exit efficiency, its AI analysis and an intraday chart with your fills on it
• Reports: breakdowns by day of week, time of day, hold time, setup, grade, symbol, side, emotion, plus a Sources & Tags tab that scores where your ideas come from. One switch flips the whole page between bars and full numeric tables, and rows under ten trades are marked thin so a one-trade strategy at 100% cannot sit at the top
• Diary: upload handwritten notes, screenshots, or typed text; Claude extracts strategy, stops, R-multiples, emotional state, and mistakes, and matches them to your actual trades
• Day Review: the session drawn as one picture, running P&L from the open to the close with every trade marked where you entered it, plus an AI coaching report graded on process rather than P&L. Each trade's grade carries the reason it was given
• Brain: a chat that answers questions against your full trading history
• Settings: the name library. Strategies, sources and tags in one place, with rename, merge and delete. Merging rewrites every trade that used the old name and remembers it, so the next diary analysis that produces the duplicate saves it under the name you kept
• Import: Thinkorswim account statement CSV and Interactive Brokers (IBKR) Activity Statement CSV, with a broker dropdown (auto-detect by default). Any other broker imports through a generic CSV template, one row per fill

Screenshots

Trade View. Every trade with its executions, MFE/MAE and exit efficiency, the realized R, and the setup you tagged. Click any row to open the full trade.

Trade Details. The executions on one trade, the planned and realized R, the stop and target you wrote before entry, and an intraday chart with your fills marked on it. Charts open on the trade day's session; the legend entries switch layers on and off.

Day Review. The session as one picture: running P&L from the open to the close with every trade marked where you entered it. The day's measures sit under it, each set against your all-time figure: win rate, profit factor, average win, average per trade against your expectancy, exit efficiency, and how much was given back from the session high. Underneath, an AI coaching report graded on process rather than P&L, which reads your trades and your diary together and is willing to tell you a profitable day was badly run.

Reports. Equity curve, drawdown against the running peak, and breakdowns by setup, timing, execution, symbol, source, tag and psychology.

Settings. The vocabulary the journal uses. Rename a strategy, merge two that mean the same thing, or delete one and reassign its trades.

Watch the walkthrough

A full tour of the app, an install from an empty folder, and three prompts that change it while the camera is running. Every prompt used in the video is in the video description, ready to paste.

Quick start

Requirements: Python 3.11+ and Node.js 18+ (the current LTS is recommended).

Windows, two steps: download or clone the repo, then double-click

1. setup.bat, once. It creates the Python environment, installs everything and creates backend\.env for your optional keys.
2. launch.bat, every time. Then open http://localhost:3010

Manual setup (Mac, Linux, or if you prefer):

# 1. Python environment + backend dependencies
python -m venv .venv
.venv\Scripts\activate         # Windows (source .venv/bin/activate on Mac/Linux)
pip install -r backend/requirements.txt

# 2. Frontend dependencies
cd frontend
npm ci
cd ..

# 3. Run both (Windows; launch.bat picks up .venv automatically)
launch.bat

launch.bat starts the FastAPI backend on http://localhost:8010 and the React frontend on http://localhost:3010. On Mac/Linux run them manually: python -m uvicorn main:app --reload --port 8010 from backend/, and PORT=3010 npm start from frontend/.

To run them on other ports, tell each side about the other: REACT_APP_API_URL for the frontend, and, only if the frontend is not on localhost, FRONTEND_ORIGINS (comma separated) for the backend's CORS allow list. Any localhost port is accepted without configuration.

Every install starts empty: no accounts, no trades, no demo data. Add your first account in the app, then import your broker's statement on the Import page.

Updating to a new release

Your trades live in backend/trading_journal.db and your keys in backend/.env. Neither is part of a release, so an update never touches them. New tables are created on the first start and nothing existing is rewritten.

If you cloned with git:

git pull
pip install -r backend/requirements.txt   # only if requirements changed
cd frontend && npm install && cd ..       # only if package.json changed
launch.bat

If you downloaded the ZIP: unzip the new version into a new folder, then copy your two files across before starting it:

copy old-folder\backend\.env               new-folder\backend\.env
copy old-folder\backend\trading_journal.db new-folder\backend\trading_journal.db

Then run npm install in frontend/ once and start it with `launch.bat