NeoTrade

A trading cockpit for Indian equities and F&O. A strategy engine watches a universe of instruments and emits fully-formed trades — size, entry reference, stop, target, the rule codes that fired, and a composite score — then either executes them (intraday) or routes them to an approval inbox (long-term). Each user connects their own broker account and chooses per strategy whether it trades on paper or with real money.

The defining constraint: the AI contribution to any trade's conviction is capped at 30% and cannot rescue a trade the rules did not already support. That cap is enforced in the type system, not by convention.

Documentation

Question	Document
What is this product, who uses it, what states matter?	PRODUCT.md
How does the code work, and where is it going?	frontend/src/handbook/ (also in the app at /system, admin-only)
What gets built next?	docs/ROADMAP.md
Visual system	DESIGN.md

Features

• Rule strategy engine — intraday and long-term strategies emitting scored, sized trade intents; new strategies plug into a registry.
• Composite scoring with a hard AI ceiling — rule conviction decides; the LLM can adjust within 30% and never below the rule floor.
• Risk-aware sizing — position size derived from account size, per-trade risk, and stop distance, with exposure limits; never computed inside a strategy.
• Approval inbox — long-term proposals wait for an explicit approve/reject and expire after three days; intraday proposals execute automatically.
• Backtesting — strategies replay through the same runner and execution simulator used live, with Indian transaction costs modelled.
• Research and chat — news/sentiment analysis and a tool-using assistant, both through a self-hosted OmniRoute LLM gateway.
• Live market data over WebSocket, with explicit live/stale/market-closed states.

Tech stack

Backend — FastAPI (Python 3.11+), MongoDB (motor), Redis, pandas/numpy for the indicator toolkit, yfinance and Zerodha Kite Connect for market data, LangChain/LangGraph for the research and chat agents, pytest for tests.

Frontend — React 19 + Vite (plain JSX), Tailwind v4, React Router 7, recharts, framer-motion, axios.

Infrastructure — Docker Compose on an Oracle Cloud VM behind Nginx + Let's Encrypt for the backend; Vercel for the frontend. Both push-to-deploy from main.

Setup

Docker (recommended)

git clone https://github.com/kushgarg132/NeoTrade.git
cd NeoTrade
# create .env with the values below, then:
docker compose up -d --build backend

MongoDB and Redis are external (managed) services, not compose containers — point MONGODB_URL and REDIS_URL at them. Also required: GOOGLE_CLIENT_ID, JWT_SECRET, CORS_ALLOWED_ORIGINS, and OMNIROUTE_API_KEY + OMNIROUTE_BASE_URL for anything using the LLM. KITE_API_KEY/KITE_API_SECRET are optional — the app treats an unconfigured broker as a normal state, not an error.

The frontend is served by Vercel; compose runs only backend and ingest.

Manual

# backend (needs Mongo and Redis reachable)
cd backend
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
uvicorn server:app --reload --port 8001

# frontend
cd frontend
npm install
npm run dev

Tests

cd backend && python -m pytest

Project structure

backend/
├── strategies/      # rule strategies (intraday, longterm) + registry
├── scoring/         # composite score, AI cap, rule floor
├── engine/          # runner, sizing, portfolio, execution, backtest, persistence
├── suggestions/     # approval inbox: store, sink, scan, service
├── auth/            # Google sign-in, JWT, refresh tokens, Kite session
├── data/            # market data providers and feeds
├── components/      # analyst/chat agents, shared models, risk rules
├── research/        # LangGraph research agent
├── routers/         # FastAPI endpoints
└── tests/

frontend/src/
├── pages/           # Dashboard, Suggestions, Portfolio, Trading, Watchlist, Scanner, Settings
├── components/      # layout + UI
├── context/         # auth state
└── utils/           # axios instance, interceptors, endpoints

API documentation

With the backend running: Swagger at /api/v1/docs, ReDoc at /api/v1/redoc.