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AI Trading BotNIFTY 50BANK NIFTYCrypto

Building a Production-Grade AI Trading Bot for Indian Markets (NIFTY 50, BANK NIFTY, Crypto)

A production-grade trading system needs more than signals. It needs streaming data, broker-safe execution, risk boundaries, auditability, and a clean path from paper trading to live capital.

Architecture

System Overview

Prabhat's trading bot architecture is built around a FastAPI backend, WebSocket-powered dashboard, Claude AI analysis layer, broker connectors, and a risk management service that guards every order before it reaches the market.

The system supports NIFTY 50, BANK NIFTY, SENSEX, Gold, Silver, Crude Oil, and Crypto instruments, with separate adapters for Zerodha Kite Connect and Binance.

+------------------+      +--------------------+      +-------------------+
| Market Data Feed | ---> | FastAPI Core Engine | ---> | Risk Manager      |
| Kite + Binance   |      | Signals + WebSocket |      | Limits + Kill Sw. |
+------------------+      +--------------------+      +---------+---------+
         |                         |                             |
         v                         v                             v
+------------------+      +--------------------+      +-------------------+
| Claude AI Layer  |      | Realtime Dashboard |      | Order Execution   |
| Context Analysis |      | PnL + Positions    |      | Paper -> Live     |
+------------------+      +--------------------+      +-------------------+
                                      |
                                      v
                         +--------------------------+
                         | Telegram + WhatsApp      |
                         | Alerts + Trade Reports   |
                         +--------------------------+

Realtime Dashboard and AI Analysis

The WebSocket dashboard streams positions, order state, live PnL, drawdown, model confidence, and risk flags without forcing traders to refresh.

Claude AI can summarize market context, detect regime shifts, explain why a setup is risky, and generate a plain-English trade journal after execution.

Live positions and realized or unrealized PnL

Instrument-level risk limits

AI market context and setup validation

Telegram and WhatsApp notifications

Paper Trading to Live Trading Flow

The execution layer treats paper trading and live trading as two modes behind the same order interface. A strategy can be tested with simulated fills, then promoted to live execution only after risk rules, sizing, and daily loss limits are proven.

Examplepython
class ExecutionMode(str, Enum):    PAPER = "paper"    LIVE = "live"async def place_order(signal: TradeSignal, mode: ExecutionMode):    risk_result = await risk_manager.validate(signal)    if not risk_result.allowed:        return TradeDecision(status="blocked", reason=risk_result.reason)    if mode == ExecutionMode.PAPER:        return await paper_broker.simulate(signal)    return await kite_or_binance.place_order(signal)

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Build production-grade backend systems, AI workflows, cloud automation, and high-signal engineering products with a developer who ships from architecture to deployment.

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