live-feed

name	live-feed
description	Set up real-time indicator computation on live WebSocket market data. Streams LTP/Quote/Depth and computes indicators in real-time with optional Plotly live charting.
argument-hint	[symbol] [exchange] [mode]
allowed-tools	Read, Write, Edit, Bash, Glob, Grep, AskUserQuestion

Create a real-time indicator feed using OpenAlgo WebSocket streaming.

Arguments

Parse $ARGUMENTS as: symbol exchange mode

• $0 = symbol (e.g., SBIN, RELIANCE, NIFTY). Default: SBIN
• $1 = exchange (e.g., NSE, NSE_INDEX). Default: NSE
• $2 = mode (e.g., ltp, quote, depth, multi). Default: quote

If no arguments, ask user for symbol and what data they want.

Instructions

1. Read the indicator-expert rules, especially:
   • rules/websocket-feeds.md — WebSocket connection and subscription
   • rules/data-fetching.md — Historical data for buffer initialization
2. Create charts/live/ directory (on-demand)
3. Create {symbol}_live_feed.py
4. Use the template from rules/assets/live_feed/template.py

Feed Types

ltp — Last Traded Price + Indicators

• Subscribe to LTP feed
• Maintain rolling buffer (last 200 ticks)
• Compute EMA, RSI on buffer
• Print real-time indicator values

quote — Full Quote + Indicators

• Subscribe to Quote feed
• Display OHLC + LTP + Volume
• Compute indicators on close buffer
• Color-coded output (bullish/bearish)

depth — Market Depth Analysis

• Subscribe to Depth feed
• Display L5 bid/ask book
• Compute bid-ask spread, order imbalance
• Show total buy vs sell quantity

multi — Multi-Symbol Feed

• Subscribe to multiple symbols
• Display watchlist table with LTP and key indicator
• Auto-refresh display

Script Structure

"""
Real-Time Indicator Feed for {SYMBOL}
Mode: {mode}
"""
import os
import time
import numpy as np
from datetime import datetime, timedelta
from dotenv import find_dotenv, load_dotenv
from openalgo import api, ta

load_dotenv(find_dotenv(), override=False)

SYMBOL = "{symbol}"
EXCHANGE = "{exchange}"

client = api(
    api_key=os.getenv("OPENALGO_API_KEY"),
    host=os.getenv("OPENALGO_HOST", "http://127.0.0.1:5000"),
    verbose=1,
)

# Pre-fetch historical data for buffer initialization
df = client.history(
    symbol=SYMBOL, exchange=EXCHANGE, interval="1m",
    start_date=(datetime.now() - timedelta(days=1)).strftime("%Y-%m-%d"),
    end_date=datetime.now().strftime("%Y-%m-%d"),
)
close_buffer = list(df["close"].values[-200:])

instruments = [{"exchange": EXCHANGE, "symbol": SYMBOL}]

def on_data(data):
    ltp = data["data"].get("ltp")
    if ltp is None:
        return

    close_buffer.append(float(ltp))
    if len(close_buffer) > 200:
        close_buffer.pop(0)

    if len(close_buffer) >= 20:
        arr = np.array(close_buffer, dtype=np.float64)
        ema_val = ta.ema(arr, 20)[-1]
        rsi_val = ta.rsi(arr, 14)[-1] if len(arr) >= 15 else float("nan")

        timestamp = datetime.now().strftime("%H:%M:%S")
        print(f"[{timestamp}] {SYMBOL} LTP:{ltp:>10.2f} | "
              f"EMA(20):{ema_val:>10.2f} | RSI(14):{rsi_val:>6.2f}")

# Connect and subscribe
client.connect()
client.subscribe_ltp(instruments, on_data_received=on_data)

print(f"Streaming {SYMBOL} on {EXCHANGE} — Press Ctrl+C to stop")
try:
    while True:
        time.sleep(1)
except KeyboardInterrupt:
    print("Stopping feed...")

client.unsubscribe_ltp(instruments)
client.disconnect()

Cleanup

The script must:

• Handle Ctrl+C gracefully
• Unsubscribe from all feeds
• Disconnect WebSocket
• Print summary of session duration and bars processed

Verbose Levels

Inform user about verbose options:

• verbose=0: Silent mode (errors only)
• verbose=1: Connection and subscription logs
• verbose=2: All data updates (debug mode)

Example Usage

/live-feed SBIN NSE ltp /live-feed NIFTY NSE_INDEX quote /live-feed SBIN NSE depth /live-feed multi NSE