DEV Community

Cover image for Building an Open-Source Market Signal Bot Using Airtel’s Free Perplexity Pro API Access
Prakash Pawar
Prakash Pawar

Posted on

Building an Open-Source Market Signal Bot Using Airtel’s Free Perplexity Pro API Access

Airtel’s 1-year Perplexity Pro offer includes full API access to the sonar-pro model. Instead of using it only for search, I used the free API credits to build an open-source real-time market signal bot that monitors price action, filters noise using LLM reasoning, and sends actionable alerts to Telegram.

The entire system runs on simple components but produces high-signal outputs suited for active traders.


🧱 System Architecture

1. Price Feed (Finnhub)

The bot polls Finnhub’s /quote endpoint for:

  • US stocks
  • Crypto pairs (e.g., BINANCE:BTCUSDT)

Only symbols with >|1.5%| intraday movement move forward.

2. LLM-Based Market Reasoning (Perplexity)

Filtered snapshots are sent to Perplexity’s sonar-pro via:

https://api.perplexity.ai/chat/completions
Enter fullscreen mode Exit fullscreen mode

The prompt instructs the model to return structured JSON:

  • should_alert: true/false
  • concise reason
  • sentiment classification (bullish, bearish, unclear)

This replaces custom heuristics with dynamic context-aware filtering.

3. Alert Formatting

Signals are composed into a short Telegram-friendly message with sentiment emojis.

4. Telegram Push Delivery

Alerts are delivered instantly using Telegram Bot API.


🔄 Core Processing Loop

FETCH prices
→ FILTER >1.5% movers
→ ANALYZE using Perplexity (JSON output)
→ FORMAT alerts
→ SEND to Telegram
Enter fullscreen mode Exit fullscreen mode

This creates a low-overhead 24/7 signal layer driven entirely by free API credits.


🧪 Code Overview (Repository Ready)

Your bot contains four main functions:

  • get_latest_price() → real-time quotes
  • analyze_trends_with_perplexity() → LLM signal classification
  • format_alert_message() → compact alert formatting
  • send_telegram_message() → asynchronous delivery

The main loop continuously aggregates movement, analyzes it, and pushes signals.


⚡ Why This Made Productive Use of Airtel’s Free Perplexity Pro

  • Zero-cost LLM inference for market reasoning
  • No need for ML models or rule-based systems
  • LLM filters out noise, preventing alert spam
  • Open-source and easy to deploy (just env vars + Python)
  • Works for both crypto and equities

Instead of just using Perplexity Pro for normal search, the API became the intelligence layer of a real-time signal engine.


Github: link

📦 What should we add next?

  • Volume spike detection
  • Multi-timeframe trend scoring
  • News + price combined signals
  • Discord & Slack integrations
  • Web dashboard for recent alerts

If you have any Query regarding this post let me know in comment or Tweet me. thank you for reading this.

Top comments (0)