kundli-ai 0.1.1

Vedic astrology engine with predictions and insights

🔮 Kundli AI — Vedic Astrology Engine

A powerful, production-ready Vedic astrology engine built in Python. Generate accurate Kundli charts, planetary positions, dashas, yogas, and human-like interpretations — all without external APIs.

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✨ Features

• 🪐 Accurate planetary calculations using Swiss Ephemeris
• 🏠 Whole sign house system
• 🔁 Vimshottari Dasha system (Mahadasha + Antardasha)
• 🧘 Yoga detection (Raj Yoga, Vipreet Raj Yoga, Exalted planets, etc.)
• 🧠 Intelligent interpretation engine
• 📜 Human-like narrative reports
• ⚡ Fast, offline, no API dependency

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📦 Installation

pip install kundli-ai

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⚙️ Setup (Important)

This library requires Swiss Ephemeris data files.

Step 1: Download ephemeris files

Download from: https://www.astro.com/ftp/swisseph/ephe/

Step 2: Set ephemeris path

from kundli import set_ephemeris_path

set_ephemeris_path("path/to/ephe")

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🚀 Quick Start

from kundli import generate_kundli, set_ephemeris_path

set_ephemeris_path("./ephe")

data = {
    "datetime": "1995-08-15T10:30:00",
    "lat": 19.0760,
    "lon": 72.8777
}

result = generate_kundli(data)

print(result["ascendant"])
print(result["planets"])
print(result["interpretation"]["summary"])
print(result["report"]["text"])

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📊 Sample Output

{
  "ascendant": {
    "longitude": 250.054,
    "rashi": "Sagittarius"
  },
  "interpretation": {
    "summary": "You are running Mercury Mahadasha and Jupiter Antardasha.",
    "yogas": ["Vipreet Raj Yoga", "Mars Exalted"],
    "insights": [
      "Mars in house 9 influences luck, dharma, and higher learning..."
    ]
  }
}

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🧠 What You Get

🔹 Kundli Data

• Ascendant (Lagna)
• 12 Houses
• Planetary Positions (Rashi + Nakshatra)

🔹 Dasha System

• Current Mahadasha
• Current Antardasha
• Full Dasha Timeline

🔹 Interpretations

• Planet + House insights
• Strength analysis (Exalted / Debilitated)
• Yogas detection
• Aspects between planets

🔹 AI-like Narrative Report

• Human-readable astrology explanation
• Structured sections for clarity

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🧩 API Reference

generate_kundli(data: dict)

Input:

{
  "datetime": "YYYY-MM-DDTHH:MM:SS",
  "lat": float,
  "lon": float
}

Output:

{
  "ascendant": {...},
  "houses": [...],
  "planets": {...},
  "planet_house_mapping": {...},
  "dasha": {...},
  "interpretation": {...},
  "report": {...}
}

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⚠️ Important Notes

• Ephemeris files are required for accurate calculations
• Results depend on correct date, time, and location
• This library uses sidereal astrology (Lahiri ayanamsa)

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🛠 Development

Clone the repo:

git clone https://github.com/rudranarayan-spec/kundli-python-npm
cd kundli-python-npm
pip install -e .

Run locally:

python main.py

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🧪 Testing

python -m build
pip install dist/*.whl

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🚀 Roadmap

• 🔮 Prediction engine (career, marriage timing)
• 📅 Transit analysis (Gochar)
• 🌐 API service (SaaS version)
• 📦 NPM package (JavaScript support)
• 🤖 Optional AI-powered narratives

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🤝 Contributing

Contributions are welcome! Feel free to open issues or submit pull requests.

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📄 License

MIT License

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⭐ Support

If you find this project useful, consider giving it a star ⭐ It helps others discover the project.

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👨‍💻 Author

Built with precision and passion for astrology + engineering.