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A simple example package

Project description

shivamprasad

Identity Toolkit & Engineering Framework
Built by Shivam Prasad | AI/ML Engineer

PyPI version Python 3.10+ License: MIT

🚀 Overview

shivamprasad is a personal engineering framework and identity package. It serves as a central registry for my tools, improved workflows, and experimental modules in:

  • Large Language Models (LLMs) & NLP
  • Multi-Agent Systems
  • Computer Vision
  • PyTorch Training Pipelines
  • Desktop Automation

Includes a hacker-style terminal introduction and system status check.

📦 Installation

pip install shivamprasad

💻 Usage

Run the identity matrix and system check directly from your terminal:

# Recommended way
python -m shivamprasad

Or via Python shell:

import shivamprasad

shivamprasad.hello()

🔧 Features

  • Cross-Platform: Works smoothly on Windows (CMD/PowerShell), Linux, macOS, and Termux (Android).
  • Zero Dependencies: Core identity module is pure Python.
  • System Check: visualizing active modules and environment status.

👨‍💻 About

I am Shivam Prasad, an AI and Machine Learning Engineer with a strong focus on building practical, real-world intelligent systems. My work spans Large Language Models (LLMs), Natural Language Processing, multi-agent architectures, computer vision, and PyTorch-based training pipelines. I am particularly interested in systems that combine reasoning, automation, and learning to solve meaningful problems beyond academic demos.

I approach AI as an engineering discipline, not just model experimentation. My projects emphasize clean architecture, reproducibility, and deployability—whether it is a desktop AI assistant, a RAG-based document intelligence system, or an object detection pipeline. I enjoy working close to the system level, integrating models with operating systems, APIs, and real user workflows.

I actively contribute to open-source and maintain personal frameworks that evolve alongside my learning, including tools for intent detection, agent orchestration, and automation. I believe sustainable progress in AI comes from responsible design, system thinking, and long-term maintainability, not shortcuts. My goal is to grow into a builder of intelligent infrastructure that scales with both technology and human needs.


Build intelligently. Scale responsibly.

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