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nihal-5/README.md

Nihal Veeramalla

AI/ML Engineer building intelligent agent systems and production AI applications.

Recent Work

Building multi-agent collaboration systems with AutoGen, LangGraph, and CrewAI. Focus on production deployments and real-world applications.

Projects

Multi-Agent Systems

AutoGen Multi-Agent Collaboration
4 specialized agents working as a team with real-time dashboard. Built with Microsoft AutoGen - agents actually debug each other's code which is pretty cool to watch.

AI Trading Simulation
Multi-agent trading where 4 traders compete using different strategies. Testing GPT-4, Gemini, and Deepseek against each other on real market data. Fun to see how different models approach the same trades.

LangGraph Task Assistant
Autonomous agent that handles web browsing and code execution. Built with LangGraph's state machine approach. Uses self-evaluation to improve results.

CrewAI Research Assistant
Multi-agent research system with specialized researcher, fact-checker, and writer roles. CrewAI's hierarchical structure makes agent collaboration cleaner.

Computer Vision

Real-time Video Analytics
Ask questions about live video in natural language. Works with YouTube streams, webcams, and video files. Real-time object detection and scene understanding.

Product OCR Pipeline
YOLO + OCR for extracting nutrition facts, barcodes, and product images from packaging. Automates tedious e-commerce data entry.

Automation

Email & WhatsApp MCP
Automated job application system using Model Context Protocol. Detects job postings, generates tailored resumes, sends WhatsApp notifications.

Tech Stack

Frameworks: AutoGen, LangGraph, CrewAI, LangChain
Languages: Python, TypeScript, JavaScript
ML/AI: PyTorch, TensorFlow, Scikit-learn, Transformers
APIs: OpenAI, Gemini, Deepseek, Brave Search
CV: OpenCV, YOLO, COCO-SSD, EasyOCR
Backend: FastAPI, Node.js, Express
Tools: Docker, Git, Jupyter, NumPy, Pandas

Current Focus

Multi-agent collaboration systems with tool calling and Model Context Protocol (MCP) integration. Researching agentic workflows, function calling patterns, and agent-to-agent communication architectures.

Contact

LinkedIn • GitHub • [email protected]

Building agents that actually work in production.

Pinned Loading

  1. ai-trading-simulation ai-trading-simulation Public

    Multi-agent AI trading simulation with GPT-4, Gemini & Deepseek. 4 autonomous traders competing with different strategies.

    Python

  2. autogen-collaborative-ai-agents autogen-collaborative-ai-agents Public

    Real-time multi-agent AI collaboration system with 4 specialized agents (Researcher, Coder, Reviewer, Synthesizer). Features live web dashboard, code execution, web search, stock/weather APIs, and …

    Python

  3. automatic-product-creator-pos-erp automatic-product-creator-pos-erp Public

    OCR + YOLO pipeline for extracting Nutrition Facts, Barcodes, and Product Hero images

    Python

  4. autonomous-task-assistant autonomous-task-assistant Public

    AI agents that autonomously completes tasks using web browsing, code execution, and self-evaluation - Built with LangGraph

    Python

  5. My-Email-MCP My-Email-MCP Public

    AI-powered email and WhatsApp automation system with intelligent job posting detection, resume generation, and approval workflow using Model Context Protocol (MCP)

    TypeScript

  6. video-query video-query Public

    Real-time video analytics with AI - Natural language queries for YouTube, webcam, and video files

    TypeScript