Agentic AI
langgraph-research-agent
Autonomous multi-step research agent built with LangGraph. Plans a research strategy, fans out parallel web searches, extracts and synthesizes findings, and produces a cited markdown report without human intervention.
- LangGraph state machine with self-correction loop
- Parallel sub-question search via concurrent fan-out
- Structured Pydantic output at every node
LangGraph
LangChain
GPT-4o
FastAPI
Pydantic v2
MCP
mcp-tools-hub
A collection of production-ready MCP (Model Context Protocol) tool servers for AI agents โ web search, HTTP fetch, file ops, SQLite queries, sandboxed code execution, and persistent agent memory.
- 6 plug-and-play MCP servers built with FastMCP
- Ready for Claude Desktop and any MCP-compatible agent
- Input validation via Pydantic on every tool
MCP
FastMCP
Claude Desktop
Pydantic v2
Python
RAG
rag-over-anything
Flexible RAG pipeline that ingests PDFs, web pages, markdown, and YouTube transcripts, indexes them with hybrid retrieval, and answers questions with cited responses. CLI and FastAPI interface included.
- Hybrid retrieval: dense vector + BM25 with RRF fusion
- Cross-encoder reranking for precision
- Every claim traced back to its source chunk
RAG
LangChain
ChromaDB
BM25
FastAPI
Multi-Agent
multi-agent-debate
LLM agents argue opposing sides of any topic across multiple rounds, then a judge agent scores both sides on factual accuracy, logic, and persuasiveness and declares a winner with reasoning.
- Configurable rounds with rebuttal memory per agent
- Structured judge verdict via Pydantic output schema
- Rich terminal output for readable debate transcripts
Multi-Agent
LangChain
GPT-4o
Pydantic v2
Rich
LLM Evaluation
llm-eval-kit
Lightweight evaluation toolkit for LLM applications. Measures faithfulness, answer relevance, context precision, and semantic drift. Runs as a pytest suite in CI and generates HTML reports with pass/fail verdicts.
- Metrics built from scratch, no vendor eval API required
- Semantic drift detection via embedding baseline comparison
- Pytest integration with assert_metric() helpers
LLM Evaluation
LLMOps
sentence-transformers
pytest
Python
MLOps
mlops-starter
A minimal, complete MLOps setup wiring experiment tracking, model registry, containerized serving, automated validation, and CI/CD together. A ready-to-clone starting point for any production ML project.
- MLflow tracking + model registry with promotion gates
- FastAPI model server with Pydantic request/response schemas
- GitHub Actions CI/CD: test, train, validate, deploy
MLflow
Kubernetes
Docker
FastAPI
GitHub Actions
Robotics / CV
AI4All
Hand gesture mimicking system and course notebooks built for the AI4ALL program at University of Maryland. Explores human-robot interaction through real-time gesture recognition.
Python
OpenCV
PyTorch
ROS
Robotics / CV
NASA Swarmathon
Cooperative multi-robot system built for the NASA Swarmathon challenge. Robots collaboratively search and collect resources using swarm intelligence, SLAM, and autonomous navigation.
C++
Python
ROS
Arduino
SLAM
Gazebo
Computer Vision
Traffic Sign Recognition
Detects and classifies traffic signs from images using MSER feature extraction and an SVM classifier. Outputs bounding boxes around detected signs with class labels.
Python
OpenCV
SVM
MSER
Computer Vision
Visual Odometry
Estimates the trajectory of a camera mounted inside a moving vehicle using sequential frame analysis. Compares a custom implementation against OpenCV's built-in visual odometry pipeline.
Python
OpenCV
Computer Vision
Lucas-Kanade Template Tracker
Implements the Lucas-Kanade optical flow algorithm to track objects (car, human, vase) across video frames using template matching and iterative gradient descent.
Python
OpenCV
Computer Vision
Underwater Buoy Detection
Continuously tracks three differently colored underwater buoys in real-time video using color segmentation and contour analysis in challenging underwater lighting conditions.
Python
OpenCV
Computer Vision
Lane Detection
Detects and tracks road lanes from a camera mounted on an autonomous vehicle. Uses Hough transforms and sliding window analysis, with turn prediction from lane curvature.
Python
OpenCV
Computer Vision
AR Tag Tracking
Detects and tracks AR tags in video frames and overlays 3D objects onto them in real time. Uses homography estimation and perspective projection for accurate augmented reality rendering.
Python
OpenCV