GitHub-Based Portfolio & Gallery of Jack J. Burleson

Welcome! This repository serves as the official portfolio and gallery for Jack J. Burleson, showcasing a curated selection of previous work, open-source projects, research, and presentations.

🎉 Recent Major Update (December 2024): The repository has been comprehensively reorganized for better maintainability and clarity. All documentation, requirements, and configuration files have been moved to organized subdirectories. See the Repository Organization section for details.

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About Me

Hi! I’m Jack J. Burleson – data scientist, research engineer, and open-source enthusiast.
I am passionate about making data science, machine learning, and advanced analytics accessible and meaningful through clear code and insightful visualizations.
This portfolio highlights select projects in engineering, data analysis, machine learning, AI/LLM integration, and technical writing.

Repository Highlights

• 🎯 8+ Active Projects: From multi-agent systems to psychometric assessments
• 📚 Comprehensive Documentation: Organized documentation structure with setup guides, development workflows, and project-specific docs
• 🔧 Production-Ready: Full testing frameworks, CI/CD integration, and deployment configurations
• 🌐 Modern Stack: Python, JavaScript/TypeScript, SvelteKit, Flask, and modern LLM integrations
• 📦 Flexible Installation: Multiple requirement files for different use cases (full, minimal, micro)
• 💾 External Storage Support: Automated configuration for managing large dependencies on external drives

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Project Gallery

Project	Description	Link
Random Forest Essentials	[New] Comprehensive analysis with interactive plots, decision boundaries, and ROC curves.	📊 View Interactive Analysis
CrewAI Multi-Agent Swarm System	Multi-agent architecture using CrewAI, with specialized swarms for ML, research, business intelligence, and documentation; includes Streamlit & CLI interfaces.	🚀 Launch Swarm | 📄 Docs
Psychometrics (NASA TLX)	[New] Comprehensive psychometric assessment toolkit implementing the NASA Task Load Index (TLX) for workload measurement with statistical analysis. Used in the Neural Architecture of Truth & Deception research project.	📊 View Project | 🔗 NATD API | 🧠 NATD Repository
RAG Model Application	[New] Complete Retrieval-Augmented Generation system with vector database, embeddings, and intelligent document retrieval using FAISS and Ollama.	🔍 View Project
Chat UI (SvelteKit)	[New] Modern, open-source chat interface for LLM interactions with support for multiple backends (OpenAI, Ollama, Hugging Face) and real-time streaming.	💬 View Project
iOS Chatbot	Flask-based chatbot application with web interface, designed for iOS-style interactions and mobile-friendly UI.	📱 View Project
LiteLLM Proxy Server	Unified API proxy for multiple LLM providers, enabling easy switching between OpenAI, Anthropic, and other providers with a single interface.	🔌 View Project
Terminal Agents	AI coding agents for the terminal; includes “build” and “plan” agents, supporting code exploration and editing with easy installation and cross-platform support.	💻 View Project
Jupyter ML & Pandas Notebooks	Collections of essential notebooks demonstrating the use of Pandas and scikit-learn in data workflows.	📓 View Notebooks
PyPI-Ready Python Template	Modern Python project template with pre-commit, Black, and CI configuration, ready for immediate use as a best-practices starter.	📦 Template Repo

More projects, research, and documentation are regularly added. See repository folders for latest content.

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Interactive Agent Swarm

Tip🤖 Run the Live Interface

This portfolio contains a full CrewAI Multi-Agent System application.
To interact with the specialized agent swarms (ML, Research, Business Intelligence), you can run the Streamlit interface locally.

🚀 Quick Start

1. Clone this repository to your local machine.

2. Configure external storage (recommended for large dependencies): bash npm run setup:external See Quick Start Guide for details.

3. Install dependencies:

   # Python dependencies (choose based on needs)
   pip install -r requirements/requirements.txt          # Full installation
   pip install -r requirements/requirements-minimal.txt   # Minimal installation
   pip install -r requirements/requirements-micro.txt     # Micro installation
   
   # NPM dependencies (for ChatUi and tooling)
   npm install

4. Launch the Swarm Interface: bash streamlit run projects/CrewAI/interface_web.py

📂 Browse Source Code | 📄 View Documentation

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Recent Additions

December 2024 - Repository Reorganization

• 📁 Organized Structure: All documentation moved to docs/, requirements to requirements/, and configs to config/ for better maintainability
• 📚 Enhanced Documentation: Comprehensive setup guides, development documentation, and project-specific docs organized in docs/ subdirectories
• ⚙️ Configuration Management: Centralized configuration files in config/ directory
• 📦 Multiple Requirements Files: Added requirements-minimal.txt and requirements-micro.txt for flexible installation options
• 🔧 NPM Integration: Full NPM support with package.json, external storage configuration, and development tooling

New Projects & Features

• Psychometrics (NASA TLX): Complete implementation of NASA Task Load Index for workload assessment with statistical analysis (View Project)
• RAG Model Application: Full RAG pipeline with vector database, embeddings, and document retrieval (View Project)
• Chat UI (SvelteKit): Modern chat interface for LLM interactions with multiple backend support (View Project)
• iOS Chatbot: Flask-based chatbot with mobile-friendly interface (View Project)
• LiteLLM Proxy: Unified API proxy for multiple LLM providers (View Project)

Enhanced Existing Projects

• Random Forest Analysis: Enhanced with interactive visualizations and decision boundary plots (View Analysis)
• CrewAI Swarm System: Full-featured, multi-swarm agent orchestration, ML/research/business/reporting specializations (README)
• Terminal Coding Agents: Terminal-based agent system, built-in “build” and “plan” agents with live installation quick start (README)
• Jupyter Notebooks: ML and pandas essentials, plus scikit-learn examples (notebooks/)

Infrastructure & Tooling

• External Storage Support: Automated configuration for using external USB drives for caches and dependencies
• Development Documentation: Comprehensive guides for Git protocol, remote Python paths, and development workflows
• Testing Framework: Complete test suite for all projects with pytest configuration
• .gitignore Improvements: Now excludes macOS ._*, .DS_Store, and other platform/editor artifacts

📋 Track all changes: See CHANGELOG.html for detailed version history

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Skills

• Programming: Python (advanced), R, JavaScript, TypeScript, SvelteKit, bash, Make
• Data Analysis: Pandas, NumPy, scikit-learn, seaborn, matplotlib
• Visualization: matplotlib, seaborn, Quarto, Jupyter, interactive dashboards
• Machine Learning & AI: scikit-learn, CrewAI, RAG systems, vector databases, embeddings, agent-based simulation, feature engineering
• LLM Integration: OpenAI API, Ollama, LiteLLM, Hugging Face, Anthropic, custom LLM backends
• Web Development: Flask, SvelteKit, Streamlit, REST APIs, WebSockets
• Documentation: Quarto, Markdown, Jupyter Notebooks, technical writing
• CI/CD & Tooling: pre-commit, Black, GitHub Actions, Poetry, npm, .gitignore hygiene
• DevOps: Docker, Git, SQL, external storage management, dependency optimization
• Other: Git, SQL, Docker, technical writing, code review, psychometric assessment

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Publications & Presentations

• Random Forest Essentials – Quarto doc, 2024. (Link)
• Talking to Agents: architecting Multi-Agent Systems – Internal seminar, 2024.
• (More manuscripts and presentations to be added.)

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Contact

• Email: jackburleson.dev@gmail.com
• LinkedIn: linkedin.com/in/jack-j-burleson
• Website: jackburleson.dev

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Socials

• GitHub
• Twitter/X
• LinkedIn
• HuggingFace

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Repository Organization

The repository has been organized into clear, maintainable directories:

JJB_Gallery/
├── requirements/          # Python dependency files
│   ├── requirements.txt          # Full installation
│   ├── requirements-minimal.txt  # Minimal installation
│   └── requirements-micro.txt     # Micro installation
├── config/                # Configuration files
│   └── pip.conf           # Pip configuration
├── docs/                  # Comprehensive documentation
│   ├── QUICK_START.md            # Quick start guide
│   ├── setup/                    # Setup & configuration guides
│   │   ├── NPM_SETUP.md
│   │   ├── EXTERNAL_STORAGE_SETUP.md
│   │   └── ...
│   ├── development/              # Development guides
│   │   ├── GIT_PROTOCOL_GUIDE.md
│   │   └── REMOTE_PYTHON_PATHS.md
│   └── ...
├── projects/             # All project implementations
│   ├── CrewAI/
│   ├── Psychometrics/
│   ├── RAG_Model/
│   ├── ChatUi/
│   └── ...
├── scripts/             # Automation and utility scripts
├── notebooks/           # Jupyter notebooks
└── Quarto/              # Quarto documents

📚 Documentation: See docs/README.md for complete documentation index.

Further Reading

Project Documentation

• Terminal Agents Project - AI coding agents for terminal
• CrewAI Multi-Agent System - Multi-agent orchestration
• Psychometrics (NASA TLX) - Workload assessment toolkit
• RAG Model Application - Retrieval-augmented generation
• Chat UI - Modern chat interface
• iOS Chatbot - Flask-based chatbot
• LiteLLM Proxy - Unified LLM API proxy

Repository Documentation

• Quick Start Guide - Get started quickly
• Documentation Index - Complete documentation
• Repository Organization - File organization guide
• CHANGELOG.html - Version history and changes
• SECURITY.html - Security policy

External Resources

• Official Python Template Repo - Best practices starter

Repository updated regularly. Check project directories for the latest code, docs, and research.