BioHacking Platform

A comprehensive wellness tracking and verification platform for supplements, peptides, blood work monitoring, and general health optimization.

🎯 Core Features

Tracking & Monitoring

• Supplements — Log, schedule, and track supplement intake
• Peptides — Protocol management, cycle tracking, and sourcing
• Blood Work — Import lab results, track biomarkers over time
• Wellness — General health metrics, sleep, exercise, subjective notes

Verification (Spectrometer Integration)

• Peptide Purity Analysis — Chemometric models for quality verification
• Supplement Authenticity — Spectral fingerprinting for product validation
• Impurity Detection — Identify contaminants or degradation

AI & Reference

• AI Assistant — Ask questions about protocols, interactions, dosing
• Peptide Dictionary — Structures, mechanisms, research references
• Supplement Database — Ingredient info, bioavailability, interactions

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📁 Project Structure

BioHacking/
├── backend/                 # Django REST API
│   ├── config/              # Django project settings
│   ├── api/                 # Core API routing
│   ├── supplements/         # Supplement tracking
│   ├── bloodwork/           # Lab results & biomarkers
│   ├── peptides/            # Peptide protocols
│   ├── wellness/            # General health tracking
│   ├── spectrometer/        # Device integration (future)
│   ├── ai_assistant/        # LLM-powered Q&A
│   └── reference/           # Dictionary/database lookups
│
├── frontend/                # React + TypeScript + Tailwind
│   ├── src/
│   │   ├── components/      # Reusable UI components
│   │   ├── pages/           # Route-level views
│   │   ├── hooks/           # Custom React hooks
│   │   ├── services/        # API client & utilities
│   │   └── types/           # TypeScript definitions
│   └── public/
│
├── ml/                      # Machine Learning & Chemometrics
│   ├── models/              # Trained model artifacts
│   ├── training/            # Training pipelines
│   ├── preprocessing/       # Spectral data preprocessing
│   └── spectrometer/        # Device-specific ML
│
├── data/                    # Data storage
│   ├── reference/           # Static reference databases
│   │   ├── peptides/        # Peptide structures & info
│   │   └── supplements/     # Supplement compound data
│   ├── spectra/             # Spectral libraries (future)
│   └── user/                # User data (gitignored)
│
└── docs/                    # Documentation
    ├── api/                 # API reference
    ├── setup/               # Installation guides
    └── guides/              # User & developer guides

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🛠️ Tech Stack

Layer	Technology
Backend	Django 5.x, Django REST Framework
Frontend	React 18, TypeScript, Tailwind CSS
Database	PostgreSQL (production), SQLite (dev)
ML/Chemometrics	PyTorch, scikit-learn, scipy
AI	OpenAI API / Local LLM via vLLM
Spectrometer	USB/Bluetooth integration, custom drivers

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🚀 Quick Start

# Backend setup
cd backend
python -m venv venv
.\venv\Scripts\activate  # Windows
pip install -r requirements.txt
python manage.py migrate
python manage.py runserver

# Frontend setup (separate terminal)
cd frontend
npm install
npm run dev

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📋 Development Roadmap

Phase 1: Foundation

• Django project scaffold
• React app scaffold
• Database models for core entities
• Basic CRUD APIs

Phase 2: Core Features

• Supplement logging & scheduling
• Blood work import (manual entry)
• Peptide protocol tracking
• Wellness journal

Phase 3: Intelligence

• AI assistant integration
• Reference dictionary UI
• Interaction warnings

Phase 4: Spectrometer

• Device communication layer
• Spectral data pipeline
• Chemometric model training
• Purity/authenticity scoring

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📄 License

Private project — All rights reserved.