TrustCode Platform – Autonomous AI Analyst

📌 Project Overview

A production-ready web application that analyzes GitHub repositories using AI-powered analysis to generate Trust Scores, code quality insights, security risks, and comprehensive reports.

🎯 Features

• 🔍 GitHub Repo Analysis via API
• 🤖 AI-powered code quality & security scanning
• 📊 Trust Score (0-100) with breakdown
• 🎨 Responsive dashboard (React + Tailwind)
• 🚀 FastAPI backend with modular services
• 🐳 Docker Compose for easy deployment
• 🔐 Secure (env vars, CORS, error handling)

🧩 Architecture

trustcode-platform/                           # Root: Full-stack GitHub Trust Analyzer
├── backend/                                 # 🐍 FastAPI Backend API (localhost:8000)
│   ├── Dockerfile                           # Backend Docker build
│   ├── requirements.txt                     # Python deps (fastapi, pydantic, httpx)
│   ├── main.py                              # FastAPI app entrypoint (/health, /analyze-repo)
│   ├── models/schemas.py                    # Pydantic models (RepoAnalysisResponse)
│   ├── utils/github_api.py                  # GitHub API client (fetch repo tree/files)
│   ├── services/ai_analyzer.py              # AI code scanning logic
│   └── services/trust_engine.py             # Trust Score calculation (0-100)
├── frontend/                                # ⚛️ React + Vite + Tailwind UI (localhost:3000)
│   ├── Dockerfile                           # Frontend Docker build
│   ├── package.json                         # NPM deps (react, vite, axios)
│   ├── vite.config.js                       # Vite bundler config
│   ├── tailwind.config.js                   # Tailwind CSS config
│   ├── postcss.config.js                    # PostCSS config
│   ├── index.html                           # HTML entrypoint
│   └── src/
│       ├── main.jsx                         # React root render
│       ├── App.jsx                          # Main dashboard component
│       ├── index.css                        # Global styles
│       └── api.js                           # API client (calls backend)
├── docker-compose.yml                       # 🐳 Orchestrates backend (8000) + frontend (3000) services
├── README.md                                # 📖 This documentation
├── TODO.md                                  # ✅ Implementation tasks complete
└── TODO_ARCH.md                             # 📋 Architecture update tracking

🐳 Docker Services

Service	Port	Description
backend	8000	FastAPI API (/docs, /analyze-repo)
frontend	3000	React app (Vite dev server)

🔄 Data Flow

User (browser) → Frontend (React) → API Call → Backend (FastAPI)
                ↓
GitHub API (utils/github_api.py) → Repo Data → AI Analyzer + Trust Engine
                ↓
JSON Response → Frontend Dashboard (Trust Score gauge, insights)

🚀 Quick Start

1. Clone & Setup

git clone <repo>
cd trustcode-platform
cp backend/.env.example backend/.env
cp frontend/.env.example frontend/.env
# Add your GITHUB_TOKEN to backend/.env

2. Run with Docker

docker-compose up --build

📋 API Endpoints

Endpoint	Method	Description
/health	GET	Health check
/analyze-repo/{repo_url}	POST	Analyze repo (body: empty JSON)

Example:

curl -X POST "http://localhost:8000/analyze-repo/https://github.com/fastapi/fastapi"

🛠️ Tech Stack

• Backend: FastAPI, Pydantic, httpx
• Frontend: React 18, Vite, Tailwind CSS
• DevOps: Docker Compose
• AI: Modular analyzer (LLM-ready)

📸 Screenshots

(Placeholder - Add after running)

• Dashboard with Trust Score gauge
• Repo metrics & AI insights
• Responsive mobile view

🔧 Development

Backend:

cd backend
pip install -r requirements.txt
uvicorn main:app --reload

Frontend:

cd frontend
npm install
npm run dev

🌟 Future Improvements

• Real LLM integration (OpenAI/Groq)
• Rate limiting & caching
• Repo file content analysis
• Export reports (PDF)