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Repolyzer is an AI-powered GitHub repository analyzer that builds system architecture diagrams, repository knowledge graphs, and intelligent summaries. It enables context-aware conversations to help developers understand and resolve repository issues.
Problem it solves: Understanding large, unfamiliar codebases is time-consuming. Repolyzer automates the analysis of repository structure, code relationships, and architecture — then exposes this knowledge via a chat interface for interactive exploration.
1 inheritance — Minimal class hierarchy (2 classes total)
24 interfaces — Strong typing for API contracts, database models, service boundaries
6. Getting Started
Prerequisites
Node.js 18+
pnpm (or npm/yarn — workspace uses package.json at root)
PostgreSQL database
Redis server
GitHub Personal Access Token (for API access)
OpenAI-compatible API key (for embeddings/chat)
Installation
# Clone
git clone https://github.com/anuzx/Repolyzer.git
cd Repolyzer
# Install dependencies (Turborepo workspaces)
pnpm install
# Generate Prisma client
pnpm --filter=db db:generate # or: cd packages/db && pnpm prisma generate# Set up environment variables# Create .env files in each app/package as needed:# - apps/backend/.env (DATABASE_URL, REDIS_URL, GITHUB_TOKEN, AI_API_KEY, PORT)# - apps/web/.env.local (NEXT_PUBLIC_API_URL)# - apps/worker/.env (DATABASE_URL, REDIS_URL, AI_API_KEY)# - packages/db/.env (DATABASE_URL)
Development Commands (from turbo.json / package.json)
# Run all apps in dev mode
pnpm dev
# Run individual apps
pnpm --filter=backend dev
pnpm --filter=web dev
pnpm --filter=worker dev
# Build all
pnpm build
# Lint
pnpm lint
# Type check
pnpm typecheck
# Database migrations
pnpm --filter=db db:migrate
pnpm --filter=db db:push
pnpm --filter=db db:studio
DATABASE_URL, REDIS_URL, GITHUB_TOKEN, AI_API_KEY, AI_BASE_URL, PORT
apps/web
NEXT_PUBLIC_API_URL
apps/worker
DATABASE_URL, REDIS_URL, AI_API_KEY, AI_BASE_URL
packages/db
DATABASE_URL
Summary
Repolyzer is a monorepo (Turborepo) with three apps (`85-file TypeScript codebase organized into 7 shared packages and 3 applications. It implements a complete pipeline: GitHub repo → clone → AST parse → chunk → embed → knowledge graph → summary → chat UI. The architecture cleanly separates API, frontend, and background worker, with shared infrastructure (queue, DB, AI, GitHub) in packages. All core pieces are present — the project appears to be in a working, structured state ready for development or deployment.
About
AI-powered GitHub repository analyzer that builds system architecture, repository knowledge graphs, and intelligent summaries, enabling context-aware conversations to understand and resolve repository issues.