🧠 Paste a GitHub URL. Get a full visual architecture walkthrough, module breakdown, key code flows, and an AI chat to explore deeper.
Every developer knows the pain: you open a new repo and face a wall of unfamiliar code. READMEs are outdated. Architecture docs don't exist. You spend hours jumping between files trying to piece together how things work.
What if you could understand any codebase in under 60 seconds?
- 📎 Paste a GitHub repo URL
- 🤖 AI agents analyze the entire codebase — architecture, modules, data flows, patterns
- 📊 Get an interactive visual walkthrough:
- 🗺️ Architecture Diagram — auto-generated Mermaid diagram showing how components connect
- 📦 Module Breakdown — every major module explained with key files highlighted
- 🔄 Key Code Flows — step-by-step walkthroughs of critical paths (auth, API lifecycle, data pipeline, etc.) with annotated code snippets
- 💬 Ask follow-up questions — chat with the codebase using semantic code search
GitHub Repo URL
│
▼
┌─────────────────┐ ┌──────────────────────────────────────┐
│ 🌐 Next.js UI │◄──►│ ⚡ FastAPI Backend │
└─────────────────┘ └──────────────┬───────────────────────┘
│
▼
┌──────────────────────────────┐
│ 🤖 Railtracks Agent Pipeline │
│ │
│ IndexerAgent ──────────────►│
│ ArchitectureAgent ────────►│
│ ModuleAgent ──────────────►│
│ FlowAgent ────────────────►│
│ DiagramAgent (+ validator) ►│
│ ComposerAgent ────────────►│
└──────┬──────────┬───────────┘
│ │
┌──────────▼┐ ┌──────▼──────────┐
│ 🧬 Augment │ │ 🌊 DigitalOcean │
│ Context │ │ Gradient AI │
│ Engine │ │ Inference │
└───────────┘ └─────────────────┘
RepoLens uses 7 specialized AI agents orchestrated as a sequential flow with a validation loop:
| Agent | Job |
|---|---|
| 🗂️ IndexerAgent | Indexes the repo using Augment Context Engine via MCP |
| 🏛️ ArchitectureAgent | Identifies architecture patterns, tech stack, and design decisions |
| 📦 ModuleAgent | Breaks the codebase into logical modules with descriptions |
| 🔄 FlowAgent | Discovers 3-5 critical code flows with step-by-step walkthroughs |
| 📊 DiagramAgent | Generates a Mermaid.js architecture diagram |
| ✅ DiagramReviewer | Validates diagram syntax and completeness (validation loop) |
| 🎼 ComposerAgent | Assembles everything into a structured response for the UI |
Plus a 💬 ChatAgent for follow-up Q&A powered by semantic code retrieval.
Augment's Context Engine is the centerpiece — it's what makes the analysis actually understand code rather than just pattern-match.
- Context Connectors index any GitHub repo into a semantic search engine
- Agents query the index via MCP (Model Context Protocol) to find relevant code
- The ChatAgent uses semantic retrieval for grounded, accurate answers
- Every code snippet shown in the UI comes from Augment's semantic search — not naive grep
# Railtracks agents connect to Augment via MCP
augment_server = connect_mcp(
MCPHttpParams(url="http://localhost:8081/mcp")
)
ArchitectureAgent = rt.agent_node(
tool_nodes=augment_server.tools, # 🧬 Augment search tools
llm=do_gradient_llm, # 🌊 DigitalOcean inference
system_message="Analyze this codebase's architecture..."
)- Gradient AI Inference Hub — powers all LLM calls across every agent (OpenAI-compatible API)
- App Platform — one-click deployment for both frontend and backend
- All inference runs through
inference.do-ai.run— zero infrastructure to manage
- Flows are just Python — no config files, no DSLs, just async/await
- Sequential pipeline with a validation loop for diagram quality
- Built-in MCP support connects directly to Augment's Context Engine
- Full observability and error handling out of the box
| Layer | Technology |
|---|---|
| 🌐 Frontend | Next.js + Tailwind CSS + shadcn/ui |
| ⚡ Backend | Python + FastAPI + uvicorn |
| 🤖 Agents | Railtracks — flows are just Python |
| 🧬 Code Intelligence | Augment Code Context Connectors + Context Engine SDK |
| 🧠 LLM Inference | DigitalOcean Gradient AI Inference Hub |
| 📊 Diagrams | Mermaid.js |
| 🚀 Deployment | DigitalOcean App Platform |
# Clone
git clone https://github.com/your-org/repolens.git && cd repolens
# Backend
cd backend
cp .env.example .env # Add your API keys
uv sync
uv run uvicorn main:app --reload --port 8000
# Frontend (new terminal)
cd frontend
pnpm install && pnpm devOpen http://localhost:3000 and paste a GitHub URL 🎉
DO_MODEL_ACCESS_KEY= # DigitalOcean Gradient AI key
AUGMENT_SESSION_AUTH= # From `auggie token print`
GITHUB_TOKEN= # GitHub PAT for repo access| Time | Action |
|---|---|
| 0:00 | 🎤 "Every developer wastes hours understanding new codebases. We fixed that." |
| 0:15 | 📎 Paste a GitHub repo URL into RepoLens |
| 0:30 | ⏳ Show the agent pipeline working — "7 AI agents powered by Railtracks, using Augment's Context Engine to deeply understand the code" |
| 1:00 | 🗺️ Walk through the architecture diagram |
| 1:30 | 📦 Show module breakdown + key code flows with annotated snippets |
| 2:00 | 💬 Ask a follow-up question in the chat — "How does authentication work?" |
| 2:30 | 🌊 "Deployed live on DigitalOcean App Platform, LLM inference via Gradient AI" |
| 2:45 | 🎯 "Try it yourself" — share the live URL |
Built with ❤️ and ☕ at the Multimodal Hackathon 2026
🤖 Built with Railtracks · 🧬 Powered by Augment Code · 🌊 Deployed on DigitalOcean