README.md

metadata

title: GLMPilot
emoji: 🚀
colorFrom: blue
colorTo: purple
sdk: docker
pinned: false
license: mit

GLMPilot

GLMPilot is an AI-native, browser-based IDE built around GLM. It combines code editing, AI chat, code completion, multi-agent review, terminal execution, and GitHub workflows in a single application.

Executive Summary

Item	Details
Product Type	Browser-based AI IDE
Primary Use Case	Build, review, and ship code faster from one workspace
AI Backbone	GLM API (chat, completion, analysis, orchestration)
Deployment Model	Monorepo with Docker and Docker Compose support
Key Integrations	GitHub, Redis, WebSocket streaming

Key Capabilities

Capability	Description	Business Value
AI Chat and Streaming	Real-time GLM assistant integrated in the IDE	Faster iteration and lower context switching
Code Completion	Context-aware inline suggestions	Higher coding velocity
Multi-Agent Review	Security, performance, style, and documentation agents	Better code quality before PR
Monaco-Based Editor	Multi-file editing with VS Code-grade engine	Familiar professional developer experience
Integrated Terminal	Browser terminal over WebSocket	In-app execution and validation
Live Preview	Real-time HTML/CSS/JS preview	Rapid UI feedback loop
GitHub Workflow	Repository import and patch/PR flow	Shorter path from idea to merge

Architecture Overview

Client (React + Monaco + Zustand)
  -> REST API (Express routes)
  -> WebSocket channel (chat tokens, terminal, execution events)

Server (Express + Agent Orchestrator)
  -> GLM service client
  -> GitHub service
  -> Redis (cache/pub-sub/coordination)

Detailed architecture: ARCHITECTURE.md

Repository Structure

Path	Purpose
packages/client	React application, IDE shell, editor and UI components
packages/server	Express API, WebSocket handlers, AI services, agent orchestration
packages/shared	Shared types, constants, and cross-package utilities
Dockerfile	Production image build configuration
docker-compose.yml	Local multi-service orchestration

Technology Stack

Layer	Technologies
Frontend	React 18, TypeScript, Vite, Tailwind CSS, Monaco, Zustand
Backend	Node.js, Express, Socket.io
AI	GLM API with streaming and retry support
Infrastructure	Docker, Docker Compose, Redis
Repository	npm workspaces monorepo

Local Development

Prerequisites

Requirement	Minimum Version
Node.js	18+
npm	9+
Docker	Recommended

Setup

git clone https://github.com/your-username/GLMPilot.git
cd GLMPilot
npm install
cp .env.example .env

Environment Variables

Variable	Required	Purpose
NODE_ENV	No	Runtime mode (development/production)
PORT	No	Server port
CLIENT_URL	No	Allowed client origin
GLM_API_KEY	Yes	GLM authentication key
GLM_BASE_URL	No	GLM API base URL
GLM_MODEL	No	Default GLM model
GITHUB_TOKEN	Optional	GitHub integration and PR automation
REDIS_URL	No	Redis connection string
LOG_LEVEL	No	Server logging verbosity

Start Redis and run development servers:

docker run -d --name glmpilot-redis -p 6379:6379 redis
npm run dev:all

Service	URL
Client	http://localhost:5173
Server	http://localhost:3001

Scripts

Command	Description
npm run dev	Start client development server
npm run dev:server	Start server development process
npm run dev:all	Run client and server concurrently
npm run build	Build shared, server, and client packages
npm run typecheck	Run TypeScript project-reference checks

Deployment

Option	Command
Docker Compose	docker-compose up --build
Single Image	docker build -t glmpilot-ide .
Single Image Run	docker run --env-file .env -p 7860:7860 glmpilot-ide

In containerized mode, the backend serves static frontend assets and API/WebSocket traffic from a single port.

API and Realtime Surface

Surface	Capability
REST	Chat, completion, review, docs and integration endpoints
SSE	Token streaming for chat responses
WebSocket	Terminal IO, execution events, chat token streaming

Package-level docs:

• packages/server/README.md
• packages/client/README.md
• packages/shared/README.md

Hackathon Readiness

Requirement Area	Current Status
GLM Integration Depth	Implemented across chat, completion, and multi-agent analysis
Codebase Documentation	Root and package-level documentation available
Setup Reproducibility	.env template and Docker-based startup provided
Demonstration Path	Import -> Generate -> Review -> Validate -> PR workflow supported

Recommended Demo Flow

1. Import a GitHub repository.
2. Use GLM chat to generate or refactor feature code.
3. Run multi-agent review and inspect findings.
4. Apply fixes and verify using preview/terminal.
5. Create a PR with summarized changes.

Contributing

1. Fork the repository.
2. Create a feature branch.
3. Commit changes.
4. Push branch.
5. Open a pull request.