🌌 Constellator

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Turn your GitHub stars into a clean, categorized Awesome list.

Constellator analyzes your starred repositories and generates an Awesome‑style markdown with clear categories, concise summaries, and sensible ordering.

✨ Features

• 🤖 AI-Powered Categorization: Uses Vercel AI Gateway with GPT-OSS models to intelligently categorize repositories
• 📊 Multi-Pass Processing: Advanced 4-pass AI pipeline for accurate classification
• 🎨 Beautiful Output: Generates clean, organized markdown files
• 🎯 Customizable: Flexible output filename and configuration options
• 🔄 Incremental Updates: Efficient processing with data persistence
• 📈 Quality Metrics: Includes star counts, activity indicators, and confidence scores
• 🎪 Interactive CLI: Beautiful terminal interface with real-time progress

🚀 Quick Start

One‑liner

npx constellator

This authenticates with GitHub, fetches your stars, runs a multi‑pass AI pipeline, and writes AWESOME.md.

Configure (recommended)

# Create/edit .constellator/config.json interactively
npx constellator config

Required:

• Vercel AI Gateway key (stored in .env as AI_GATEWAY_API_KEY)
• GitHub token (stored in .env as GITHUB_TOKEN, written automatically after constellator login)

Usage

First-time setup

# Configure your settings interactively
npx constellator config

Run (creates AWESOME.md)

npx constellator

Custom output filename

npx constellator --name MY_STARS.md

Authentication (if needed)

npx constellator login

Check authentication status:

npx constellator whoami

Logout and clear stored token

npx constellator logout

🎯 How It Works

Constellator uses a sophisticated 4-pass AI processing pipeline:

Pass 0 — Facts Extraction

• Analyzes repository README files
• Extracts key facts, capabilities, and tech stack
• Identifies repository purpose and features

Pass 1 — Expansion & Summaries

• Generates concise repository summaries
• Creates key topic tags
• Proposes initial category candidates

Pass 2 — Streamline & Primary Assignment

• Merges overlapping categories
• Assigns exactly one primary category per repository
• Ensures consistent categorization

Pass 3 — Quality Assurance

• Validates category assignments
• Handles edge cases and misclassifications
• Optimizes category structure

📁 Output Structure

Constellator generates several files in your project directory:

your-project/
├── AWESOME.md                    # Main categorized list (or custom name)
├── .constellator/
│   ├── config.json               # Your configuration settings
│   ├── constellator.json          # Processed repository data with categories
│   ├── repos.json                # Raw repository metadata (renamed from stars.json)
│   └── category-glossary.json    # AI-learned category definitions
└── .env                          # Environment variables (AI Gateway key only)

Key Files Created

• AWESOME.md: The main output file with your organized repository list
• .constellator/constellator.json: Complete processed data with all repository metadata, categories, and AI analysis
• .constellator/repos.json: Raw repository data fetched from GitHub
• .constellator/category-glossary.json: AI-learned category definitions for consistency across runs

⚙️ Configuration

Configuration Files

Constellator uses two configuration files:

1. Environment Variables (.env)

Place your runtime secrets here. Bun auto-loads .env.

# .env file
# Vercel AI Gateway (required)
AI_GATEWAY_API_KEY=vck_your_vercel_ai_gateway_key_here

# GitHub token (recommended; set via `constellator login`)
GITHUB_TOKEN=ghp_your_token_here

2. Application Settings (.constellator/config.json)

Non-secret app settings go here

{
  "CONSTELLATE_MAX_REPOS": "100",
  "CONSTELLATE_MODEL": "openai/gpt-4o-mini",
  "CONSTELLATE_FALLBACK_MODELS": ["openai/gpt-3.5-turbo", "openai/gpt-4"]
}

Configuration Options

| Variable | File | Default | Description | | ----------------------------- | --------------------------- | ---------------------- | -------------------------------- | | AI_GATEWAY_API_KEY | .env | Required | Vercel AI Gateway API key | | GITHUB_TOKEN | .env | Recommended | GitHub token (saved after login) | | CONSTELLATE_MAX_REPOS | .constellator/config.json | 100 | Maximum repositories to process | | CONSTELLATE_MODEL | .constellator/config.json | openai/gpt-4o-mini | Primary AI model to use | | CONSTELLATE_FALLBACK_MODELS | .constellator/config.json | openai/gpt-3.5-turbo | Fallback AI models |

🔐 Getting a GitHub token

You have three easy options. Pick one:

• Option A: Device flow (interactive, recommended)

  • Run: npx constellator login
  • Follow the on-screen instructions (opens GitHub in your browser)
  • Constellator saves a short‑lived token in ~/.constellator.json

• Option B: GitHub CLI (if you already use gh)

  • Run: gh auth login and complete the prompts
  • Constellator detects and uses your CLI token automatically

• Option C: Personal Access Token (manual)

  1. Go to GitHub → Settings → Developer settings → Personal access tokens
  2. Choose either:
     • Fine‑grained token: limit to your account, set Repository access to the repos you want Constellator to read
     • Classic token: simplest; scopes below
  3. Scopes to select:
     • Required: read:user, public_repo
     • Optional (for private repos): repo
  4. Copy the token and store it in .env like:

GITHUB_TOKEN=ghp_your_token_here

Tips:

• You can create/edit the config interactively with: npx constellator config
• To verify auth quickly: npx constellator login or run with --rate-limit to see API credits
• After successful login, Constellator writes GITHUB_TOKEN=... to .env in your current directory

CLI Options

| Option | Description | Example | | ------------------------ | -------------------------------------------------- | ------------------------------------- | | --name <filename> | Custom output filename | --name MY_AWESOME.md | | --version | Print version and exit | --version | | --max-repos <n> | Override max repositories for this run | --max-repos 500 | | --set KEY=VALUE | Override any config key (repeatable) | --set CONSTELLATE_MAX_CATEGORIES=60 | | --artifacts-dir <path> | Directory for artifacts (default: .constellator) | --artifacts-dir .cache/constellator | | --min-size <n> | Minimum category size in README | --min-size 2 | | --open | Open generated README on completion (macOS) | --open | | --batch-size <n> | Pass‑1 batch size (default: 4) | --batch-size 6 | | --timeout <ms> | Network timeout per request (default: 30000) | --timeout 45000 | | --rate-limit | Print GitHub rate limit before/after the run | --rate-limit | | -h, --help | Show help | --help | | login | Interactive authentication setup | npx constellator login | | logout | Clear stored credentials | npx constellator logout |

Examples

# Change output file
npx constellator --name MY_STARS.md

# Run with more repos and stricter README filter
npx constellator --max-repos 500 --min-size 2

# Override a config key without editing files
npx constellator --set CONSTELLATE_MAX_CATEGORIES=60

# Use a custom artifacts directory
npx constellator --artifacts-dir .cache/constellator

# Increase batch size and timeout, and open the file when done
npx constellator --batch-size 6 --timeout 45000 --open

# Print GitHub rate limit before/after
npx constellator --rate-limit

🎨 Example Output

# Awesome – Generated by Constellator

> Categories distilled from your stars via multi‑pass AI. Updated 2025-01-15.

## Table of Contents

- [AI Agents](#ai-agents)
- [Web Development](#web-development)
- [DevOps Tools](#devops-tools)

## AI Agents

### transfinite-ai/agentic (⭐ 15,432)

Advanced AI agent framework for autonomous task execution.

**Tags:** ai, agents, automation, python
**Capabilities:** Task planning, tool integration, multi-step reasoning

🔧 Development

Project Structure

constellator/
├── index.tsx              # Main CLI application
├── cli.cjs               # Executable wrapper script
├── .env                  # Environment variables (AI Gateway key only)
├── lib/
│   ├── ai.ts             # AI processing pipeline
│   ├── auth.ts           # GitHub authentication
│   ├── github.ts         # GitHub API client
│   ├── models.ts         # AI model selection
│   ├── schemas.ts        # Data validation schemas
│   └── utils.ts          # Utility functions
├── .constellator/         # Application configuration & data files
│   ├── config.json       # User configuration settings
│   ├── constellator.json  # Processed repository data
│   ├── repos.json        # Raw repository metadata
│   └── category-glossary.json # AI-learned category definitions
├── dist/                 # Compiled JavaScript output
└── package.json          # Package configuration

Running locally (development)

git clone https://github.com/mislavjc/constellator
cd constellator
pnpm install # or npm/yarn
npx ts-node index.tsx

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Uses Vercel AI Gateway for AI processing
• Terminal UI powered by Ink

🐛 Troubleshooting

Common Issues

No starred repositories found

• Verify your GitHub token in .env has the correct permissions
• Check that you have starred repositories

AI Gateway authentication failed

• Verify your AI_GATEWAY_API_KEY in .env is correct
• Make sure you're using a valid Vercel AI Gateway key

AI Gateway API rate limit exceeded

• Reduce CONSTELLATE_MAX_REPOS in .constellator/config.json or wait for rate limit reset
• Consider upgrading your Vercel AI Gateway plan

Configuration not found

• Run npx constellator config to set up your configuration
• Ensure .constellator/config.json exists with proper settings
• Make sure .env contains AI_GATEWAY_API_KEY (and GITHUB_TOKEN if not using gh)

Getting Help

• Check the Issues page
• Review the configuration files above
• Ensure both .env and .constellator/config.json are properly configured

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