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Common questions and answers about Adastrea Director.
Adastrea Director is an AI-powered game development assistant that provides context-aware documentation search, intelligent planning, and autonomous monitoring capabilities. It's designed to help game developers work more efficiently by providing intelligent assistance throughout the development lifecycle.
Yes, Adastrea Director is open source (see the LICENSE file for details). However, you'll need API keys for LLM providers (Gemini or OpenAI). Google Gemini offers a generous free tier, making it possible to use Adastrea Director at no cost for API usage.
Adastrea Director is specifically designed for game development and offers:
- Context-aware: Understands your project documentation
- Planning capabilities: Breaks down goals into actionable tasks
- Autonomous agents: Proactive monitoring and optimization
- Game dev focused: Tailored for Unreal Engine and game development
Yes! The standalone mode works with any project. However, the Unreal Engine plugin provides the best experience for UE developers with integrated in-editor features.
- Python: 3.9+ (3.12+ recommended)
- RAM: 4GB minimum, 8GB+ recommended
- Storage: 2GB free space
- OS: Windows 10+, macOS 10.14+, Ubuntu 20.04+
See System Requirements for details.
Yes, you need an API key for one of these LLM providers:
- Google Gemini (Recommended - free tier available)
- OpenAI (Pay-per-use)
- Ollama (Completely local, no API key needed)
For embeddings, HuggingFace is used by default (no API key required).
- Go to Google AI Studio
- Sign in with your Google account
- Click "Get API Key" or "Create API Key"
- Copy your API key
- Configure in Adastrea Director:
python main.py --set-api-key gemini
Partially. You can:
- β Use Ollama for local LLM (completely offline)
- β Use HuggingFace embeddings (offline after first download)
- β Cannot use cloud LLM providers (Gemini, OpenAI)
Use the smart installer which handles Apple Silicon dependencies:
python install_dependencies.pyIt will guide you through any platform-specific steps needed.
Ubuntu/Debian:
sudo apt-get install python3-tkmacOS:
brew install python-tkWindows: tkinter is included with Python on Windows. Reinstall Python if missing.
- Install:
./setup.sh - Configure API key:
python main.py --set-api-key gemini - Ingest docs:
python ingest.py --docs-dir /path/to/docs - Start using:
python main.pyorpython gui_director.py
See Quick Start Tutorial for details.
The first query loads the embedding model and LLM, which can take 5-10 seconds. Subsequent queries are much faster (1-3 seconds). This is normal behavior.
Use the ingestion script:
# Ingest your documentation
python ingest.py --docs-dir /path/to/your/docs
# For Adastrea game developers
python ingest_game_repo.pySee Document Ingestion Guide for details.
Yes! Supported file types include:
-
.md,.txt,.rst- Documentation -
.py,.cpp,.h,.cs- Code files - Custom types via
--file-typesflag
Re-run ingestion with the --update flag:
python ingest.py --docs-dir /path/to/docs --updateThis will process new/changed files without re-processing everything.
Ask natural language questions about your project:
- "What is the main gameplay loop?"
- "How do I implement feature X?"
- "Where is the player movement code?"
- "What are the requirements for Y?"
- "Explain the architecture of Z"
Be specific for best results!
Possible reasons:
- Not enough documents ingested: Ingest relevant documentation
- Question too vague: Be more specific
- Information not in documents: Add relevant docs
- Wrong context: Rephrase your question
Yes! In the GUI:
- Press
Ctrl+Eor use File β Export Conversation - Choose format (text, markdown, JSON)
The Planning System (Phase 2) breaks down high-level development goals into actionable tasks with dependencies, priorities, and code suggestions.
# Interactive mode
python planner.py --interactive
# Single goal
python planner.py "Your goal here"
# Export plan
python planner.py "Your goal" --export markdown --output plan.mdSee Planning System Guide for details.
- Markdown - For documentation and sharing
- JSON - For programmatic use
- Text - Simple text format
Yes! The planner suggests implementation approaches with code examples. However, you should review and adapt the code for your specific needs.
Autonomous agents (Phase 3) are proactive AI assistants that monitor your project for performance issues, bugs, and code quality problems without requiring manual queries.
# Start all agents
python agent_orchestrator_cli.py start --all
# Check status
python agent_orchestrator_cli.py status
# View dashboard
python agent_dashboard.py --auto-startSee Autonomous Agents Guide for details.
Currently available agents:
- Performance Agent: Monitors performance metrics
- Bug Detection Agent: Identifies potential bugs
- Code Quality Agent: Reviews code quality
More agents coming in future phases!
Not yet, but this is planned for a future release. Check the main README for the current roadmap.
- Copy
Plugins/AdastreaDirectorto your UE project'sPluginsfolder - Regenerate project files
- Build your project
- Launch UE Editor
- Open Window β Developer Tools β Adastrea Director
See Plugin Setup Guide for details.
Unreal Engine 5.0 and later are supported.
No, the plugin includes the Python backend. However, the standalone version is useful for:
- Testing and development
- Features not yet in the plugin
- Non-UE projects
Yes! They can run simultaneously and even share the same knowledge base.
-
Vector Database:
./chroma_db(configurable) -
Configuration:
~/.adastrea/config.json -
Logs:
./logs(if enabled)
Yes! Data is stored locally except for:
- LLM API calls (sent to provider)
- Optional telemetry (disabled by default)
Use Ollama for completely local, private operation.
Yes! Supported providers:
- Google Gemini
- OpenAI (GPT-3.5, GPT-4)
- Ollama (local)
Configure via settings or command line.
Yes! If you have a CUDA-compatible GPU:
- HuggingFace embeddings automatically use GPU
- Some LLM providers support GPU
- Check with
nvidia-smito verify GPU usage
Free Option:
- Google Gemini free tier (generous limits)
- HuggingFace embeddings (free, offline)
- Total cost: $0/month
Paid Option:
- OpenAI API (pay-per-use, typically $0.01-$0.10 per query)
- OpenAI embeddings (optional)
Backup these directories:
-
./chroma_db- Vector database -
~/.adastrea/config.json- Configuration
# Backup command
tar -czf adastrea-backup.tar.gz chroma_db ~/.adastrea/config.json- Check tkinter is installed:
python -m tkinter - Try CLI mode:
python main.py - Check error logs
- See Troubleshooting Guide
- First query is always slow (model loading) - normal
- Check internet connection (for cloud LLMs)
- Check GPU usage:
nvidia-smi - Consider using lighter models
Configure your API key:
# Via CLI
python main.py --set-api-key gemini
# Via GUI
python gui_director.py
# Settings β API KeysSee the comprehensive Troubleshooting Guide.
See Contributing Guide for details on:
- Code contributions
- Documentation improvements
- Bug reports
- Feature requests
- Check existing issues
- If not reported, create a new issue
- Include:
- Description of the bug
- Steps to reproduce
- Expected vs actual behavior
- System information
- Error logs (if any)
Yes! We welcome feature suggestions:
- Check discussions
- Create a new discussion with your idea
- Explain the use case and benefits
- π Wiki: Comprehensive documentation
- π Issues: Report bugs
- π¬ Discussions: Ask questions
- π§ Contact: @Mittenzx
Join the discussions on GitHub:
Check the examples/ directory in the repository:
- Phase 1 examples (RAG usage)
- Phase 2 examples (Planning)
- Phase 3 examples (Agents)
Didn't find your answer? Ask in Discussions or create an issue.
Adastrea Director | GitHub | Issues | Discussions
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