Quick Start
This guide will help you get QuestFoundry up and running.
Installation
Prerequisites
Python 3.11 or later
uv package manager
Install from Source
# Clone repository
git clone https://github.com/pvliesdonk/questfoundry.git
cd questfoundry
# Install with uv
uv sync
# Verify installation
uv run qf version
Basic Usage
Compile Domain to Code
QuestFoundry uses MyST files as the source of truth. Compile them to Python:
qf compile
This generates:
Pydantic models from
ontology/Role configurations from
roles/LangGraph definitions from
loops/
Run a Workflow
Start an interactive story creation session:
qf ask "Create a mystery story set in a Victorian mansion"
The Showrunner will orchestrate the 8 roles to create your story.
Configure LLM Provider
QuestFoundry supports multiple LLM providers. Configure in your project:
# Use Ollama (local)
qf config set provider ollama
qf config set model qwen3:8b
# Use OpenAI
qf config set provider openai
qf config set model gpt-4o
Example Project
See examples/mystery_manor/ for a complete example:
cd examples/mystery_manor
# Inspect the cold store
sqlite3 project.qfdb "SELECT anchor, title FROM sections;"
# Read a scene
sqlite3 project.qfdb "SELECT content FROM sections WHERE anchor='scene_1';"
Next Steps
Read the Architecture to understand the system design
Explore the 8 Roles and their responsibilities
Check the API Reference for programmatic usage