GraphDreamer is a PyTorch-based system for generating compositional 3D scenes from scene graphs. It implements a coarse-to-fine approach where objects are represented as implicit signed distance functions (SDFs) and optimized using gradient signals from 2D diffusion models (DeepFloyd IF for coarse stage, Stable Diffusion for refinement). The system takes text prompts describing objects and their relationships, constructs a scene graph, and generates 3D meshes representing the composed scene. Architecture follows the threestudio framework with modular components for data handling, geometry, materials, guidance, rendering, and system orchestration. Key entry points are in launch.py which supports training, validation, testing, and export modes via command-line interface.