Welcome to the WarMatrix Command Center. Follow this guide to initialize the tactical simulation suite and prepare for deployment.
Before proceeding, ensure your station is equipped with the following:
- Node.js: v20 or higher.
- Python: v3.10 to v3.12 (v3.12 recommended).
- Git: Required for repository management and model acquisition.
- NVIDIA GPU: Required for high-performance local AI inference (VRAM: 8GB+ recommended, 4GB minimum with quantization).
Initialize the primary interface and the simulation engine.
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Frontend Installation:
# Install dependencies npm install -
Simulation Backend Setup:
# Navigate to root (if not already there) cd WarMatrix # Create and activate virtual environment python -m venv .venv & .\.venv\Scripts\Activate.ps1 # (1) Install core simulation engine requirements # Installs: numpy, fastapi, uvicorn, pydantic pip install -r backend/requirements.txt # (2) Install AI server requirements (GPU/LLM inference stack) # Installs: torch (CUDA 12.8), transformers, peft, bitsandbytes, accelerate # NOTE: Skip this step if you are using LM Studio (Method C in Phase 3). pip install -r ai_server/requirements.txt
WarMatrix uses a dedicated AI server for tactical synthesis and scenario generation. Choose the method that best fits your hardware capabilities:
Use this if you want to get up and running quickly using a standard virtual environment. 👉 View Quick Start Guide
Use this for the best performance. Optimized for NVIDIA GPUs using Conda and Unsloth for ultra-fast response times. 👉 View High-Performance Guide
Use this if you are VRAM-constrained or want to run the model on a separate machine in your network via LM Studio. 👉 View LM Studio Guide
Once all components are configured, you can launch the entire suite concurrently:
# Launch both Frontend and Backend concurrently
npm run devThe Command Console will be available at http://localhost:3000.
Document maintained by the WarMatrix Operational Command.