.env.example

# KernelBench RL Environment Variables
# Copy this file to .env and fill in your values:
#   cp .env.example .env
#
# Architecture:
#   - Kernel evaluation: Modal (remote GPUs)
#   - Training/inference: Tinker (remote GPUs)
#   - RAG embeddings: Local (MLX on Apple Silicon, or CUDA/CPU elsewhere)

# =============================================================================
# Required
# =============================================================================

# Tinker API key for distributed training and sampling
# Get your key from: https://console.tinker.thinkingmachines.ai
TINKER_API_KEY=your-api-key-here

# Modal tokens for remote GPU kernel evaluation
# Get from: https://modal.com/settings
# MODAL_TOKEN_ID=your-modal-token-id
# MODAL_TOKEN_SECRET=your-modal-token-secret

# HuggingFace token for downloading models (required for MLX embeddings)
# Get from: https://huggingface.co/settings/tokens
HF_TOKEN=your-huggingface-token-here

# =============================================================================
# RAG Configuration
# =============================================================================

# Use MLX for embeddings on Apple Silicon (default: auto-detect)
# Options: "mlx" (Apple Silicon), "cuda" (NVIDIA GPU), "cpu" (fallback)
# RAG_DEVICE=mlx

# =============================================================================
# Optional
# =============================================================================

# Path to KernelBench repository (usually auto-detected from installed package)
# KERNELBENCH_ROOT=/path/to/KernelBench

# CUDA device selection (only for CUDA environments)
# CUDA_VISIBLE_DEVICES=0