feat: introduce GRPO GPU fallback support, enhance training script with warmstart tagging, and add learning rate parameter for improved training flexibility

feat: enhance SFT training process with new tokenization method, implement custom trainer class for loss computation, and update README with GRPO launcher details for Unsloth LoRA integration

fix: update README with SFT training configuration details, modify modal training scripts to disable assistant-only loss and packing for compatibility, and adjust test assertions to reflect these changes

feat: introduce reward ablation configurations for enhanced training flexibility, implement YAML loading with extends support, and add reward variant tracking in training scripts

feat: enhance reward configuration management with new logging functions, add parallel Modal training guidelines to documentation, and improve reward config hashing for deterministic behavior

feat: update README with GPU-utilization tuning instructions, enhance modal training script with run name parameter, and modify GRPO configuration for trace logging and vLLM settings

feat: enhance CyberSecurity_OWASP observation model with scenario prompt, improve GRPO batch configuration validation, and add scenario grouping for adaptive difficulty curriculum

feat: add episode trace fingerprinting for improved trace logging and update reward penalties in GRPO configuration

feat: enhance scenario authoring and caching mechanisms, update action submission terminology, and improve reward configuration for CyberSecurity_OWASP environment

feat: enhance training image setup and add startup notice for Modal execution, improve dependency installation process, and implement training heartbeat for monitoring

feat: update training configuration and documentation for Modal execution, including new model integration and enhanced tracking utilities

feat: implement RL environment server with training infrastructure and Modal integration

feat: integrate Trackio for experiment tracking and add Modal training infrastructure with environment and test utilities.

feat: implement core RL training infrastructure and architecture documentation