chore: track binary assets with git-lfs

feat(v2): implement multi-step environment with PaperState and per-step rewards

feat(v2): filter None fields from OrigamiAction in client step payload

feat(v2): update train_grpo.py for step-level prompts and per_step_reward

feat(v2): update OrigamiAction/Observation/State for multi-step mode

feat(v2): add step_reward.py — per-step Kawasaki/Maekawa/coverage reward

feat(v2): add max_folds to tasks + waterbomb_base + map_fold tasks

feat(v2): add extract_crease_json and valid_crease reward to training/reward.py

feat(v2): port PaperState to origami_server/engine/paper_state.py

chore(v2): add shapely dependency for PaperState intersection detection

feat(v2): port CreaseGraph to origami_server/engine/graph.py

docs: add V2 handoff and plan documents

feat: add hackathon demo script and result charts

feat: add Modal eval script for GRPO checkpoints

feat: update origami viewer UI

feat: expand reward pipeline and GRPO training config

chore: ignore pycache, outputs, and trainer state

chore: add HF Spaces frontmatter to README

revert: restore train_origami.ipynb to Prasanna's exact version

chore: restore Prasanna's notebook, add Modal launch section

feat: Railway deployment + multi-task GRPO + Modal B200 training

Update training notebook

Add MAX_CONCURRENT_ENVS, sync latest changes

Update viewer

Add GRPO training notebook + Dockerfile for cloud training (#1)

Rename server/ to origami_server/ to avoid module name conflict with uvicorn.server

Match optigami Dockerfile exactly

Debug: unbuffered output + debug logging to see actual error

Origami RL environment with Three.js viewer

initial commit