RAGEN / scripts /convert_rl_to_sft_rubikscube.py
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#!/usr/bin/env python3
"""
Convert RL eval trajectories from Rubik's Cube 2x2 into LLM SFT-ready chat data.
Input: runs/<exp>/trajectories/step_XXXXXX/trajectories.jsonl
Output: runs/<exp>/sft/step_XXXXXX_sft.jsonl
Each output JSON line contains:
- messages: [{role: system|user|assistant, content: str}, ...]
- meta: {episode_return: float, episode_success: bool, global_step: int}
We mirror the FrozenLake converter structure:
- system: "You're a helpful assistant. "
- user: env_instruction + per-turn state blocks
- assistant: tag-only actions, one per step
- user: reward after each action
"""
import argparse
import json
from pathlib import Path
from typing import List, Tuple
try:
import yaml # type: ignore
except Exception:
yaml = None
# Rubik's 2x2 actions (env uses 1..12; PPO wrapper stores 0..11)
RUBIK_ACTIONS = [
"U", "U'", "D", "D'", "L", "L'", "R", "R'", "F", "F'", "B", "B'",
]
COLORS = ['W', 'O', 'G', 'R', 'B', 'Y']
def load_env_instruction_and_cfg(repo_root: Path) -> Tuple[str, int, str, bool, int]:
"""Load RubiksCube2x2 env instruction and base agent_proxy configs.
Returns: (instruction, max_tokens, action_sep, enable_think, max_actions)
"""
instruction = (
"You are solving a 2x2 Rubik's Cube (Pocket Cube). The goal is to restore the cube so that each of the faces consists of a single, unique color.\n"
"Available actions use standard Singmaster notation for face rotations: U, U', D, D', L, L', R, R', F, F', B, B'.\n"
"- Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).\n"
"- Modifiers: A letter alone means 90° clockwise (e.g., 'R'). A letter with prime (') means 90° counter-clockwise (e.g., \"R'\")."
"Respond with a sequence of actions separated by \"||\".\n"
"Example: <answer>U</answer>\n\n"
"Your available actions are:\n"
"U, U', D, D', L, L', R, R', F, F', B, B'\n"
"You can make up to 20 actions, separated by the action separator \" || \"\n"
)
max_tokens = 96
action_sep = "||"
enable_think = True
max_actions = 20
if yaml is None:
return instruction, max_tokens, action_sep, enable_think, max_actions
# envs.yaml
envs_yaml = repo_root / "config" / "envs.yaml"
if envs_yaml.exists():
try:
with open(envs_yaml, "r", encoding="utf-8") as f:
envs = yaml.safe_load(f)
if isinstance(envs, dict) and "custom_envs" in envs and "RubiksCube2x2" in envs["custom_envs"]:
e = envs["custom_envs"]["RubiksCube2x2"]
instruction = e.get("env_instruction", instruction)
max_tokens = int(e.get("max_tokens", max_tokens))
max_actions = int(e.get("max_actions_per_traj", max_actions))
except Exception:
pass
# base.yaml
base_yaml = repo_root / "config" / "base.yaml"
if base_yaml.exists():
try:
with open(base_yaml, "r", encoding="utf-8") as f:
base_cfg = yaml.safe_load(f)
ap = base_cfg.get("agent_proxy", {}) if isinstance(base_cfg, dict) else {}
action_sep = ap.get("action_sep", action_sep)
enable_think = bool(ap.get("enable_think", enable_think))
except Exception:
pass
return instruction, max_tokens, action_sep, enable_think, max_actions
def decode_state_to_text(state_vec: List[float]) -> str:
"""Decode one-hot length 24*6 vector into sticker letters.
Returns a compact textual block listing each face in order: U, L, F, R, B, D.
"""
if not state_vec:
return ""
n = len(state_vec)
if n % len(COLORS) != 0:
return ""
n_stickers = n // len(COLORS)
if n_stickers != 24:
# Unknown shape; still try to decode row-wise
pass
# decode one-hot to color letter per sticker
stickers: List[str] = []
for i in range(n_stickers):
base = i * len(COLORS)
cell = state_vec[base: base + len(COLORS)]
idx = max(range(len(COLORS)), key=lambda k: cell[k])
c = COLORS[idx] if 0 <= idx < len(COLORS) else '?'
stickers.append(c)
# format faces (4 stickers per face)
faces = [stickers[i*4:(i+1)*4] for i in range(6)]
face_names = ["Up (U)", "Left (L)", "Front (F)", "Right (R)", "Back (B)", "Down (D)"]
lines = ["=== Rubik's Cube 2x2 State ===\n"]
for name, face in zip(face_names, faces):
lines.append(f"{name}: [{face[0]}, {face[1]}] \n [{face[2]}, {face[3]}]")
lines.append("\nAvailable actions: \n" + ", ".join(RUBIK_ACTIONS))
return "\n".join(lines)
def build_messages_for_episode(
states: List[List[float]],
actions: List[int],
rewards: List[float],
instruction: str,
max_tokens: int,
action_sep: str,
enable_think: bool,
max_actions: int,
) -> List[dict]:
messages = [
{"role": "system", "content": "You're a helpful assistant. "},
{"role": "user", "content": instruction},
]
total_actions = len(actions)
for t, state in enumerate(states):
state_text = decode_state_to_text(state)
actions_left = max(0, max_actions - t)
format_prompt = (
"<think> [Your thoughts] </think> <answer> [your answer] </answer>"
if enable_think
else "<answer> [your answer] </answer>"
)
length_prompt = f"Max response length: {max_tokens} words (tokens)."
messages[-1]["content"] += (
f"\nTurn {t + 1}:\n"
f"State:\n{state_text}\n"
f"\nWhat is your next move?\n"
f"You have {actions_left} actions left. Always output: {format_prompt}"
f"with no extra text. {length_prompt}"
)
if t < total_actions:
a = actions[t]
a_name = RUBIK_ACTIONS[int(a)] if 0 <= int(a) < len(RUBIK_ACTIONS) else str(a)
if enable_think:
assistant_text = f"<think> </think><answer>{a_name}</answer>"
else:
assistant_text = f"<answer>{a_name}</answer>"
messages.append({"role": "assistant", "content": assistant_text})
r = rewards[t] if t < len(rewards) else 0.0
messages.append({"role": "user", "content": f"Reward:\n{r}\n"})
# import pdb;pdb.set_trace()
return messages[:-1]
def find_latest_step_dir(traj_root: Path) -> Path:
step_dirs = [p for p in traj_root.iterdir() if p.is_dir() and p.name.startswith("step_")]
if not step_dirs:
raise FileNotFoundError(f"No step_* directories under {traj_root}")
step_dirs.sort(key=lambda p: int(p.name.split("_")[-1]))
return step_dirs[-1]
def convert_file(step_dir: Path, output_dir: Path, repo_root: Path, include_failed: bool, max_actions_cap: int | None) -> Path:
traj_path = step_dir / "trajectories.jsonl"
metrics_path = step_dir / "metrics.json"
if not traj_path.exists():
raise FileNotFoundError(f"Missing trajectories.jsonl at {traj_path}")
instruction, max_tokens, action_sep, enable_think, default_max_actions = load_env_instruction_and_cfg(repo_root)
max_actions = int(max_actions_cap) if max_actions_cap is not None else int(default_max_actions)
output_dir.mkdir(parents=True, exist_ok=True)
out_path = output_dir / f"{step_dir.name}_sft.jsonl"
# Read global step from metrics if available
global_step = None
if metrics_path.exists():
try:
with open(metrics_path, "r", encoding="utf-8") as f:
m = json.load(f)
global_step = m.get("global_step")
except Exception:
pass
written = 0
with open(traj_path, "r", encoding="utf-8") as fin, open(out_path, "w", encoding="utf-8") as fout:
for line in fin:
line = line.strip()
if not line:
continue
traj = json.loads(line)
ep_success = bool(traj.get("episode_success", False))
if (not include_failed) and (not ep_success):
continue
states = traj.get("states", [])
actions = traj.get("actions", [])
rewards = traj.get("rewards", [])
if len(actions) > max_actions:
continue
messages = build_messages_for_episode(
states=states,
actions=actions,
rewards=rewards,
instruction=instruction,
max_tokens=max_tokens,
action_sep=action_sep,
enable_think=enable_think,
max_actions=max_actions,
)
record = {
"messages": messages,
"meta": {
"episode_return": traj.get("episode_return", None),
"episode_success": ep_success,
"global_step": global_step,
},
}
fout.write(json.dumps(record, ensure_ascii=False) + "\n")
written += 1
if written == 0:
with open(out_path, "w", encoding="utf-8"):
pass
return out_path
def main():
parser = argparse.ArgumentParser(description="Convert Rubik's Cube 2x2 RL trajectories to LLM SFT chat JSONL")
parser.add_argument("run_dir", help="Path to the run directory (contains trajectories/)")
parser.add_argument("--step", default=None, help="Specific step directory name (e.g., step_123456)")
parser.add_argument("--include_failed", action="store_true", help="Include failed episodes in SFT data")
parser.add_argument("--max_actions", type=int, default=None, help="Override max actions cap (default from envs.yaml)")
args = parser.parse_args()
repo_root = Path(__file__).resolve().parents[1]
run_dir = Path(args.run_dir)
traj_root = run_dir / "trajectories"
if not traj_root.exists():
raise FileNotFoundError(f"Not found trajectories directory: {traj_root}")
step_dir = traj_root / args.step if args.step else find_latest_step_dir(traj_root)
output_dir = run_dir / "sft"
out_path = convert_file(step_dir=step_dir, output_dir=output_dir, repo_root=repo_root, include_failed=args.include_failed, max_actions_cap=args.max_actions)
print(f"SFT data written to: {out_path}")
if __name__ == "__main__":
main()