File size: 9,553 Bytes
70a7f67 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 | #!/usr/bin/env python3
"""
Convert RL test trajectories from Blackjack into LLM SFT-ready language trajectories.
Uses pre-recorded text_states from the training script to ensure exact match with environment feedback.
Input: runs/<exp>/trajectories/step_XXXXXX/trajectories.jsonl
Output: runs/<exp>/sft/step_XXXXXX_sft.jsonl
"""
import argparse
import json
import os
from pathlib import Path
from typing import List, Tuple
try:
import yaml # type: ignore
except Exception:
yaml = None
ACTION_LOOKUP = {0: "Stick", 1: "Hit"}
def load_env_instruction_and_cfg(repo_root: Path) -> Tuple[str, int, bool, str, int]:
"""Load Blackjack env_instruction, max_tokens, enable_think, action_sep, max_actions.
Fallbacks are provided if YAML is unavailable or keys are missing.
"""
instruction = (
"You are playing Blackjack against a dealer. The dealer must hit on 16 or less and stand on 17 or more.\n"
"Choose either Stick or Hit. Respond with a single action.\n"
"Example: <answer>Hit</answer>"
)
max_tokens = 64
enable_think = True
action_sep = "||"
max_actions = 10
if yaml is None:
instruction += (
"\nYour available actions are:\n"
"Stick, Hit\n"
f"You can make up to {max_actions} actions, separated by the action separator \" " + action_sep + " \"\n"
)
return instruction, max_tokens, enable_think, action_sep, max_actions
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):
bj = envs.get("Blackjack", {})
if isinstance(bj, dict):
instruction = bj.get("env_instruction", instruction)
max_tokens = int(bj.get("max_tokens", max_tokens))
max_actions = int(bj.get("max_actions_per_traj", max_actions))
except Exception:
pass
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
instruction += (
"\nYour available actions are:\n"
"Stick, Hit\n"
f"You can make up to {max_actions} actions, separated by the action separator \" " + action_sep + " \"\n"
)
return instruction, max_tokens, enable_think, action_sep, max_actions
def build_messages_for_episode(
text_states: List[str],
actions: List[int],
rewards: List[float],
instruction: str,
max_tokens: int,
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)
# 遍历每一步动作
for t in range(len(actions)):
# 获取当前步骤的文本状态
# text_states[0] 是初始状态, text_states[1] 是 action[0] 之后的状态
current_text_state = text_states[t]
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)."
# --- 核心修改：使用保存的文本状态并拼接 Question ---
turn_content = (
f"\nTurn {t + 1}:\n"
f"State:\n"
f"{current_text_state}\n" # text_state 已经包含了 === Blackjack Game State === 等内容
f"What is your next move?\n"
f"You have {actions_left} actions left. Always output: {format_prompt}"
f" with no extra text. Strictly follow this format. {length_prompt}"
)
# 追加到上一条 user 消息（如果是第一回合）或者新建 user 消息
if messages[-1]["role"] == "user":
messages[-1]["content"] += turn_content
else:
messages.append({"role": "user", "content": turn_content})
# 添加 Assistant 回复
action_id = int(actions[t])
action_name = ACTION_LOOKUP.get(action_id, "unknown")
assistant_text = (
f"<think></think><answer>{action_name}</answer>" if enable_think else f"<answer>{action_name}</answer>"
)
messages.append({"role": "assistant", "content": assistant_text})
# 添加 Reward 信息
reward_val = rewards[t]
messages.append({"role": "user", "content": f"Reward:\n{reward_val}\n"})
# 移除最后一条仅包含 Reward 的 User 消息（SFT 数据通常以 Assistant 结尾）
if messages[-1]["role"] == "user":
messages.pop()
return messages
def convert_file(step_dir: Path, output_dir: Path, repo_root: Path, include_failed: bool = False, max_actions: int = 10) -> 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, enable_think, action_sep, cfg_max_actions = load_env_instruction_and_cfg(repo_root)
if max_actions is None:
max_actions = cfg_max_actions
output_dir.mkdir(parents=True, exist_ok=True)
out_path = output_dir / f"{step_dir.name}_sft.jsonl"
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
# 读取新的 text_states 字段
text_states = traj.get("text_states", [])
actions = traj.get("actions", [])
rewards = traj.get("rewards", [])
# 兼容性检查：如果该轨迹是旧代码生成的（没有 text_states），则跳过
if not text_states:
# Silently skip or warn
continue
if len(actions) > max_actions:
continue
messages = build_messages_for_episode(
text_states=text_states,
actions=actions,
rewards=rewards,
instruction=instruction,
max_tokens=max_tokens,
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:
# 创建空文件以防报错，或者写入一个空数组
with open(out_path, "w", encoding="utf-8") as f:
pass
print("Warning: No trajectories converted. Check if input file has 'text_states' or if filtering is too strict.")
return out_path
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 main():
parser = argparse.ArgumentParser(description="Convert Blackjack 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_499712)")
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="Max actions cap for filtering and counter display")
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=args.max_actions)
print(f"SFT data written to: {out_path}")
if __name__ == "__main__":
main() |