scripts/convert_rl_to_sft_sudoku.py

#!/usr/bin/env python3
import argparse
import json
import math
from pathlib import Path
from typing import List, Tuple, Set, Dict

def infer_grid_size_from_state_len(n: int) -> int:
    """Given flattened one-hot length n = G*G*(G+1), solve for integer G."""
    for G in range(2, 17):
        if G * G * (G + 1) == n:
            return G
    raise ValueError(f"Cannot infer grid size from state length {n}")

def state_to_matrix(state_vec: List[float], G: int) -> List[List[int]]:
    """Convert one-hot vector to GxG integer matrix."""
    cell_dim = G + 1
    matrix = []
    for r in range(G):
        row = []
        for c in range(G):
            base = (r * G + c) * cell_dim
            cell_data = state_vec[base : base + cell_dim]
            # argmax to find value
            val = 0
            max_v = -1e9
            for k, v in enumerate(cell_data):
                if v > max_v:
                    max_v = v
                    val = k
            row.append(val)
        matrix.append(row)
    return matrix

def check_conflict(grid: List[List[int]], r: int, c: int, val: int, G: int) -> bool:
    """Check if placing val at (r,c) causes a conflict in current grid."""
    if val == 0:
        return False
        
    # Row check
    for j in range(G):
        if j != c and grid[r][j] == val:
            return True
    # Col check
    for i in range(G):
        if i != r and grid[i][c] == val:
            return True
    # Box check
    box_size = int(math.sqrt(G))
    br, bc = (r // box_size) * box_size, (c // box_size) * box_size
    for i in range(br, br + box_size):
        for j in range(bc, bc + box_size):
            if (i, j) != (r, c) and grid[i][j] == val:
                return True
    return False

def get_valid_moves(grid: List[List[int]], G: int) -> Dict[Tuple[int, int], List[int]]:
    """Compute valid numbers for all empty cells."""
    valid_moves = {}
    box_size = int(math.sqrt(G))
    
    for r in range(G):
        for c in range(G):
            if grid[r][c] == 0:
                possibles = []
                for v in range(1, G + 1):
                    is_row_ok = all(grid[r][j] != v for j in range(G))
                    is_col_ok = all(grid[i][c] != v for i in range(G))
                    br, bc = (r // box_size) * box_size, (c // box_size) * box_size
                    is_box_ok = True
                    for i in range(br, br + box_size):
                        for j in range(bc, bc + box_size):
                            if grid[i][j] == v:
                                is_box_ok = False
                                break
                    if is_row_ok and is_col_ok and is_box_ok:
                        possibles.append(v)
                if possibles:
                    valid_moves[(r + 1, c + 1)] = possibles # 1-indexed keys
    return valid_moves

def render_ascii_board(grid: List[List[int]], initial_grid: List[List[int]], G: int) -> str:
    """Render the board in the rich ASCII format seen in logs."""
    box_size = int(math.sqrt(G))
    lines = []
    
    header = "=" * 50 + "\nSUDOKU PUZZLE\n" + "=" * 50
    lines.append(header)

    for r in range(G):
        if r > 0 and r % box_size == 0:
            row_sep = []
            for c in range(G):
                if c > 0 and c % box_size == 0:
                    row_sep.append("-") 
                row_sep.append("----")
            lines.append("-" * (G * 4 + int(G/box_size)*2))

        row_str = []
        for c in range(G):
            if c > 0 and c % box_size == 0:
                row_str.append("|")
            
            val = grid[r][c]
            is_init = (initial_grid[r][c] != 0)
            
            if val == 0:
                cell_str = " . "
            else:
                is_conflict = check_conflict(grid, r, c, val, G)
                if is_conflict and not is_init:
                    cell_str = f"*{val}*"
                elif is_init:
                    cell_str = f"[{val}]"
                else:
                    cell_str = f" {val} " # User placed
            
            row_str.append(cell_str)
        
        lines.append("".join(row_str))

    lines.append("\nLegend: [N]=initial cell, N=user-placed, *N*=conflict, .=empty")
    return "\n".join(lines)

def decode_action(action_id: int, G: int) -> Tuple[int, int, int]:
    """Map discrete id -> 1-indexed (row, col, num)."""
    row0 = action_id // (G * G)
    rem = action_id % (G * G)
    col0 = rem // G
    num = (rem % G) + 1
    return row0 + 1, col0 + 1, num

def build_messages_for_episode(
    states: List[List[float]],
    actions: List[int],
    rewards: List[float],
    max_tokens: int,
    max_actions: int,
) -> List[dict]:
    
    # Infer G from first state
    G = infer_grid_size_from_state_len(len(states[0]))
    box_size = int(math.sqrt(G))
    
    grid_history = [state_to_matrix(s, G) for s in states]
    initial_grid = grid_history[0] 
    
    sys_msg = "You're a helpful assistant. "
    
    intro_prompt = (
        f"You are solving a Sudoku puzzle. Fill in the grid so that every row, column, "
        f"and {box_size}x{box_size} box contains the numbers 1-{G} without repetition.\n"
        "Initial cells are shown in [brackets] and cannot be modified. Empty cells are shown as dots (.).\n"
        "Place numbers one at a time using the format: <answer>place 1 at row 2 col 3</answer> or <answer>1,2,3</answer>\n"
        "The environment will provide feedback on valid/invalid moves and show conflicts if any occur.\n"
    )

    messages = [
        {"role": "system", "content": sys_msg},
        {"role": "user", "content": intro_prompt},
    ]

    # Main loop iterates over steps
    for t in range(len(states)):
        # If this state corresponds to a step where no action was taken (end of episode), stop
        if t >= len(actions):
            break

        current_grid = grid_history[t]
        actions_left = max(0, max_actions - t)
        
        # --- 1. Prepare Reward String (Combined into this User turn) ---
        # If t > 0, we have a reward from the previous action (at t-1)
        reward_prefix = ""
        if t > 0:
            prev_reward = rewards[t-1] if (t-1) < len(rewards) else 0.0
            # Double newline to separate from the previous content logically
            reward_prefix = f"Reward:\n{prev_reward}\n\n"

        # --- 2. Render Board ---
        board_str = render_ascii_board(current_grid, initial_grid, G)
        
        # --- 3. Calc Valid Moves ---
        valid_map = get_valid_moves(current_grid, G)
        valid_str_lines = ["\n💡 VALID NUMBERS FOR EMPTY CELLS:"]
        sorted_keys = sorted(valid_map.keys())
        if not sorted_keys:
            valid_str_lines.append("   (None)")
        else:
            count = 0
            for (r, c) in sorted_keys:
                vals = valid_map[(r,c)]
                valid_str_lines.append(f"   - ({r},{c}): {vals}")
                count += 1
                if count > 15: 
                    valid_str_lines.append("   ... (list truncated)")
                    break
        # valid_section = "\n".join(valid_str_lines)
        valid_section = ""

        # --- 4. Stats ---
        total_cells = G * G
        filled_cells = sum(1 for r in range(G) for c in range(G) if current_grid[r][c] != 0)
        init_cells = sum(1 for r in range(G) for c in range(G) if initial_grid[r][c] != 0)
        placed_cells = filled_cells - init_cells
        if placed_cells < 0: placed_cells = 0

        stats_section = (
            f"\nProgress: {filled_cells}/{total_cells} cells filled ({init_cells} initial, {placed_cells} placed)\n"
            f"Steps: {t}/{max_actions}"
        )

        # --- 5. Construct User Content ---
        turn_header = f"Turn {t + 1}:\nState:"
        
        constraint_prompt = (
            f"You have {actions_left} actions left. Always output: <think> [Your thoughts] </think> "
            f"<answer> [your answer] </answer> with no extra text. Strictly follow this format. "
            f"Max response length: {max_tokens} words (tokens)."
        )

        # COMBINE: Reward + Header + Board + Valid + Stats + Constraint
        full_user_text = (
            f"{reward_prefix}{turn_header}\n"
            f"{board_str}{valid_section}\n{stats_section}\n{constraint_prompt}"
        )

        # --- 6. Append to Messages ---
        if t == 0:
            # First turn: Append to the "Intro" user message
            messages[-1]["content"] += ("\n" + full_user_text)
        else:
            # Subsequent turns: New User message containing (Reward + State)
            messages.append({"role": "user", "content": full_user_text})

        # --- 7. Assistant Response ---
        r_act, c_act, n_act = decode_action(actions[t], G)
        ans_text = f"place {n_act} at row {r_act} col {c_act}"
        assistant_text = f"<think> </think><answer>{ans_text}</answer>"
        messages.append({"role": "assistant", "content": assistant_text})

    return messages

def convert_file(step_dir: Path, output_dir: Path, include_failed: bool = False, max_actions_override: int | None = 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}")

    max_tokens = 150
    
    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

            states = traj.get("states", [])
            actions = traj.get("actions", [])
            rewards = traj.get("rewards", [])

            if not states:
                continue

            G = infer_grid_size_from_state_len(len(states[0]))
            if max_actions_override is not None:
                eff_max = max_actions_override
            else:
                eff_max = 20 if G == 4 else int(G*G * 1.5)

            messages = build_messages_for_episode(
                states=states,
                actions=actions,
                rewards=rewards,
                max_tokens=max_tokens,
                max_actions=eff_max,
            )

            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

    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 Sudoku RL trajectories to LLM SFT chat JSONL (Rich Format, Merged Reward)")
    parser.add_argument("run_dir", help="Path to the run directory (contains trajectories/)")
    parser.add_argument("--step", default=None, help="Specific step directory name")
    parser.add_argument("--include_failed", action="store_true", help="Include failed episodes")
    parser.add_argument("--max_actions", type=int, default=None, help="Max actions cap display")
    args = parser.parse_args()

    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, 
        include_failed=args.include_failed, 
        max_actions_override=args.max_actions
    )
    print(f"SFT data written to: {out_path}")

if __name__ == "__main__":
    main()