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# Copyright (c) 2021-2026 DexForce Technology Co., Ltd.
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# Licensed under the Apache License, Version 2.0 (the "License");
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#     http://www.apache.org/licenses/LICENSE-2.0
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from __future__ import annotations

from typing import Dict, Any, Callable
import torch


class BaseAlgorithm:
    """Base class for RL algorithms.

    Algorithms must implement buffer initialization, rollout collection, and
    policy update. Trainer depends only on this interface to remain
    algorithm-agnostic.
    """

    device: torch.device

    def initialize_buffer(
        self, num_steps: int, num_envs: int, obs_dim: int, action_dim: int
    ) -> None:
        """Initialize internal buffer(s) required by the algorithm."""
        raise NotImplementedError

    def collect_rollout(
        self,
        env,
        policy,
        obs: torch.Tensor,
        num_steps: int,
        on_step_callback: Callable | None = None,
    ) -> Dict[str, Any]:
        """Collect trajectories and return logging info (e.g., reward components)."""
        raise NotImplementedError

    def update(self) -> Dict[str, float]:
        """Update policy using collected data and return training losses."""
        raise NotImplementedError
