"""
Data models for the SRE OpenEnv environment.

Adaptive implementation that uses Pydantic BaseModel in OpenEnv 0.1 (Python 3.11)
and dataclasses in legacy environments (Python 3.9) to ensure cross-version 
compatibility and avoid inheritance conflicts.
"""

from __future__ import annotations

import os
import sys
from dataclasses import dataclass, field, asdict
from typing import Literal, List, Optional, Any, TypeVar, Union, Dict
from pydantic import BaseModel, Field

# Try to import from openenv.core (v0.1) or openenv_core (legacy/shim)
try:
    from openenv.core.env_server import Action, Observation, State
    # If we got here and it's 0.1, these are likely Pydantic models
    IS_PYDANTIC = issubclass(Action, BaseModel)
except (ImportError, TypeError):
    try:
        from openenv_core.env_server import Action, Observation, State
        # In legacy, these are usually dataclasses
        IS_PYDANTIC = False
    except ImportError:
        # Fallback if neither is available
        class Action: pass
        class Observation: pass
        class State: pass
        IS_PYDANTIC = False


if IS_PYDANTIC:
    # --- Pydantic v2 implementation (Modern) ---
    class SREAction(Action):
        action_type: Literal["run_shell", "patch_file"] = "run_shell"
        command: str = ""
        file_path: str = ""
        content: str = ""

    class SREObservation(Observation):
        stdout: str = ""
        stderr: str = ""
        exit_code: int = 0
        truncated: bool = False
        message: str = ""
        
        # Necessary for legacy server extraction
        reward: Optional[float] = 0.0
        done: bool = False

    class SREState(State):
        episode_id: str = ""
        step_count: int = 0
        task_id: str = ""
        task_name: str = ""
        description: str = ""
        difficulty: str = ""
        max_steps: int = 30
        is_done: bool = False
        current_reward: float = 0.0
        action_history: List[str] = Field(default_factory=list)

else:
    # --- Dataclass implementation (Legacy) ---
    @dataclass
    class SREAction(Action):
        action_type: Literal["run_shell", "patch_file"] = "run_shell"
        command: str = ""
        file_path: str = ""
        content: str = ""

        def __post_init__(self):
            # Compatibility for legacy initialization
            pass

    @dataclass
    class SREObservation(Observation):
        stdout: str = ""
        stderr: str = ""
        exit_code: int = 0
        truncated: bool = False
        message: str = ""
        
        # Necessary for legacy server extraction
        reward: Optional[float] = 0.0
        done: bool = False

    @dataclass
    class SREState(State):
        episode_id: str = ""
        step_count: int = 0
        task_id: str = ""
        task_name: str = ""
        description: str = ""
        difficulty: str = ""
        max_steps: int = 30
        is_done: bool = False
        current_reward: float = 0.0
        action_history: List[str] = field(default_factory=list)

def to_dict(obj: Any) -> Dict[str, Any]:
    """
    Polymorphic helper to convert either a Pydantic model or a dataclass to a dict.
    Useful for cross-version compatibility with openenv-core.
    """
    if isinstance(obj, BaseModel):
        # Pydantic v2 uses model_dump, v1 uses dict
        return obj.model_dump() if hasattr(obj, "model_dump") else obj.dict()
    elif hasattr(obj, "__dataclass_fields__"):
        return asdict(obj)
    elif isinstance(obj, dict):
        return obj
    else:
        # Fallback for other types
        return dict(obj) if hasattr(obj, "__dict__") else obj

# Add Dict to imports