"""Subtext Arena client."""
from __future__ import annotations

from typing import Dict

from openenv.core import EnvClient
from openenv.core.client_types import StepResult
from openenv.core.env_server.types import State

from .models import SubtextArenaAction, SubtextArenaObservation


class SubtextArenaEnv(
    EnvClient[SubtextArenaAction, SubtextArenaObservation, State]
):
    """Client for Subtext Arena.

    Example:
        >>> with SubtextArenaEnv(base_url="http://localhost:8000") as env:
        ...     obs = env.reset().observation
        ...     # Inspect transcript first
        ...     obs = env.step(SubtextArenaAction(tool="get_transcript")).observation
        ...     # Then check prosody on the full clip
        ...     obs = env.step(SubtextArenaAction(
        ...         tool="get_prosody_features",
        ...         tool_args={},
        ...     )).observation
        ...     # Submit a belief
        ...     result = env.step(SubtextArenaAction(
        ...         tool="submit_belief",
        ...         tool_args={"label": "sarcastic", "confidence": 0.85},
        ...     ))
        ...     print("done:", result.done, "reward:", result.reward)
    """

    def _step_payload(self, action: SubtextArenaAction) -> Dict:
        return {
            "tool": action.tool,
            "tool_args": action.tool_args or {},
        }

    def _parse_result(self, payload: Dict) -> StepResult[SubtextArenaObservation]:
        obs_data = payload.get("observation", {}) or {}
        observation = SubtextArenaObservation(
            clip_id=obs_data.get("clip_id", ""),
            speaker=obs_data.get("speaker", ""),
            duration_s=float(obs_data.get("duration_s", 0.0) or 0.0),
            is_pivot=bool(obs_data.get("is_pivot", False)),
            tool_used=obs_data.get("tool_used", ""),
            tool_output=obs_data.get("tool_output", ""),
            step=int(obs_data.get("step", 0) or 0),
            max_steps=int(obs_data.get("max_steps", 6) or 6),
            audio_calls_so_far=int(obs_data.get("audio_calls_so_far", 0) or 0),
            error=obs_data.get("error"),
            done=payload.get("done", False),
            reward=payload.get("reward"),
            metadata=obs_data.get("metadata", {}) or {},
        )
        return StepResult(
            observation=observation,
            reward=payload.get("reward"),
            done=payload.get("done", False),
        )

    def _parse_state(self, payload: Dict) -> State:
        return State(
            episode_id=payload.get("episode_id"),
            step_count=int(payload.get("step_count", 0) or 0),
        )