"""Mutable counters and maps for one agent stream."""

from __future__ import annotations

from dataclasses import dataclass, field
from typing import Any


@dataclass
class AgentEventRelayState:
    """Tracks text, thinking steps, tool depth, and pending tool-call metadata.

    **Task span (`spanId`)** — ``active_span_id`` groups steps and tools for one
    open delegating ``task`` episode. ``active_task_run_id`` is the LangGraph
    ``run_id`` of that ``task`` so the span clears only when that run ends, not
    when child tools end. Open/close uses ``relay.task_span`` helpers.

    **Tool ↔ thinking link (`thinkingStepId`)** — Each tool run gets a thinking-row
    id (``tool_step_ids[run_id]``, emitted as ``data-thinking-step`` ``data.id``).
    ``tool_activity_metadata`` supplies ``metadata`` for ``tool-input-start`` /
    ``tool-input-available`` (``handlers.tool_start``) and
    ``tool-output-available`` (``handlers.tool_end``).
    """

    accumulated_text: str = ""
    current_text_id: str | None = None
    thinking_step_counter: int = 0
    tool_step_ids: dict[str, str] = field(default_factory=dict)
    completed_step_ids: set[str] = field(default_factory=set)
    last_active_step_id: str | None = None
    last_active_step_title: str = ""
    last_active_step_items: list[str] = field(default_factory=list)
    just_finished_tool: bool = False
    active_tool_depth: int = 0
    called_update_memory: bool = False
    current_reasoning_id: str | None = None
    pending_tool_call_chunks: list[dict[str, Any]] = field(default_factory=list)
    lc_tool_call_id_by_run: dict[str, str] = field(default_factory=dict)
    file_path_by_run: dict[str, str] = field(default_factory=dict)
    index_to_meta: dict[int, dict[str, str]] = field(default_factory=dict)
    ui_tool_call_id_by_run: dict[str, str] = field(default_factory=dict)
    current_lc_tool_call_id: dict[str, str | None] = field(
        default_factory=lambda: {"value": None}
    )
    # Open ``task`` delegation span (one id shared by nested activity); unset outside.
    active_span_id: str | None = None
    active_task_run_id: str | None = None
    # Span id minted when a ``task`` tool_call_chunk registers (before ``on_tool_start``).
    pending_task_span_by_lc: dict[str, str] = field(default_factory=dict)

    def span_metadata_if_active(self) -> dict[str, Any] | None:
        """``{"spanId": ...}`` when a span is active; ``None`` otherwise."""
        if self.active_span_id:
            return {"spanId": self.active_span_id}
        return None

    def tool_activity_metadata(
        self, *, thinking_step_id: str | None
    ) -> dict[str, Any] | None:
        """Build ``metadata`` for tool SSE and ``tool-call`` persistence.

        Contract (keys omitted when not applicable):

        - ``spanId`` (str): present while a task-delegation span is active
          (same value as ``span_metadata_if_active()``).
        - ``thinkingStepId`` (str): equals the thinking-step row ``id`` for this
          tool (``data-thinking-step`` payload ``data.id`` on the wire).

        Returns ``None`` if neither applies. Whitespace-only
        ``thinking_step_id`` is ignored.
        """
        out: dict[str, Any] = {}
        if self.active_span_id:
            out["spanId"] = self.active_span_id
        tid = (thinking_step_id or "").strip()
        if tid:
            out["thinkingStepId"] = tid
        return out if out else None

    @classmethod
    def for_invocation(
        cls,
        *,
        initial_step_id: str | None = None,
        initial_step_title: str = "",
        initial_step_items: list[str] | None = None,
    ) -> AgentEventRelayState:
        counter = 1 if initial_step_id else 0
        return cls(
            thinking_step_counter=counter,
            last_active_step_id=initial_step_id,
            last_active_step_title=initial_step_title,
            last_active_step_items=list(initial_step_items or []),
        )

    def next_thinking_step_id(self, step_prefix: str) -> str:
        self.thinking_step_counter += 1
        return f"{step_prefix}-{self.thinking_step_counter}"