"""Agent event dataclasses — emitted during run_stream() and forwarded to WebSocket clients."""

from dataclasses import dataclass, field


@dataclass
class ToolStarted:
    """Emitted immediately when a tool call begins, before execution completes."""

    tool_name: str
    arguments: dict
    is_subagent: bool = False   # True when emitted from inside run_ephemeral


@dataclass
class ToolEvent:
    """Emitted when a tool call finishes — carries the result."""

    tool_name: str
    arguments: dict
    result: str
    success: bool
    is_subagent: bool = False   # True when emitted from inside run_ephemeral


@dataclass
class TextDelta:
    """A chunk of text from the streaming LLM response."""

    delta: str


@dataclass
class ThinkingDelta:
    """A chunk of thinking/reasoning text from the streaming LLM response."""

    delta: str


@dataclass
class ThinkingEnd:
    """Marks the end of the thinking phase."""


@dataclass
class StreamEnd:
    """Marks the end of the streaming response."""

    full_content: str
    context_tokens: int | None = None   # total tokens used in this turn
    max_context_tokens: int = 0         # ollama_num_ctx from config


@dataclass
class ContextCompressed:
    """Emitted after context compression runs successfully."""

    messages_before: int
    messages_after: int


@dataclass
class TurnThinking:
    """Full thinking/reasoning block from a tool-calling turn (complete() response).

    Unlike ThinkingDelta (which streams chunks), this carries the full text at once
    because complete() is non-streaming. Emitted before tool calls for that turn.
    is_subagent=True when emitted from run_ephemeral().
    """

    thinking: str
    is_subagent: bool = False


AgentEvent = (
    ToolStarted | ToolEvent | TextDelta | ThinkingDelta | ThinkingEnd
    | StreamEnd | ContextCompressed | TurnThinking
)