# This file was auto-generated by Fern from our API Definition.

from __future__ import annotations

import typing

import pydantic
from ..core.pydantic_utilities import IS_PYDANTIC_V2, update_forward_refs
from ..core.unchecked_base_model import UncheckedBaseModel
from .dynamic_variable_assignment import DynamicVariableAssignment
from .dynamic_variables_config_output import DynamicVariablesConfigOutput
from .pre_tool_speech_mode import PreToolSpeechMode
from .tool_call_sound_behavior import ToolCallSoundBehavior
from .tool_call_sound_type import ToolCallSoundType
from .tool_error_handling_mode import ToolErrorHandlingMode
from .tool_execution_mode import ToolExecutionMode


class ClientToolConfigOutput(UncheckedBaseModel):
    """
    A client tool is one that sends an event to the user's client to trigger something client side
    """

    name: str
    description: str = pydantic.Field()
    """
    Description of when the tool should be used and what it does.
    """

    response_timeout_secs: typing.Optional[int] = pydantic.Field(default=None)
    """
    The maximum time in seconds to wait for the tool call to complete. Must be between 1 and 120 seconds (inclusive).
    """

    disable_interruptions: typing.Optional[bool] = pydantic.Field(default=None)
    """
    If true, the user will not be able to interrupt the agent while this tool is running.
    """

    force_pre_tool_speech: typing.Optional[bool] = pydantic.Field(default=None)
    """
    DEPRECATED: use `pre_tool_speech` instead. If true, the agent will speak before the tool call.
    """

    pre_tool_speech: typing.Optional[PreToolSpeechMode] = pydantic.Field(default=None)
    """
    Controls whether the agent speaks before this tool is called. 'auto' (default) decides based on recent tool latency, 'force' always asks the agent to speak, 'off' fully opts out regardless of latency.
    """

    assignments: typing.Optional[typing.List[DynamicVariableAssignment]] = pydantic.Field(default=None)
    """
    Configuration for extracting values from tool responses and assigning them to dynamic variables
    """

    tool_call_sound: typing.Optional[ToolCallSoundType] = pydantic.Field(default=None)
    """
    Predefined tool call sound type to play during tool execution. If not specified, no tool call sound will be played.
    """

    tool_call_sound_behavior: typing.Optional[ToolCallSoundBehavior] = pydantic.Field(default=None)
    """
    Determines when the tool call sound should play. 'auto' only plays when there's pre-tool speech, 'always' plays for every tool call.
    """

    tool_error_handling_mode: typing.Optional[ToolErrorHandlingMode] = pydantic.Field(default=None)
    """
    Controls how tool errors are processed before being shared with the agent. 'auto' determines handling based on tool type (summarized for native integrations, hide for others), 'summarized' sends an LLM-generated summary, 'passthrough' sends the raw error, 'hide' does not share the error with the agent.
    """

    parameters: typing.Optional["ObjectJsonSchemaPropertyOutput"] = pydantic.Field(default=None)
    """
    Schema for any parameters to pass to the client
    """

    expects_response: typing.Optional[bool] = pydantic.Field(default=None)
    """
    If true, calling this tool should block the conversation until the client responds with some response which is passed to the llm. If false then we will continue the conversation without waiting for the client to respond, this is useful to show content to a user but not block the conversation
    """

    dynamic_variables: typing.Optional[DynamicVariablesConfigOutput] = pydantic.Field(default=None)
    """
    Configuration for dynamic variables
    """

    execution_mode: typing.Optional[ToolExecutionMode] = pydantic.Field(default=None)
    """
    Determines when and how the tool executes: 'immediate' executes the tool right away when requested by the LLM, 'post_tool_speech' waits for the agent to finish speaking before executing, 'async' runs the tool in the background without blocking - best for long-running operations.
    """

    if IS_PYDANTIC_V2:
        model_config: typing.ClassVar[pydantic.ConfigDict] = pydantic.ConfigDict(extra="allow", frozen=True)  # type: ignore # Pydantic v2
    else:

        class Config:
            frozen = True
            smart_union = True
            extra = pydantic.Extra.allow


from .object_json_schema_property_output import ObjectJsonSchemaPropertyOutput  # noqa: E402, I001

update_forward_refs(ClientToolConfigOutput)
