# This file was auto-generated by Fern from our API Definition. import typing from ....core.client_wrapper import AsyncClientWrapper, SyncClientWrapper from ....core.request_options import RequestOptions from ....types.agent_workflow_request_model import AgentWorkflowRequestModel from .raw_client import AsyncRawDraftsClient, RawDraftsClient # this is used as the default value for optional parameters OMIT = typing.cast(typing.Any, ...) class DraftsClient: def __init__(self, *, client_wrapper: SyncClientWrapper): self._raw_client = RawDraftsClient(client_wrapper=client_wrapper) @property def with_raw_response(self) -> RawDraftsClient: """ Retrieves a raw implementation of this client that returns raw responses. Returns ------- RawDraftsClient """ return self._raw_client def create( self, agent_id: str, *, branch_id: str, conversation_config: typing.Dict[str, typing.Any], platform_settings: typing.Dict[str, typing.Any], workflow: AgentWorkflowRequestModel, name: str, tags: typing.Optional[typing.Sequence[str]] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> typing.Any: """ Create a new draft for an agent Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. branch_id : str The ID of the agent branch to use conversation_config : typing.Dict[str, typing.Any] Conversation config for the draft platform_settings : typing.Dict[str, typing.Any] Platform settings for the draft workflow : AgentWorkflowRequestModel Workflow for the draft name : str Name for the draft tags : typing.Optional[typing.Sequence[str]] Tags to help classify and filter the agent request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- typing.Any Successful Response Examples -------- from elevenlabs import ( AgentWorkflowRequestModel, AgentWorkflowRequestModelNodesValue_End, AstAndOperatorNodeInputChildrenItem_BooleanLiteral, ElevenLabs, WorkflowEdgeModelInput, WorkflowEdgeModelInputForwardCondition_Expression, WorkflowExpressionConditionModelInputExpression_AndOperator, ) client = ElevenLabs( api_key="YOUR_API_KEY", ) client.conversational_ai.agents.drafts.create( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", branch_id="agtbrch_8901k4t9z5defmb8vh3e9361y7nj", conversation_config={"key": "value"}, platform_settings={"key": "value"}, workflow=AgentWorkflowRequestModel( edges={ "entry_to_tool_a": WorkflowEdgeModelInput( source="entry_node", target="tool_node_a", forward_condition=WorkflowEdgeModelInputForwardCondition_Expression( expression=WorkflowExpressionConditionModelInputExpression_AndOperator( children=[ AstAndOperatorNodeInputChildrenItem_BooleanLiteral( value=True, ) ], ), ), ), "start_to_entry": WorkflowEdgeModelInput( source="start_node", target="entry_node", forward_condition=WorkflowEdgeModelInputForwardCondition_Expression( expression=WorkflowExpressionConditionModelInputExpression_AndOperator( children=[ AstAndOperatorNodeInputChildrenItem_BooleanLiteral( value=True, ) ], ), ), ), "tool_a_to_failure": WorkflowEdgeModelInput( source="tool_node_a", target="failure_node", forward_condition=WorkflowEdgeModelInputForwardCondition_Expression( expression=WorkflowExpressionConditionModelInputExpression_AndOperator( children=[ AstAndOperatorNodeInputChildrenItem_BooleanLiteral( value=True, ) ], ), ), ), "tool_a_to_tool_b": WorkflowEdgeModelInput( source="tool_node_a", target="tool_node_b", forward_condition=WorkflowEdgeModelInputForwardCondition_Expression( expression=WorkflowExpressionConditionModelInputExpression_AndOperator( children=[ AstAndOperatorNodeInputChildrenItem_BooleanLiteral( value=True, ) ], ), ), ), "tool_b_to_agent_transfer": WorkflowEdgeModelInput( source="tool_node_b", target="success_transfer", forward_condition=WorkflowEdgeModelInputForwardCondition_Expression( expression=WorkflowExpressionConditionModelInputExpression_AndOperator( children=[ AstAndOperatorNodeInputChildrenItem_BooleanLiteral( value=True, ) ], ), ), ), "tool_b_to_conversation": WorkflowEdgeModelInput( source="tool_node_b", target="success_conversation", forward_condition=WorkflowEdgeModelInputForwardCondition_Expression( expression=WorkflowExpressionConditionModelInputExpression_AndOperator( children=[ AstAndOperatorNodeInputChildrenItem_BooleanLiteral( value=True, ) ], ), ), ), "tool_b_to_end": WorkflowEdgeModelInput( source="tool_node_b", target="success_end", forward_condition=WorkflowEdgeModelInputForwardCondition_Expression( expression=WorkflowExpressionConditionModelInputExpression_AndOperator( children=[ AstAndOperatorNodeInputChildrenItem_BooleanLiteral( value=True, ) ], ), ), ), "tool_b_to_phone": WorkflowEdgeModelInput( source="tool_node_b", target="success_phone", forward_condition=WorkflowEdgeModelInputForwardCondition_Expression( expression=WorkflowExpressionConditionModelInputExpression_AndOperator( children=[ AstAndOperatorNodeInputChildrenItem_BooleanLiteral( value=True, ) ], ), ), ), }, nodes={ "entry_node": AgentWorkflowRequestModelNodesValue_End(), "failure_node": AgentWorkflowRequestModelNodesValue_End(), "start_node": AgentWorkflowRequestModelNodesValue_End(), "success_conversation": AgentWorkflowRequestModelNodesValue_End(), "success_end": AgentWorkflowRequestModelNodesValue_End(), "success_phone": AgentWorkflowRequestModelNodesValue_End(), "success_transfer": AgentWorkflowRequestModelNodesValue_End(), "tool_node_a": AgentWorkflowRequestModelNodesValue_End(), "tool_node_b": AgentWorkflowRequestModelNodesValue_End(), }, ), name="name", ) """ _response = self._raw_client.create( agent_id, branch_id=branch_id, conversation_config=conversation_config, platform_settings=platform_settings, workflow=workflow, name=name, tags=tags, request_options=request_options, ) return _response.data def delete( self, agent_id: str, *, branch_id: str, request_options: typing.Optional[RequestOptions] = None ) -> typing.Any: """ Delete a draft for an agent Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. branch_id : str The ID of the agent branch to use request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- typing.Any Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.conversational_ai.agents.drafts.delete( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", branch_id="agtbrch_8901k4t9z5defmb8vh3e9361y7nj", ) """ _response = self._raw_client.delete(agent_id, branch_id=branch_id, request_options=request_options) return _response.data class AsyncDraftsClient: def __init__(self, *, client_wrapper: AsyncClientWrapper): self._raw_client = AsyncRawDraftsClient(client_wrapper=client_wrapper) @property def with_raw_response(self) -> AsyncRawDraftsClient: """ Retrieves a raw implementation of this client that returns raw responses. Returns ------- AsyncRawDraftsClient """ return self._raw_client async def create( self, agent_id: str, *, branch_id: str, conversation_config: typing.Dict[str, typing.Any], platform_settings: typing.Dict[str, typing.Any], workflow: AgentWorkflowRequestModel, name: str, tags: typing.Optional[typing.Sequence[str]] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> typing.Any: """ Create a new draft for an agent Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. branch_id : str The ID of the agent branch to use conversation_config : typing.Dict[str, typing.Any] Conversation config for the draft platform_settings : typing.Dict[str, typing.Any] Platform settings for the draft workflow : AgentWorkflowRequestModel Workflow for the draft name : str Name for the draft tags : typing.Optional[typing.Sequence[str]] Tags to help classify and filter the agent request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- typing.Any Successful Response Examples -------- import asyncio from elevenlabs import ( AgentWorkflowRequestModel, AgentWorkflowRequestModelNodesValue_End, AstAndOperatorNodeInputChildrenItem_BooleanLiteral, AsyncElevenLabs, WorkflowEdgeModelInput, WorkflowEdgeModelInputForwardCondition_Expression, WorkflowExpressionConditionModelInputExpression_AndOperator, ) client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.conversational_ai.agents.drafts.create( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", branch_id="agtbrch_8901k4t9z5defmb8vh3e9361y7nj", conversation_config={"key": "value"}, platform_settings={"key": "value"}, workflow=AgentWorkflowRequestModel( edges={ "entry_to_tool_a": WorkflowEdgeModelInput( source="entry_node", target="tool_node_a", forward_condition=WorkflowEdgeModelInputForwardCondition_Expression( expression=WorkflowExpressionConditionModelInputExpression_AndOperator( children=[ AstAndOperatorNodeInputChildrenItem_BooleanLiteral( value=True, ) ], ), ), ), "start_to_entry": WorkflowEdgeModelInput( source="start_node", target="entry_node", forward_condition=WorkflowEdgeModelInputForwardCondition_Expression( expression=WorkflowExpressionConditionModelInputExpression_AndOperator( children=[ AstAndOperatorNodeInputChildrenItem_BooleanLiteral( value=True, ) ], ), ), ), "tool_a_to_failure": WorkflowEdgeModelInput( source="tool_node_a", target="failure_node", forward_condition=WorkflowEdgeModelInputForwardCondition_Expression( expression=WorkflowExpressionConditionModelInputExpression_AndOperator( children=[ AstAndOperatorNodeInputChildrenItem_BooleanLiteral( value=True, ) ], ), ), ), "tool_a_to_tool_b": WorkflowEdgeModelInput( source="tool_node_a", target="tool_node_b", forward_condition=WorkflowEdgeModelInputForwardCondition_Expression( expression=WorkflowExpressionConditionModelInputExpression_AndOperator( children=[ AstAndOperatorNodeInputChildrenItem_BooleanLiteral( value=True, ) ], ), ), ), "tool_b_to_agent_transfer": WorkflowEdgeModelInput( source="tool_node_b", target="success_transfer", forward_condition=WorkflowEdgeModelInputForwardCondition_Expression( expression=WorkflowExpressionConditionModelInputExpression_AndOperator( children=[ AstAndOperatorNodeInputChildrenItem_BooleanLiteral( value=True, ) ], ), ), ), "tool_b_to_conversation": WorkflowEdgeModelInput( source="tool_node_b", target="success_conversation", forward_condition=WorkflowEdgeModelInputForwardCondition_Expression( expression=WorkflowExpressionConditionModelInputExpression_AndOperator( children=[ AstAndOperatorNodeInputChildrenItem_BooleanLiteral( value=True, ) ], ), ), ), "tool_b_to_end": WorkflowEdgeModelInput( source="tool_node_b", target="success_end", forward_condition=WorkflowEdgeModelInputForwardCondition_Expression( expression=WorkflowExpressionConditionModelInputExpression_AndOperator( children=[ AstAndOperatorNodeInputChildrenItem_BooleanLiteral( value=True, ) ], ), ), ), "tool_b_to_phone": WorkflowEdgeModelInput( source="tool_node_b", target="success_phone", forward_condition=WorkflowEdgeModelInputForwardCondition_Expression( expression=WorkflowExpressionConditionModelInputExpression_AndOperator( children=[ AstAndOperatorNodeInputChildrenItem_BooleanLiteral( value=True, ) ], ), ), ), }, nodes={ "entry_node": AgentWorkflowRequestModelNodesValue_End(), "failure_node": AgentWorkflowRequestModelNodesValue_End(), "start_node": AgentWorkflowRequestModelNodesValue_End(), "success_conversation": AgentWorkflowRequestModelNodesValue_End(), "success_end": AgentWorkflowRequestModelNodesValue_End(), "success_phone": AgentWorkflowRequestModelNodesValue_End(), "success_transfer": AgentWorkflowRequestModelNodesValue_End(), "tool_node_a": AgentWorkflowRequestModelNodesValue_End(), "tool_node_b": AgentWorkflowRequestModelNodesValue_End(), }, ), name="name", ) asyncio.run(main()) """ _response = await self._raw_client.create( agent_id, branch_id=branch_id, conversation_config=conversation_config, platform_settings=platform_settings, workflow=workflow, name=name, tags=tags, request_options=request_options, ) return _response.data async def delete( self, agent_id: str, *, branch_id: str, request_options: typing.Optional[RequestOptions] = None ) -> typing.Any: """ Delete a draft for an agent Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. branch_id : str The ID of the agent branch to use request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- typing.Any Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.conversational_ai.agents.drafts.delete( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", branch_id="agtbrch_8901k4t9z5defmb8vh3e9361y7nj", ) asyncio.run(main()) """ _response = await self._raw_client.delete(agent_id, branch_id=branch_id, request_options=request_options) return _response.data