# This file was auto-generated by Fern from our API Definition. from __future__ import annotations import typing from ...core.client_wrapper import AsyncClientWrapper, SyncClientWrapper from ...core.request_options import RequestOptions from ...types.agent_failure_response_example import AgentFailureResponseExample from ...types.agent_successful_response_example import AgentSuccessfulResponseExample from ...types.conversation_history_transcript_common_model_input import ConversationHistoryTranscriptCommonModelInput from ...types.create_unit_test_response_model import CreateUnitTestResponseModel from ...types.get_tests_page_response_model import GetTestsPageResponseModel from ...types.get_tests_summaries_by_ids_response_model import GetTestsSummariesByIdsResponseModel from ...types.get_unit_test_response_model import GetUnitTestResponseModel from ...types.test_from_conversation_metadata_input import TestFromConversationMetadataInput from ...types.unit_test_common_model_type import UnitTestCommonModelType from ...types.unit_test_tool_call_evaluation_model_input import UnitTestToolCallEvaluationModelInput from .raw_client import AsyncRawTestsClient, RawTestsClient from .types.create_unit_test_request_dynamic_variables_value import CreateUnitTestRequestDynamicVariablesValue from .types.update_unit_test_request_dynamic_variables_value import UpdateUnitTestRequestDynamicVariablesValue if typing.TYPE_CHECKING: from .invocations.client import AsyncInvocationsClient, InvocationsClient # this is used as the default value for optional parameters OMIT = typing.cast(typing.Any, ...) class TestsClient: def __init__(self, *, client_wrapper: SyncClientWrapper): self._raw_client = RawTestsClient(client_wrapper=client_wrapper) self._client_wrapper = client_wrapper self._invocations: typing.Optional[InvocationsClient] = None @property def with_raw_response(self) -> RawTestsClient: """ Retrieves a raw implementation of this client that returns raw responses. Returns ------- RawTestsClient """ return self._raw_client def create( self, *, chat_history: typing.Sequence[ConversationHistoryTranscriptCommonModelInput], success_condition: str, success_examples: typing.Sequence[AgentSuccessfulResponseExample], failure_examples: typing.Sequence[AgentFailureResponseExample], name: str, tool_call_parameters: typing.Optional[UnitTestToolCallEvaluationModelInput] = OMIT, dynamic_variables: typing.Optional[ typing.Dict[str, typing.Optional[CreateUnitTestRequestDynamicVariablesValue]] ] = OMIT, type: typing.Optional[UnitTestCommonModelType] = OMIT, from_conversation_metadata: typing.Optional[TestFromConversationMetadataInput] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> CreateUnitTestResponseModel: """ Creates a new agent response test. Parameters ---------- chat_history : typing.Sequence[ConversationHistoryTranscriptCommonModelInput] success_condition : str A prompt that evaluates whether the agent's response is successful. Should return True or False. success_examples : typing.Sequence[AgentSuccessfulResponseExample] Non-empty list of example responses that should be considered successful failure_examples : typing.Sequence[AgentFailureResponseExample] Non-empty list of example responses that should be considered failures name : str tool_call_parameters : typing.Optional[UnitTestToolCallEvaluationModelInput] How to evaluate the agent's tool call (if any). If empty, the tool call is not evaluated. dynamic_variables : typing.Optional[typing.Dict[str, typing.Optional[CreateUnitTestRequestDynamicVariablesValue]]] Dynamic variables to replace in the agent config during testing type : typing.Optional[UnitTestCommonModelType] from_conversation_metadata : typing.Optional[TestFromConversationMetadataInput] Metadata of a conversation this test was created from (if applicable). request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- CreateUnitTestResponseModel Successful Response Examples -------- from elevenlabs import ( AgentFailureResponseExample, AgentSuccessfulResponseExample, ConversationHistoryTranscriptCommonModelInput, ElevenLabs, ) client = ElevenLabs( api_key="YOUR_API_KEY", ) client.conversational_ai.tests.create( chat_history=[ ConversationHistoryTranscriptCommonModelInput( role="user", time_in_call_secs=1, ) ], success_condition="success_condition", success_examples=[ AgentSuccessfulResponseExample( response="response", ) ], failure_examples=[ AgentFailureResponseExample( response="response", ) ], name="name", ) """ _response = self._raw_client.create( chat_history=chat_history, success_condition=success_condition, success_examples=success_examples, failure_examples=failure_examples, name=name, tool_call_parameters=tool_call_parameters, dynamic_variables=dynamic_variables, type=type, from_conversation_metadata=from_conversation_metadata, request_options=request_options, ) return _response.data def get(self, test_id: str, *, request_options: typing.Optional[RequestOptions] = None) -> GetUnitTestResponseModel: """ Gets an agent response test by ID. Parameters ---------- test_id : str The id of a chat response test. This is returned on test creation. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetUnitTestResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.conversational_ai.tests.get( test_id="TeaqRRdTcIfIu2i7BYfT", ) """ _response = self._raw_client.get(test_id, request_options=request_options) return _response.data def update( self, test_id: str, *, chat_history: typing.Sequence[ConversationHistoryTranscriptCommonModelInput], success_condition: str, success_examples: typing.Sequence[AgentSuccessfulResponseExample], failure_examples: typing.Sequence[AgentFailureResponseExample], name: str, tool_call_parameters: typing.Optional[UnitTestToolCallEvaluationModelInput] = OMIT, dynamic_variables: typing.Optional[ typing.Dict[str, typing.Optional[UpdateUnitTestRequestDynamicVariablesValue]] ] = OMIT, type: typing.Optional[UnitTestCommonModelType] = OMIT, from_conversation_metadata: typing.Optional[TestFromConversationMetadataInput] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> GetUnitTestResponseModel: """ Updates an agent response test by ID. Parameters ---------- test_id : str The id of a chat response test. This is returned on test creation. chat_history : typing.Sequence[ConversationHistoryTranscriptCommonModelInput] success_condition : str A prompt that evaluates whether the agent's response is successful. Should return True or False. success_examples : typing.Sequence[AgentSuccessfulResponseExample] Non-empty list of example responses that should be considered successful failure_examples : typing.Sequence[AgentFailureResponseExample] Non-empty list of example responses that should be considered failures name : str tool_call_parameters : typing.Optional[UnitTestToolCallEvaluationModelInput] How to evaluate the agent's tool call (if any). If empty, the tool call is not evaluated. dynamic_variables : typing.Optional[typing.Dict[str, typing.Optional[UpdateUnitTestRequestDynamicVariablesValue]]] Dynamic variables to replace in the agent config during testing type : typing.Optional[UnitTestCommonModelType] from_conversation_metadata : typing.Optional[TestFromConversationMetadataInput] Metadata of a conversation this test was created from (if applicable). request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetUnitTestResponseModel Successful Response Examples -------- from elevenlabs import ( AgentFailureResponseExample, AgentSuccessfulResponseExample, ConversationHistoryTranscriptCommonModelInput, ElevenLabs, ) client = ElevenLabs( api_key="YOUR_API_KEY", ) client.conversational_ai.tests.update( test_id="TeaqRRdTcIfIu2i7BYfT", chat_history=[ ConversationHistoryTranscriptCommonModelInput( role="user", time_in_call_secs=1, ) ], success_condition="success_condition", success_examples=[ AgentSuccessfulResponseExample( response="response", ) ], failure_examples=[ AgentFailureResponseExample( response="response", ) ], name="name", ) """ _response = self._raw_client.update( test_id, chat_history=chat_history, success_condition=success_condition, success_examples=success_examples, failure_examples=failure_examples, name=name, tool_call_parameters=tool_call_parameters, dynamic_variables=dynamic_variables, type=type, from_conversation_metadata=from_conversation_metadata, request_options=request_options, ) return _response.data def delete(self, test_id: str, *, request_options: typing.Optional[RequestOptions] = None) -> typing.Any: """ Deletes an agent response test by ID. Parameters ---------- test_id : str The id of a chat response test. This is returned on test creation. 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.tests.delete( test_id="TeaqRRdTcIfIu2i7BYfT", ) """ _response = self._raw_client.delete(test_id, request_options=request_options) return _response.data def summaries( self, *, test_ids: typing.Sequence[str], request_options: typing.Optional[RequestOptions] = None ) -> GetTestsSummariesByIdsResponseModel: """ Gets multiple agent response tests by their IDs. Returns a dictionary mapping test IDs to test summaries. Parameters ---------- test_ids : typing.Sequence[str] List of test IDs to fetch. No duplicates allowed. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetTestsSummariesByIdsResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.conversational_ai.tests.summaries( test_ids=["test_id_1", "test_id_2"], ) """ _response = self._raw_client.summaries(test_ids=test_ids, request_options=request_options) return _response.data def list( self, *, cursor: typing.Optional[str] = None, page_size: typing.Optional[int] = None, search: typing.Optional[str] = None, request_options: typing.Optional[RequestOptions] = None, ) -> GetTestsPageResponseModel: """ Lists all agent response tests with pagination support and optional search filtering. Parameters ---------- cursor : typing.Optional[str] Used for fetching next page. Cursor is returned in the response. page_size : typing.Optional[int] How many Tests to return at maximum. Can not exceed 100, defaults to 30. search : typing.Optional[str] Search query to filter tests by name. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetTestsPageResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.conversational_ai.tests.list( cursor="cursor", page_size=1, search="search", ) """ _response = self._raw_client.list( cursor=cursor, page_size=page_size, search=search, request_options=request_options ) return _response.data @property def invocations(self): if self._invocations is None: from .invocations.client import InvocationsClient # noqa: E402 self._invocations = InvocationsClient(client_wrapper=self._client_wrapper) return self._invocations class AsyncTestsClient: def __init__(self, *, client_wrapper: AsyncClientWrapper): self._raw_client = AsyncRawTestsClient(client_wrapper=client_wrapper) self._client_wrapper = client_wrapper self._invocations: typing.Optional[AsyncInvocationsClient] = None @property def with_raw_response(self) -> AsyncRawTestsClient: """ Retrieves a raw implementation of this client that returns raw responses. Returns ------- AsyncRawTestsClient """ return self._raw_client async def create( self, *, chat_history: typing.Sequence[ConversationHistoryTranscriptCommonModelInput], success_condition: str, success_examples: typing.Sequence[AgentSuccessfulResponseExample], failure_examples: typing.Sequence[AgentFailureResponseExample], name: str, tool_call_parameters: typing.Optional[UnitTestToolCallEvaluationModelInput] = OMIT, dynamic_variables: typing.Optional[ typing.Dict[str, typing.Optional[CreateUnitTestRequestDynamicVariablesValue]] ] = OMIT, type: typing.Optional[UnitTestCommonModelType] = OMIT, from_conversation_metadata: typing.Optional[TestFromConversationMetadataInput] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> CreateUnitTestResponseModel: """ Creates a new agent response test. Parameters ---------- chat_history : typing.Sequence[ConversationHistoryTranscriptCommonModelInput] success_condition : str A prompt that evaluates whether the agent's response is successful. Should return True or False. success_examples : typing.Sequence[AgentSuccessfulResponseExample] Non-empty list of example responses that should be considered successful failure_examples : typing.Sequence[AgentFailureResponseExample] Non-empty list of example responses that should be considered failures name : str tool_call_parameters : typing.Optional[UnitTestToolCallEvaluationModelInput] How to evaluate the agent's tool call (if any). If empty, the tool call is not evaluated. dynamic_variables : typing.Optional[typing.Dict[str, typing.Optional[CreateUnitTestRequestDynamicVariablesValue]]] Dynamic variables to replace in the agent config during testing type : typing.Optional[UnitTestCommonModelType] from_conversation_metadata : typing.Optional[TestFromConversationMetadataInput] Metadata of a conversation this test was created from (if applicable). request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- CreateUnitTestResponseModel Successful Response Examples -------- import asyncio from elevenlabs import ( AgentFailureResponseExample, AgentSuccessfulResponseExample, AsyncElevenLabs, ConversationHistoryTranscriptCommonModelInput, ) client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.conversational_ai.tests.create( chat_history=[ ConversationHistoryTranscriptCommonModelInput( role="user", time_in_call_secs=1, ) ], success_condition="success_condition", success_examples=[ AgentSuccessfulResponseExample( response="response", ) ], failure_examples=[ AgentFailureResponseExample( response="response", ) ], name="name", ) asyncio.run(main()) """ _response = await self._raw_client.create( chat_history=chat_history, success_condition=success_condition, success_examples=success_examples, failure_examples=failure_examples, name=name, tool_call_parameters=tool_call_parameters, dynamic_variables=dynamic_variables, type=type, from_conversation_metadata=from_conversation_metadata, request_options=request_options, ) return _response.data async def get( self, test_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> GetUnitTestResponseModel: """ Gets an agent response test by ID. Parameters ---------- test_id : str The id of a chat response test. This is returned on test creation. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetUnitTestResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.conversational_ai.tests.get( test_id="TeaqRRdTcIfIu2i7BYfT", ) asyncio.run(main()) """ _response = await self._raw_client.get(test_id, request_options=request_options) return _response.data async def update( self, test_id: str, *, chat_history: typing.Sequence[ConversationHistoryTranscriptCommonModelInput], success_condition: str, success_examples: typing.Sequence[AgentSuccessfulResponseExample], failure_examples: typing.Sequence[AgentFailureResponseExample], name: str, tool_call_parameters: typing.Optional[UnitTestToolCallEvaluationModelInput] = OMIT, dynamic_variables: typing.Optional[ typing.Dict[str, typing.Optional[UpdateUnitTestRequestDynamicVariablesValue]] ] = OMIT, type: typing.Optional[UnitTestCommonModelType] = OMIT, from_conversation_metadata: typing.Optional[TestFromConversationMetadataInput] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> GetUnitTestResponseModel: """ Updates an agent response test by ID. Parameters ---------- test_id : str The id of a chat response test. This is returned on test creation. chat_history : typing.Sequence[ConversationHistoryTranscriptCommonModelInput] success_condition : str A prompt that evaluates whether the agent's response is successful. Should return True or False. success_examples : typing.Sequence[AgentSuccessfulResponseExample] Non-empty list of example responses that should be considered successful failure_examples : typing.Sequence[AgentFailureResponseExample] Non-empty list of example responses that should be considered failures name : str tool_call_parameters : typing.Optional[UnitTestToolCallEvaluationModelInput] How to evaluate the agent's tool call (if any). If empty, the tool call is not evaluated. dynamic_variables : typing.Optional[typing.Dict[str, typing.Optional[UpdateUnitTestRequestDynamicVariablesValue]]] Dynamic variables to replace in the agent config during testing type : typing.Optional[UnitTestCommonModelType] from_conversation_metadata : typing.Optional[TestFromConversationMetadataInput] Metadata of a conversation this test was created from (if applicable). request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetUnitTestResponseModel Successful Response Examples -------- import asyncio from elevenlabs import ( AgentFailureResponseExample, AgentSuccessfulResponseExample, AsyncElevenLabs, ConversationHistoryTranscriptCommonModelInput, ) client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.conversational_ai.tests.update( test_id="TeaqRRdTcIfIu2i7BYfT", chat_history=[ ConversationHistoryTranscriptCommonModelInput( role="user", time_in_call_secs=1, ) ], success_condition="success_condition", success_examples=[ AgentSuccessfulResponseExample( response="response", ) ], failure_examples=[ AgentFailureResponseExample( response="response", ) ], name="name", ) asyncio.run(main()) """ _response = await self._raw_client.update( test_id, chat_history=chat_history, success_condition=success_condition, success_examples=success_examples, failure_examples=failure_examples, name=name, tool_call_parameters=tool_call_parameters, dynamic_variables=dynamic_variables, type=type, from_conversation_metadata=from_conversation_metadata, request_options=request_options, ) return _response.data async def delete(self, test_id: str, *, request_options: typing.Optional[RequestOptions] = None) -> typing.Any: """ Deletes an agent response test by ID. Parameters ---------- test_id : str The id of a chat response test. This is returned on test creation. 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.tests.delete( test_id="TeaqRRdTcIfIu2i7BYfT", ) asyncio.run(main()) """ _response = await self._raw_client.delete(test_id, request_options=request_options) return _response.data async def summaries( self, *, test_ids: typing.Sequence[str], request_options: typing.Optional[RequestOptions] = None ) -> GetTestsSummariesByIdsResponseModel: """ Gets multiple agent response tests by their IDs. Returns a dictionary mapping test IDs to test summaries. Parameters ---------- test_ids : typing.Sequence[str] List of test IDs to fetch. No duplicates allowed. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetTestsSummariesByIdsResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.conversational_ai.tests.summaries( test_ids=["test_id_1", "test_id_2"], ) asyncio.run(main()) """ _response = await self._raw_client.summaries(test_ids=test_ids, request_options=request_options) return _response.data async def list( self, *, cursor: typing.Optional[str] = None, page_size: typing.Optional[int] = None, search: typing.Optional[str] = None, request_options: typing.Optional[RequestOptions] = None, ) -> GetTestsPageResponseModel: """ Lists all agent response tests with pagination support and optional search filtering. Parameters ---------- cursor : typing.Optional[str] Used for fetching next page. Cursor is returned in the response. page_size : typing.Optional[int] How many Tests to return at maximum. Can not exceed 100, defaults to 30. search : typing.Optional[str] Search query to filter tests by name. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetTestsPageResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.conversational_ai.tests.list( cursor="cursor", page_size=1, search="search", ) asyncio.run(main()) """ _response = await self._raw_client.list( cursor=cursor, page_size=page_size, search=search, request_options=request_options ) return _response.data @property def invocations(self): if self._invocations is None: from .invocations.client import AsyncInvocationsClient # noqa: E402 self._invocations = AsyncInvocationsClient(client_wrapper=self._client_wrapper) return self._invocations