b6iddlmZddlZddlmZmZddlmZddlm Z ddl m Z ddl m Z dd lmZdd lmZdd lmZdd lmZdd lmZddlmZddlmZddlmZddlmZddl m!Z!ddl"m#Z#ddl$m%Z%m&Z&ddl'm(Z(ejRr@ddl*m+Z+m,Z,ddl-m.Z.m/Z/ddl0m1Z1m2Z2ddl3m4Z4m5Z5ddl6m7Z7m8Z8ddl9m:Z:m;Z;ddlZ>ddl?m@Z@mAZAejejdZDGd d!ZEGd"d#ZFy)$) annotationsN)AsyncClientWrapperSyncClientWrapper)RequestOptions)+AdhocAgentConfigOverrideForTestRequestModel)!AgentPlatformSettingsRequestModel)#AgentSimulatedChatTestResponseModel) AgentSortBy)AgentWorkflowRequestModel)#ConversationSimulationSpecification)ConversationalConfig)CreateAgentResponseModel)GetAgentResponseModel)GetAgentsPageResponseModel)#GetTestSuiteInvocationResponseModel)PromptEvaluationCriteria)SingleTestRunRequestModel) SortDirection)AsyncRawAgentsClientRawAgentsClient)EBodyPatchesAnAgentSettingsV1ConvaiAgentsAgentIdPatchProcedureRefsItem)AsyncBranchesClientBranchesClient)AsyncDeploymentsClientDeploymentsClient)AsyncDraftsClient DraftsClient)AsyncKnowledgeBaseClientKnowledgeBaseClient)AsyncLinkClient LinkClient)AsyncLlmUsageClientLlmUsageClient)AsyncSummariesClientSummariesClient)AsyncWidgetClient WidgetClient.c $eZdZddZeddZeeeedd ddZdddd d dZddd!d Z deeeeeeedd d"d Z ddddddddd  d#d Z edd d$dZ eedd d%dZ eedd d&dZeedd d'dZedZedZedZedZedZedZedZedZy)( AgentsClientct||_||_d|_d|_d|_d|_d|_d|_d|_ d|_ yNclient_wrapper) r _raw_client_client_wrapper _summaries_widget_link_knowledge_base _llm_usage _branches _deployments_draftsselfr/s u/root/.openclaw/workspace/visionaryfx/venv/lib/python3.12/site-packages/elevenlabs/conversational_ai/agents/client.py__init__zAgentsClient.__init__*sQ*.I-<@6: 26 EI;?:>@D6: c|jS)z Retrieves a raw implementation of this client that returns raw responses. Returns ------- RawAgentsClient r0r;s r<with_raw_responsezAgentsClient.with_raw_response6r>Nplatform_settingsworkflownametagsrequest_optionsc\|jj||||||}|jS)a Create an agent from a config object Parameters ---------- conversation_config : ConversationalConfig Conversation configuration for an agent platform_settings : typing.Optional[AgentPlatformSettingsRequestModel] Platform settings for the agent are all settings that aren't related to the conversation orchestration and content. workflow : typing.Optional[AgentWorkflowRequestModel] Workflow for the agent. This is used to define the flow of the conversation and how the agent interacts with tools. name : typing.Optional[str] A name to make the agent easier to find tags : typing.Optional[typing.Sequence[str]] Tags to help classify and filter the agent request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- CreateAgentResponseModel Successful Response Examples -------- from elevenlabs import ConversationalConfig, ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.conversational_ai.agents.create( conversation_config=ConversationalConfig(), ) conversation_configrErFrGrHrIr0createdatar;rLrErFrGrHrI _responses r<rNzAgentsClient.createAs>b$$++ 3/+ , ~~r> version_id branch_idrIcX|jj||||}|jS)au Retrieve config for an agent Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. version_id : typing.Optional[str] The ID of the agent version to use branch_id : typing.Optional[str] The ID of the branch to use request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetAgentResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.conversational_ai.agents.get( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", version_id="version_id", branch_id="branch_id", ) rRr0getrOr;agent_idrSrTrIrQs r<rWzAgentsClient.get|s6V$$(( yRa) ~~r>rIcT|jj||}|jS)aF Delete an agent Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- None Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.conversational_ai.agents.delete( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", ) rZr0deleterOr;rYrIrQs r<r]zAgentsClient.deletes)6$$++Ho+V ~~r> rTrLrErFrGrHversion_descriptionprocedure_refsrIc d|jj||||||||| |  } | jS)a" Patches an Agent settings Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. branch_id : typing.Optional[str] The ID of the branch to use conversation_config : typing.Optional[ConversationalConfig] Conversation configuration for an agent platform_settings : typing.Optional[AgentPlatformSettingsRequestModel] Platform settings for the agent are all settings that aren't related to the conversation orchestration and content. workflow : typing.Optional[AgentWorkflowRequestModel] Workflow for the agent. This is used to define the flow of the conversation and how the agent interacts with tools. name : typing.Optional[str] A name to make the agent easier to find tags : typing.Optional[typing.Sequence[str]] Tags to help classify and filter the agent version_description : typing.Optional[str] Description for this version when publishing changes (only applicable for versioned agents) procedure_refs : typing.Optional[typing.Sequence[BodyPatchesAnAgentSettingsV1ConvaiAgentsAgentIdPatchProcedureRefsItem]] List of procedure refs used for this agent version. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetAgentResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.conversational_ai.agents.update( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", branch_id="branch_id", ) r_r0updaterO r;rYrTrLrErFrGrHr`rarIrQs r<rdzAgentsClient.updatesJH$$++  3/ 3)+,  ~~r> page_sizesearcharchivedshow_only_owned_agentssort_directionsort_bycursorrIc `|jj||||||||} | jS)a Returns a list of your agents and their metadata. Parameters ---------- page_size : typing.Optional[int] How many Agents to return at maximum. Can not exceed 100, defaults to 30. search : typing.Optional[str] Search by agents name. archived : typing.Optional[bool] Filter agents by archived status show_only_owned_agents : typing.Optional[bool] If set to true, the endpoint will omit any agents that were shared with you by someone else and include only the ones you own sort_direction : typing.Optional[SortDirection] The direction to sort the results sort_by : typing.Optional[AgentSortBy] The field to sort the results by cursor : typing.Optional[str] Used for fetching next page. Cursor is returned in the response. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetAgentsPageResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.conversational_ai.agents.list( page_size=1, search="search", archived=True, show_only_owned_agents=True, sort_direction="asc", sort_by="name", cursor="cursor", ) rfr0listrO r;rgrhrirjrkrlrmrIrQs r<rpzAgentsClient.listsD~$$))#9)+*  ~~r>rGrIcV|jj|||}|jS)a Create a new agent by duplicating an existing one Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. name : typing.Optional[str] A name to make the agent easier to find request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- CreateAgentResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.conversational_ai.agents.duplicate( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", ) rrr0 duplicaterOr;rYrGrIrQs r<ruzAgentsClient.duplicategs-J$$..xdTc.d ~~r>extra_evaluation_criterianew_turns_limitrIcZ|jj|||||}|jS)a Run a conversation between the agent and a simulated user. Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. simulation_specification : ConversationSimulationSpecification A specification detailing how the conversation should be simulated extra_evaluation_criteria : typing.Optional[typing.Sequence[PromptEvaluationCriteria]] A list of evaluation criteria to test new_turns_limit : typing.Optional[int] Maximum number of new turns to generate in the conversation simulation request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AgentSimulatedChatTestResponseModel Successful Response Examples -------- from elevenlabs import ( AgentConfig, ConversationSimulationSpecification, ElevenLabs, ) client = ElevenLabs( api_key="YOUR_API_KEY", ) client.conversational_ai.agents.simulate_conversation( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", simulation_specification=ConversationSimulationSpecification( simulated_user_config=AgentConfig( first_message="Hello, how can I help you today?", language="en", disable_first_message_interruptions=False, ), ), ) simulation_specificationrxryrIr0simulate_conversationrOr;rYr|rxryrIrQs r<r~z"AgentsClient.simulate_conversations;p$$:: %=&?++ ; ~~r>cZ|jj|||||}|jS)a Run a conversation between the agent and a simulated user and stream back the response. Response is streamed back as partial lists of messages that should be concatenated and once the conversation has complete a single final message with the conversation analysis will be sent. Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. simulation_specification : ConversationSimulationSpecification A specification detailing how the conversation should be simulated extra_evaluation_criteria : typing.Optional[typing.Sequence[PromptEvaluationCriteria]] A list of evaluation criteria to test new_turns_limit : typing.Optional[int] Maximum number of new turns to generate in the conversation simulation request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- None Examples -------- from elevenlabs import ( AgentConfig, ConversationSimulationSpecification, ElevenLabs, ) client = ElevenLabs( api_key="YOUR_API_KEY", ) client.conversational_ai.agents.simulate_conversation_stream( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", simulation_specification=ConversationSimulationSpecification( simulated_user_config=AgentConfig( first_message="Hello, how can I help you today?", language="en", disable_first_message_interruptions=False, ), ), ) r{r0simulate_conversation_streamrOrs r<rz)AgentsClient.simulate_conversation_streams<n$$AA %=&?++ B ~~r>agent_config_overriderTrIcZ|jj|||||}|jS)a Run selected tests on the agent with provided configuration. If the agent configuration is provided, it will be used to override default agent configuration. Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. tests : typing.Sequence[SingleTestRunRequestModel] List of tests to run on the agent agent_config_override : typing.Optional[AdhocAgentConfigOverrideForTestRequestModel] Configuration overrides to use for testing. If not provided, the agent's default configuration will be used. branch_id : typing.Optional[str] ID of the branch to run the tests on. If not provided, the tests will be run on the agent default configuration. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetTestSuiteInvocationResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs, SingleTestRunRequestModel client = ElevenLabs( api_key="YOUR_API_KEY", ) client.conversational_ai.agents.run_tests( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", tests=[ SingleTestRunRequestModel( test_id="test_id", ) ], ) testsrrTrIr0 run_testsrOr;rYrrrTrIrQs r<rzAgentsClient.run_testss;d$$.. "7+ / ~~r>cn|jddlm}||j|_|jS)Nr)r'r.)r2summaries.clientr'r1)r;r's r< summarieszAgentsClient.summariesKs+ ?? " 9-T=Q=QRDOr>cn|jddlm}||j|_|jS)Nr)r)r.)r3 widget.clientr)r1)r;r)s r<widgetzAgentsClient.widgetS+ <<  3't7K7KLDL||r>cn|jddlm}||j|_|jS)Nr)r#r.)r4 link.clientr#r1)r;r#s r<linkzAgentsClient.link[s+ ::  /#43G3GHDJzzr>cn|jddlm}||j|_|jS)Nr)r!r.)r5knowledge_base.clientr!r1)r;r!s r<knowledge_basezAgentsClient.knowledge_basecs0    ' B#6dFZFZ#[D ###r>cn|jddlm}||j|_|jS)Nr)r%r.)r6llm_usage.clientr%r1)r;r%s r< llm_usagezAgentsClient.llm_usageks+ ?? " 8,Dcn|jddlm}||j|_|jS)Nr)rr.)r7branches.clientrr1)r;rs r<brancheszAgentsClient.branchesss+ >> ! 7+4;O;OPDN~~r>cn|jddlm}||j|_|jS)Nr)rr.)r8deployments.clientrr1)r;rs r< deploymentszAgentsClient.deployments{s0    $ = 1AUAU VD    r>cn|jddlm}||j|_|jS)Nr)rr.)r9 drafts.clientrr1)r;rs r<draftszAgentsClient.draftsrr>)r/r)returnrrLrrE2typing.Optional[AgentPlatformSettingsRequestModel]rF*typing.Optional[AgentWorkflowRequestModel]rGtyping.Optional[str]rH%typing.Optional[typing.Sequence[str]]rItyping.Optional[RequestOptions]rr rYstrrSrrTrrIrrrrYrrIrrNonerYrrTrrLz%typing.Optional[ConversationalConfig]rErrFrrGrrHrr`rrazgtyping.Optional[typing.Sequence[BodyPatchesAnAgentSettingsV1ConvaiAgentsAgentIdPatchProcedureRefsItem]]rIrrrrgtyping.Optional[int]rhrrityping.Optional[bool]rjrrkztyping.Optional[SortDirection]rlztyping.Optional[AgentSortBy]rmrrIrrrrYrrGrrIrrr rYrr|r rx:typing.Optional[typing.Sequence[PromptEvaluationCriteria]]ryrrIrrr rYrr|r rxrryrrIrrr rYrrz*typing.Sequence[SingleTestRunRequestModel]rzr<r+r+)s ;  QU?C%)6:;?929N 9 = 9 # 94999 "9~,0*.;? ..) . ( . 9 . .`[_D+/EIPT?C%)6:48 ;?PP( P C P N P=P#P4P2P P9P Pj+/'+*.8<9=04'+;?I(I% I ( I !6 I7I.I%I9I $I^&*;? &&# & 9 & " &Zae04;???#F ? $^ ? . ?9? -?Lae04;?>>#F > $^ > . >9> >J_c*.;?99: 9 \ 9 ( 999 -9v$$!!r>r+c $eZdZddZeddZeeeedd ddZdddd d dZddd!d Z deeeeeeedd d"d Z ddddddddd  d#d Z edd d$dZ eedd d%dZ eedd d&dZeedd d'dZedZedZedZedZedZedZedZedZy)(AsyncAgentsClientct||_||_d|_d|_d|_d|_d|_d|_d|_ d|_ yr-) rr0r1r2r3r4r5r6r7r8r9r:s r<r=zAsyncAgentsClient.__init__sQ/~N-AE;? 7; JN@D?CEI;? r>c|jS)z Retrieves a raw implementation of this client that returns raw responses. Returns ------- AsyncRawAgentsClient r@rAs r<rBz#AsyncAgentsClient.with_raw_responserCr>NrDcxK|jj||||||d{}|jS7w)ay Create an agent from a config object Parameters ---------- conversation_config : ConversationalConfig Conversation configuration for an agent platform_settings : typing.Optional[AgentPlatformSettingsRequestModel] Platform settings for the agent are all settings that aren't related to the conversation orchestration and content. workflow : typing.Optional[AgentWorkflowRequestModel] Workflow for the agent. This is used to define the flow of the conversation and how the agent interacts with tools. name : typing.Optional[str] A name to make the agent easier to find tags : typing.Optional[typing.Sequence[str]] Tags to help classify and filter the agent request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- CreateAgentResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs, ConversationalConfig client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.conversational_ai.agents.create( conversation_config=ConversationalConfig(), ) asyncio.run(main()) rKNrMrPs r<rNzAsyncAgentsClient.createsLr**11 3/+ 2  ~~ s %:8:rRctK|jj||||d{}|jS7w)a Retrieve config for an agent Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. version_id : typing.Optional[str] The ID of the agent version to use branch_id : typing.Optional[str] The ID of the branch to use request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetAgentResponseModel 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.get( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", version_id="version_id", branch_id="branch_id", ) asyncio.run(main()) rRNrVrXs r<rWzAsyncAgentsClient.getsDf**.. yRa/  ~~ s #868rZcpK|jj||d{}|jS7w)a Delete an agent Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- None Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.conversational_ai.agents.delete( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", ) asyncio.run(main()) rZNr\r^s r<r]zAsyncAgentsClient.deletes7F**11(O1\\ ~~]s !646r_c K|jj||||||||| |  d{} | jS7w)a Patches an Agent settings Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. branch_id : typing.Optional[str] The ID of the branch to use conversation_config : typing.Optional[ConversationalConfig] Conversation configuration for an agent platform_settings : typing.Optional[AgentPlatformSettingsRequestModel] Platform settings for the agent are all settings that aren't related to the conversation orchestration and content. workflow : typing.Optional[AgentWorkflowRequestModel] Workflow for the agent. This is used to define the flow of the conversation and how the agent interacts with tools. name : typing.Optional[str] A name to make the agent easier to find tags : typing.Optional[typing.Sequence[str]] Tags to help classify and filter the agent version_description : typing.Optional[str] Description for this version when publishing changes (only applicable for versioned agents) procedure_refs : typing.Optional[typing.Sequence[BodyPatchesAnAgentSettingsV1ConvaiAgentsAgentIdPatchProcedureRefsItem]] List of procedure refs used for this agent version. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetAgentResponseModel 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.update( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", branch_id="branch_id", ) asyncio.run(main()) r_Nrcres r<rdzAsyncAgentsClient.updateEsXX**11  3/ 3)+2   ~~  s )><>rfc |K|jj||||||||d{} | jS7w)a Returns a list of your agents and their metadata. Parameters ---------- page_size : typing.Optional[int] How many Agents to return at maximum. Can not exceed 100, defaults to 30. search : typing.Optional[str] Search by agents name. archived : typing.Optional[bool] Filter agents by archived status show_only_owned_agents : typing.Optional[bool] If set to true, the endpoint will omit any agents that were shared with you by someone else and include only the ones you own sort_direction : typing.Optional[SortDirection] The direction to sort the results sort_by : typing.Optional[AgentSortBy] The field to sort the results by cursor : typing.Optional[str] Used for fetching next page. Cursor is returned in the response. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetAgentsPageResponseModel 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.list( page_size=1, search="search", archived=True, show_only_owned_agents=True, sort_direction="asc", sort_by="name", cursor="cursor", ) asyncio.run(main()) rfNrorqs r<rpzAsyncAgentsClient.listsRN**//#9)+0   ~~  s '<:<rrcrK|jj|||d{}|jS7w)an Create a new agent by duplicating an existing one Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. name : typing.Optional[str] A name to make the agent easier to find request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- CreateAgentResponseModel 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.duplicate( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", ) asyncio.run(main()) rrNrtrvs r<ruzAsyncAgentsClient.duplicates:Z**44XDZi4jj ~~ks "757rwcvK|jj|||||d{}|jS7w)a Run a conversation between the agent and a simulated user. Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. simulation_specification : ConversationSimulationSpecification A specification detailing how the conversation should be simulated extra_evaluation_criteria : typing.Optional[typing.Sequence[PromptEvaluationCriteria]] A list of evaluation criteria to test new_turns_limit : typing.Optional[int] Maximum number of new turns to generate in the conversation simulation request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AgentSimulatedChatTestResponseModel Successful Response Examples -------- import asyncio from elevenlabs import ( AgentConfig, AsyncElevenLabs, ConversationSimulationSpecification, ) client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.conversational_ai.agents.simulate_conversation( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", simulation_specification=ConversationSimulationSpecification( simulated_user_config=AgentConfig( first_message="Hello, how can I help you today?", language="en", disable_first_message_interruptions=False, ), ), ) asyncio.run(main()) r{Nr}rs r<r~z'AsyncAgentsClient.simulate_conversation"sJ@**@@ %=&?++ A  ~~ $979cvK|jj|||||d{}|jS7w)aJ Run a conversation between the agent and a simulated user and stream back the response. Response is streamed back as partial lists of messages that should be concatenated and once the conversation has complete a single final message with the conversation analysis will be sent. Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. simulation_specification : ConversationSimulationSpecification A specification detailing how the conversation should be simulated extra_evaluation_criteria : typing.Optional[typing.Sequence[PromptEvaluationCriteria]] A list of evaluation criteria to test new_turns_limit : typing.Optional[int] Maximum number of new turns to generate in the conversation simulation request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- None Examples -------- import asyncio from elevenlabs import ( AgentConfig, AsyncElevenLabs, ConversationSimulationSpecification, ) client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.conversational_ai.agents.simulate_conversation_stream( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", simulation_specification=ConversationSimulationSpecification( simulated_user_config=AgentConfig( first_message="Hello, how can I help you today?", language="en", disable_first_message_interruptions=False, ), ), ) asyncio.run(main()) r{Nrrs r<rz.AsyncAgentsClient.simulate_conversation_streamksJ~**GG %=&?++ H  ~~ rrcvK|jj|||||d{}|jS7w)a* Run selected tests on the agent with provided configuration. If the agent configuration is provided, it will be used to override default agent configuration. Parameters ---------- agent_id : str The id of an agent. This is returned on agent creation. tests : typing.Sequence[SingleTestRunRequestModel] List of tests to run on the agent agent_config_override : typing.Optional[AdhocAgentConfigOverrideForTestRequestModel] Configuration overrides to use for testing. If not provided, the agent's default configuration will be used. branch_id : typing.Optional[str] ID of the branch to run the tests on. If not provided, the tests will be run on the agent default configuration. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetTestSuiteInvocationResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs, SingleTestRunRequestModel client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.conversational_ai.agents.run_tests( agent_id="agent_3701k3ttaq12ewp8b7qv5rfyszkz", tests=[ SingleTestRunRequestModel( test_id="test_id", ) ], ) asyncio.run(main()) rNrrs r<rzAsyncAgentsClient.run_testssIt**44 "7+ 5  ~~ rcn|jddlm}||j|_|jS)Nr)r&r.)r2rr&r1)r;r&s r<rzAsyncAgentsClient.summariess+ ?? " >2$BVBVWDOr>cn|jddlm}||j|_|jS)Nr)r(r.)r3rr(r1)r;r(s r<rzAsyncAgentsClient.widget+ <<  8,Dcn|jddlm}||j|_|jS)Nr)r"r.)r4rr"r1)r;r"s r<rzAsyncAgentsClient.links+ ::  4(8L8LMDJzzr>cn|jddlm}||j|_|jS)Nr)r r.)r5rr r1)r;r s r<rz AsyncAgentsClient.knowledge_bases0    ' G#;4K_K_#`D ###r>cn|jddlm}||j|_|jS)Nr)r$r.)r6rr$r1)r;r$s r<rzAsyncAgentsClient.llm_usages+ ?? " =1AUAUVDOr>cn|jddlm}||j|_|jS)Nr)rr.)r7rrr1)r;rs r<rzAsyncAgentsClient.branchess+ >> ! <0@T@TUDN~~r>cn|jddlm}||j|_|jS)Nr)rr.)r8rrr1)r;rs r<rzAsyncAgentsClient.deployments&s0    $ B 6dFZFZ [D    r>cn|jddlm}||j|_|jS)Nr)rr.)r9rrr1)r;rs r<rzAsyncAgentsClient.drafts.rr>)r/r)rrrrrrrrrrrrrr>r<rrs @  QU?C%)6:;?A2AN A = A # A4A9A "AN,0*.;? 66) 6 ( 6 9 6 6pae$T+/EIPT?C%)6:48 ;?XX( X C X N X=X#X4X2X X9X Xz+/'+*.8<9=04'+;?Q(Q% Q ( Q !6 Q7Q.Q%Q9Q $Qn&*;? ..# . 9 . " .jae04;?GG#F G $^ G . G9G -G\ae04;?FF#F F $^ F . F9F FZ_c*.;?AA: A \ A ( A9A -AF$$!!r>r)G __future__rtypingcore.client_wrapperrrcore.request_optionsr8types.adhoc_agent_config_override_for_test_request_modelr+types.agent_platform_settings_request_modelr .types.agent_simulated_chat_test_response_modelr types.agent_sort_byr "types.agent_workflow_request_modelr +types.conversation_simulation_specificationr types.conversational_configr!types.create_agent_response_modelrtypes.get_agent_response_modelr$types.get_agents_page_response_modelr.types.get_test_suite_invocation_response_modelr types.prompt_evaluation_criteriar#types.single_test_run_request_modelrtypes.sort_directionr raw_clientrrYtypes.body_patches_an_agent_settings_v_1_convai_agents_agent_id_patch_procedure_refs_itemr TYPE_CHECKINGrrrrrrrrrrr r!rr"r#rr$r%rr&r'rr(r)castAnyrr+rrr>r<rs# H2s\a.K^?ICNaHL1= DM>T8EG>v{{6::s#` ` Fh h r>