Implementation:Elevenlabs Elevenlabs python GetAgentResponseModel

Field	Value
source	Elevenlabs_Elevenlabs_python
domains	Conversational AI, Agent Management, API Response
last_updated	2026-02-15

Overview

Description

GetAgentResponseModel is a Pydantic model representing the full response returned when retrieving an agent from the ElevenLabs Conversational AI API. It is the top-level response object that aggregates all facets of an agent's configuration, including conversation settings, metadata, platform settings, phone numbers, WhatsApp accounts, workflows, and version/branch tracking.

This model is auto-generated by Fern from the ElevenLabs API definition and inherits from UncheckedBaseModel. It serves as the primary data structure for agent retrieval operations.

Usage

GetAgentResponseModel is returned by the ElevenLabs API when fetching an agent by ID. It provides a comprehensive view of the agent's current state, including all configuration, metadata, and connected channels (phone, WhatsApp). It is typically consumed by client applications to display or manage agent settings.

Code Reference

Source Location

src/elevenlabs/types/get_agent_response_model.py

Class Signature

class GetAgentResponseModel(UncheckedBaseModel):
    ...

Import Statement

from elevenlabs.types import GetAgentResponseModel

I/O Contract

Field	Type	Required	Description
agent_id	str	Yes	The ID of the agent.
name	str	Yes	The name of the agent.
conversation_config	ConversationalConfig	Yes	The conversation configuration of the agent.
metadata	AgentMetadataResponseModel	Yes	The metadata of the agent.
platform_settings	Optional[AgentPlatformSettingsResponseModel]	No	The platform settings of the agent.
phone_numbers	Optional[List[GetAgentResponseModelPhoneNumbersItem]]	No	The phone numbers of the agent.
whatsapp_accounts	Optional[List[GetWhatsAppAccountResponse]]	No	WhatsApp accounts assigned to the agent.
workflow	Optional[AgentWorkflowResponseModel]	No	The workflow of the agent.
access_info	Optional[ResourceAccessInfo]	No	The access information of the agent for the user.
tags	Optional[List[str]]	No	Agent tags used to categorize the agent.
version_id	Optional[str]	No	The ID of the version the agent is on.
branch_id	Optional[str]	No	The ID of the branch the agent is on.
main_branch_id	Optional[str]	No	The ID of the main branch for this agent.

Usage Examples

Retrieving and Inspecting an Agent

from elevenlabs import ElevenLabs

client = ElevenLabs(api_key="your-api-key")
agent = client.conversational_ai.agents.get(agent_id="agent_abc123")

# agent is a GetAgentResponseModel instance
print(f"Agent: {agent.name} (ID: {agent.agent_id})")
print(f"Branch: {agent.branch_id}")
print(f"Tags: {agent.tags}")

Accessing Nested Configuration

# Access the conversation configuration
conv_config = agent.conversation_config

# Access phone numbers if assigned
if agent.phone_numbers:
    for phone in agent.phone_numbers:
        print(f"Phone: {phone}")

# Check version and branch info
if agent.version_id:
    print(f"Version: {agent.version_id}")
if agent.branch_id:
    print(f"Branch: {agent.branch_id}")

Related Pages

• Elevenlabs_Elevenlabs_python_AgentConfig - Core agent configuration nested within the conversation config
• Elevenlabs_Elevenlabs_python_AgentBranchSummary - Branch summary model for agent versioning
• Elevenlabs_Elevenlabs_python_PromptAgentApiModelInput - Agent prompt configuration input
• Elevenlabs_Elevenlabs_python_AuthSettings - Authentication settings for the agent