pydo.genai.update_agent()

Generated on 9 Jun 2026 from pydo version v0.36.0

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Usage 

client.genai.update_agent(
    uuid="\"123e4567-e89b-12d3-a456-426614174000\"",
    body={
        "agent_log_insights_enabled": True,
        "allowed_domains": [...],
        "anthropic_key_uuid": "\"12345678-1234-1234-1234-123456789012\"",
        ...,
    },
)
Returns JSONRaises HttpResponseError

Description

To update an agent, send a PUT request to /v2/gen-ai/agents/{uuid}. The response body is a JSON object containing the agent.

Parameters

uuid string required

Unique agent id

agent_log_insights_enabled boolean optional

Example: True

allowed_domains array of strings optional

Example: ['example string']

Optional list of allowed domains for the chatbot - Must use fully qualified domain name (FQDN) such as https://example.com

anthropic_key_uuid string optional

Example: "12345678-1234-1234-1234-123456789012"

Optional anthropic key uuid for use with anthropic models

clear_mcp_servers boolean optional

Example: True

When true, removes all MCP servers from the agent. Use this instead of sending an empty mcp_servers array.

conversation_logs_enabled boolean optional

Example: True

Optional update of conversation logs enabled

description string optional

Example: "My Agent Description"

Agent description

instruction string optional

Example: "You are an agent who thinks deeply about the world"

Agent instruction. Instructions help your agent to perform its job effectively. See Write Effective Agent Instructions for best practices.

k integer optional

Example: 5

How many results should be considered from an attached knowledge base

max_tokens integer optional

Example: 100

Specifies the maximum number of tokens the model can process in a single input or output, set as a number between 1 and 512. This determines the length of each response.

mcp_servers array of objects optional

MCP (Model Context Protocol) servers to attach to the agent

Show child properties
allowed_tools array of strings optional

Example: ['example string']

Optional list of allowed tool names to expose from this server

authorization string optional

Example: example string

Optional authorization header value for the MCP server

headers object optional

Optional additional headers to send to the MCP server

server_label string optional

Example: example string

A label identifying this MCP server

server_url string optional

Example: example string

The URL of the MCP server

model_provider_key_uuid string optional

Example: "12345678-1234-1234-1234-123456789012"

Optional Model Provider uuid for use with provider models

model_router_uuid string optional

Example: "12345678-1234-1234-1234-123456789012"

model_uuid string optional

Example: "12345678-1234-1234-1234-123456789012"

Identifier for the foundation model.

name string optional

Example: "My New Agent Name"

Agent name

open_ai_key_uuid string optional

Example: "12345678-1234-1234-1234-123456789012"

Optional OpenAI key uuid for use with OpenAI models

project_id string optional

Example: "12345678-1234-1234-1234-123456789012"

The id of the DigitalOcean project this agent will belong to

provide_citations boolean optional

Example: True

reasoning_effort string optional

Example: "low"

retrieval_method string optional

- RETRIEVAL_METHOD_UNKNOWN: The retrieval method is unknown
- RETRIEVAL_METHOD_REWRITE: The retrieval method is rewrite
- RETRIEVAL_METHOD_STEP_BACK: The retrieval method is step back
- RETRIEVAL_METHOD_SUB_QUERIES: The retrieval method is sub queries
- RETRIEVAL_METHOD_NONE: The retrieval method is none

One of: RETRIEVAL_METHOD_UNKNOWN, RETRIEVAL_METHOD_REWRITE, RETRIEVAL_METHOD_STEP_BACK, RETRIEVAL_METHOD_SUB_QUERIES, RETRIEVAL_METHOD_NONE

Default: RETRIEVAL_METHOD_UNKNOWN

router_preset_slug string optional

Example: "general"

tags array of strings optional

Example: ['example string']

A set of abitrary tags to organize your agent

temperature number optional

Example: 0.7

Controls the model’s creativity, specified as a number between 0 and 1. Lower values produce more predictable and conservative responses, while higher values encourage creativity and variation.

thinking_token_budget integer optional

Example: 123

top_p number optional

Example: 0.9

Defines the cumulative probability threshold for word selection, specified as a number between 0 and 1. Higher values allow for more diverse outputs, while lower values ensure focused and coherent responses.

uuid string optional

Example: "12345678-1234-1234-1234-123456789012"

Unique agent id

Request Sample

Show Request Sample 
import os
from pydo import Client

client = Client(token=os.environ.get("DIGITALOCEAN_TOKEN"))

req = {
  "agent_log_insights_enabled": True,
  "allowed_domains": [
    "example string"
  ],
  "anthropic_key_uuid": "\"12345678-1234-1234-1234-123456789012\"",
  "clear_mcp_servers": True,
  "conversation_logs_enabled": True,
  "description": "\"My Agent Description\"",
  "instruction": "\"You are an agent who thinks deeply about the world\"",
  "k": 5,
  "max_tokens": 100,
  "mcp_servers": [
    {
      "allowed_tools": [
        "example string"
      ],
      "authorization": "example string",
      "server_label": "example string",
      "server_url": "example string"
    }
  ],
  "model_provider_key_uuid": "\"12345678-1234-1234-1234-123456789012\"",
  "model_router_uuid": "\"12345678-1234-1234-1234-123456789012\"",
  "model_uuid": "\"12345678-1234-1234-1234-123456789012\"",
  "name": "\"My New Agent Name\"",
  "open_ai_key_uuid": "\"12345678-1234-1234-1234-123456789012\"",
  "project_id": "\"12345678-1234-1234-1234-123456789012\"",
  "provide_citations": True,
  "reasoning_effort": "\"low\"",
  "retrieval_method": "RETRIEVAL_METHOD_UNKNOWN",
  "router_preset_slug": "\"general\"",
  "tags": [
    "example string"
  ],
  "temperature": 0.7,
  "thinking_token_budget": 123,
  "top_p": 0.9,
  "uuid": "\"12345678-1234-1234-1234-123456789012\""
}

resp = client.genai.update_agent(uuid="\"123e4567-e89b-12d3-a456-426614174000\"", body=req)

Response Example

Show Response Example 
{
  "agent": {
    "anthropic_api_key": {
      "created_at": "2023-01-01T00:00:00Z",
      "created_by": "12345",
      "deleted_at": "2023-01-01T00:00:00Z",
      "name": "example name",
      "updated_at": "2023-01-01T00:00:00Z",
      "uuid": "123e4567-e89b-12d3-a456-426614174000"
    },
    "api_key_infos": [],
    "api_keys": [],
    "chatbot": {
      "allowed_domains": [
        "example string"
      ],
      "button_background_color": "example string",
      "logo": "example string",
      "name": "example name",
      "primary_color": "example string",
      "secondary_color": "example string",
      "starting_message": "example string"
    },
    "chatbot_identifiers": [],
    "child_agents": [],
    "conversation_logs_enabled": true,
    "created_at": "2023-01-01T00:00:00Z",
    "deployment": {
      "created_at": "2023-01-01T00:00:00Z",
      "name": "example name",
      "status": "STATUS_UNKNOWN",
      "updated_at": "2023-01-01T00:00:00Z",
      "url": "example string",
      "uuid": "123e4567-e89b-12d3-a456-426614174000",
      "visibility": "VISIBILITY_UNKNOWN"
    },
    "description": "example string",
    "functions": [],
    "guardrails": [],
    "if_case": "example string",
    "instruction": "example string",
    "k": 123,
    "knowledge_bases": [],
    "logging_config": {
      "galileo_project_id": "123e4567-e89b-12d3-a456-426614174000",
      "galileo_project_name": "example name",
      "insights_enabled": true,
      "insights_enabled_at": "2023-01-01T00:00:00Z",
      "log_stream_id": "123e4567-e89b-12d3-a456-426614174000",
      "log_stream_name": "example name"
    },
    "max_tokens": 123,
    "mcp_servers": [],
    "model": {
      "capabilities": [
        "example string"
      ],
      "context_window": "12345",
      "created_at": "2023-01-01T00:00:00Z",
      "endpoints": [],
      "inference_name": "example name",
      "inference_version": "example string",
      "is_foundational": true,
      "kb_default_chunk_size": 123,
      "kb_max_chunk_size": 123,
      "kb_min_chunk_size": 123,
      "lifecycle_status": "example string",
      "name": "example name",
      "parameter_count": 123,
      "parent_uuid": "123e4567-e89b-12d3-a456-426614174000",
      "provider": "MODEL_PROVIDER_DIGITALOCEAN",
      "reasoning_efforts": [
        "example string"
      ],
      "settings": [],
      "thinking": true,
      "type": "example string",
      "updated_at": "2023-01-01T00:00:00Z",
      "upload_complete": true,
      "url": "example string",
      "usecases": [
        "MODEL_USECASE_AGENT",
        "MODEL_USECASE_GUARDRAIL"
      ],
      "uuid": "123e4567-e89b-12d3-a456-426614174000"
    },
    "model_provider_key": {
      "api_key_uuid": "123e4567-e89b-12d3-a456-426614174000",
      "created_at": "2023-01-01T00:00:00Z",
      "created_by": "12345",
      "deleted_at": "2023-01-01T00:00:00Z",
      "models": [],
      "name": "example name",
      "provider": "MODEL_PROVIDER_DIGITALOCEAN",
      "updated_at": "2023-01-01T00:00:00Z"
    },
    "model_router": {
      "created_at": "2023-01-01T00:00:00Z",
      "description": "example string",
      "name": "example name",
      "regions": [
        "example string"
      ],
      "updated_at": "2023-01-01T00:00:00Z",
      "uuid": "123e4567-e89b-12d3-a456-426614174000"
    },
    "name": "example name",
    "openai_api_key": {
      "created_at": "2023-01-01T00:00:00Z",
      "created_by": "12345",
      "deleted_at": "2023-01-01T00:00:00Z",
      "models": [],
      "name": "example name",
      "updated_at": "2023-01-01T00:00:00Z",
      "uuid": "123e4567-e89b-12d3-a456-426614174000"
    },
    "parent_agents": [],
    "project_id": "123e4567-e89b-12d3-a456-426614174000",
    "provide_citations": true,
    "reasoning_effort": "example string",
    "region": "example string",
    "retrieval_method": "RETRIEVAL_METHOD_UNKNOWN",
    "route_created_at": "2023-01-01T00:00:00Z",
    "route_created_by": "12345",
    "route_name": "example name",
    "route_uuid": "123e4567-e89b-12d3-a456-426614174000",
    "tags": [
      "example string"
    ],
    "temperature": 123,
    "template": {
      "created_at": "2023-01-01T00:00:00Z",
      "description": "example string",
      "guardrails": [],
      "instruction": "example string",
      "k": 123,
      "knowledge_bases": [],
      "long_description": "\"Enhance your customer service with an AI agent designed to provide consistent, helpful, and accurate support across multiple channels. This template creates an agent that can answer product questions, troubleshoot common issues, process simple requests, and maintain a friendly, on-brand voice throughout customer interactions. Reduce response times, handle routine inquiries efficiently, and ensure your customers feel heard and helped.\"",
      "max_tokens": 123,
      "name": "example name",
      "short_description": "\"This template has been designed with question-answer and conversational use cases in mind. It comes with validated agent instructions, fine-tuned model settings, and preconfigured guardrails defined for customer support-related use cases.\"",
      "summary": "example string",
      "tags": [
        "example string"
      ],
      "temperature": 123,
      "template_type": "AGENT_TEMPLATE_TYPE_STANDARD",
      "top_p": 123,
      "updated_at": "2023-01-01T00:00:00Z",
      "uuid": "123e4567-e89b-12d3-a456-426614174000"
    },
    "thinking_token_budget": 123,
    "top_p": 123,
    "updated_at": "2023-01-01T00:00:00Z",
    "url": "example string",
    "user_id": "12345",
    "uuid": "123e4567-e89b-12d3-a456-426614174000",
    "version_hash": "example string",
    "vpc_egress_ips": [
      "example string"
    ],
    "vpc_uuid": "\"12345678-1234-1234-1234-123456789012\"",
    "workspace": {
      "agents": [],
      "created_at": "2023-01-01T00:00:00Z",
      "created_by": "12345",
      "created_by_email": "[email protected]",
      "deleted_at": "2023-01-01T00:00:00Z",
      "description": "example string",
      "evaluation_test_cases": [],
      "name": "example name",
      "updated_at": "2023-01-01T00:00:00Z",
      "uuid": "123e4567-e89b-12d3-a456-426614174000"
    }
  }
}

More Information

See /v2/gen-ai/agents/{uuid} in the API reference for additional detail on responses, headers, parameters, and more.

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