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API Reference
Agents
Create an Agent
post/v2/gen-ai/agents

To create a new agent, send a POST request to /v2/gen-ai/agents. The response body contains a JSON object with the newly created agent object.

Body ParametersExpand Collapse
anthropic_key_uuid: optional string

Optional Anthropic API key ID to use with Anthropic models

description: optional string

A text description of the agent, not used in inference

instruction: optional string

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

knowledge_base_uuid: optional array of string

Ids of the knowledge base(s) to attach to the agent

model_uuid: optional string

Identifier for the foundation model.

name: optional string

Agent name

open_ai_key_uuid: optional string

Optional OpenAI API key ID to use with OpenAI models

project_id: optional string

The id of the DigitalOcean project this agent will belong to

region: optional string

The DigitalOcean region to deploy your agent in

tags: optional array of string

Agent tag to organize related resources

ReturnsExpand Collapse
agent: optional APIAgent { anthropic_api_key, api_key_infos, api_keys, 37 more }

An Agent

anthropic_api_key: optional APIAnthropicAPIKeyInfo { created_at, created_by, deleted_at, 3 more }

Anthropic API Key Info

created_at: optional string

Key creation date

formatdate-time
created_by: optional string

Created by user id from DO

formatuint64
deleted_at: optional string

Key deleted date

formatdate-time
name: optional string

Name

updated_at: optional string

Key last updated date

formatdate-time
uuid: optional string

Uuid

api_key_infos: optional array of APIAgentAPIKeyInfo { created_at, created_by, deleted_at, 3 more }

Api key infos

created_at: optional string

Creation date

formatdate-time
created_by: optional string

Created by

formatuint64
deleted_at: optional string

Deleted date

formatdate-time
name: optional string

Name

secret_key: optional string
uuid: optional string

Uuid

api_keys: optional array of object { api_key }

Api keys

api_key: optional string

Api key

chatbot: optional object { button_background_color, logo, name, 3 more }

A Chatbot

button_background_color: optional string
name: optional string

Name of chatbot

primary_color: optional string
secondary_color: optional string
starting_message: optional string
chatbot_identifiers: optional array of object { agent_chatbot_identifier }

Chatbot identifiers

agent_chatbot_identifier: optional string

Agent chatbot identifier

child_agents: optional array of APIAgent { anthropic_api_key, api_key_infos, api_keys, 37 more }

Child agents

conversation_logs_enabled: optional boolean

Whether conversation logs are enabled for the agent

created_at: optional string

Creation date / time

formatdate-time
deployment: optional object { created_at, name, status, 4 more }

Description of deployment

created_at: optional string

Creation date / time

formatdate-time
name: optional string

Name

status: optional "STATUS_UNKNOWN" or "STATUS_WAITING_FOR_DEPLOYMENT" or "STATUS_DEPLOYING" or 6 more
Accepts one of the following:
"STATUS_UNKNOWN"
"STATUS_WAITING_FOR_DEPLOYMENT"
"STATUS_DEPLOYING"
"STATUS_RUNNING"
"STATUS_FAILED"
"STATUS_WAITING_FOR_UNDEPLOYMENT"
"STATUS_UNDEPLOYING"
"STATUS_UNDEPLOYMENT_FAILED"
"STATUS_DELETED"
updated_at: optional string

Last modified

formatdate-time
url: optional string

Access your deployed agent here

uuid: optional string

Unique id

visibility: optional APIDeploymentVisibility
  • VISIBILITY_UNKNOWN: The status of the deployment is unknown
  • VISIBILITY_DISABLED: The deployment is disabled and will no longer service requests
  • VISIBILITY_PLAYGROUND: Deprecated: No longer a valid state
  • VISIBILITY_PUBLIC: The deployment is public and will service requests from the public internet
  • VISIBILITY_PRIVATE: The deployment is private and will only service requests from other agents, or through API keys
Accepts one of the following:
"VISIBILITY_UNKNOWN"
"VISIBILITY_DISABLED"
"VISIBILITY_PLAYGROUND"
"VISIBILITY_PUBLIC"
"VISIBILITY_PRIVATE"
description: optional string

Description of agent

functions: optional array of object { api_key, created_at, created_by, 9 more }
api_key: optional string

Api key

created_at: optional string

Creation date / time

formatdate-time
created_by: optional string

Created by user id from DO

formatuint64
description: optional string

Agent description

faas_name: optional string
faas_namespace: optional string
input_schema: optional unknown
name: optional string

Name

output_schema: optional unknown
updated_at: optional string

Last modified

formatdate-time
url: optional string

Download your agent here

uuid: optional string

Unique id

guardrails: optional array of object { agent_uuid, created_at, default_response, 10 more }

The guardrails the agent is attached to

agent_uuid: optional string
created_at: optional string
formatdate-time
default_response: optional string
description: optional string
guardrail_uuid: optional string
is_attached: optional boolean
is_default: optional boolean
metadata: optional unknown
name: optional string
priority: optional number
formatint32
type: optional "GUARDRAIL_TYPE_UNKNOWN" or "GUARDRAIL_TYPE_JAILBREAK" or "GUARDRAIL_TYPE_SENSITIVE_DATA" or "GUARDRAIL_TYPE_CONTENT_MODERATION"
Accepts one of the following:
"GUARDRAIL_TYPE_UNKNOWN"
"GUARDRAIL_TYPE_JAILBREAK"
"GUARDRAIL_TYPE_SENSITIVE_DATA"
"GUARDRAIL_TYPE_CONTENT_MODERATION"
updated_at: optional string
formatdate-time
uuid: optional string
if_case: optional string
instruction: optional string

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

k: optional number
formatint64
knowledge_bases: optional array of APIKnowledgeBase { added_to_agent_at, created_at, database_id, 10 more }

Knowledge bases

added_to_agent_at: optional string

Time when the knowledge base was added to the agent

formatdate-time
created_at: optional string

Creation date / time

formatdate-time
database_id: optional string
embedding_model_uuid: optional string
is_public: optional boolean

Whether the knowledge base is public or not

last_indexing_job: optional APIIndexingJob { completed_datasources, created_at, data_source_uuids, 12 more }

IndexingJob description

completed_datasources: optional number

Number of datasources indexed completed

formatint64
created_at: optional string

Creation date / time

formatdate-time
data_source_uuids: optional array of string
finished_at: optional string
formatdate-time
knowledge_base_uuid: optional string

Knowledge base id

phase: optional "BATCH_JOB_PHASE_UNKNOWN" or "BATCH_JOB_PHASE_PENDING" or "BATCH_JOB_PHASE_RUNNING" or 4 more
Accepts one of the following:
"BATCH_JOB_PHASE_UNKNOWN"
"BATCH_JOB_PHASE_PENDING"
"BATCH_JOB_PHASE_RUNNING"
"BATCH_JOB_PHASE_SUCCEEDED"
"BATCH_JOB_PHASE_FAILED"
"BATCH_JOB_PHASE_ERROR"
"BATCH_JOB_PHASE_CANCELLED"
started_at: optional string
formatdate-time
status: optional "INDEX_JOB_STATUS_UNKNOWN" or "INDEX_JOB_STATUS_PARTIAL" or "INDEX_JOB_STATUS_IN_PROGRESS" or 4 more
Accepts one of the following:
"INDEX_JOB_STATUS_UNKNOWN"
"INDEX_JOB_STATUS_PARTIAL"
"INDEX_JOB_STATUS_IN_PROGRESS"
"INDEX_JOB_STATUS_COMPLETED"
"INDEX_JOB_STATUS_FAILED"
"INDEX_JOB_STATUS_NO_CHANGES"
"INDEX_JOB_STATUS_PENDING"
tokens: optional number

Number of tokens

formatint64
total_datasources: optional number

Number of datasources being indexed

formatint64
total_items_failed: optional string

Total Items Failed

formatuint64
total_items_indexed: optional string

Total Items Indexed

formatuint64
total_items_skipped: optional string

Total Items Skipped

formatuint64
updated_at: optional string

Last modified

formatdate-time
uuid: optional string

Unique id

name: optional string

Name of knowledge base

project_id: optional string
region: optional string

Region code

tags: optional array of string

Tags to organize related resources

updated_at: optional string

Last modified

formatdate-time
user_id: optional string

Id of user that created the knowledge base

formatint64
uuid: optional string

Unique id for knowledge base

logging_config: optional object { galileo_project_id, galileo_project_name, insights_enabled, 3 more }
galileo_project_id: optional string

Galileo project identifier

galileo_project_name: optional string

Name of the Galileo project

insights_enabled: optional boolean

Whether insights are enabled

insights_enabled_at: optional string

Timestamp when insights were enabled

formatdate-time
log_stream_id: optional string

Identifier for the log stream

log_stream_name: optional string

Name of the log stream

max_tokens: optional number
formatint64
model: optional APIAgentModel { agreement, created_at, inference_name, 12 more }

Description of a Model

agreement: optional APIAgreement { description, name, url, uuid }

Agreement Description

description: optional string
name: optional string
url: optional string
uuid: optional string
created_at: optional string

Creation date / time

formatdate-time
inference_name: optional string

Internally used name

inference_version: optional string

Internally used version

is_foundational: optional boolean

True if it is a foundational model provided by do

metadata: optional unknown

Additional meta data

name: optional string

Name of the model

parent_uuid: optional string

Unique id of the model, this model is based on

provider: optional "MODEL_PROVIDER_DIGITALOCEAN" or "MODEL_PROVIDER_ANTHROPIC" or "MODEL_PROVIDER_OPENAI"
Accepts one of the following:
"MODEL_PROVIDER_DIGITALOCEAN"
"MODEL_PROVIDER_ANTHROPIC"
"MODEL_PROVIDER_OPENAI"
updated_at: optional string

Last modified

formatdate-time
upload_complete: optional boolean

Model has been fully uploaded

url: optional string

Download url

usecases: optional array of "MODEL_USECASE_UNKNOWN" or "MODEL_USECASE_AGENT" or "MODEL_USECASE_FINETUNED" or 4 more

Usecases of the model

Accepts one of the following:
"MODEL_USECASE_UNKNOWN"
"MODEL_USECASE_AGENT"
"MODEL_USECASE_FINETUNED"
"MODEL_USECASE_KNOWLEDGEBASE"
"MODEL_USECASE_GUARDRAIL"
"MODEL_USECASE_REASONING"
"MODEL_USECASE_SERVERLESS"
uuid: optional string

Unique id

version: optional APIModelVersion { major, minor, patch }

Version Information about a Model

major: optional number

Major version number

formatint64
minor: optional number

Minor version number

formatint64
patch: optional number

Patch version number

formatint64
name: optional string

Agent name

openai_api_key: optional APIOpenAIAPIKeyInfo { created_at, created_by, deleted_at, 4 more }

OpenAI API Key Info

created_at: optional string

Key creation date

formatdate-time
created_by: optional string

Created by user id from DO

formatuint64
deleted_at: optional string

Key deleted date

formatdate-time
models: optional array of APIAgentModel { agreement, created_at, inference_name, 12 more }

Models supported by the openAI api key

agreement: optional APIAgreement { description, name, url, uuid }

Agreement Description

description: optional string
name: optional string
url: optional string
uuid: optional string
created_at: optional string

Creation date / time

formatdate-time
inference_name: optional string

Internally used name

inference_version: optional string

Internally used version

is_foundational: optional boolean

True if it is a foundational model provided by do

metadata: optional unknown

Additional meta data

name: optional string

Name of the model

parent_uuid: optional string

Unique id of the model, this model is based on

provider: optional "MODEL_PROVIDER_DIGITALOCEAN" or "MODEL_PROVIDER_ANTHROPIC" or "MODEL_PROVIDER_OPENAI"
Accepts one of the following:
"MODEL_PROVIDER_DIGITALOCEAN"
"MODEL_PROVIDER_ANTHROPIC"
"MODEL_PROVIDER_OPENAI"
updated_at: optional string

Last modified

formatdate-time
upload_complete: optional boolean

Model has been fully uploaded

url: optional string

Download url

usecases: optional array of "MODEL_USECASE_UNKNOWN" or "MODEL_USECASE_AGENT" or "MODEL_USECASE_FINETUNED" or 4 more

Usecases of the model

Accepts one of the following:
"MODEL_USECASE_UNKNOWN"
"MODEL_USECASE_AGENT"
"MODEL_USECASE_FINETUNED"
"MODEL_USECASE_KNOWLEDGEBASE"
"MODEL_USECASE_GUARDRAIL"
"MODEL_USECASE_REASONING"
"MODEL_USECASE_SERVERLESS"
uuid: optional string

Unique id

version: optional APIModelVersion { major, minor, patch }

Version Information about a Model

major: optional number

Major version number

formatint64
minor: optional number

Minor version number

formatint64
patch: optional number

Patch version number

formatint64
name: optional string

Name

updated_at: optional string

Key last updated date

formatdate-time
uuid: optional string

Uuid

parent_agents: optional array of APIAgent { anthropic_api_key, api_key_infos, api_keys, 37 more }

Parent agents

project_id: optional string
provide_citations: optional boolean

Whether the agent should provide in-response citations

region: optional string

Region code

retrieval_method: optional APIRetrievalMethod
  • 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
Accepts one of the following:
"RETRIEVAL_METHOD_UNKNOWN"
"RETRIEVAL_METHOD_REWRITE"
"RETRIEVAL_METHOD_STEP_BACK"
"RETRIEVAL_METHOD_SUB_QUERIES"
"RETRIEVAL_METHOD_NONE"
route_created_at: optional string

Creation of route date / time

formatdate-time
route_created_by: optional string
formatuint64
route_name: optional string

Route name

route_uuid: optional string
tags: optional array of string

Agent tag to organize related resources

temperature: optional number
formatfloat
template: optional object { created_at, description, guardrails, 15 more }

Represents an AgentTemplate entity

created_at: optional string

The agent template's creation date

formatdate-time
description: optional string

Deprecated - Use summary instead

guardrails: optional array of object { priority, uuid }

List of guardrails associated with the agent template

priority: optional number

Priority of the guardrail

formatint32
uuid: optional string

Uuid of the guardrail

instruction: optional string

Instructions for the agent template

k: optional number

The 'k' value for the agent template

formatint64
knowledge_bases: optional array of APIKnowledgeBase { added_to_agent_at, created_at, database_id, 10 more }

List of knowledge bases associated with the agent template

added_to_agent_at: optional string

Time when the knowledge base was added to the agent

formatdate-time
created_at: optional string

Creation date / time

formatdate-time
database_id: optional string
embedding_model_uuid: optional string
is_public: optional boolean

Whether the knowledge base is public or not

last_indexing_job: optional APIIndexingJob { completed_datasources, created_at, data_source_uuids, 12 more }

IndexingJob description

completed_datasources: optional number

Number of datasources indexed completed

formatint64
created_at: optional string

Creation date / time

formatdate-time
data_source_uuids: optional array of string
finished_at: optional string
formatdate-time
knowledge_base_uuid: optional string

Knowledge base id

phase: optional "BATCH_JOB_PHASE_UNKNOWN" or "BATCH_JOB_PHASE_PENDING" or "BATCH_JOB_PHASE_RUNNING" or 4 more
Accepts one of the following:
"BATCH_JOB_PHASE_UNKNOWN"
"BATCH_JOB_PHASE_PENDING"
"BATCH_JOB_PHASE_RUNNING"
"BATCH_JOB_PHASE_SUCCEEDED"
"BATCH_JOB_PHASE_FAILED"
"BATCH_JOB_PHASE_ERROR"
"BATCH_JOB_PHASE_CANCELLED"
started_at: optional string
formatdate-time
status: optional "INDEX_JOB_STATUS_UNKNOWN" or "INDEX_JOB_STATUS_PARTIAL" or "INDEX_JOB_STATUS_IN_PROGRESS" or 4 more
Accepts one of the following:
"INDEX_JOB_STATUS_UNKNOWN"
"INDEX_JOB_STATUS_PARTIAL"
"INDEX_JOB_STATUS_IN_PROGRESS"
"INDEX_JOB_STATUS_COMPLETED"
"INDEX_JOB_STATUS_FAILED"
"INDEX_JOB_STATUS_NO_CHANGES"
"INDEX_JOB_STATUS_PENDING"
tokens: optional number

Number of tokens

formatint64
total_datasources: optional number

Number of datasources being indexed

formatint64
total_items_failed: optional string

Total Items Failed

formatuint64
total_items_indexed: optional string

Total Items Indexed

formatuint64
total_items_skipped: optional string

Total Items Skipped

formatuint64
updated_at: optional string

Last modified

formatdate-time
uuid: optional string

Unique id

name: optional string

Name of knowledge base

project_id: optional string
region: optional string

Region code

tags: optional array of string

Tags to organize related resources

updated_at: optional string

Last modified

formatdate-time
user_id: optional string

Id of user that created the knowledge base

formatint64
uuid: optional string

Unique id for knowledge base

long_description: optional string

The long description of the agent template

max_tokens: optional number

The max_tokens setting for the agent template

formatint64
model: optional APIAgentModel { agreement, created_at, inference_name, 12 more }

Description of a Model

agreement: optional APIAgreement { description, name, url, uuid }

Agreement Description

description: optional string
name: optional string
url: optional string
uuid: optional string
created_at: optional string

Creation date / time

formatdate-time
inference_name: optional string

Internally used name

inference_version: optional string

Internally used version

is_foundational: optional boolean

True if it is a foundational model provided by do

metadata: optional unknown

Additional meta data

name: optional string

Name of the model

parent_uuid: optional string

Unique id of the model, this model is based on

provider: optional "MODEL_PROVIDER_DIGITALOCEAN" or "MODEL_PROVIDER_ANTHROPIC" or "MODEL_PROVIDER_OPENAI"
Accepts one of the following:
"MODEL_PROVIDER_DIGITALOCEAN"
"MODEL_PROVIDER_ANTHROPIC"
"MODEL_PROVIDER_OPENAI"
updated_at: optional string

Last modified

formatdate-time
upload_complete: optional boolean

Model has been fully uploaded

url: optional string

Download url

usecases: optional array of "MODEL_USECASE_UNKNOWN" or "MODEL_USECASE_AGENT" or "MODEL_USECASE_FINETUNED" or 4 more

Usecases of the model

Accepts one of the following:
"MODEL_USECASE_UNKNOWN"
"MODEL_USECASE_AGENT"
"MODEL_USECASE_FINETUNED"
"MODEL_USECASE_KNOWLEDGEBASE"
"MODEL_USECASE_GUARDRAIL"
"MODEL_USECASE_REASONING"
"MODEL_USECASE_SERVERLESS"
uuid: optional string

Unique id

version: optional APIModelVersion { major, minor, patch }

Version Information about a Model

major: optional number

Major version number

formatint64
minor: optional number

Minor version number

formatint64
patch: optional number

Patch version number

formatint64
name: optional string

Name of the agent template

short_description: optional string

The short description of the agent template

summary: optional string

The summary of the agent template

tags: optional array of string

List of tags associated with the agent template

temperature: optional number

The temperature setting for the agent template

formatfloat
template_type: optional "AGENT_TEMPLATE_TYPE_STANDARD" or "AGENT_TEMPLATE_TYPE_ONE_CLICK"
  • AGENT_TEMPLATE_TYPE_STANDARD: The standard agent template
  • AGENT_TEMPLATE_TYPE_ONE_CLICK: The one click agent template
Accepts one of the following:
"AGENT_TEMPLATE_TYPE_STANDARD"
"AGENT_TEMPLATE_TYPE_ONE_CLICK"
top_p: optional number

The top_p setting for the agent template

formatfloat
updated_at: optional string

The agent template's last updated date

formatdate-time
uuid: optional string

Unique id

top_p: optional number
formatfloat
updated_at: optional string

Last modified

formatdate-time
url: optional string

Access your agent under this url

user_id: optional string

Id of user that created the agent

formatuint64
uuid: optional string

Unique agent id

version_hash: optional string

The latest version of the agent

workspace: optional APIWorkspace { agents, created_at, created_by, 7 more }
Create an Agent
  • http
  • typescript
  • python
curl https://api.digitalocean.com/v2/gen-ai/agents \
    -H 'Content-Type: application/json' \
    -H "Authorization: Bearer $DIGITALOCEAN_ACCESS_TOKEN"
{
  "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": [
      {
        "created_at": "2023-01-01T00:00:00Z",
        "created_by": "12345",
        "deleted_at": "2023-01-01T00:00:00Z",
        "name": "example name",
        "secret_key": "example string",
        "uuid": "123e4567-e89b-12d3-a456-426614174000"
      }
    ],
    "api_keys": [
      {
        "api_key": "example string"
      }
    ],
    "chatbot": {
      "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": [
      {
        "agent_chatbot_identifier": "123e4567-e89b-12d3-a456-426614174000"
      }
    ],
    "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": [
      {
        "api_key": "example string",
        "created_at": "2023-01-01T00:00:00Z",
        "created_by": "12345",
        "description": "example string",
        "faas_name": "example name",
        "faas_namespace": "example name",
        "input_schema": {},
        "name": "example name",
        "output_schema": {},
        "updated_at": "2023-01-01T00:00:00Z",
        "url": "example string",
        "uuid": "123e4567-e89b-12d3-a456-426614174000"
      }
    ],
    "guardrails": [
      {
        "agent_uuid": "123e4567-e89b-12d3-a456-426614174000",
        "created_at": "2023-01-01T00:00:00Z",
        "default_response": "example string",
        "description": "example string",
        "guardrail_uuid": "123e4567-e89b-12d3-a456-426614174000",
        "is_attached": true,
        "is_default": true,
        "metadata": {},
        "name": "example name",
        "priority": 123,
        "type": "GUARDRAIL_TYPE_UNKNOWN",
        "updated_at": "2023-01-01T00:00:00Z",
        "uuid": "123e4567-e89b-12d3-a456-426614174000"
      }
    ],
    "if_case": "example string",
    "instruction": "example string",
    "k": 123,
    "knowledge_bases": [
      {
        "added_to_agent_at": "2023-01-01T00:00:00Z",
        "created_at": "2023-01-01T00:00:00Z",
        "database_id": "123e4567-e89b-12d3-a456-426614174000",
        "embedding_model_uuid": "123e4567-e89b-12d3-a456-426614174000",
        "is_public": true,
        "last_indexing_job": {
          "completed_datasources": 123,
          "created_at": "2023-01-01T00:00:00Z",
          "data_source_uuids": [
            "example string"
          ],
          "finished_at": "2023-01-01T00:00:00Z",
          "knowledge_base_uuid": "123e4567-e89b-12d3-a456-426614174000",
          "phase": "BATCH_JOB_PHASE_UNKNOWN",
          "started_at": "2023-01-01T00:00:00Z",
          "status": "INDEX_JOB_STATUS_UNKNOWN",
          "tokens": 123,
          "total_datasources": 123,
          "total_items_failed": "12345",
          "total_items_indexed": "12345",
          "total_items_skipped": "12345",
          "updated_at": "2023-01-01T00:00:00Z",
          "uuid": "123e4567-e89b-12d3-a456-426614174000"
        },
        "name": "example name",
        "project_id": "123e4567-e89b-12d3-a456-426614174000",
        "region": "example string",
        "tags": [
          "example string"
        ],
        "updated_at": "2023-01-01T00:00:00Z",
        "user_id": "user_id",
        "uuid": "123e4567-e89b-12d3-a456-426614174000"
      }
    ],
    "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,
    "model": {
      "agreement": {
        "description": "example string",
        "name": "example name",
        "url": "example string",
        "uuid": "123e4567-e89b-12d3-a456-426614174000"
      },
      "created_at": "2023-01-01T00:00:00Z",
      "inference_name": "example name",
      "inference_version": "example string",
      "is_foundational": true,
      "metadata": {},
      "name": "example name",
      "parent_uuid": "123e4567-e89b-12d3-a456-426614174000",
      "provider": "MODEL_PROVIDER_DIGITALOCEAN",
      "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",
      "version": {
        "major": 123,
        "minor": 123,
        "patch": 123
      }
    },
    "name": "example name",
    "openai_api_key": {
      "created_at": "2023-01-01T00:00:00Z",
      "created_by": "12345",
      "deleted_at": "2023-01-01T00:00:00Z",
      "models": [
        {
          "agreement": {
            "description": "example string",
            "name": "example name",
            "url": "example string",
            "uuid": "123e4567-e89b-12d3-a456-426614174000"
          },
          "created_at": "2023-01-01T00:00:00Z",
          "inference_name": "example name",
          "inference_version": "example string",
          "is_foundational": true,
          "metadata": {},
          "name": "example name",
          "parent_uuid": "123e4567-e89b-12d3-a456-426614174000",
          "provider": "MODEL_PROVIDER_DIGITALOCEAN",
          "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",
          "version": {
            "major": 123,
            "minor": 123,
            "patch": 123
          }
        }
      ],
      "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,
    "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": [
        {
          "priority": 123,
          "uuid": "123e4567-e89b-12d3-a456-426614174000"
        }
      ],
      "instruction": "example string",
      "k": 123,
      "knowledge_bases": [
        {
          "added_to_agent_at": "2023-01-01T00:00:00Z",
          "created_at": "2023-01-01T00:00:00Z",
          "database_id": "123e4567-e89b-12d3-a456-426614174000",
          "embedding_model_uuid": "123e4567-e89b-12d3-a456-426614174000",
          "is_public": true,
          "last_indexing_job": {
            "completed_datasources": 123,
            "created_at": "2023-01-01T00:00:00Z",
            "data_source_uuids": [
              "example string"
            ],
            "finished_at": "2023-01-01T00:00:00Z",
            "knowledge_base_uuid": "123e4567-e89b-12d3-a456-426614174000",
            "phase": "BATCH_JOB_PHASE_UNKNOWN",
            "started_at": "2023-01-01T00:00:00Z",
            "status": "INDEX_JOB_STATUS_UNKNOWN",
            "tokens": 123,
            "total_datasources": 123,
            "total_items_failed": "12345",
            "total_items_indexed": "12345",
            "total_items_skipped": "12345",
            "updated_at": "2023-01-01T00:00:00Z",
            "uuid": "123e4567-e89b-12d3-a456-426614174000"
          },
          "name": "example name",
          "project_id": "123e4567-e89b-12d3-a456-426614174000",
          "region": "example string",
          "tags": [
            "example string"
          ],
          "updated_at": "2023-01-01T00:00:00Z",
          "user_id": "user_id",
          "uuid": "123e4567-e89b-12d3-a456-426614174000"
        }
      ],
      "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,
      "model": {
        "agreement": {
          "description": "example string",
          "name": "example name",
          "url": "example string",
          "uuid": "123e4567-e89b-12d3-a456-426614174000"
        },
        "created_at": "2023-01-01T00:00:00Z",
        "inference_name": "example name",
        "inference_version": "example string",
        "is_foundational": true,
        "metadata": {},
        "name": "example name",
        "parent_uuid": "123e4567-e89b-12d3-a456-426614174000",
        "provider": "MODEL_PROVIDER_DIGITALOCEAN",
        "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",
        "version": {
          "major": 123,
          "minor": 123,
          "patch": 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"
    },
    "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",
    "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": [
        {
          "archived_at": "2023-01-01T00:00:00Z",
          "created_at": "2023-01-01T00:00:00Z",
          "created_by_user_email": "[email protected]",
          "created_by_user_id": "12345",
          "dataset": {
            "created_at": "2023-01-01T00:00:00Z",
            "dataset_name": "example name",
            "dataset_uuid": "123e4567-e89b-12d3-a456-426614174000",
            "file_size": "12345",
            "has_ground_truth": true,
            "row_count": 123
          },
          "dataset_name": "example name",
          "dataset_uuid": "123e4567-e89b-12d3-a456-426614174000",
          "description": "example string",
          "latest_version_number_of_runs": 123,
          "metrics": [
            {
              "description": "example string",
              "inverted": true,
              "metric_name": "example name",
              "metric_type": "METRIC_TYPE_UNSPECIFIED",
              "metric_uuid": "123e4567-e89b-12d3-a456-426614174000",
              "metric_value_type": "METRIC_VALUE_TYPE_UNSPECIFIED",
              "range_max": 123,
              "range_min": 123
            }
          ],
          "name": "example name",
          "star_metric": {
            "metric_uuid": "123e4567-e89b-12d3-a456-426614174000",
            "name": "example name",
            "success_threshold": 123,
            "success_threshold_pct": 123
          },
          "test_case_uuid": "123e4567-e89b-12d3-a456-426614174000",
          "total_runs": 123,
          "updated_at": "2023-01-01T00:00:00Z",
          "updated_by_user_email": "[email protected]",
          "updated_by_user_id": "12345",
          "version": 123
        }
      ],
      "name": "example name",
      "updated_at": "2023-01-01T00:00:00Z",
      "uuid": "123e4567-e89b-12d3-a456-426614174000"
    }
  }
}
Returns Examples
{
  "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": [
      {
        "created_at": "2023-01-01T00:00:00Z",
        "created_by": "12345",
        "deleted_at": "2023-01-01T00:00:00Z",
        "name": "example name",
        "secret_key": "example string",
        "uuid": "123e4567-e89b-12d3-a456-426614174000"
      }
    ],
    "api_keys": [
      {
        "api_key": "example string"
      }
    ],
    "chatbot": {
      "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": [
      {
        "agent_chatbot_identifier": "123e4567-e89b-12d3-a456-426614174000"
      }
    ],
    "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": [
      {
        "api_key": "example string",
        "created_at": "2023-01-01T00:00:00Z",
        "created_by": "12345",
        "description": "example string",
        "faas_name": "example name",
        "faas_namespace": "example name",
        "input_schema": {},
        "name": "example name",
        "output_schema": {},
        "updated_at": "2023-01-01T00:00:00Z",
        "url": "example string",
        "uuid": "123e4567-e89b-12d3-a456-426614174000"
      }
    ],
    "guardrails": [
      {
        "agent_uuid": "123e4567-e89b-12d3-a456-426614174000",
        "created_at": "2023-01-01T00:00:00Z",
        "default_response": "example string",
        "description": "example string",
        "guardrail_uuid": "123e4567-e89b-12d3-a456-426614174000",
        "is_attached": true,
        "is_default": true,
        "metadata": {},
        "name": "example name",
        "priority": 123,
        "type": "GUARDRAIL_TYPE_UNKNOWN",
        "updated_at": "2023-01-01T00:00:00Z",
        "uuid": "123e4567-e89b-12d3-a456-426614174000"
      }
    ],
    "if_case": "example string",
    "instruction": "example string",
    "k": 123,
    "knowledge_bases": [
      {
        "added_to_agent_at": "2023-01-01T00:00:00Z",
        "created_at": "2023-01-01T00:00:00Z",
        "database_id": "123e4567-e89b-12d3-a456-426614174000",
        "embedding_model_uuid": "123e4567-e89b-12d3-a456-426614174000",
        "is_public": true,
        "last_indexing_job": {
          "completed_datasources": 123,
          "created_at": "2023-01-01T00:00:00Z",
          "data_source_uuids": [
            "example string"
          ],
          "finished_at": "2023-01-01T00:00:00Z",
          "knowledge_base_uuid": "123e4567-e89b-12d3-a456-426614174000",
          "phase": "BATCH_JOB_PHASE_UNKNOWN",
          "started_at": "2023-01-01T00:00:00Z",
          "status": "INDEX_JOB_STATUS_UNKNOWN",
          "tokens": 123,
          "total_datasources": 123,
          "total_items_failed": "12345",
          "total_items_indexed": "12345",
          "total_items_skipped": "12345",
          "updated_at": "2023-01-01T00:00:00Z",
          "uuid": "123e4567-e89b-12d3-a456-426614174000"
        },
        "name": "example name",
        "project_id": "123e4567-e89b-12d3-a456-426614174000",
        "region": "example string",
        "tags": [
          "example string"
        ],
        "updated_at": "2023-01-01T00:00:00Z",
        "user_id": "user_id",
        "uuid": "123e4567-e89b-12d3-a456-426614174000"
      }
    ],
    "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,
    "model": {
      "agreement": {
        "description": "example string",
        "name": "example name",
        "url": "example string",
        "uuid": "123e4567-e89b-12d3-a456-426614174000"
      },
      "created_at": "2023-01-01T00:00:00Z",
      "inference_name": "example name",
      "inference_version": "example string",
      "is_foundational": true,
      "metadata": {},
      "name": "example name",
      "parent_uuid": "123e4567-e89b-12d3-a456-426614174000",
      "provider": "MODEL_PROVIDER_DIGITALOCEAN",
      "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",
      "version": {
        "major": 123,
        "minor": 123,
        "patch": 123
      }
    },
    "name": "example name",
    "openai_api_key": {
      "created_at": "2023-01-01T00:00:00Z",
      "created_by": "12345",
      "deleted_at": "2023-01-01T00:00:00Z",
      "models": [
        {
          "agreement": {
            "description": "example string",
            "name": "example name",
            "url": "example string",
            "uuid": "123e4567-e89b-12d3-a456-426614174000"
          },
          "created_at": "2023-01-01T00:00:00Z",
          "inference_name": "example name",
          "inference_version": "example string",
          "is_foundational": true,
          "metadata": {},
          "name": "example name",
          "parent_uuid": "123e4567-e89b-12d3-a456-426614174000",
          "provider": "MODEL_PROVIDER_DIGITALOCEAN",
          "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",
          "version": {
            "major": 123,
            "minor": 123,
            "patch": 123
          }
        }
      ],
      "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,
    "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": [
        {
          "priority": 123,
          "uuid": "123e4567-e89b-12d3-a456-426614174000"
        }
      ],
      "instruction": "example string",
      "k": 123,
      "knowledge_bases": [
        {
          "added_to_agent_at": "2023-01-01T00:00:00Z",
          "created_at": "2023-01-01T00:00:00Z",
          "database_id": "123e4567-e89b-12d3-a456-426614174000",
          "embedding_model_uuid": "123e4567-e89b-12d3-a456-426614174000",
          "is_public": true,
          "last_indexing_job": {
            "completed_datasources": 123,
            "created_at": "2023-01-01T00:00:00Z",
            "data_source_uuids": [
              "example string"
            ],
            "finished_at": "2023-01-01T00:00:00Z",
            "knowledge_base_uuid": "123e4567-e89b-12d3-a456-426614174000",
            "phase": "BATCH_JOB_PHASE_UNKNOWN",
            "started_at": "2023-01-01T00:00:00Z",
            "status": "INDEX_JOB_STATUS_UNKNOWN",
            "tokens": 123,
            "total_datasources": 123,
            "total_items_failed": "12345",
            "total_items_indexed": "12345",
            "total_items_skipped": "12345",
            "updated_at": "2023-01-01T00:00:00Z",
            "uuid": "123e4567-e89b-12d3-a456-426614174000"
          },
          "name": "example name",
          "project_id": "123e4567-e89b-12d3-a456-426614174000",
          "region": "example string",
          "tags": [
            "example string"
          ],
          "updated_at": "2023-01-01T00:00:00Z",
          "user_id": "user_id",
          "uuid": "123e4567-e89b-12d3-a456-426614174000"
        }
      ],
      "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,
      "model": {
        "agreement": {
          "description": "example string",
          "name": "example name",
          "url": "example string",
          "uuid": "123e4567-e89b-12d3-a456-426614174000"
        },
        "created_at": "2023-01-01T00:00:00Z",
        "inference_name": "example name",
        "inference_version": "example string",
        "is_foundational": true,
        "metadata": {},
        "name": "example name",
        "parent_uuid": "123e4567-e89b-12d3-a456-426614174000",
        "provider": "MODEL_PROVIDER_DIGITALOCEAN",
        "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",
        "version": {
          "major": 123,
          "minor": 123,
          "patch": 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"
    },
    "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",
    "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": [
        {
          "archived_at": "2023-01-01T00:00:00Z",
          "created_at": "2023-01-01T00:00:00Z",
          "created_by_user_email": "[email protected]",
          "created_by_user_id": "12345",
          "dataset": {
            "created_at": "2023-01-01T00:00:00Z",
            "dataset_name": "example name",
            "dataset_uuid": "123e4567-e89b-12d3-a456-426614174000",
            "file_size": "12345",
            "has_ground_truth": true,
            "row_count": 123
          },
          "dataset_name": "example name",
          "dataset_uuid": "123e4567-e89b-12d3-a456-426614174000",
          "description": "example string",
          "latest_version_number_of_runs": 123,
          "metrics": [
            {
              "description": "example string",
              "inverted": true,
              "metric_name": "example name",
              "metric_type": "METRIC_TYPE_UNSPECIFIED",
              "metric_uuid": "123e4567-e89b-12d3-a456-426614174000",
              "metric_value_type": "METRIC_VALUE_TYPE_UNSPECIFIED",
              "range_max": 123,
              "range_min": 123
            }
          ],
          "name": "example name",
          "star_metric": {
            "metric_uuid": "123e4567-e89b-12d3-a456-426614174000",
            "name": "example name",
            "success_threshold": 123,
            "success_threshold_pct": 123
          },
          "test_case_uuid": "123e4567-e89b-12d3-a456-426614174000",
          "total_runs": 123,
          "updated_at": "2023-01-01T00:00:00Z",
          "updated_by_user_email": "[email protected]",
          "updated_by_user_id": "12345",
          "version": 123
        }
      ],
      "name": "example name",
      "updated_at": "2023-01-01T00:00:00Z",
      "uuid": "123e4567-e89b-12d3-a456-426614174000"
    }
  }
}