system_config object. The name field in the config is required and will be used to derive the agent_key.
Request Body
object
required
Complete agent configuration object
Show system_config Properties
Show system_config Properties
string
required
Agent name (used to derive agent_key)
string
required
Type of agent (e.g., “llm_agent”)
string
required
Instructions defining agent behavior
object
required
array
Connected knowledge bases for retrieval
array
Available tools (e.g., [“tavily_search”])
curl -X POST https://api.artaios.ai/api/v1/agent/ \
-H "x-api-key: YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"system_config": {
"name": "Support Agent",
"agent_type": "llm_agent",
"system_prompt": "You are a helpful customer support agent.",
"llm_config": {
"model": "gpt-4o",
"temperature": 0.7
}
}
}'
import requests
data = {
"system_config": {
"name": "Support Agent",
"agent_type": "llm_agent",
"system_prompt": "You are a helpful customer support agent.",
"llm_config": {
"model": "gpt-4o",
"temperature": 0.7
}
}
}
response = requests.post(
"https://api.artaios.ai/api/v1/agent/",
headers={"x-api-key": "YOUR_API_KEY"},
json=data
)
agent = response.json()
const data = {
system_config: {
name: "Support Agent",
agent_type: "llm_agent",
system_prompt: "You are a helpful customer support agent.",
llm_config: {
model: "gpt-4o",
temperature: 0.7
}
}
};
const response = await fetch('https://api.artaios.ai/api/v1/agent/', {
method: 'POST',
headers: {
'x-api-key': 'YOUR_API_KEY',
'Content-Type': 'application/json'
},
body: JSON.stringify(data)
});
const agent = await response.json();
Response
Returns the created agent configuration:{
"id": "550e8400-e29b-41d4-a716-446655440001",
"agent_key": "support_agent",
"name": "Support Agent",
"architecture": "llm_agent",
"entry_point": "main",
"is_public": false,
"is_shared": false,
"origin_url": null,
"owner": "user_123",
"company": "company_456",
"system_config": {
"name": "Support Agent",
"agent_type": "llm_agent",
"system_prompt": "You are a helpful customer support agent.",
"llm_config": {
"model": "gpt-4o",
"temperature": 0.7,
"max_tokens": 1000
},
"knowledge_bases": [
{
"name": "support_docs",
"knowledge_base_type": "milvus",
"knowledge_base_id": "kb_123"
}
]
},
"version_number": "1.0.0",
"config_hash": "b2c3d4e5f6a7",
"created_at": "2025-01-15T10:30:00Z",
"updated_at": "2025-01-15T10:30:00Z"
}
The
agent_key is automatically derived from the agent name and serves as a unique identifier for the agent.