Get Agent Config
agent_configs.retrieve(stragent_config_id) -> AgentConfigRetrieveResponse
GET/v5/agent_configs/{agent_config_id}
Fetch a single stored agent configuration by id, including its persistent_workspace flag and any repos override.
This returns the saved record as-is and does not compute task params; use
{agent_config_id}/resolve when you need the config projected into the params
a task would run with. A user caller can only read a config they created unless
fine-grained access control grants access, while a service account can read any
config under the account; a missing or out-of-scope id returns a 404.
Get Agent Config
import os
from scale_gp_beta import SGPClient
client = SGPClient(
api_key=os.environ.get("SGP_API_KEY"), # This is the default and can be omitted
)
agent_config = client.agent_configs.retrieve(
"agent_config_id",
)
print(agent_config.id){
"id": "id",
"allowed_tools": [
"string"
],
"created_at": "2019-12-27T18:11:19.117Z",
"harness": "harness",
"model": "model",
"name": "name",
"system_prompt": "system_prompt",
"updated_at": "2019-12-27T18:11:19.117Z",
"description": "description",
"object": "agent_config",
"persistent_workspace": true,
"repos": [
{
"url": "x",
"depth": 1,
"path": "path"
}
]
}Returns Examples
{
"id": "id",
"allowed_tools": [
"string"
],
"created_at": "2019-12-27T18:11:19.117Z",
"harness": "harness",
"model": "model",
"name": "name",
"system_prompt": "system_prompt",
"updated_at": "2019-12-27T18:11:19.117Z",
"description": "description",
"object": "agent_config",
"persistent_workspace": true,
"repos": [
{
"url": "x",
"depth": 1,
"path": "path"
}
]
}