Log to a Tool

Log to a Tool.

You can use query parameters version_id, or environment, to target an existing version of the Tool. Otherwise the default deployed version will be chosen.

Instead of targeting an existing version explicitly, you can instead pass in Tool details in the request body. In this case, we will check if the details correspond to an existing version of the Tool, if not we will create a new version. This is helpful in the case where you are storing or deriving your Tool details in code.

Log to a Tool. You can use query parameters `version_id`, or `environment`, to target an existing version of the Tool. Otherwise the default deployed version will be chosen. Instead of targeting an existing version explicitly, you can instead pass in Tool details in the request body. In this case, we will check if the details correspond to an existing version of the Tool, if not we will create a new version. This is helpful in the case where you are storing or deriving your Tool details in code.

Query parameters

version_idstringOptional

A specific Version ID of the Tool to log to.

environmentstringOptional

Name of the Environment identifying a deployed version to log to.

Request

This endpoint expects an object.

pathstringOptional

Path of the Tool, including the name. This locates the Tool in the Humanloop filesystem and is used as as a unique identifier. For example: folder/name or just name.

idstringOptional

ID for an existing Tool.

toolobjectOptional

Details of your Tool. A new Tool version will be created if the provided details are new.

start_timedatetimeOptional

When the logged event started.

end_timedatetimeOptional

When the logged event ended.

outputstringOptional

Generated output from your model for the provided inputs. Can be None if logging an error, or if creating a parent Log with the intention to populate it later.

created_atdatetimeOptional

User defined timestamp for when the log was created.

errorstringOptional

Error message if the log is an error.

provider_latencydoubleOptional

Duration of the logged event in seconds.

stdoutstringOptional

Captured log and debug statements.

provider_requestmap from strings to anyOptional

Raw request sent to provider.

provider_responsemap from strings to anyOptional

Raw response received the provider.

inputsmap from strings to anyOptional

The inputs passed to the prompt template.

sourcestringOptional

Identifies where the model was called from.

metadatamap from strings to anyOptional

Any additional metadata to record.

source_datapoint_idstringOptional

Unique identifier for the Datapoint that this Log is derived from. This can be used by Humanloop to associate Logs to Evaluations. If provided, Humanloop will automatically associate this Log to Evaluations that require a Log for this Datapoint-Version pair.

trace_parent_idstringOptional

The ID of the parent Log to nest this Log under in a Trace.

userstringOptional

End-user ID related to the Log.

environmentstringOptional

The name of the Environment the Log is associated to.

savebooleanOptionalDefaults to true

Whether the request/response payloads will be stored on Humanloop.

log_idstringOptional

This will identify a Log. If you don't provide a Log ID, Humanloop will generate one for you.

Response

Successful Response

idstring

String ID of log.

tool_idstring

ID of the Tool the log belongs to.

version_idstring

ID of the specific version of the Tool.

session_idstring or null

String ID of session the log belongs to.

1	from humanloop import Humanloop
2	client = Humanloop(api_key="YOUR_API_KEY", )
3	client.tools.log(path='math-tool', tool={'function': {'name': 'multiply', 'description': 'Multiply two numbers', 'parameters': {'type': 'object'
4	, 'properties': {'a': {'type': 'number'}, 'b': {'type': 'number'}}
5	, 'required': ['a', 'b']
6	}}}, inputs={'a': 5
7	, 'b': 7
8	}, output='35', )

1	{
2	"id": "data_abc123",
3	"tool_id": "tl_def456",
4	"version_id": "tv_ghi789",
5	"session_id": "sesh_hw012"
6	}

Headers

Query parameters

Request

Response

Errors