POST
/
v1
/
eval

Send over a input that a AI generated a response for, and the model will generate an evaluation based on some desired metrics.

The evaluate API can be used for either single metric evaluations or multiple metric evaluations. It is also capable of evaluating in RAG settings with an optional context field and against a ground-truth answer if one is available.

Authorizations

Authorization
string
header
required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Body

application/json

A request to an Atla evaluator via the /eval endpoint.

model_id
string
required

The ID or name of the Atla evaluator model to use. This may point to a specific model version or a model family. If a model family is provided, the default model version for that family will be used.

model_input
string
required

The input given to a model which produced the model_output to be evaluated.

model_output
string
required

The output of the model which is being evaluated. This is the model_output from the model_input.

evaluation_criteria
string

The criteria used to evaluate the model_output. Only one of evaluation_criteria or metric_name can be provided.

expected_model_output
string

An optional reference ("ground-truth" / "gold standard") answer against which to evaluate the model_output.

few_shot_examples
object[]

A list of few-shot examples for the evaluation.

metric_name
string

The name of the metric to use for the evaluation. Only one of evaluation_criteria or metric_name can be provided.

model_context
string

Any additional context provided to the model which received the model_input and produced the model_output.

Response

200 - application/json

A response to an Atla evaluator via the /eval endpoint.

request_id
string
required

The ID of the request the response is for.

result
object
required

The result of the evaluation.

status
enum<string>

Response status enum.

Available options:
success,
error