👨‍💻 API Reference 📣 Release Notes 📺 Request a Demo

Explainability REST API Guide

PreviousEnvironments REST API Guide NextServer Info REST API Guide

Last updated 7 hours ago

Was this helpful?

Fetch slice query

Parse slice query data

post

/v3/slice-query/parse

Authorizations

Body

model_idstring uuidrequired

querystringrequired

Responses

application/json

cURL

JavaScript

Python

HTTP

curl -L \
  --request POST \
  --url '/v3/slice-query/parse' \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{"model_id":"123e4567-e89b-12d3-a456-426614174000","query":"text"}'

200

400

500

501

{
  "api_version": "3.0",
  "kind": "NORMAL",
  "data": {
    "environment_name": "text",
    "is_prod": true,
    "is_slice": true,
    "model_name": "text",
    "table_name": "text"
  }
}

Successfully parsed slice query

Fetch slice query

Fetch slice query data

post

/v3/slice-query/fetch

Authorizations

Body

model_idstring uuidrequired

querystringrequired

sampleboolean

max_rowsinteger

columnsstring[]

Responses

application/json

cURL

JavaScript

Python

HTTP

curl -L \
  --request POST \
  --url '/v3/slice-query/fetch' \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{"model_id":"123e4567-e89b-12d3-a456-426614174000","query":"text","columns":[null]}'

200

400

500

{
  "api_version": "3.0",
  "kind": "NORMAL",
  "data": {
    "metadata": {
      "is_slice": true,
      "columns": [
        "text"
      ],
      "dtypes": [
        "text"
      ],
      "env": {
        "id": "123e4567-e89b-12d3-a456-426614174000",
        "type": "PRE_PRODUCTION",
        "name": "text"
      },
      "model": {
        "id": "123e4567-e89b-12d3-a456-426614174000",
        "name": "text",
        "version": "text"
      }
    },
    "rows": [
      []
    ]
  }
}

Slice query data fetch successful

Get feature impact

Get feature impact for the given environment or a slice query

post

/v3/analytics/feature-impact

Authorizations

Body

data_sourceone ofrequired

Feature Impact api data sources

model_idstring uuidrequired

Unique ID of model.

num_refsinteger

Number of reference points used in the explanations. Only for non text inputs

num_iterationsinteger

The maximum number of ablated model inferences per feature. Only for non text inputs

ci_levelnumber

The confidence interval level (between 0 and 1) to use for all confidence intervals computed. Only for non text inputs

min_supportinteger

Specify a minimum support to retrieve top words. Only for Text data (NLP models)

output_columnsstring[]

Only used for NLP (TEXT inputs) models. Output column names to compute feature impact on. If None, use all.

ref_env_idstring uuid

environment to use for the reference dataset.

Responses

application/json

cURL

JavaScript

Python

HTTP

curl -L \
  --request POST \
  --url '/v3/analytics/feature-impact' \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{"data_source":{"source_type":"ENVIRONMENT","env_type":"PRE_PRODUCTION"},"model_id":"123e4567-e89b-12d3-a456-426614174000","output_columns":[null]}'

200

400

500

501

{
  "api_version": "3.0",
  "kind": "NORMAL",
  "data": {
    "response_type": "FEATURE_IMPACT_TEXT",
    "model_task": "text",
    "model_input_type": "text",
    "output_name": "sentiment",
    "tokens": {},
    "min_support": 15,
    "num_inputs": 200,
    "env_name": "bank_churn",
    "env_uuid": "bcb8e333-39d1-4ba5-a485-dec1591f7122",
    "created_at": "2023-12-12 18:21:07.616438+00:00"
  }
}

Feature Impact ran successfully on the given data

Get feature importance

Get feature importance for the given environment or a slice query

post

/v3/analytics/feature-importance

Authorizations

Body

data_sourceone ofrequired

model_idstring uuidrequired

num_refsinteger

Number of reference points used in the explanations

num_iterationsinteger

The maximum number of ablated model inferences per feature

ci_levelnumber

The confidence interval level (between 0 and 1) to use for all confidence intervals computed

ref_env_idstring uuid

environment to use for the reference dataset.

Responses

application/json

cURL

JavaScript

Python

HTTP

curl -L \
  --request POST \
  --url '/v3/analytics/feature-importance' \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{"data_source":{"source_type":"ENVIRONMENT","env_type":"PRE_PRODUCTION"},"model_id":"123e4567-e89b-12d3-a456-426614174000"}'

200

400

500

501

{
  "api_version": "3.0",
  "kind": "NORMAL",
  "data": {
    "model_task": "text",
    "model_input_type": "text",
    "total_input_samples": 10000,
    "valid_input_samples": 9000,
    "ci_level": 0.9,
    "feature_names": [
      "CreditScore",
      "Geography",
      "Age"
    ],
    "fixed_sample_ci": [
      0.04,
      0.002,
      0.1
    ],
    "loss": "pointwise_logloss",
    "mean_loss": 2.41122,
    "mean_loss_ci": 0.0434,
    "mean_loss_increase_importance": [
      -0.0581,
      -0.097,
      -0.0707
    ],
    "num_refs": 500,
    "random_sample_ci": [
      0.024,
      0.0204,
      0.0246
    ],
    "num_inputs": 250,
    "num_iterations": 200,
    "env_name": "bank_churn",
    "env_uuid": "bcb8e333-39d1-4ba5-a485-dec1591f7122",
    "created_at": "2023-12-12 18:21:07.616438+00:00"
  }
}

Feature Importance ran successfully on the given data

Get model scores

Get model scores for the given environment or a slice query

post

/v3/analytics/scores

Authorizations

Body

data_sourceone ofrequired

model_idstring uuidrequired

Model uuid

binary_thresholdnumber

Threshold for binary classification models

top_kinteger

Top K for ranking models

metricsenum[]

Responses

application/json

cURL

JavaScript

Python

HTTP

curl -L \
  --request POST \
  --url '/v3/analytics/scores' \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{"data_source":{"source_type":"ENVIRONMENT","env_type":"PRE_PRODUCTION"},"model_id":"123e4567-e89b-12d3-a456-426614174000","metrics":["AUC"]}'

200

400

500

501

{
  "api_version": "3.0",
  "kind": "NORMAL",
  "data": {
    "model_task": "REGRESSION",
    "total_samples": 10000,
    "valid_samples": 9500,
    "r_squared": 0.6934094625050112,
    "root_mean_squared_error": 0.43712324037225403,
    "mean_absolute_error": 0.34032740270302,
    "predictions": [
      6.346766948699951,
      5.74676698811151
    ],
    "targets": [
      6,
      5
    ],
    "error_distribution": {
      "count": [
        2,
        6
      ],
      "bins": [
        0,
        1,
        2
      ]
    }
  }
}

Scoring ran successfully on the given data

Update precomputed feature impact

Compute and update cached feature impact on an environment

put

/v3/analytics/precompute-feature-impact

Authorizations

Body

model_idstring uuidrequired

Unique identifier for model.

env_idstring uuidrequired

Unique identifier for environment.

env_typestringrequired

Type of environment. Either PRE_PRODUCTION or PRODUCTION.

num_refsinteger

Number of reference points used in the explanations

num_iterationsinteger

The maximum number of ablated model inferences per feature

ci_levelnumber

The confidence interval level (between 0 and 1) to use for all confidence intervals computed

min_supportinteger

Used for TEXT models to specify a minimum support (number of times a specific work was present in the sample data) to retrieve top words. Default to 15.

Responses

application/json

cURL

JavaScript

Python

HTTP

curl -L \
  --request PUT \
  --url '/v3/analytics/precompute-feature-impact' \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{"model_id":"123e4567-e89b-12d3-a456-426614174000","env_id":"123e4567-e89b-12d3-a456-426614174000","env_type":"text"}'

200

400

404

500

501

{
  "api_version": "3.0",
  "kind": "NORMAL",
  "data": {
    "job": {
      "id": "123e4567-e89b-12d3-a456-426614174000",
      "name": "text"
    }
  }
}

Feature impact pre-computation update ran successfully on the given data

Precompute feature impact

Compute and cache feature impact on an environment

post

/v3/analytics/precompute-feature-impact

Authorizations

Body

model_idstring uuidrequired

Unique identifier for model.

env_idstring uuidrequired

Unique identifier for environment.

env_typestringrequired

Type of environment. Either PRE_PRODUCTION or PRODUCTION.

num_refsinteger

Number of reference points used in the explanations

num_iterationsinteger

The maximum number of ablated model inferences per feature

ci_levelnumber

The confidence interval level (between 0 and 1) to use for all confidence intervals computed

min_supportinteger

Used for TEXT models to specify a minimum support (number of times a specific work was present in the sample data) to retrieve top words. Default to 15.

Responses

application/json

cURL

JavaScript

Python

HTTP

curl -L \
  --request POST \
  --url '/v3/analytics/precompute-feature-impact' \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{"model_id":"123e4567-e89b-12d3-a456-426614174000","env_id":"123e4567-e89b-12d3-a456-426614174000","env_type":"text"}'

200

400

404

500

501

{
  "api_version": "3.0",
  "kind": "NORMAL",
  "data": {
    "job": {
      "id": "123e4567-e89b-12d3-a456-426614174000",
      "name": "text"
    }
  }
}

Feature impact pre-computation ran successfully on the given data

Get precomputed feature impact

Get precomputed feature impact for a model

post

/v3/analytics/feature-impact/precomputed

Authorizations

Body

model_idstring uuidrequired

Unique identifier for the model.

Responses

application/json

cURL

JavaScript

Python

HTTP

curl -L \
  --request POST \
  --url '/v3/analytics/feature-impact/precomputed' \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{"model_id":"123e4567-e89b-12d3-a456-426614174000"}'

200

400

404

500

501

{
  "api_version": "3.0",
  "kind": "NORMAL",
  "data": {
    "response_type": "FEATURE_IMPACT_TEXT",
    "model_task": "text",
    "model_input_type": "text",
    "output_name": "sentiment",
    "tokens": {},
    "min_support": 15,
    "num_inputs": 200,
    "env_name": "bank_churn",
    "env_uuid": "bcb8e333-39d1-4ba5-a485-dec1591f7122",
    "created_at": "2023-12-12 18:21:07.616438+00:00"
  }
}

Precomputed Feature impact retrieval ran successfully on the given data

Update precomputed feature importance

Compute and update cached feature importance on an environment

put

/v3/analytics/precompute-feature-importance

Authorizations

Body

model_idstring uuidrequired

env_idstring uuidrequired

env_typestringrequired

num_refsinteger

Number of reference points used in the explanations

num_iterationsinteger

The maximum number of ablated model inferences per feature

ci_levelnumber

The confidence interval level (between 0 and 1) to use for all confidence intervals computed

Responses

application/json

cURL

JavaScript

Python

HTTP

curl -L \
  --request PUT \
  --url '/v3/analytics/precompute-feature-importance' \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{"model_id":"123e4567-e89b-12d3-a456-426614174000","env_id":"123e4567-e89b-12d3-a456-426614174000","env_type":"text"}'

200

400

404

500

501

{
  "api_version": "3.0",
  "kind": "NORMAL",
  "data": {
    "job": {
      "id": "123e4567-e89b-12d3-a456-426614174000",
      "name": "text"
    }
  }
}

Feature importance pre-computation update ran successfully on the given data

Precompute feature importance

Compute and cache feature importance on an environment

post

/v3/analytics/precompute-feature-importance

Authorizations

Body

model_idstring uuidrequired

env_idstring uuidrequired

env_typestringrequired

num_refsinteger

Number of reference points used in the explanations

num_iterationsinteger

The maximum number of ablated model inferences per feature

ci_levelnumber

The confidence interval level (between 0 and 1) to use for all confidence intervals computed

Responses

application/json

cURL

JavaScript

Python

HTTP

curl -L \
  --request POST \
  --url '/v3/analytics/precompute-feature-importance' \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{"model_id":"123e4567-e89b-12d3-a456-426614174000","env_id":"123e4567-e89b-12d3-a456-426614174000","env_type":"text"}'

200

400

404

500

501

{
  "api_version": "3.0",
  "kind": "NORMAL",
  "data": {
    "job": {
      "id": "123e4567-e89b-12d3-a456-426614174000",
      "name": "text"
    }
  }
}

Feature importance pre-computation ran successfully on the given data

Get precomputed feature importance

Get precomputed feature importance for a model

post

/v3/analytics/feature-importance/precomputed

Authorizations

Body

model_idstring uuidrequired

Unique identifier for model.

Responses

application/json

cURL

JavaScript

Python

HTTP

curl -L \
  --request POST \
  --url '/v3/analytics/feature-importance/precomputed' \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{"model_id":"123e4567-e89b-12d3-a456-426614174000"}'

200

400

404

500

501

{
  "api_version": "3.0",
  "kind": "NORMAL",
  "data": {
    "model_task": "text",
    "model_input_type": "text",
    "total_input_samples": 10000,
    "valid_input_samples": 9000,
    "ci_level": 0.9,
    "feature_names": [
      "CreditScore",
      "Geography",
      "Age"
    ],
    "fixed_sample_ci": [
      0.04,
      0.002,
      0.1
    ],
    "loss": "pointwise_logloss",
    "mean_loss": 2.41122,
    "mean_loss_ci": 0.0434,
    "mean_loss_increase_importance": [
      -0.0581,
      -0.097,
      -0.0707
    ],
    "num_refs": 500,
    "random_sample_ci": [
      0.024,
      0.0204,
      0.0246
    ],
    "num_inputs": 250,
    "num_iterations": 200,
    "env_name": "bank_churn",
    "env_uuid": "bcb8e333-39d1-4ba5-a485-dec1591f7122",
    "created_at": "2023-12-12 18:21:07.616438+00:00"
  }
}

Precomputed Feature importance retrieval ran successfully on the given data

Get predictions from a model

post

/v3/predict

Authorizations

Body

model_idstring uuidrequired

chunk_sizeinteger

dataobject[]required

Responses

application/json

cURL

JavaScript

Python

HTTP

curl -L \
  --request POST \
  --url '/v3/predict' \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{"model_id":"123e4567-e89b-12d3-a456-426614174000","data":[{"CreditScore":619,"Geography":"France","Gender":"Female","Age":42,"Tenure":2,"Balance":0,"NumOfProducts":1,"HasCrCard":"Yes","IsActiveMember":"Yes","EstimatedSalary":101348.88}]}'

200

400

404

500

{
  "api_version": "3.0",
  "kind": "NORMAL",
  "data": {
    "predictions": [
      {
        "probability_christian": 0.706
      }
    ]
  }
}

Predictions ran successfully on the given data