gliner2-base-v1

Authorizations

x-api-key

string

header

required

x-project-id

string

header

required

Body

application/json

model

string

default:gliner2-base-v1

required

Model identifier (fixed for this playground). Use request examples to change use cases.

Allowed value: "gliner2-base-v1"

Example:

"gliner2-base-v1"

input

string<textarea>

required

Multi-line text or document content to send to the model.

Required string length: 1 - 131072

metadata

object

Use-case options for the model. Three use cases are supported:

ner — extract entities for the given labels.
json — extract structured fields defined by a schema.
classification — assign labels from candidate sets defined by a schema.

Hide child attributes

metadata.usecase

enum<string>

default:ner

Which operation to run and which other fields apply: ner uses labels; json and classification use schema.

Available options:

ner,

json,

classification

metadata.labels

string[]

Entity types to extract, used when usecase is ner. Each label becomes a key in the returned entities object.

Example:

[
  "programming language",
  "database",
  "technology",
  "protocol"
]

metadata.threshold

number

default:0.5

Minimum confidence score (0–1) an entity must reach to be returned (used with ner). Lower values surface more, lower-confidence matches.

Required range: 0 <= x <= 1

metadata.schema

object

Extraction/classification definition, used when usecase is json or classification. For json, each group maps to field definitions in name::type::description form (e.g. "email::str::Email address"). For classification, each group maps to a list of candidate labels (e.g. ["positive", "negative", "neutral"]).

Hide child attributes

metadata.schema.{key}

string[]

Example:

{
  "contact": [
    "name::str::Full name",
    "email::str::Email address",
    "phone::str::Phone number"
  ]
}

Response

Success

The response is of type object.

Endpoints

Batch API

gliner2-base-v1

Authorizations

Body

Response