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Create Project

Create a new project on the Humanloop platform by defining inputs and outputs and associated users.

Request Body REQUIRED
name Name REQUIRED
outputs object[] REQUIRED
name Name REQUIRED
data_sources object[]
field_id The associated dataset field_id to link to your project input REQUIRED
display_name Display Name
description Description
instructions Instructions
data_type DataTypes

Possible values: [text, categorical, multi_categorical, quantitative, character_offsets, url, ordinal_regression, file_pdf]

An enumeration.

task_type object
labels object[]
id Id
name Name
display_name Display Name
description Description
count Count
steps Steps
meta object
input Input
inputs object[] REQUIRED
name Name REQUIRED
data_sources object[]
field_id The associated dataset field_id to link to your project input REQUIRED
data_type DataTypes

Possible values: [text, categorical, multi_categorical, quantitative, character_offsets, url, ordinal_regression, file_pdf]

An enumeration.

description Description
display_only Display Only
meta object
instructions Instructions
guidelines Guidelines
description Description
users string[] REQUIRED
learner_config object
policy object

A policy for how how many annotations to get on some proportion of the data.

Providing multiple annotations for the same data-points provides consensus metrics and can help improve the quality of the final annotations provided to the model

num_annotators How many different annotators to assign to each data-point
data_proportion How many data points you want multi-annotated
object Object
id Unique identifier for the policy.
task_allocation_strategy TaskAllocationStrategy

Possible values: [automatic, manual]

Strategy for automatic task allocation

Controls whether new tasks are automatically allocated when a user completes their tasks.

task_allocation_batch_size Task Allocation Batch Size
review_existing_annotations If your dataset fields contain existing annotations then these can be used to warm start your project by specifying their field id as output data sources. You can have your annotator users first review these annotations before they are used to train your model by setting this 'review_existing_annotations' bool to True.
Responses
200

Successful Response

Schema
id Id REQUIRED
name Name REQUIRED
shared_id Shared Id
external_id External Id
active Active REQUIRED
auth_key Auth Key REQUIRED
pred_count Pred Count REQUIRED
created_at date-time REQUIRED
default_dataset_id Default Dataset Id
description Description
guidelines Guidelines
policy object
instructions Instructions
status ProjectStatus

Possible values: [Maintenance, Exploration, Annotation]

Current status of learner

updated_at date-time
inputs object[] REQUIRED
data_type DataTypes REQUIRED

Possible values: [text, categorical, multi_categorical, quantitative, character_offsets, url, ordinal_regression, file_pdf]

An enumeration.

description Description
data_sources object[] REQUIRED
id Id REQUIRED
name Name REQUIRED
display_only Display Only REQUIRED
id Id REQUIRED
learner_id Learner Id REQUIRED
meta object
name Name REQUIRED
project_id Project Id REQUIRED
updated_at date-time REQUIRED
created_at date-time REQUIRED
outputs object[] REQUIRED
created_at date-time REQUIRED
updated_at date-time
data_type DataTypes

Possible values: [text, categorical, multi_categorical, quantitative, character_offsets, url, ordinal_regression, file_pdf]

An enumeration.

description Description
data_sources object[] REQUIRED
id Id REQUIRED
name Name REQUIRED
display_name Display Name REQUIRED
id Id REQUIRED
input Input
instructions Instructions
labels object[]
name Name REQUIRED
id Id REQUIRED
display_name Display Name
description Description
count Count
object Object
output_id Output Id REQUIRED
output object

Output data to be nested inside the label response payload

id Id
name Name REQUIRED
display_name Display Name
description Description
task_type TaskTypes REQUIRED

Possible values: [classification, multi_label_classification, sequence_tagging, ordinal_regression]

What ML tasks we support for our outputs

data_key Data Key
data_type DataTypes

Possible values: [text, categorical, multi_categorical, quantitative, character_offsets, url, ordinal_regression, file_pdf]

An enumeration.

meta object
project_id Project Id
object Object
created_at date-time
updated_at date-time
learner_id Learner Id REQUIRED
meta object
name Name REQUIRED
project_id Project Id REQUIRED
task_type TaskTypes REQUIRED

Possible values: [classification, multi_label_classification, sequence_tagging, ordinal_regression]

What ML tasks we support for our outputs

users object[] REQUIRED
active Active REQUIRED
email_address Email Address REQUIRED
full_name Full Name REQUIRED
id Id REQUIRED
intent Intent
role RoleEnum REQUIRED

Possible values: [owner, annotator, admin]

An enumeration.

tier_id Tier Id REQUIRED
tier object REQUIRED
updated_at date-time REQUIRED
created_at date-time REQUIRED
id Id REQUIRED
name Name REQUIRED
limits object REQUIRED
projects Projects REQUIRED
annotators Annotators REQUIRED
dataset_size Dataset Size REQUIRED
predictions Predictions REQUIRED
created_at date-time REQUIRED
updated_at date-time
username Username REQUIRED
verified Verified REQUIRED
complete_tasks Complete Tasks
incomplete_tasks Incomplete Tasks
complete_and_not_flagged_tasks Complete And Not Flagged Tasks
incomplete_and_not_flagged_tasks Incomplete And Not Flagged Tasks
learner object
id Id REQUIRED
current_status Status REQUIRED

Possible values: [Untrained, Waiting, Training, Scoring]

Current status of learner

evaluations object[]
id Id REQUIRED
created_at date-time
updated_at date-time
eval_metrics object REQUIRED
latest_evaluation object
id Id REQUIRED
created_at date-time
updated_at date-time
eval_metrics object REQUIRED
datasets object[]
id Id REQUIRED
name Name REQUIRED
count Count REQUIRED
description Description
fields object[]
id Id REQUIRED
name Name REQUIRED
data_type DataTypes REQUIRED

Possible values: [text, categorical, multi_categorical, quantitative, character_offsets, url, ordinal_regression, file_pdf]

An enumeration.

display_name Display Name
data_count Data Count REQUIRED
data_without_tasks_count Data Without Tasks Count REQUIRED
tasks_count Tasks Count REQUIRED
latest_completed_tasks_batch_size Latest Completed Tasks Batch Size REQUIRED
completed_tasks_count Completed Tasks Count REQUIRED
incomplete_tasks_count Incomplete Tasks Count REQUIRED
flagged_count Flagged Count REQUIRED
task_allocation_strategy TaskAllocationStrategy REQUIRED

Possible values: [automatic, manual]

Strategy for automatic task allocation

Controls whether new tasks are automatically allocated when a user completes their tasks.

task_allocation_batch_size Task Allocation Batch Size REQUIRED
422

Validation Error

Schema
detail object[]
loc string[] REQUIRED
msg Message REQUIRED
type Error Type REQUIRED