Labelator.io - python client
Python client for Labelator.io - labeling and ML training studio
Install
pip install labelatorio
Getting your API token
Docs:
Full Labelator.io documentation can be found here docs.labelator.io
Page dedicated this client can be found here
Usage
Connecting client
import labelatorio
client = labelatorio.Client(api_token="your_api_token")
Getting project info
Package requirements are handled using pip. To install them do
# get project by id
existing_project = client.projects.get("2fab1778-e8b1-4327-ac83-16dd0e783ab4")
# if you have just name
existing_project = client.projects.get_by_name("my name")
# or if you don't know the exact name
existing_project = client.projects.search("my name")
Adding, updating documents
df = pd.DataFrame({
"key":["first","second"], # mandatory
"text":["this is my first text", "completely different text..."], # mandatory
"my_custom_column":["note 1",None] # optional
"labels":[["ClassA"],None] #optional if you have labels - should be defined in project
})
ids = client.documents.add_documents(project_id, data=df)
client.documents.set_labels(project_id,ids[1],["ClassB"])
Quering documents
# simple keyword search ...
found = client.documents.search(keyword="completely different")
# find all documents where "ClassA" was predicted
found = client.documents.search( predicted_label="ClassA")
# find all documents where "ClassA" was incorrectly predicted
found = client.documents.search( false_positives="ClassA")
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