Profile tabular data. The Swagger UI isn't able to call this currently.

Sample curl request:

curl -X 'POST'         -H "X-API-Key: <password>"         -H "Content-Type: application/json"         'http://localhost:8000/log'         --data-raw '{
    "datasetId": "model-62",
    "multiple": {
        "columns": [ "age", "workclass", "fnlwgt", "education" ],
        "data": [
            [ 25, "Private", 226802, "11th" ]
        ]
    }
}'

Sample Python client request:

from whylogs_container_client import AuthenticatedClient
import whylogs_container_client.api.profile.log as Log
from whylogs_container_client.models import LogRequest, LogMultiple
from datetime import datetime

client = AuthenticatedClient(base_url="http://localhost:8000", token="password", prefix="", auth_header_name="X-API-Key")

data = LogRequest(
    dataset_id="model-1",
    timestamp=int(datetime.now().timestamp() * 1000),
    multiple=LogMultiple(
        columns=["col1", "col2"],
        data=[[1, 2], [3, 4]],
    )
)

response = Log.sync_detailed(client=client, json_body=data)
if response.status_code != 200:
    raise Exception(f"Failed to log data. Status code: {response.status_code}")
# API is async, it won't fail and has no return body

Sample Python request (using requests):

import requests

# Define your API key
api_key = "<password>"

# API endpoint
url = 'http://localhost:8000/log'

# Sample data
data = {
    "datasetId": "model-62",
    "multiple": {
        "columns": ["age", "workclass", "fnlwgt", "education"],
        "data": [
            [25, "Private", 226802, "11th"]
        ]
    }
}

# Make the POST request
headers = {"X-API-Key": api_key}
response = requests.post(url, json=data, headers=headers)

This endpoint requires a custom configuration to set up before hand. See https://docs.whylabs.ai/docs/integrations-whylogs-container/ for setting up embeddings support.

Log embeddings data. The Swagger UI isn't able to call this currently.

Sample curl request:

curl -X 'POST'         -H "X-API-Key: <password>"         -H "Content-Type: application/octet-stream"         'http://localhost:8000/log-embeddings'         --data-raw '{
    "datasetId": "model-62",
    "timestamp": 1634235000,
    "embeddings": {
        "embeddings": [[0.12, 0.45, 0.33, 0.92]]
    }
}'

Sample Python request (using requests):

import requests

# Define your API key
api_key = "<password>"

# API endpoint
url = 'http://localhost:8000/log-embeddings'

# Sample data
data = {
    "datasetId": "model-62",
    "timestamp": 1634235000,  # an example timestamp
    "embeddings": {
        "embeddings": [[0.12, 0.45, 0.33, 0.92]]
    }
}

# Make the POST request
headers = {"X-API-Key": api_key, "Content-Type": "application/octet-stream"}
response = requests.post(url, json=data, headers=headers)

This is a convenience wrapper around the llm request type for calling /log, which accepts bulk data.

Run langkit evaluation and return the validation results, as well as the generated metrics.

Args: log (bool, optional): Determines if logging to WhyLabs is enabled for the request. Defaults to True.

Get a list of available metrics that can be referenced in policies.

Log the output of /status