Batch Classification

Prepare your Data

You'll have to upload a CSV, Excel, or JSONL file. Each record should have a 'text' field. For guidance on how to prepare your data for batch classification, see our Data Preparation Guide.

Create a New Job

Navigate to the Batch Jobs page in the sidebar, and click "+ New Batch Job" at the top.

Upload Data and Select Options

Follow the steps to choose a classifier or entity extraction model, and upload your input data as a CSV, Excel sheet, or JSONL. Depending on the model, you may be able to select a confidence threshold or maximum number of labels. You can also specify the type of output file you want.

Start Your Job

Click "Submit" on the final screen to start your job. You'll get an email when it's done, and you can preview and download the results from the Batch Jobs page.

Prepare your Data

You'll have to upload a CSV, Excel, or JSONL file. Each record should have a 'text' field. For guidance on how to prepare your data for batch classification, see our Data Preparation Guide.

Make a POST request to the Batch API

import requests
api_key = 'xx-your-api-key-here'
file_path = 'path-to-file.csv'
url = "https://api.trytaylor.ai/api/batch_jobs/create"
 
# Prepare the form data
form_data = {
    "model": "naics",
    "threshold": 0.2,
    "top_k": 5,
    "columns_to_classify": [3],  # zero-indexed column index
    "output_format": "csv",
}
 
# Prepare the file to be uploaded
files = {"file": (file_path, open(file_path, "rb"), "text/csv")}
 
# Send the POST request
response = requests.post(
    url,
    headers={"Authorization": f"Bearer {api_key}"},
    data=form_data,
    files=files
)
 
# Check the response
if response.status_code == 200:
    print("Job started successfully:", response.json())
else:
    print("Error:", response.status_code, response.text)