Tagging API

Tag any text with only few lines of code.



  1. ✨ Create a Workspace
  2. 🔑 Get your API Key
  3. 🧠 Activate Text Tagging API
  4. Download HrFlow.ai's Postman


API Endpoint

Get more information about the endpoint 🧠 Tag a Text.

Step 1: Configure your Postman Environment

Following the steps from the HrFlow.ai Postman publication will make you land on this page:


First, click on the "Environments" tab on the left side of your Postman window. Then, fill in the Empty - Environment template with the correct values. The compulsory variables for Tagging are:

Finally, save the environment and ensure that you selected Empty - Environment as your current environment.


Postman Environment Configuration

Step 2: Get your First Tagging Results

Fill in your body parameters in a raw format. The body contains four parameters :

  • [MANDATORY] text: the text for which you want to assign some tags.
  • [MANDATORY] algorithm_key: the tagger's name can be one of the following

Algorithm Key

Tagging Set


Grand domaines of job the French ROME


Domaines of job the French ROME


Metiers of job the French ROME


Appellations of job the French ROME


Skills referential defined by HrFlow.ai

  • [OPTIONNAL] top_n: number of tags returned through the API. Defaults to 1.
  • [OPTIONNAL] output_lang: the returned tags will be either in fr (French) or en (English). Defaults to fr.

The result of your tagging lies into data and contains:

  • predictions: AI prediction scores sorted in a descending order
  • tags: tags associated to the prediction scores.

Advanced Topics

1. Try Tagging in your Favorite Programming Language

Once you have tried the request in Postman, you can directly convert it to work with your favorite programming language. Here is an example with Python and the module Requests.

import requests
import json

url = "https://api.hrflow.ai/v1/text/tagging"

payload = json.dumps({
  "algorithm_key": "tagger-rome-family",
  "text": "Our client, specialized in the sale and mechanics of heavy goods vehicles with a national network, is looking for heavy goods vehicle mechanics for its sites based in Arras, Lens and Douai.",
  "top_n": 3,
  "output_lang": "en"
headers = {
  'Content-Type': 'application/json'

response = requests.request("POST", url, headers=headers, data=payload)


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