Tagline

Text Extraction

Streamline your data acquisition process

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Sales Optimization

Qualify sales leads effectively by extracting relevant text from websites

Content Categorization

Categorize webpages with precision for improved organization

Profile Screening

Screen profile pages for specific work experience, enhancing your recruitment process

Getting Started

Enter the full URL including the https://, for example https://www.pyqai.com, to extract all relevant text from a given website. If you aren't happy with what it generated, feel free to re-run it as many times as you want.

API Integration

Want to use this via API? Sign up here to get your API token and Account ID!Try out the following code examples to get this model integrated into your app quickly:

Run via CURL

curl --location --request POST 'https://predict.pyqai.com/' --header 'Authorization: <YOUR API TOKEN HERE>' --header 'Content-Type: application/json' --data-raw '{"model": "136", "version": "451", "account": "<YOUR ACCOUNT ID HERE>", "input_sequence": "Your input goes here", "candidate_labels": ["a class","another class"]}'


import requests
import json

headers = { 'Authorization': "",'Content-Type': 'application/json'}
json_input = { "model": 136, "version": 451, "account": ,"input_sequence": "Your input goes here", "candidate_labels": ["a class","another class"]}
url = "https://predict.pyqai.com"

response = requests.post(headers=headers, json = json_input, url = url )
print(json.loads(response.content))


var myHeaders = new Headers();
myHeaders.append("Authorization", "");
myHeaders.append("Content-Type", "application/json");

var raw = JSON.stringify({
  "model": 136,
  "version": 451,
  "account": ,
  "input_sequence": "Your input here",
  "candidate_labels": [
    "a category",
    "another category"
  ]
});

var requestOptions = {
  method: 'POST',
  headers: myHeaders,
  body: raw,
  redirect: 'follow'
};

fetch("https://predict.pyqai.com", requestOptions)
  .then(response => response.text())
  .then(result => console.log(result))
  .catch(error => console.log('error', error));

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