Airport Lounge Service Pricing Competition Checker API

API Endpoint Specifications

  • Endpoint Path: /api/1/airport-lounge-membership
  • Type of Data: JSON & 5/minute
  • Data Source: BUYFROMLO
  • Request Limit: 500 request/month
  • Script & Integration: Code to integrate with cURL, JS, Python, Ruby, Php, Node.js, Java, .NET, Rust, Go, Typescript
Airport Lounge Service Pricing Competition Checker API Endpoint Basic Info

API Endpoint Path

required

Airport Lounge Service Pricing Competition Checker

/api/1/airport-lounge-membership


Call Method

Required

POST

Type of Data Return

JSON

Output structured JSON data on AI blog content


Available API Arguments & Parameters

token

required

BUYFROMLO API token. Free and paid subscription API are available: /api/3/blogchain, and accessible to on-site APP on /app/3/blogchain as well

originalContent

required

Input the main theme or topic regarding this blog content

topic_name

required

Set who is writing this blog article, such as Lawyer, Marketer, Engineer, etc

role

required

Enter an expected tone of this article, such as positive, suspicious, etc

tableofcontentquantity

required

FALSE


language

Optional

input the outcome content language. Current available language has en, ja, sc, fr, ru

llmModel

Optional

Current avalable model are OpenAI GPT, Palm, Gemini, Llama & Claude

apikey

Optional

Free trial API is required to input a LLM api key. Current available model is OpenAI GPT.


Airport Lounge Service Pricing Competition Checker

/api/1/airport-lounge-membership

TRY IT OUT

Code Integration and Response

Python Code Sample


import requests

apiendpoint = "https://api.buyfromlo.com/api/3/blogchain"

## Required Arguments & Parameters ##

originalContent = "raw content materials or context for reference"
topic_name = "topic idea"
role = "who writes this content"
tableofcontentquantity = "how many subtitles are included. Max. is 8 subtitles"

## Optional Arguments & Parameters ##
language = "Input a language. Default is en"

## Optional and For free trial users only ##
llmModel = "Input openAI or hugging face Gemini, Llama. Paid users unnecessarily input this value."
apikey = "Input openai api key or hugging face api key. Paid users unnecessarily input this value."

headers={"Authorization": "Bearer " + token}

## Call the api ##
response = requests.post(apiendpoint, json={"originalContent":"", "topic_name":"", "role": "", "tableofcontentquantity": "", "language":language, "llmModel": llmModel, "apikey":apikey}, headers= headers)
print(response.status_code)
print(response.json())

JSON Response Sample


{
    "Totaltokenused":"",
    "Title":"",
    "excerpt":"",
    "table of contents": [],
    "content body": []
}