AI Blog Chain API
API Endpoint Specifications
- Endpoint Path: /api/3/blogchain
- Type of Data: JSON & 1/minute
- Data Source: BUYFROMLO, Gemini, Llama, Palm, Claude, OpenAI
- Request Limit: 100,000 tokens/month (Approximate 73,000 English words)
- Script & Integration: Code to integrate with cURL, JS, Python, Ruby, Php, Node.js, Java, .NET, Rust, Go, Typescript
AI Blog Chain API Endpoint Basic Info
API Endpoint Path
required
AI Blog Content Generator API
api/3/blogchain
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
Raw content materials or context for blog generation
topic_name
required
Input the main theme or topic regarding this blog content
role
required
Set who is writing this blog article, such as Lawyer, Marketer, Engineer, etc
tableofcontentquantity
required
Enter a core keyword related to this blog content
coreKeywords
required
FALSE
language
Optional
Input the content language. Current available language has en, ja, sc, fr, ru
potentialkWss
Optional
Submit a list of target keywords. Max. length of the list is 10 keywords
AI Blog Content Generator API
api/3/blogchain
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."
data={"originalContent":"", "topic_name":"", "role": "", "tableofcontentquantity": "", "language":language, "llmModel": llmModel, "apikey":apikey}
headers={"Authorization": "Bearer " + token}
## Call the api ##
response = requests.post(apiendpoint, json=data, headers=headers)
print(response.status_code)
print(response.json())
JSON Response Sample
{
"Totaltokenused":" " (integer),
"Title":" " (string),
"excerpt":" " (string),
"table of contents": [] (array),
"content body": [] (array),
}