import openai

def classify_website(website):
    prompt = "Website classification:\n\nWebsite: {} \nCategory:".format(website)
    model_response = openai.Completion.create(
        model="gpt-3.5-turbo",
        prompt=prompt,
        max_tokens=1,
        temperature=0.2,
        n=1,
        stop=None,
        temperature=0.2
    )
    
    category = model_response.choices[0].text.strip()
    
    return category

def determine_piracy_type(website):
    prompt = "Piracy type detection:\n\nWebsite: {} \nType:".format(website)
    model_response = openai.Completion.create(
        model="gpt-3.5-turbo",
        prompt=prompt,
        max_tokens=1,
        temperature=0.2,
        n=1,
        stop=None,
        temperature=0.2
    )
    
    piracy_type = model_response.choices[0].text.strip()
    
    return piracy_type

# Set up OpenAI API credentials
openai.api_key = "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"

# Get website list input from the user
websites = input("Enter a comma-separated list of websites to classify: ").split(",")

# Classify each website
for website in websites:
    website = website.strip()
    classification = classify_website(website)
    
    if classification == "Piracy":
        piracy_type = determine_piracy_type(website)
        print("The website {} is classified as: Piracy - {}".format(website, piracy_type))
    else:
        print("The website {} is classified as: Legal".format(website))
{}
region:us
TAGS
#region-us 

import openai

def classify_website(website):
    prompt = "Website classification:\n\nWebsite: {} \nCategory:".format(website)
    model_response = URL(
        model="gpt-3.5-turbo",
        prompt=prompt,
        max_tokens=1,
        temperature=0.2,
        n=1,
        stop=None,
        temperature=0.2
    )
    
    category = model_response.choices[0].URL()
    
    return category

def determine_piracy_type(website):
    prompt = "Piracy type detection:\n\nWebsite: {} \nType:".format(website)
    model_response = URL(
        model="gpt-3.5-turbo",
        prompt=prompt,
        max_tokens=1,
        temperature=0.2,
        n=1,
        stop=None,
        temperature=0.2
    )
    
    piracy_type = model_response.choices[0].URL()
    
    return piracy_type

# Set up OpenAI API credentials
openai.api_key = "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"

# Get website list input from the user
websites = input("Enter a comma-separated list of websites to classify: ").split(",")

# Classify each website
for website in websites:
    website = URL()
    classification = classify_website(website)
    
    if classification == "Piracy":
        piracy_type = determine_piracy_type(website)
        print("The website {} is classified as: Piracy - {}".format(website, piracy_type))
    else:
        print("The website {} is classified as: Legal".format(website))
# Set up OpenAI API credentials
openai.api_key = "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" # Get website list input from the user
websites = input("Enter a comma-separated list of websites to classify: ").split(",") # Classify each website
for website in websites:
    website = URL()
    classification = classify_website(website)
    
    if classification == "Piracy":
        piracy_type = determine_piracy_type(website)
        print("The website {} is classified as: Piracy - {}".format(website, piracy_type))
    else:
        print("The website {} is classified as: Legal".format(website))
TAGS
#region-us 
 # Set up OpenAI API credentials
openai.api_key = "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" # Get website list input from the user
websites = input("Enter a comma-separated list of websites to classify: ").split(",") # Classify each website
for website in websites:
    website = URL()
    classification = classify_website(website)
    
    if classification == "Piracy":
        piracy_type = determine_piracy_type(website)
        print("The website {} is classified as: Piracy - {}".format(website, piracy_type))
    else:
        print("The website {} is classified as: Legal".format(website))