import requests
import openai

# Set up the CoinMarketCap API endpoint and parameters
url = 'https://pro-api.coinmarketcap.com/v1/cryptocurrency/listings/latest'
parameters = {
  'start': '1',
  'limit': '10',
  'convert': 'USD'
}

# Set up the OpenAI API credentials
openai.api_key = '<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>'

# Fetch the latest cryptocurrency prices from the CoinMarketCap API
response = requests.get(url, headers={'X-CMC_PRO_API_KEY': '<03365e9f-2220-4083-90a7-151a70bb40ae>'}, params=parameters)

# Check if the response is successful
if response.status_code == 200:
  # Extract the data from the API response
  data = response.json()
  # Extract the relevant data from the API response
  bitcoin_price = data['data']['cryptocurrency_list'][0]['quote']['USD']['price']
  ethereum_price = data['data']['cryptocurrency_list'][1]['quote']['USD']['price']
  bitcoin_margin = data['data']['cryptocurrency_list'][0]['quote']['USD']['percent_change_24h']
  ethereum_margin = data['data']['cryptocurrency_list'][1]['quote']['USD']['percent_change_24h']

  # Use the OpenAI API to generate a prediction for the margin
  prompt = f"Based on the latest cryptocurrency prices, what will be the margin for Bitcoin and Ethereum in the next 24 hours?"
  model = "text-davinci-002"
  response = openai.Completion.create(
    engine=model,
    prompt=prompt,
    temperature=0.5,
    max_tokens=50,
    n=1,
    stop=None,
    timeout=20,
  )

  # Extract the predicted margin from the OpenAI API response
  predicted_margin = response.choices[0].text.strip()

  # Print the results
  print("Latest cryptocurrency prices:")
  print(f"Bitcoin: ${bitcoin_price:.2f}")
  print(f"Ethereum: ${ethereum_price:.2f}")
  print("24-hour margin:")
  print(f"Bitcoin: {bitcoin_margin:.2f}%")
  print(f"Ethereum: {ethereum_margin:.2f}%")
  print("Predicted margin for the next 24 hours:")
  print(predicted_margin)

else:
  print("Error: API request failed")