from transformers import pipeline
import openai

# Initialize the exploit detection model
exploit_detector = pipeline("text-classification", model="Canstralian/CySec_Known_Exploit_Analyzer")

# Initialize OpenAI API (or Replit's API)
openai.api_key = "your-openai-api-key"  # Replace with your actual API key

def detect_and_remediate(exploit_input):
    """
    Detects an exploit in the input and generates remediation code if an exploit is found.

    Args:
        exploit_input (str): The code or log input that might contain an exploit.

    Returns:
        str: The remediation code or a message indicating no exploit was detected.
    """
    # Step 1: Detect the exploit
    exploit_result = exploit_detector(exploit_input)
    if exploit_result[0]['label'] == "EXPLOIT_DETECTED":
        print("Exploit detected!")

        # Step 2: Generate remediation code
        remediation_prompt = f"Generate Python code to fix the following exploit: {exploit_input}"
        remediation_response = openai.Completion.create(
            engine="code-davinci-002",  # Or Replit's equivalent code model
            prompt=remediation_prompt,
            max_tokens=150
        )

        # Extracting the generated remediation code
        remediation_code = remediation_response.choices[0].text.strip()

        return remediation_code
    else:
        return "No exploit detected."

if __name__ == "__main__":
    # Example input: a piece of code or log indicating a vulnerability
    input_code = "Vulnerable code snippet here"
    remediation = detect_and_remediate(input_code)
    print("Remediation Code:", remediation)