from http.server import BaseHTTPRequestHandler, HTTPServer
from urllib.parse import parse_qs
import json
import logging
from datetime import datetime
from openai import OpenAI # OpenAI Python client

# Configure logging
logging.basicConfig(
    filename="duplicati_logs.log",
    level=logging.INFO,
    format="%(asctime)s - %(message)s",
)

# OpenAI API configuration
API_KEY = "sk-175159668af9430ea6208f5636b24198"  # Replace with your OpenAI API key
MODEL = "deepseek-chat"

class DuplicatiLogHandler(BaseHTTPRequestHandler):
    def do_POST(self):
        # Get the length of the data
        content_length = int(self.headers["Content-Length"])
        # Read the POST data
        post_data = self.rfile.read(content_length).decode("utf-8")
        # Parse the form-urlencoded data
        data = parse_qs(post_data)

        # Log the data
        self.log_data(data)

        # Send the log message to OpenAI API for analysis
        analysis_result, diagnostic_message = self.send_to_openai(data)
        if analysis_result:
            logging.info(f"OpenAI Analysis Result: {analysis_result}")
            if diagnostic_message:
                logging.info(f"Diagnostic Message: {diagnostic_message}")

        # Send a response
        self.send_response(200)
        self.send_header("Content-type", "application/json")
        self.end_headers()
        response = {
            "status": "success",
            "message": "Log received",
            "analysis_result": analysis_result,
            "diagnostic_message": diagnostic_message,
        }
        self.wfile.write(json.dumps(response).encode("utf-8"))

    def log_data(self, data):
        """Log the received data to a file."""
        log_entry = {
            "timestamp": datetime.now().isoformat(),
            "data": data,
        }
        logging.info(json.dumps(log_entry))

    def send_to_openai(self, data):
        """Send the raw log data to OpenAI API for analysis."""
        try:
            # Prepare the messages for OpenAI API
            messages = [
                {
                    "role": "system",
                    "content": "You are an operator analyzing backup logs. "
                              "Check the log message for abnormalities and respond with 'normal' or 'abnormal'. "
                              "If the backup is abnormal, provide a detailed diagnostic message explaining the issue and suggesting possible fixes.",
                },
                {
                    "role": "user",
                    "content": json.dumps(data),  # Pass the raw data as a JSON string
                },
            ]

            # Make a request to OpenAI API
            client = OpenAI(api_key=API_KEY, base_url="https://api.deepseek.com")
            response = client.chat.completions.create(
                model=MODEL,
                messages=messages,
    max_tokens=1024,
    temperature=0.7,
    stream=False

            )

            # Parse the response
            chat_response = response.choices[0].message.content

            # Extract analysis result and diagnostic message
            if "abnormal" in chat_response.lower():
                analysis_result = "abnormal"
                diagnostic_message = chat_response  # Use the full response as the diagnostic message
            else:
                analysis_result = "normal"
                diagnostic_message = chat_response 

            return analysis_result, diagnostic_message
        except Exception as e:
            logging.error(f"Failed to send data to OpenAI API: {e}")
            return None, None

def run(server_class=HTTPServer, handler_class=DuplicatiLogHandler, port=8680):
    server_address = ("", port)
    httpd = server_class(server_address, handler_class)
    print(f"Starting Duplicati log server on port {port}...")
    httpd.serve_forever()

if __name__ == "__main__":
    run()