#!/usr/bin/env python3

# Modified version from https://github.com/R34LUS3R/GPT3-cli/blob/main/gpt.py

import argparse

import json

import os

import sys

sys.path.append('/usr/lib/vmware/vsan/perfsvc/')

import requests

import xml.dom.minidom

# Set default values for command-line arguments

MODEL = "text-davinci-003" # model to use

TOKEN_COUNT = 300 # number of tokens to generate

TEMPERATURE = 0.4 # temperature

TOP_P = 1 # top_p value

FREQUENCY = 0.5 # frequency penalty

PRESENCE = 0.5 # presence penalty

ESXCLI_NS = "http://www.vmware.com/Products/ESX/5.0/esxcli/"

def main():

"""Main entry point."""

# Parse command-line arguments

parser = argparse.ArgumentParser()

parser.add_argument("prompt", nargs="+", default="",

help="prompt to use as input for the GPT-3 model")

args = parser.parse_args()

# Get the OpenAI API key

api_key = "FILL_ME_IN"

# Set up the API request

url = "https://api.openai.com/v1/completions"

headers = {

"Authorization": f"Bearer {api_key}",

"Content-Type": "application/json",

}

data = {

"model": MODEL,

"prompt": ' '.join(args.prompt),

"temperature": TEMPERATURE,

"top_p": TOP_P,

"frequency_penalty": FREQUENCY,

"presence_penalty": PRESENCE,

"max_tokens": TOKEN_COUNT,

}

# Send the API request

response = requests.post(url, headers=headers, json=data)

# Check for errors in the API response

if response.status_code != 200:

print("Error:", response.json()["error"])

return

# Extract the text from the response

text = response.json()["choices"][0]["text"]

# Print the output

# print(text)

doc = xml.dom.minidom.Document()

outputEl = doc.createElementNS(ESXCLI_NS, "output")

outputEl.setAttribute("xmlns", ESXCLI_NS)

doc.appendChild(outputEl)

structEl = doc.createElementNS(ESXCLI_NS, "structure")

structEl.setAttribute("typeName", "Result")

fieldEl = doc.createElementNS(ESXCLI_NS, "field")

fieldEl.setAttribute("name", "Answer")

structEl.appendChild(fieldEl)

boolEl = doc.createElementNS(ESXCLI_NS, "string")

fieldEl.appendChild(boolEl)

boolEl.appendChild(doc.createTextNode(text.strip()))

outputEl.appendChild(structEl)

print(doc.toxml())

if __name__ == "__main__":

main()