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import queue
import sys
import os
import threading
import time
import curses
from openai import OpenAI
from help import HelpCommands, start_chat
from style import StyleLog
# Read in token from "token" file
# TODO: env variable in future?
with open("token", "r") as file:
token = file.readlines()
client = OpenAI(api_key=token[0].strip())
def text_call(api_call_queue, messages, model):
response = client.chat.completions.create(
model=model,
messages=messages
)
api_call_queue.put(response.choices[0].message.content)
def image_call(api_call_queue, messages, model):
response = client.chat.completions.create(
model=model,
messages=messages
)
api_call_queue.put(response.choices[0].message.content)
def main():
model = ""
if len(sys.argv) > 1:
model = sys.argv[1]
else:
model = "gpt-3.5-turbo"
helper = HelpCommands(model)
styler = StyleLog()
messages = start_chat(model, styler)
while True:
user_input = styler.prompt("user", "")
status, messages, model = helper.command(user_input, messages, model, styler)
if status == 1:
break
elif status == 2:
continue
global api_call_done
api_call_done = threading.Event()
api_call_queue = queue.Queue()
if model == "dall-e-2" or model == "dall-e-3":
response_thread = threading.Thread(target=image_call, args=(api_call_queue, messages, model,))
else:
response_thread = threading.Thread(target=text_call, args=(api_call_queue, messages, model,))
response_thread.start()
ellipsis_thread = threading.Thread(target=styler.show_ellipsis, args=(api_call_done,))
ellipsis_thread.start()
response_thread.join()
api_call_done.set()
ellipsis_thread.join()
ai_response = api_call_queue.get()
messages.append({"role": "assistant", "content": ai_response})
styler.prompt("assistant", f"{ai_response}\n")
# TODO: Add some form of token check, as to not overflow
if __name__ == "__main__":
main()
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