import re

class ChatgptManager:
  def __init__(self, openAIClient, model="gpt-3.5-turbo-1106", tokenLimit=8000):
    self.client = openAIClient
    self.tokenLimit = tokenLimit
    self.model = model

  def getResponseForUserInput(self, userInput, systemPrompt):
    self.messages = []
    newMessage = {"role":"system", "content":systemPrompt}
    if not self.isTokeLimitExceeding(newMessage):
      self.messages.append(newMessage)
    else:
      raise ValueError("System Prompt Too long.")

    userMessage = {"role":"user", "content":userInput}
    if not self.isTokeLimitExceeding(userMessage):
      self.messages.append(userMessage)
    else:
      raise ValueError("Token Limit exceeding. With user input")

    # completion = self.client.chat.completions.create(
    #   model="gpt-3.5-turbo-1106",
    #   messages=self.messages,
    #   temperature=0,
    # )
    
    completion = self.client.chat.completions.create(
      model=self.model,
      messages=self.messages,
      temperature=0,
    )

    gptResponse = completion.choices[0].message.content

    self.messages.append({"role": "assistant", "content": gptResponse})
    return gptResponse

  def isTokeLimitExceeding(self, newMessage=None, truncate=True, throwError=True):
    if self.getTokenCount(newMessage=newMessage) > self.tokenLimit:
      return True
    return False


  def getTokenCount(self, newMessage=None):
    """Token count including new Message"""

    def getWordsCount(text):
      return len(re.findall(r'\b\w+\b', text))

    messages = self.messages[:]
    if newMessage!=None:
      messages.append(newMessage)

    combinedContent = " ".join(msg["content"] for msg in messages)
    currentTokensInMessages = getWordsCount(combinedContent)
    return currentTokensInMessages