Handle history token count model limit

[bnonni]

• Currently passing the entire "history" list to API model and using OpenAI latest gpt 4 185k
• As token count approaches 185k, the model has less and less tokens for the output response
• Also, by sending all messages to AI model, the cost to the group grows with each message since input & output tokens cost $
• Need a scalable approach for determining how many messages to send to AI model to balance response quality and cost

MVP

• Look at the token_count being updated with each message
• If its >= 92500, send half the history to AI model

        messages_history = self.history[self.history_len :] if self.history_tokens >= 90000 else self.history