| from LLM import Bot | |
| import random | |
| class Parse_Prompt(Bot): | |
| def __init__(self): | |
| super().__init__() | |
| self.change = True | |
| self.model1 = None | |
| self.model2 = None | |
| self.chat_history_1 = [] | |
| self.chat_history_2 = [] | |
| def model_init(self): | |
| return random.sample(self.models, 2) | |
| def clear_history(self): | |
| self.chat_history_1 = [] | |
| self.chat_history_2 = [] | |
| def change_models(self): | |
| self.clear_history() | |
| self.change = True | |
| def current_model1(self): | |
| return self.model1 | |
| def current_model2(self): | |
| return self.model2 | |
| def gen_output(self, temp, prompt): | |
| if self.change: | |
| [self.model1, self.model2] = self.model_init() | |
| self.change = False | |
| self.chat_history_1.append([prompt, self.response(self.model1, prompt, temp)]) | |
| self.chat_history_2.append([prompt, self.response(self.model2, prompt, temp)]) | |
| return self.chat_history_1, self.chat_history_2 |