| from models.whisper_model import AudioTranslator | |
| from models.llm_model import LlmReasoner | |
| class Chat: | |
| def __init__(self, args) -> None: | |
| self.args = args | |
| def init_model(self): | |
| print('\033[1;33m' + "Initializing models...".center(50, '-') + '\033[0m') | |
| self.audio_translator = AudioTranslator(self.args) | |
| self.llm_reasoner = LlmReasoner(self.args) | |
| print('\033[1;32m' + "Model initialization finished!".center(50, '-') + '\033[0m') | |
| def video2log(self, video_path): | |
| audio_results = self.audio_translator(video_path) | |
| en_log_result = [] | |
| en_log_result_tmp = "" | |
| audio_transcript = self.audio_translator.match(audio_results) | |
| en_log_result_tmp += f"\n{audio_transcript}" | |
| en_log_result.append(en_log_result_tmp) | |
| en_log_result = "\n\n".join(en_log_result) | |
| print(f"\033[1;34mLog: \033[0m\n{en_log_result}\n") | |
| return en_log_result | |
| def chat2video(self, args, user_input, en_log_result): | |
| self.llm_reasoner.create_qa_chain(args, en_log_result) | |
| en_user_input = user_input | |
| print("\n\033[1;32mGnerating response...\033[0m") | |
| answer, generated_question, source_documents = self.llm_reasoner(en_user_input) | |
| print(f"\033[1;32mQuestion: \033[0m{user_input}") | |
| print(f"\033[1;32mAnswer: \033[0m{answer[0][1]}") | |
| self.clean_history() | |
| return answer, generated_question, source_documents | |
| def clean_history(self): | |
| self.llm_reasoner.clean_history() | |
| return |