| from utils import get_embeddings, search_document_annoy, \ | |
| answer_with_gpt3_with_function_calls, transform_user_question, debug_print | |
| def get_response_from_model(user_input, top_k=3, annoy_metric='dot', model_name="gpt-3.5-turbo", user_query_preprocess=False): | |
| assert top_k > 0, 'k must be an integer greater than 0' | |
| if user_query_preprocess: | |
| chatgpt_question = transform_user_question(user_input, model_name) | |
| else: | |
| chatgpt_question = user_input | |
| debug_print("chatgpt_question: ", chatgpt_question) | |
| try: | |
| user_q_embedding = get_embeddings(chatgpt_question) | |
| document = search_document_annoy(user_q_embedding, top_k=top_k, metric=annoy_metric) | |
| reply = answer_with_gpt3_with_function_calls(document, user_input, model_name) | |
| return reply | |
| except Exception as e: | |
| print(e) | |
| return "Error when trying to get embedding for the user query. Please try with a shorter question." | |