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from utils import get_embeddings, search_document_annoy, \
answer_with_gpt3_with_function_calls, transform_user_question, debug_print
# add input parameter: need api_key for demo
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)
print(f"returning reply: {reply}")
return reply
except Exception as e:
print(f"returning error: {e}")
return e._message
# return "Error when trying to get embedding for the user query. Please try with a shorter question."
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