from mathtext_fastapi.logging import prepare_message_data_for_logging from mathtext.sentiment import sentiment from mathtext.text2int import text2int import re def build_nlu_response_object(type, data, confidence): """ Builds a json object from the result of nlu functions to send back to Turn.io Inputs - type: str - the type of nlu run (integer or sentiment-analysis) - data: str - the student message - confidence: - the nlu confidence score. Integer is ''. Sentiment analysis is a float """ return {'type': type, 'data': data, 'confidence': confidence} def test_for_float_or_int(message_data, message_text): nlu_response = {} if type(message_text) == int or type(message_text) == float: nlu_response = build_nlu_response_object('integer', message_text, '') prepare_message_data_for_logging(message_data, nlu_response) return nlu_response def test_for_number_sequence(message_text_arr, message_data, message_text): nlu_response = {} if all(ele.isdigit() for ele in message_text_arr): nlu_response = build_nlu_response_object('integer', ','.join(message_text_arr), '') prepare_message_data_for_logging(message_data, nlu_response) return nlu_response def run_text2int_on_each_list_item(message_text_arr): """ Checks each item in an array to see if it can be converted to an integer Input - message_text_arr: list - a set of text extracted from the student message Output - student_response_arr: list - a set of integers derived from the nlu function """ student_response_arr = [] for student_response in message_text_arr: int_api_resp = text2int(student_response.lower()) student_response_arr.append(int_api_resp) return student_response_arr def run_sentiment_analysis(message_text): # TODO: Add intent labelling here # TODO: Add logic to determine whether intent labeling or sentiment analysis is more appropriate (probably default to intent labeling) return sentiment(message_text) def evaluate_message_with_nlu(message_data): message_text = message_data['message_body'] message_text_arr = re.split(", |,| ", message_text.strip()) # TODO: Replace this with appropriate utility function (is_int, is_float, render_int_or_float) nlu_response = test_for_float_or_int(message_data, message_text) if len(nlu_response) > 0: return nlu_response # TODO: Replace this with appropriate utility function nlu_response = test_for_number_sequence(message_text_arr, message_data, message_text) if len(nlu_response) > 0: return nlu_response student_response_arr = run_text2int_on_each_list_item(message_text_arr) # '32202' is text2int's error code for non-integer student answers (ie., "I don't know") # If any part of the list is 32202, sentiment analysis will run # TODO: Need to replace this with logic that recognizes multiple intents (Maybe 36 = "sentiment analysis" & "integer") student_response_arr = run_text2int_on_each_list_item(message_text_arr) if 32202 in student_response_arr: sentiment_api_resp = sentiment(message_text) nlu_response = build_nlu_response_object('sentiment', sentiment_api_resp[0]['label'], sentiment_api_resp[0]['score']) else: if len(student_response_arr) > 1: nlu_response = build_nlu_response_object('integer', ','.join(str(num) for num in student_response_arr), '' ) else: nlu_response = build_nlu_response_object('integer', student_response_arr[0], '') prepare_message_data_for_logging(message_data, nlu_response) return nlu_response