大量意图后列出索引超出范围错误

Question

我目前正在开发聊天机器人。它适用于较少的意图，但在添加更多意图后，我得到索引错误。它适用于某些模式，但是当我添加更多模式时，事情变得很难看。 同样，它适用于某些模式。但是，有时（我不知道为什么）我会出错。我收到的错误消息是：

Traceback (most recent call last):
  File "C:\Users\emrey\AppData\Local\Programs\Python\Python37\lib\tkinter\__init__.py", line 1705, in __call__
    return self.func(*args)
  File "C:/Users/emrey/OneDrive/Belgeler/AIChatBot/app.py", line 59, in _on_enter_pressed
    self._insert_message(msg, "You")
  File "C:/Users/emrey/OneDrive/Belgeler/AIChatBot/app.py", line 71, in _insert_message
    msg2 = f"{bot_name}: {get_response(predict_class(msg.lower()),intents)}\n\n"
  File "C:\Users\emrey\OneDrive\Belgeler\AIChatBot\WolE.py", line 47, in predict_class
    if results[0][1] < 0.7:
IndexError: list index out of range

你能告诉我为什么会出现这个错误吗？这是代码：

    import random
    import json
    import pickle
    import numpy as np
    import nltk
    from nltk.stem import WordNetLemmatizer
    import csv
    import codecs
    import urllib.request
    
    from tensorflow.keras.models import load_model
    
    base_url = "https://weather.visualcrossing.com/VisualCrossingWebServices/rest/services/timeline/W%C3%BCrzburg/today?unitGroup=metric&key=Y8925G8VV2MZK49WQ38Z2Q3RC"
    
    
    lemmatizer = WordNetLemmatizer() 
    intents = json.loads(open('intentsWolE.json',encoding='utf-8').read())
    
    words = pickle.load(open('words.pk1','rb'))
    classes = pickle.load(open('classses.pk1','rb'))
    model = load_model('chatbot_model.model')
    
    bot_name = "Genesis"
    
    def clean_up_sentence(sentence):
        sentence_words = nltk.word_tokenize(sentence)
        sentence_words = [lemmatizer.lemmatize(word) for word in sentence_words]
        return sentence_words
    
    def bag_of_words(sentence):
        sentence_words = clean_up_sentence(sentence)
        bag = [0] * len(words)
        for w in sentence_words:
            for i, word in enumerate(words):
                if word == w:
                    bag[i] = 1
        return np.array(bag)
    
    def predict_class(sentence):
        global results
        bow = bag_of_words(sentence)
        res = model.predict(np.array([bow]))[0]
        ERROR_THRESHOLD = 0.25
        results = [[i,r] for i, r in enumerate(res) if r > ERROR_THRESHOLD]
        results.sort(key=lambda x: x[1], reverse=True)
        if results[0][1] < 0.7:
            return [{'intent': 'not_understand', 'probability': '0.9999999'}]
        return_list = []
        for r in results:
            return_list.append({'intent': classes[r[0]], 'probability': str(r[1])})
            print(return_list)
        return return_list
    
    def weather_report():
        CSVBytes = urllib.request.urlopen(base_url)
        CSVText = csv.reader(codecs.iterdecode(CSVBytes, 'utf-8'))
        for Row in CSVText:
            FirstRow = Row
        return FirstRow[9] + " and " + FirstRow[14]
    
    def get_response(intents_list,intents_json):
        tag = intents_list[0]['intent']
        list_of_intents = intents_json['intents']
        for i in list_of_intents:
            if i['tag'] == tag:
                result = random.choice(i['responses'])
                if result == "weather_report":
                   result = weather_report()
                break
        return result

我试过的是：

START
I am hugnry
2021-07-14 15:17:08.242833: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:176] None of the MLIR Optimization Passes are enabled (registered 2)
What do you mean?
I am hungry
[{'intent': 'hunger', 'probability': '0.9998872'}]
What do you want to eat?
Francnian restrant
Traceback (most recent call last):
  File "C:/Users/emrey/OneDrive/Belgeler/AIChatBot/WolE.py", line 75, in <module>
    ints = predict_class(message.lower())
  File "C:/Users/emrey/OneDrive/Belgeler/AIChatBot/WolE.py", line 46, in predict_class
    if results[0][1] < 0.7:
IndexError: list index out of range

Process finished with exit code 1

Answer 1

我在一个类似的程序中遇到过这个错误，我能够直接追踪问题是因为返回了一个空列表。我通过在我的代码中添加一个 try 和 except 来解决这个问题：

global result
try:
    tag = intents_list[0]['intent']
    list_of_intents = intents_json['intents']
    for i in list_of_intents:
        if i['tag'] == tag:
            result = random.choice(i['responses'])
            break
except:
    result = "I cannot understand this statement. Perhaps rephrase it or type it differently?"
return result

也许你可以做到这一点？或者，我尝试的另一件事是重新训练我的模型，但这可能是 time-consuming.

大量意图后列出索引超出范围错误

List index out of range error after a lot of intents

python

nltk

chatbot

deep-learning