无法检索机器人响应:ERR_NAME_NOT_RESOLVED 和 Flask 应用程序在 AWS 上部署时出现 403 错误

def get_formalities_reply(formality): if any(remove_punctuation_marks(formality).lower() in remove_punctuation_marks(greet).lower() for greet in constants.GREETING_INPUTS): return random.choice(constants.GREETING_REPLIES) elif any(remove_punctuation_marks(formality).lower() in remove_punctuation_marks(thanks).lower() for thanks in constants.THANKS_INPUTS): return random.choice(constants.THANKS_REPLIES) def get_lemmatized_tokens(text): normalized_tokens = nltk.word_tokenize(remove_punctuation_marks(text.lower())) return [nltk.stem.WordNetLemmatizer().lemmatize(normalized_token) for normalized_token in normalized_tokens] corpus = open('corpus.txt', 'r', errors='ignore').read().lower() documents = nltk.sent_tokenize(corpus) def get_query_reply(query): documents.append(query) tfidf_results = TfidfVectorizer(tokenizer=get_lemmatized_tokens, stop_words='english').fit_transform(documents) cosine_similarity_results = cosine_similarity(tfidf_results[-1], tfidf_results).flatten() best_index = cosine_similarity_results.argsort()[-2] documents.remove(query) if cosine_similarity_results[best_index] == 0: return "I am sorry! I don't understand you..." else: return documents[best_index] def remove_punctuation_marks(text): …