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from machine_learning import model, words, labels, ans_data, nlp |
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import datetime |
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import random |
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import numpy |
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def bag_of_words(s, words): |
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bag = [0 for _ in range(len(words))] |
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s_words = nlp(s.lower()) |
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s_words = [word.lemma_ for word in s_words] |
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for se in s_words: |
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for i, w in enumerate(words): |
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if w == se: |
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bag[i] = 1 |
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return numpy.array(bag) |
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unknown = ["I'm afraid I don't follow; could you perhaps give more detail?", |
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"I'm sorry, but I need you to elaborate a little bit more.", "I don't understand, can you try another question?"] |
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def chat(): |
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print("Start talking with the bot (type quit to stop)!") |
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print("\n---------------------------------------------\nCellanet: Hello there!") |
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while True: |
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inp = input("You: ") |
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if inp.lower() == "quit": |
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break |
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results = model.predict([bag_of_words(inp, words)]) |
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results_index = numpy.argmax(results) |
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max_result = numpy.max(results) |
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if max_result < 0.65: |
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tag = 'unknown' |
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else: |
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tag = labels[results_index] |
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responses = [] |
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print(f"({tag})") |
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if tag in ans_data: |
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if tag == 'what time': |
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responses.append(f"Now is {datetime.datetime.now()}.") |
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else: |
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for x in ans_data[tag]: |
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for z in x: |
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responses.append(z) |
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else: |
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for x in unknown: |
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responses.append(x) |
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print('Cellanet:', random.choice(responses)) |
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def onlineChat(inp): |
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print("\n---------------------------------------------\n") |
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while True: |
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if inp.lower() == "quit": |
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break |
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results = model.predict([bag_of_words(inp, words)]) |
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results_index = numpy.argmax(results) |
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max_result = numpy.max(results) |
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if max_result < 0.05: |
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tag = 'unknown' |
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else: |
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tag = labels[results_index] |
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responses = [] |
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print(f"({tag})") |
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if tag in ans_data: |
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if tag == 'what time': |
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responses.append(f"Now is {datetime.datetime.now()}.") |
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else: |
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for x in ans_data[tag]: |
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for z in x: |
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responses.append(z) |
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else: |
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for x in unknown: |
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responses.append(f"{x}") |
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f = open('question and answer.txt', 'a') |
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f.write(f"- - {inp}\n - {random.choice(responses)}.\n\n\n") |
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f.close() |
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return f"Cellanet: {random.choice(responses)}" |
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