Create new file

chatbot.py

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+from scipy import rand
+from machine_learning import model, words, labels, ans_data, npl
+import datetime
+import random
+import numpy
+
+
+
+def bag_of_words(s, words):
+    bag = [0 for _ in range(len(words))]
+    s_words = npl(s.lower())
+    s_words = [word.lemma_ for word in s_words]
+
+    for se in s_words:
+        for i, w in enumerate(words):
+            if w == se:
+                bag[i] = 1
+            
+    return numpy.array(bag)
+
+unknown = ["I'm afraid I don't follow; could you perhaps give more detail?", 
+           "I'm sorry, but I need you to elaborate a little bit more.", "I don't understand, can you try another question?"]
+
+def chat():
+    print("Start talking with the bot (type quit to stop)!")
+    print("\n---------------------------------------------\nCellanet: Hello there!")
+    while True:
+        inp = input("You: ")
+        if inp.lower() == "quit":
+            break
+
+        results = model.predict([bag_of_words(inp, words)])
+#         print(f"Predict: {results}\n")
+        results_index = numpy.argmax(results)
+        
+        max_result = numpy.max(results)
+#         print(f"max: {max_result}")
+        
+        if max_result < 0.65:
+            tag = 'unknown'
+        else:
+            tag = labels[results_index]
+        
+        responses = []
+        print(f"({tag})")
+        
+        if tag in ans_data:
+            if tag == 'what time':
+                responses.append(f"Now is {datetime.datetime.now()}.")
+            else:
+                for x in ans_data[tag]:
+                    for z in x:
+                        responses.append(z)
+        else:
+            for x in unknown:
+                responses.append(x)
+            
+            
+        print('Cellanet:', random.choice(responses))
+        # return f"Cellanet: {random.choice(responses)}."
+
+
+def onlineChat(inp):
+    print("\n---------------------------------------------\n")
+    while True:
+        # inp = input("You: ")
+        if inp.lower() == "quit":
+            break
+
+        results = model.predict([bag_of_words(inp, words)])
+#         print(f"Predict: {results}\n")
+        results_index = numpy.argmax(results)
+        
+        max_result = numpy.max(results)
+#         print(f"max: {max_result}")
+        
+        if max_result < 0.45:
+            tag = 'unknown'
+        else:
+            tag = labels[results_index]
+        
+        responses = []
+        print(f"({tag})")
+        
+        if tag in ans_data:
+            if tag == 'what time':
+                responses.append(f"Now is {datetime.datetime.now()}.")
+            else:
+                for x in ans_data[tag]:
+                    for z in x:
+                        responses.append(z)
+        else:
+            for x in unknown:
+                responses.append(f"*********** {x} ***********")
+
+        f = open('question and answer.txt', 'a')
+        f.write(f"- - {inp}\n  - {random.choice(responses)}.\n\n\n")
+        f.close()
+
+        return f"Cellanet: {random.choice(responses)}"
+
+
+
+# chat()