Added classes for 0.0.2 prerelease

Author: Cipher

Janex.py

@@ -1,169 +1,167 @@
 import json
 import string
 
-class NoMatchingIntentError(Exception):
-    pass
+class IntentMatcher:
+    def __init__(self, intents_file_path):
+        self.intents_file_path = intents_file_path
+        self.intents = self.train()
 
-def Tokenize(input_string):
-    input_string = input_string.strip()
-    input_string = input_string.translate(str.maketrans("", "", string.punctuation))
-    words = input_string.split()
+    class NoMatchingIntentError(Exception):
+        pass
 
-    words = stem_list(words)
+    def Tokenize(self, input_string):
+        input_string = input_string.strip()
+        input_string = input_string.translate(str.maketrans("", "", string.punctuation))
+        words = input_string.split()
 
-    return words
+        words = self.stem_list(words)
 
-def Tokenize_List(input_list):
-    stemmedwords = []
-    for word in input_list:
-        token = Tokenize(word)
-        Tokenwords.append(token)
+        return words
 
-    return Tokenwords
+    def Tokenize_List(self, input_list):
+        Tokenwords = []
+        for word in input_list:
+            token = self.Tokenize(word)
+            Tokenwords.append(token)
 
-def train(intents_file_path):
-    with open(intents_file_path, 'r') as json_data:
-        intents = json.load(json_data)
-    return intents
+        return Tokenwords
 
-def patterncompare(input_string, intents_file_path):
-    input_string = input_string.lower()
-    HighestSimilarity = 0
-    MostSimilarPattern = None
-    SimilarityPercentage = 0
+    def train(self):
+        with open(self.intents_file_path, 'r') as json_data:
+            intents = json.load(json_data)
+        return intents
 
-    patterns = []
-    Similarity = 0
+    def patterncompare(self, input_string):
+        input_string = input_string.lower()
+        HighestSimilarity = 0
+        MostSimilarPattern = None
+        SimilarityPercentage = 0
 
-    with open(intents_file_path, 'r') as json_data:
-        intents = json.load(json_data)
+        patterns = []
+        Similarity = 0
+
+        WordList2 = self.Tokenize(input_string)
+
+        for intent_class in self.intents['intents']:
+            OverallWordList = []
+            Similarity = 0
+
+            patterns = intent_class.get('patterns')
+            for pattern in patterns:
+                WordList = []
+                pattern = pattern.lower()
+                WordList = self.Tokenize(pattern)
+                OverallWordList.append(WordList)
+                NewList = []
+                NewBag = []
+
+                for word in WordList:
+                    word = self.stem(word)
+                    NewList.append(word)
+
+                for word in WordList2:
+                    word = self.stem(word)
+                    NewBag.append(word)
 
-    WordList2 = Tokenize(input_string)
+                WordList = NewList
+                WordList2 = NewBag
 
-    for intent_class in intents['intents']:
-        OverallWordList = []
+                for word in WordList2:
+                    if word in WordList:
+                        Similarity = Similarity + 1
+
+                    if Similarity > HighestSimilarity:
+                        SimilarityPercentage = Similarity / len(OverallWordList + WordList2)
+                        HighestSimilarity = Similarity
+                        MostSimilarPattern = intent_class
+
+        print(f"Similarity: {SimilarityPercentage:.2f}%")
+
+        if MostSimilarPattern:
+            return MostSimilarPattern
+        else:
+            raise self.NoMatchingIntentError("No matching intent class found.")
+
+    def responsecompare(self, input_string, intent_class):
+        input_string = input_string.lower()
+        HighestSimilarity = 0
+        SimilarityPercentage = 0
+        MostSimilarResponse = None
+
+        responses = []
         Similarity = 0
 
-        patterns = intent_class.get('patterns')
-        for pattern in patterns:
-            WordList = []
-            pattern = pattern.lower()
-            WordList = Tokenize(pattern)
-            OverallWordList.append(WordList)
+        WordList2 = self.Tokenize(input_string)
+
+        if intent_class is not None:
+            responses = intent_class.get('responses')
+        else:
+            raise self.NoMatchingIntentError("No matching intent class found.")
+
+        for response in responses:
+
+            Similarity = 0
+            pattern = response.lower()
+            WordList = self.Tokenize(response)
             NewList = []
             NewBag = []
 
             for word in WordList:
-                word = stem(word)
+                word = self.stem(word)
                 NewList.append(word)
 
             for word in WordList2:
-                word = stem(word)
+                word = self.stem(word)
                 NewBag.append(word)
 
             WordList = NewList
             WordList2 = NewBag
 
             for word in WordList2:
                 if word in WordList:
-                    Similarity = Similarity + 1
+                    Similarity = (Similarity+1/len(WordList + WordList2))
 
                 if Similarity > HighestSimilarity:
-                    SimilarityPercentage = Similarity / len(OverallWordList + WordList2)
-# Just to test the mathy bit idk am autistic and gay so maths isn't strong suit                    print(len(OverallWordList+WordList2s)
+                    SimilarityPercentage = Similarity * 100
                     HighestSimilarity = Similarity
-                    MostSimilarPattern = intent_class
-
-    print(f"Similarity: {SimilarityPercentage:.2f}%")
-
-    if MostSimilarPattern:
-        return MostSimilarPattern
-    else:
-        raise NoMatchingIntentError("No matching intent class found.")
-
-def responsecompare(input_string, intents_file_path, intent_class):
-    input_string = input_string.lower()
-    HighestSimilarity = 0
-    SimilarityPercentage = 0
-    MostSimilarResponse = None
-
-    responses = []
-    Similarity = 0
-
-    with open(intents_file_path, 'r') as json_data:
-        intents = json.load(json_data)
-
-    WordList2 = Tokenize(input_string)
-
-    if intent_class is not None:
-        responses = intent_class.get('responses')
-    else:
-        raise NoMatchingIntentError("No matching intent class found.")
-
-    for response in responses:
-
-        Similarity = 0
-        pattern = response.lower()
-        WordList = Tokenize(response)
-        NewList = []
-        NewBag = []
-
-        for word in WordList:
-            word = stem(word)
-            NewList.append(word)
-
-        for word in WordList2:
-            word = stem(word)
-            NewBag.append(word)
-
-        WordList = NewList
-        WordList2 = NewBag
-
-        for word in WordList2:
-            if word in WordList:
-                Similarity = (Similarity+1/len(WordList + WordList2))
-
-            if Similarity > HighestSimilarity:
-                SimilarityPercentage = Similarity * 100
-                HighestSimilarity = Similarity
-                MostSimilarResponse = response
-
-    print(f"Similarity: {SimilarityPercentage:.2f}%")
-
-    # Convert MSR back into original string
-    for response in responses:
-        lowresponselist = []
-        lowresponse = response.lower()
-        lowresponselist = stem_sentence(lowresponse)
-
-        for lowresponse in lowresponselist:
-            if lowresponse == MostSimilarResponse:
-                MostSImilarResponse = response
-
-    return MostSimilarResponse
-
-def stem(input_word):
-    suffixes = ['ing', 'ly', 'ed', 'es', "'s", 'er', 'est', 'y', 'ily', 'able', 'ful', 'ness', 'less', 'ment', 'ive', 'ize', 'ous']
-    for suffix in suffixes:
-        if input_word.endswith(suffix):
-            input_word = input_word[:-len(suffix)]
-            break
-    return input_word
-
-def stem_sentence(input_string):
-    wordlist = []
-    stemmedwords = []
-    wordlist = input_string.split()
-    for input_word in wordlist:
-        word = stem(input_word)
-        stemmedwords.append(word)
-
-    return stemmedwords
-
-def stem_list(input_list):
-    stemmedwords = []
-    for word in input_list:
-        stemmedword = stem(word)
-        stemmedwords.append(stemmedword)
-
-    return stemmedwords
+                    MostSimilarResponse = response
+
+        print(f"Similarity: {SimilarityPercentage:.2f}%")
+
+        # Convert MSR back into the original string
+        for response in responses:
+            lowresponselist = []
+            lowresponse = response.lower()
+            lowresponselist = self.stem_sentence(lowresponse)
+
+            for lowresponse in lowresponselist:
+                if lowresponse == MostSimilarResponse:
+                    MostSimilarResponse = response
+
+        return MostSimilarResponse
+
+    def stem(self, input_word):
+        suffixes = ['ing', 'ly', 'ed', 'es', "'s", 'er', 'est', 'y', 'ily', 'able', 'ful', 'ness', 'less', 'ment', 'ive', 'ize', 'ous']
+        for suffix in suffixes:
+            if input_word.endswith(suffix):
+                input_word = input_word[:-len(suffix)]
+                break
+        return input_word
+
+    def stem_sentence(self, input_string):
+        wordlist = []
+        stemmedwords = []
+        wordlist = input_string.split()
+        for input_word in wordlist:
+            word = self.stem(input_word)
+            stemmedwords.append(word)
+
+        return stemmedwords
+
+    def stem_list(self, input_list):
+        stemmedwords = []
+        for word in input_list:
+            stemmedword = self.stem(word)
+            stemmedwords.append(stemmedword)
+
+        return stemmedwords

__pycache__/Janex.cpython-311.pyc

@@ -1,16 +1,17 @@
 from Janex import *
 
-input_string = input("You: ")
+intents_file_path = "intents.json"
+matcher = IntentMatcher(intents_file_path)
 
-words = Tokenize(input_string)
+input_string = input("You: ")
+words = matcher.Tokenize(input_string)
 
-intents_file_path = "intents.json"
+intent_class = matcher.patterncompare(input_string)
 
-intent_class = patterncompare(input_string, intents_file_path)
+print(intent_class.get("tag"))
 
-BestResponse = responsecompare(input_string, intents_file_path, intent_class)
+best_response = matcher.responsecompare(input_string, intent_class)
 
-print(BestResponse)
+print(best_response)
 
-stemmed_words = stem_sentence(input_string)
-# print(stemmed_words)
+stemmed_words = matcher.stem_sentence(input_string)