updated word2vec with get_cos_sim function for frontend

word2vec.py

@@ -1,5 +1,6 @@
 from gensim.models import Word2Vec
 from collections import defaultdict
+import os
 
 def load_word2vec_model(model_path):
     '''
@@ -67,10 +68,25 @@ def cosine_similarity(vector_a, vector_b):
 
     similarity = dot_prod / (mag_a * mag_b)
     return similarity
+
+
+def get_cosine_similarity(word1, word2, time_slice):
+    '''
+        Return the cosine similarity of two words
+    '''
+    # TO DO: MOET NETTER
+    
+    # Return if path does not exist
+    if not os.path.exists(f'models/{time_slice}.model'):
+        return 
+    
+    model = load_word2vec_model(f'models/{time_slice}.model')
+    dict = model_dictionary(model)
+    return cosine_similarity(dict[word1], dict[word2])
     
 
 def main():
-    model = load_word2vec_model('../models/archaic_cbow.model')
+    model = load_word2vec_model('models/archaic_cbow.model')
     archaic_cbow_dict = model_dictionary(model)
     
     score = cosine_similarity(archaic_cbow_dict['Πελοπόννησος'], archaic_cbow_dict['σπάργανον'])
@@ -80,7 +96,7 @@ def main():
     # print(vector)
 
     # Iterate over all words and print their vectors
-    # iterate_over_words(model)
+    iterate_over_words(model)
 
 
 if __name__ == "__main__":