fix keyword

app.py

@@ -36,9 +36,9 @@ def greet(name, descriptions):
 
     # run keyword extraction
     kw_model = KeyBERT()
-    keyword_extract(kw_model, 1, save_output=f'results/{name}/{1}_keyword.png')
-    keyword_extract(kw_model, 2, save_output=f'results/{name}/{2}_keyword.png')
-    keyword_extract(kw_model, 3, save_output=f'results/{name}/{3}_keyword.png')
+    keyword_extract(descriptions, kw_model, 1, save_output=f'results/{name}/{1}_keyword.png')
+    keyword_extract(descriptions, kw_model, 2, save_output=f'results/{name}/{2}_keyword.png')
+    keyword_extract(descriptions, kw_model, 3, save_output=f'results/{name}/{3}_keyword.png')
     outputs.append(Image.open(f'results/{name}/1_keyword.png'))
     outputs.append(Image.open(f'results/{name}/2_keyword.png'))
     outputs.append(Image.open(f'results/{name}/3_keyword.png'))

keyword_extraction.py

@@ -3,7 +3,7 @@ import matplotlib.pyplot as plt
 import pandas as pd
 import seaborn as sns
 
-doc = """
+test_doc = """
 Database that collects, administrative, clinical and demographic information on hospital discharges (including deaths, sign-outs and transfers). Some provinces and territories also use the DAD to capture day surgery.
 
 
@@ -31,7 +31,7 @@ The Discharge Abstract Database is a database for information on all separation
 Captures administrative, clinical and demographic information on discharges for acute care facilities (including deaths, sign-outs and transfers).
       """
 
-def keyword_extract(kw_model, n_grams, save_output='results/'):
+def keyword_extract(doc, kw_model, n_grams, save_output='results/'):
     keyword_onegram = kw_model.extract_keywords(doc, keyphrase_ngram_range=(1, n_grams), stop_words=None)
     words = list(zip(*keyword_onegram))[0]
     scores = list(zip(*keyword_onegram))[1]
@@ -46,5 +46,5 @@ if __name__ == '__main__':
     keyword_extract(kw_model, 1)
     keyword_extract(kw_model, 2)
     keyword_extract(kw_model, 3)
-    keywords = kw_model.extract_keywords(doc, highlight=True)
+    keywords = kw_model.extract_keywords(test_doc, highlight=True)
     print(keywords)

main.py

@@ -71,9 +71,9 @@ filename.open('w', encoding='utf-8').write(svg)
 
 # run keyword extraction
 kw_model = KeyBERT()
-keyword_extract(kw_model, 1, save_output=f'results/DAD/{1}_keyword.png')
-keyword_extract(kw_model, 2, save_output=f'results/DAD/{2}_keyword.png')
-keyword_extract(kw_model, 3, save_output=f'results/DAD/{3}_keyword.png')
+keyword_extract(descriptions, kw_model, 1, save_output=f'results/DAD/{1}_keyword.png')
+keyword_extract(descriptions, kw_model, 2, save_output=f'results/DAD/{2}_keyword.png')
+keyword_extract(descriptions, kw_model, 3, save_output=f'results/DAD/{3}_keyword.png')
 keywords = kw_model.extract_keywords(doc, highlight=True)
 print(keywords)