Update classification.py

classification.py

@@ -4,6 +4,41 @@ from sentence_transformers import SentenceTransformer, util
 import numpy as np
 import torch
 
+### Functions needed for Classfication
+
+def addCategories(df,df_all):
+    categories = df.to_dict("records")
+    categories_all = df_all.to_dict("list")
+    for cat in categories:
+        if cat['topic'] not in categories_all['topic']:
+            categories_all['topic'].append(cat['topic'])
+            categories_all['description'].append(cat['description'])
+            categories_all['experts'].append(cat['experts'])
+            print(f"AFTER ADDINGS Those are the categories_all : {categories_all}")
+
+    return gr.update(choices=categories_all['topic']),pd.DataFrame.from_dict(categories_all)
+    
+df_cat_filter = df_cate.to_dict("list")["topic"]
+
+def filterByTopics(filters, categories):
+    value_filtered = []
+    categories = categories.to_dict("records")
+    for cat in categories:
+        if cat['topic'] in filters:
+            value_filtered.append(cat)
+    
+    return gr.DataFrame(label='categories', value=pd.DataFrame(value_filtered), interactive=True)
+
+### End
+    
+def reset_cate(df_categories):
+    if df_categories.equals(df_cate):
+        df_categories = pd.DataFrame([['', '', '']], columns=['topic', 'description', 'expert'])
+    else:
+        df_categories = df_cate.copy()
+    return df_categories
+
+
 def load_data(file_obj):
     # Assuming file_obj is a file-like object uploaded via Gradio, use `pd.read_excel` directly on it
     return pd.read_excel(file_obj)