Update app.py

app.py

@@ -110,7 +110,7 @@ df_cate = pd.DataFrame(categories)
 # def update_label(label1):
 #     return gr.update(choices=list(df.columns))
 
-# Functions needed for Split Files
+### Functions needed for Split Files
 
 def functionCall(fi_input, dropdown, choice):
     if choice == "Intelligent split":
@@ -128,7 +128,33 @@ def change_textbox(dropdown,radio):
 
 ### Split files end
 
+### 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'])
@@ -220,10 +246,19 @@ with gr.Blocks() as demo:
             dd_source_class = gr.Dropdown(label="Source Column", multiselect=False, scale=7)
             sl_treshold = gr.Slider(minimum=0, maximum=1, value=0.45, step=0.05, label='Similarity Treshold')
         gr.Markdown("### The predefined categories can be modified at any time")
+        
+        dd_filter = gr.Dropdown(choices=df_cat_filter, label = "Choose your filters here", multiselect=True, allow_custom_value=True)
+        
+        btn_filter = gr.Button("Filter")
+        
         df_category = gr.DataFrame(label='categories', value=df_cate, interactive=True)
+        df_category_hidden = gr.DataFrame(value=df_cate, visible=False)
+        
         with gr.Row():
-            btn_reset_df = gr.Button("Reset Categories")
+            btn_reset_df = gr.Button("Reset categories")
             btn_classif = gr.Button("Categorize")
+            btn_add_categories = gr.Button("Add categories")
+
 
     with gr.Tab(" Personalised Charts Generation"):
         gr.Markdown("### This section will create a chart using two columns of your choice")
@@ -297,7 +332,9 @@ with gr.Blocks() as demo:
     #classification
     btn_classif.click(classification, inputs=[dd_source_class, fi_excel, df_category, sl_treshold], outputs=[fi_excel, df_output])
     btn_reset_df.click(reset_cate, inputs=df_category, outputs=df_category)
-
+    btn_filter.click(filterByTopics, inputs=[dd_filter, df_category_hidden], outputs=df_category)
+    btn_add_categories.click(addCategories, inputs=[df_category, df_category_hidden],outputs=[dd_filter,df_category_hidden])    
+    
     #charts
     btn_chart.click(create_bar_plot, inputs=[fi_excel, dd_label1, dd_label2], outputs=[plt_figure])