add policy action

app.py

@@ -60,8 +60,9 @@ with st.expander("ℹ️ - About this app", expanded=False):
                 not at specific Sector level but are applicable at economic \
                 wide scale. """)               
     st.write("")
-apps = [processing.app, target_extraction.app, netzero.app, ghg.app,
-        policyaction.app, indicator.app, conditional.app, sector.app]
+apps = [processing.app, policyaction.app]
+#target_extraction.app, netzero.app, ghg.app,
+ #       policyaction.app, indicator.app, conditional.app, sector.app]
         #adapmit.app]
          
         #  policyaction.app, indicator.app, ]

utils/policyaction_classifier.py

@@ -8,11 +8,6 @@ from utils.preprocessing import processingpipeline
 import streamlit as st
 from transformers import pipeline
 
-## Labels dictionary ###
-_lab_dict = {
-            'NEGATIVE':'NO TARGET INFO',
-            'TARGET':'TARGET',
-            }
 
 @st.cache_resource
 def load_policyactionClassifier(config_file:str = None, classifier_name:str = None):
@@ -93,9 +88,11 @@ def policyaction_classification(haystack_doc:pd.DataFrame,
     categories = list(truth_df.columns)
     truth_df['Policy-Action Label'] = truth_df.apply(lambda x: {i if x[i]=='True' 
                                         else None for i in categories}, axis=1)
+    st.dataframe(truth_df)                                    
     truth_df['Policy-Action Label'] = truth_df.apply(lambda x: 
                                   list(x['Policy-Action Label'] -{None}),axis=1)
 
-    haystack_doc['Policy-Action Label'] =  list(truth_df['Policy-Action Label'])   
+    haystack_doc['Policy-Action Label'] =  list(truth_df['Policy-Action Label']) 
+    st.dataframe(haystack_doc)  
 
     return haystack_doc