NA

.gitignore

@@ -139,4 +139,5 @@ dmypy.json
 # project file 
 project.yaml
 
-.idea/
+.idea/
+ev_database.db

README.md

@@ -5,7 +5,6 @@ colorFrom: indigo
 colorTo: indigo
 sdk: docker
 app_port: 8501
-app_file: app.py
 pinned: false
 license: apache-2.0
 short_description: EV Assistant using vectara-agent

app.py

@@ -1,5 +1,6 @@
 from PIL import Image
 import sys
+import os
 
 import streamlit as st
 from streamlit_pills import pills
@@ -156,16 +157,18 @@ def setup_db():
             sql_script = sql_file.read()
             cursor.executescript(sql_script)
 
+        hf_token = os.getenv('HF_TOKEN')
+
         # Load data into ev_population table
-        df = load_dataset("vectara/ev-dataset", data_files="Electric_Vehicle_Population_Data.csv")['train'].to_pandas()
+        df = load_dataset("vectara/ev-dataset", data_files="Electric_Vehicle_Population_Data.csv", use_auth_token=hf_token)['train'].to_pandas()
         df.to_sql('ev_population', conn, if_exists='replace', index=False)
 
         # Load data into county_registrations table
-        df = load_dataset("vectara/ev-dataset", data_files="Electric_Vehicle_Population_Size_History_By_County.csv")['train'].to_pandas()
+        df = load_dataset("vectara/ev-dataset", data_files="Electric_Vehicle_Population_Size_History_By_County.csv", use_auth_token=hf_token)['train'].to_pandas()
         df.to_sql('county_registrations', conn, if_exists='replace', index=False)
 
         # Load data into ev_registrations table
-        df = load_dataset("vectara/ev-dataset", data_files="Electric_Vehicle_Title_and_Registration_Activity.csv")['train'].to_pandas()
+        df = load_dataset("vectara/ev-dataset", data_files="Electric_Vehicle_Title_and_Registration_Activity.csv", use_auth_token=hf_token)['train'].to_pandas()
         df.to_sql('ev_registrations', conn, if_exists='replace', index=False)
 
         # Commit changes and close connection