Update app.py

app.py

@@ -26,8 +26,10 @@ else:
     st.write(f"Data Preview ({csv_file.name}):")
     st.dataframe(data.head())
 
-# Step 2: Load CSV data into SQLite database with dynamic table name
-conn = sqlite3.connect(':memory:')  # Use an in-memory SQLite database
+# Step 2: Load CSV data into a persistent SQLite database
+# Use a persistent database file instead of in-memory to retain schema context
+db_file = 'my_database.db'
+conn = sqlite3.connect(db_file)
 table_name = csv_file.name.split('.')[0] if csv_file else "default_table"
 data.to_sql(table_name, conn, index=False, if_exists='replace')
 
@@ -38,8 +40,8 @@ valid_columns = list(data.columns)
 st.write(f"Valid columns: {valid_columns}")
 
 # Step 3: Set up the SQL Database for LangChain
-db = SQLDatabase.from_uri('sqlite:///:memory:')
-db.raw_connection = conn  # Use the in-memory connection for LangChain
+db = SQLDatabase.from_uri(f'sqlite:///{db_file}')
+db.raw_connection = conn  # Use the persistent database connection for LangChain
 
 # Step 4: Create the SQL agent with increased iteration and time limits
 sql_agent = create_sql_agent(