Update app.py

app.py

@@ -104,31 +104,21 @@ class InterestCalculatorApp:
         except requests.RequestException as e:
             st.error(f"Failed to download rates: {e}")
 
-    def ask_tapas(self, query, df):
-        # Convert the DataFrame to a list of dictionaries
-        table = df.to_dict('records')
+    def ask_tapas(self, query, table):
+        if isinstance(table, pd.DataFrame):
+            # Convert the DataFrame to a list of dictionaries
+            table_dict = table.to_dict('records')
     
-        # Initialize tokenized table
-        tokenized_table = []
+            # Tokenize each cell in the table
+            tokenized_table = [[self.tokenizer.tokenize(str(cell)) for cell in row.values()] for row in table_dict]
     
-        # Tokenize each row in the table
-        for row in table:
-            tokenized_row = []
-            for column_name, cell in row.items():
-                # Ensure that the cell is converted to a string before tokenizing
-                tokenized_row.append(self.tokenizer.tokenize(str(cell)))
-            tokenized_table.append(tokenized_row)
+            # Encode tokens and convert them to PyTorch tensors
+            inputs = self.tokenizer(table=tokenized_table, queries=query, return_tensors="pt", padding=True)
     
-        # Create DataFrame from tokenized table
-        df_tokenized = pd.DataFrame(tokenized_table)
-    
-        # Tokenize the query
-        tokenized_query = self.tokenizer.tokenize(query)
-    
-        # Encode tokens and convert them to PyTorch tensors
-        inputs = self.tokenizer(table=df_tokenized, queries=tokenized_query, return_tensors="pt", padding=True)
+            return inputs
+        else:
+            raise TypeError("Table must be of type pd.DataFrame")
     
-        return inputs
 
 
 def main():