Update app.py

app.py

@@ -1,20 +1,18 @@
 import streamlit as st
 import pandas as pd
-import requests
-from datetime import datetime
+import datetime
 from transformers import AutoTokenizer, AutoModelForTableQuestionAnswering
+import requests
 
 class InterestCalculatorApp:
     def __init__(self):
-        self.invoices_df = None
-        self.base_rates_df = None
+        self.invoices_df = pd.DataFrame()  # Initialize as empty DataFrame
+        self.base_rates_df = pd.DataFrame()  # Initialize as empty DataFrame
         self.late_payment_interest = st.sidebar.slider("Late Payment Interest Rate (%)", min_value=0.0, max_value=10.0, value=4.0)
         self.compounding_method = st.sidebar.selectbox("Compounding Method", ["x% above Base Rate (daily)", 
                                                                             "x% above Base Rate (annually)",
                                                                              "Quarterly compounding (25 Mar, 24 Jun, 29 Sep, 25 Dec)",
                                                                              "Quarterly compounding (1 Mar, 1 Jun, 1 Sep, 1 Dec)"])
-
-        # Load TAPAS model
         self.tokenizer = AutoTokenizer.from_pretrained("google/tapas-large-finetuned-wtq")
         self.model = AutoModelForTableQuestionAnswering.from_pretrained("google/tapas-large-finetuned-wtq")
 
@@ -26,9 +24,9 @@ class InterestCalculatorApp:
             st.error(f"Failed to load invoices: {e}")
 
     def calculate_interest(self):
-        if self.invoices_df is not None and self.base_rates_df is not None:
+        if not self.invoices_df.empty and not self.base_rates_df.empty:
             st.write("Calculating interest...")
-            today = datetime.today()
+            today = datetime.datetime.today()
             interests = []
             for index, invoice in self.invoices_df.iterrows():
                 due_date = invoice['Due Date']
@@ -73,7 +71,7 @@ class InterestCalculatorApp:
         interest = 0
         compounded_amount = amount
         for month, day in quarterly_dates:
-            compounding_date = datetime(today.year, month, day)
+            compounding_date = datetime.datetime(today.year, month, day)
             if compounding_date > today:
                 break
             if compounding_date > due_date:
@@ -105,14 +103,12 @@ class InterestCalculatorApp:
             st.error(f"Failed to download rates: {e}")
 
     def ask_tapas(self, query, table):
-        if isinstance(table, pd.DataFrame):
-            tokenized_query = self.tokenizer.tokenize(query)
-            tokenized_table = [[self.tokenizer.tokenize(str(cell)) for cell in row] for row in table.values]
-
-            inputs = self.tokenizer(table=tokenized_table, queries=[tokenized_query], return_tensors="pt", padding=True)
-            return inputs
-        else:
-            raise TypeError("Table must be of type pd.DataFrame")
+        if not isinstance(table, pd.DataFrame):
+            raise TypeError("Expected the table to be a pd.DataFrame, got {}".format(type(table).__name__))
+        inputs = self.tokenizer(table=table, queries=[query], return_tensors="pt", padding=True)
+        outputs = self.model(**inputs)
+        predicted_answer = self.tokenizer.decode(outputs.logits.argmax(dim=-1))
+        return predicted_answer
 
 def main():
     st.title("Interest Calculation App")
@@ -126,13 +122,9 @@ def main():
 
     query = st.text_input("Enter your query:")
     if query:
-        # Assuming you have a DataFrame named 'invoices_df' containing the invoice data
         if not app.invoices_df.empty:
-            # Display the invoice data
             st.write("Invoice Data:")
             st.write(app.invoices_df)
-
-            # Call TAPAS model to answer user's query
             answer = app.ask_tapas(query, app.invoices_df)
             st.write("Answer:", answer)
         else: