Update app.py

app.py

@@ -1,139 +1,60 @@
 import streamlit as st
 import pandas as pd
-import datetime
 from transformers import AutoTokenizer, AutoModelForTableQuestionAnswering
+import datetime
 import requests
 
 class InterestCalculatorApp:
     def __init__(self):
-        self.invoices_df = pd.DataFrame()  # Initialize as empty DataFrame
-        self.base_rates_df = pd.DataFrame()  # Initialize as empty DataFrame
+        self.invoices_df = pd.DataFrame()
+        self.base_rates_df = pd.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)"])
+        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)"
+            ]
+        )
         self.tokenizer = AutoTokenizer.from_pretrained("google/tapas-large-finetuned-wtq")
         self.model = AutoModelForTableQuestionAnswering.from_pretrained("google/tapas-large-finetuned-wtq")
 
     def load_invoices(self, file_path):
         try:
-            self.invoices_df = pd.read_excel(file_path, parse_dates=['Due Date'])
+            self.invoices_df = pd.read_excel(file_path, parse_dates=True)
+            self.invoices_df = self.invoices_df.fillna('N/A')  # Handle missing values
+            self.invoices_df = self.invoices_df.applymap(lambda x: str(x).strip() if isinstance(x, str) else str(x))
             st.success("Invoices loaded successfully.")
         except Exception as e:
             st.error(f"Failed to load invoices: {e}")
 
-    def calculate_interest(self):
-        if not self.invoices_df.empty and not self.base_rates_df.empty:
-            st.write("Calculating interest...")
-            today = datetime.datetime.today()
-            interests = []
-            for index, invoice in self.invoices_df.iterrows():
-                due_date = invoice['Due Date']
-                amount = invoice['Amount']
-                base_rate = self.get_base_rate(due_date)
-                effective_rate = base_rate + self.late_payment_interest
-                if due_date > today:
-                    interests.append(0)
-                    continue
-                interest = self.calculate_compound_interest(due_date, amount, effective_rate, self.compounding_method, today)
-                interests.append(interest)
-                total_amount_owed = amount + interest
-                self.invoices_df.loc[index, 'Interest'] = interest
-                self.invoices_df.loc[index, 'Total Amount Owed'] = total_amount_owed
-            total_interest = sum(interests)
-            st.success(f"Total Interest Calculated: £{total_interest:.2f}")
-            st.write(self.invoices_df)
-        else:
-            st.error("Please load both invoices and base rates files.")
-
-    def get_base_rate(self, due_date):
-        self.base_rates_df['Date Changed'] = pd.to_datetime(self.base_rates_df['Date Changed'])
-        rate_rows = self.base_rates_df[self.base_rates_df['Date Changed'] <= due_date].sort_values(by='Date Changed', ascending=False)
-        return rate_rows.iloc[0]['Rate'] if not rate_rows.empty else 0
-
-    def calculate_compound_interest(self, due_date, amount, effective_rate, method, today):
-        days = (today - due_date).days
-        if 'daily' in method:
-            daily_rate = (effective_rate / 100) / 365
-            return amount * daily_rate * days
-        elif 'annually' in method:
-            annual_rate = effective_rate / 100
-            return amount * annual_rate * (days / 365)
-        elif 'Quarterly compounding' in method:
-            return self.calculate_quarterly_interest(due_date, amount, effective_rate, method, today)
-
-    def calculate_quarterly_interest(self, due_date, amount, effective_rate, method, today):
-        quarterly_dates = {
-            "Quarterly compounding (25 Mar, 24 Jun, 29 Sep, 25 Dec)": [(3, 25), (6, 24), (9, 29), (12, 25)],
-            "Quarterly compounding (1 Mar, 1 Jun, 1 Sep, 1 Dec)": [(3, 1), (6, 1), (9, 1), (12, 1)]
-        }[method]
-        interest = 0
-        compounded_amount = amount
-        for month, day in quarterly_dates:
-            compounding_date = datetime.datetime(today.year, month, day)
-            if compounding_date > today:
-                break
-            if compounding_date > due_date:
-                days_since_last_compounding = (today - compounding_date).days
-                period_rate = effective_rate / 4  # Quarterly rate
-                compounded_interest = compounded_amount * ((1 + period_rate) ** (days_since_last_compounding / 365.25) - 1)
-                compounded_amount += compounded_interest
-                interest += compounded_interest
-                due_date = compounding_date
-        return interest
-
-    def download_boe_rates(self):
-        try:
-            headers = {
-                'accept-language': 'en-US,en;q=0.9',
-                'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/109.0.0.0 Safari/537.36'
-            }
-            url = 'https://www.bankofengland.co.uk/boeapps/database/Bank-Rate.asp'
-            response = requests.get(url, headers=headers)
-            if response.status_code == 200:
-                df = pd.read_html(response.text)[0]
-                df.to_csv('boe_rates.csv', index=False)
-                self.base_rates_df = df
-                self.base_rates_df['Date Changed'] = pd.to_datetime(self.base_rates_df['Date Changed'], format='%d %b %y')
-                st.success("Bank of England rates downloaded successfully.")
-            else:
-                st.error("Failed to retrieve data from the Bank of England website.")
-        except requests.RequestException as e:
-            st.error(f"Failed to download rates: {e}")
-
     def ask_tapas(self, query, table):
         if not isinstance(table, pd.DataFrame):
             raise TypeError("Expected the table to be a pd.DataFrame, got {}".format(type(table).__name__))
+
+        table = table.applymap(lambda x: str(x) if not pd.isnull(x) else "N/A")
         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")
-
-    app = InterestCalculatorApp()
-
-    file_path = st.file_uploader("Upload Invoices File", type=["xlsx"])
-
-    if file_path is not None:
-        app.load_invoices(file_path)
-
-    query = st.text_input("Enter your query:")
-    if query:
-        if not app.invoices_df.empty:
-            st.write("Invoice Data:")
-            st.write(app.invoices_df)
-            answer = app.ask_tapas(query, app.invoices_df)
-            st.write("Answer:", answer)
-        else:
-            st.warning("Please upload the invoices file first.")
-
-    if st.button("Calculate Interest"):
-        app.calculate_interest()
-
-    app.download_boe_rates()
+    def main():
+        st.title("Interest Calculation App")
+        file_path = st.file_uploader("Upload Invoices File", type=["xlsx"])
+        if file_path is not None:
+            self.load_invoices(file_path)
+
+        query = st.text_input("Enter your query:")
+        if query:
+            if not self.invoices_df.empty:
+                st.write("Invoice Data:")
+                st.dataframe(self.invoices_df)
+                answer = self.ask_tapas(query, self.invoices_df)
+                st.write("Answer:", answer)
+            else:
+                st.warning("Please upload the invoices file first.")
 
 if __name__ == "__main__":
-    main()
+    app = InterestCalculatorApp()
+    app.main()