albhu commited on
Commit
e5ac618
·
verified ·
1 Parent(s): 1a571c7

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +36 -12
app.py CHANGED
@@ -12,7 +12,7 @@ def main():
12
 
13
  if api_key:
14
  # Download BOE rates
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- download_boe_rates()
16
 
17
  # Allow user to upload Excel sheet
18
  uploaded_file = st.file_uploader("Upload Excel file", type=["xlsx", "xls"])
@@ -40,7 +40,7 @@ def main():
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  })
41
 
42
  # Calculate late interest
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- df_with_interest = calculate_late_interest(df_calculate, late_interest_rate)
44
 
45
  # Display calculated late interest
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  total_late_interest = df_with_interest['late_interest'].sum()
@@ -48,14 +48,7 @@ def main():
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  st.write(total_late_interest)
49
 
50
  # Generate conversation prompt
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- prompt = "I have analyzed the provided Excel sheet. "
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- if due_dates:
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- prompt += f"The due dates in the sheet are: {', '.join(str(date) for date in due_dates)}. "
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- if payment_dates:
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- prompt += f"The payment dates in the sheet are: {', '.join(str(date) for date in payment_dates)}. "
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- if amounts:
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- prompt += f"The amounts in the sheet are: {', '.join(str(amount) for amount in amounts)}. "
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- prompt += "Based on this information, what would you like to discuss?"
59
 
60
  # Allow user to engage in conversation
61
  user_input = st.text_input("Start a conversation:")
@@ -68,21 +61,36 @@ def main():
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  {"role": "system", "content": prompt},
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  {"role": "user", "content": user_input}
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  ],
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- max_tokens=1800
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  )
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  response = completion.choices[0].message['content']
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  st.write("AI's Response:")
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  st.write(response)
 
 
 
 
 
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  else:
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  st.warning("Please enter your OpenAI API key.")
78
 
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  # Function to calculate late interest
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- def calculate_late_interest(data, late_interest_rate):
81
  # Calculate late days and late interest
82
  data['late_days'] = (data['payment_date'] - data['due_date']).dt.days.clip(lower=0)
83
  data['late_interest'] = data['late_days'] * data['amount'] * (late_interest_rate / 100)
 
 
 
 
 
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  return data
85
 
 
 
 
 
 
86
  # Function to analyze Excel sheet and extract relevant information
87
  def analyze_excel(df):
88
  # Extract due dates and payment dates
@@ -111,10 +119,26 @@ def download_boe_rates():
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  df = pd.read_html(response.text)[0]
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  df.to_csv('boe_rates.csv', index=False)
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  st.success("Bank of England rates downloaded successfully.")
 
114
  else:
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  st.error("Failed to retrieve data from the Bank of England website.")
 
116
  except requests.RequestException as e:
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  st.error(f"Failed to download rates: {e}")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
118
 
119
  if __name__ == "__main__":
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  main()
 
12
 
13
  if api_key:
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  # Download BOE rates
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+ boe_rates_df = download_boe_rates()
16
 
17
  # Allow user to upload Excel sheet
18
  uploaded_file = st.file_uploader("Upload Excel file", type=["xlsx", "xls"])
 
40
  })
41
 
42
  # Calculate late interest
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+ df_with_interest = calculate_late_interest(df_calculate, late_interest_rate, boe_rates_df)
44
 
45
  # Display calculated late interest
46
  total_late_interest = df_with_interest['late_interest'].sum()
 
48
  st.write(total_late_interest)
49
 
50
  # Generate conversation prompt
51
+ prompt = generate_conversation_prompt(df)
 
 
 
 
 
 
 
52
 
53
  # Allow user to engage in conversation
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  user_input = st.text_input("Start a conversation:")
 
61
  {"role": "system", "content": prompt},
62
  {"role": "user", "content": user_input}
63
  ],
64
+ max_tokens=1800 # Adjust this value to allow longer responses
65
  )
66
  response = completion.choices[0].message['content']
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  st.write("AI's Response:")
68
  st.write(response)
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+
70
+ # Button to clear cache
71
+ if st.button("Clear Cache"):
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+ st.cache.clear()
73
+
74
  else:
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  st.warning("Please enter your OpenAI API key.")
76
 
77
  # Function to calculate late interest
78
+ def calculate_late_interest(data, late_interest_rate, boe_rates_df):
79
  # Calculate late days and late interest
80
  data['late_days'] = (data['payment_date'] - data['due_date']).dt.days.clip(lower=0)
81
  data['late_interest'] = data['late_days'] * data['amount'] * (late_interest_rate / 100)
82
+
83
+ # Consider additional factors like Bank of England base rate
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+ data['boe_base_rate'] = data['due_date'].map(lambda x: get_boe_base_rate(x, boe_rates_df))
85
+ data['late_interest'] += data['amount'] * (data['boe_base_rate'] / 100)
86
+
87
  return data
88
 
89
+ # Function to get Bank of England base rate for a given date
90
+ def get_boe_base_rate(date, boe_rates_df):
91
+ closest_date = boe_rates_df['Date Changed'].iloc[(boe_rates_df['Date Changed']-date).abs().argsort()[0]]
92
+ return boe_rates_df[boe_rates_df['Date Changed'] == closest_date]['Base Rate'].values[0]
93
+
94
  # Function to analyze Excel sheet and extract relevant information
95
  def analyze_excel(df):
96
  # Extract due dates and payment dates
 
119
  df = pd.read_html(response.text)[0]
120
  df.to_csv('boe_rates.csv', index=False)
121
  st.success("Bank of England rates downloaded successfully.")
122
+ return df
123
  else:
124
  st.error("Failed to retrieve data from the Bank of England website.")
125
+ return None
126
  except requests.RequestException as e:
127
  st.error(f"Failed to download rates: {e}")
128
+ return None
129
+
130
+ # Function to generate conversation prompt
131
+ def generate_conversation_prompt(df):
132
+ prompt = "I have analyzed the provided Excel sheet. "
133
+ due_dates, payment_dates, amounts = analyze_excel(df)
134
+ if due_dates:
135
+ prompt += f"The due dates in the sheet are: {', '.join(str(date) for date in due_dates)}. "
136
+ if payment_dates:
137
+ prompt += f"The payment dates in the sheet are: {', '.join(str(date) for date in payment_dates)}. "
138
+ if amounts:
139
+ prompt += f"The amounts in the sheet are: {', '.join(str(amount) for amount in amounts)}. "
140
+ prompt += "Based on this information, what would you like to discuss?"
141
+ return prompt
142
 
143
  if __name__ == "__main__":
144
  main()