Update app.py
Browse files
app.py
CHANGED
@@ -4,6 +4,7 @@ import uuid
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import datetime
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import logging
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import re
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# Setup logging
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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@@ -18,8 +19,8 @@ except ImportError:
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AutoModelForCausalLM = None
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AutoTokenizer = None
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# Initialize AI model (
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model_name = "
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if TRANSFORMERS_AVAILABLE:
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try:
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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@@ -34,7 +35,7 @@ else:
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model = None
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# Database setup
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conn = sqlite3.connect("erp.db")
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cursor = conn.cursor()
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# Create tables
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@@ -85,6 +86,7 @@ def initialize_chart_of_accounts():
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("1.2.2", "Laptop", "Asset", "1.2", True, True),
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("1.2.3", "Inventory", "Asset", "1.2", True, True),
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("1.2.4", "Accounts Receivable", "Asset", "1.2", True, True),
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("2", "Liabilities", "Liability", None, True, False),
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("2.1", "Accounts Payable", "Liability", "2", True, True),
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("2.2", "Loan Payable", "Liability", "2", True, True),
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@@ -107,40 +109,37 @@ def initialize_chart_of_accounts():
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logging.info("Chart of accounts initialized.")
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# Enhanced fallback parser
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def parse_prompt(prompt):
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if model and tokenizer:
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try:
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input_text = f"""
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Parse the following accounting prompt into a JSON object with:
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- debit: {{account, type, amount}}
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- credit: {{account, type, amount}}
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-
- payment_method: 'cash', 'credit', or null
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Prompt: {prompt}
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"""
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inputs = tokenizer(input_text, return_tensors="pt")
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outputs = model.generate(**inputs, max_length=300)
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response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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return json.loads(response)
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except Exception as e:
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logging.warning(f"Model parsing failed: {e}. Using fallback parser.")
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# Fallback parser
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prompt_lower = prompt.lower().strip()
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amount = None
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# Extract amount
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match = re.search(r'\$[\d,.]+', prompt_lower)
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if match:
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try:
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amount = float(match.group().replace('$', '').replace(',', ''))
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except ValueError:
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return None
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if not amount:
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return None
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#
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account_mappings = {
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"laptop": ("Laptop", "Asset"),
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"inventory": ("Inventory", "Asset"),
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@@ -149,14 +148,17 @@ def parse_prompt(prompt):
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"plant": ("Plant", "Asset"),
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"office supplies": ("Office Supplies", "Expense"),
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"cash": ("Cash", "Asset"),
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"receivable": ("Accounts Receivable", "Asset"),
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"sold goods": ("Sales Revenue", "Revenue"),
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"sales": ("Sales Revenue", "Revenue"),
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"rent": ("Rent Expense", "Expense"),
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"salary": ("Salary Expense", "Expense"),
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"paid": ("Cash", "Asset"),
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"bought": ("Laptop", "Asset"),
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"purchased": ("Laptop", "Asset")
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}
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debit_account = None
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@@ -165,75 +167,81 @@ def parse_prompt(prompt):
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credit_type = None
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payment_method = None
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#
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debit_account, debit_type = account, acc_type
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if debit_account and credit_account:
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return {
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"debit": {"account": debit_account, "type": debit_type, "amount": amount},
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"credit": {"account": credit_account, "type": credit_type, "amount": amount},
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"payment_method": payment_method
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}
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return None
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# Generate journal entry
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def generate_journal_entry(
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debit_account = parsed["debit"]["account"]
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amount = parsed["debit"]["amount"]
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# Handle ambiguous payment method
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if not payment_method and not follow_up_response:
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return {"status": "clarify", "message": "Was this bought on cash or credit? (cash/credit)", "original_prompt": prompt}
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# Determine credit account
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credit_account = None
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credit_type = None
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if follow_up_response:
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follow_up_lower = follow_up_response.lower()
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if follow_up_lower == "cash":
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credit_account, credit_type = "Cash", "Asset"
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elif follow_up_lower == "credit":
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credit_account, credit_type = "Accounts Payable", "Liability"
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else:
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return "Invalid response. Please specify 'cash' or 'credit'."
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elif payment_method == "cash":
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credit_account, credit_type = parsed["credit"]["account"], parsed["credit"]["type"]
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elif payment_method == "credit":
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credit_account, credit_type = "Accounts Payable", "Liability"
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else:
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return "Invalid payment method specified."
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# Validate accounts
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cursor.execute("SELECT account_id, account_type, allow_posting FROM chart_of_accounts WHERE account_name = ?", (debit_account,))
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credit_result = cursor.fetchone()
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if not debit_result or not credit_result:
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return "One or both accounts not found
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if not debit_result[2] or not credit_result[2]:
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return "Posting not allowed for one or both accounts."
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# Validate account types
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if debit_result[1] != parsed["debit"]["type"] or credit_result[1] != credit_type:
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return "Account type mismatch."
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# Create journal entry
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entry_id = str(uuid.uuid4())
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date = datetime.datetime.now().isoformat()
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cursor.execute("""
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INSERT INTO journal_entries (entry_id, date, debit_account_id, credit_account_id, amount, description)
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VALUES (?, ?, ?, ?, ?, ?)
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""", (entry_id, date, debit_result[0], credit_result[0], amount,
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conn.commit()
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logging.info(f"Journal entry created: Debit {debit_account} ${amount}, Credit {credit_account} ${amount}")
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return f"Journal Entry Created: Debit {debit_account} ${amount}, Credit {credit_account} ${amount}"
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# Generate T-account
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def generate_t_account(account_name):
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return t_account
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#
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def
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initialize_chart_of_accounts()
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print("AI ERP System: Enter accounting prompts or 't-account <account_name>' to view T-accounts. Type 'exit' to quit.")
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pending_prompt = result["original_prompt"]
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else:
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print(result)
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except KeyboardInterrupt:
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print("\nExiting...")
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break
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except Exception as e:
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logging.error(f"Error processing prompt: {e}")
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print("An error occurred. Please try again.")
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if __name__ == "__main__":
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import datetime
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import logging
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import re
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import gradio as gr
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# Setup logging
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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AutoModelForCausalLM = None
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AutoTokenizer = None
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# Initialize AI model (t5-small for better accounting parsing; fallback to distilbert)
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model_name = "t5-small" # Smaller model for free tier
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if TRANSFORMERS_AVAILABLE:
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try:
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = None
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# Database setup
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conn = sqlite3.connect("erp.db", check_same_thread=False)
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cursor = conn.cursor()
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# Create tables
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("1.2.2", "Laptop", "Asset", "1.2", True, True),
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("1.2.3", "Inventory", "Asset", "1.2", True, True),
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("1.2.4", "Accounts Receivable", "Asset", "1.2", True, True),
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("1.2.5", "Bank", "Asset", "1.2", True, True),
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("2", "Liabilities", "Liability", None, True, False),
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("2.1", "Accounts Payable", "Liability", "2", True, True),
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("2.2", "Loan Payable", "Liability", "2", True, True),
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logging.info("Chart of accounts initialized.")
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# Enhanced fallback parser
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def parse_prompt(prompt, state):
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if model and tokenizer:
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try:
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input_text = f"""
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Parse the following accounting prompt into a JSON object with:
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- debit: {{account, type, amount}}
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- credit: {{account, type, amount}}
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- payment_method: 'cash', 'credit', 'bank', or null
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Prompt: {prompt}
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"""
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inputs = tokenizer(input_text, return_tensors="pt")
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outputs = model.generate(**inputs, max_length=300)
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response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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return json.loads(response), state
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except Exception as e:
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logging.warning(f"Model parsing failed: {e}. Using fallback parser.")
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# Fallback parser
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prompt_lower = prompt.lower().strip()
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amount = None
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match = re.search(r'\$[\d,.]+', prompt_lower)
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if match:
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try:
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amount = float(match.group().replace('$', '').replace(',', ''))
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except ValueError:
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return {"error": "Invalid amount format."}, state
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if not amount:
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return {"error": "No amount found in prompt."}, state
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# Account mappings
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account_mappings = {
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"laptop": ("Laptop", "Asset"),
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"inventory": ("Inventory", "Asset"),
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"plant": ("Plant", "Asset"),
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"office supplies": ("Office Supplies", "Expense"),
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"cash": ("Cash", "Asset"),
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"bank": ("Bank", "Asset"),
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"receivable": ("Accounts Receivable", "Asset"),
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"sold goods": ("Sales Revenue", "Revenue"),
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"sales": ("Sales Revenue", "Revenue"),
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"rent": ("Rent Expense", "Expense"),
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"salary": ("Salary Expense", "Expense"),
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"paid": ("Cash", "Asset"),
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"bought": ("Laptop", "Asset"),
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"purchased": ("Laptop", "Asset"),
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"owner's draw": ("Drawings", "Equity"),
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"loan": ("Loan Payable", "Liability")
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}
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debit_account = None
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credit_type = None
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payment_method = None
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# Check if this is a follow-up response
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if state.get("pending_prompt"):
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follow_up = prompt_lower
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if follow_up in ["cash", "credit", "bank"]:
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payment_method = follow_up
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parsed = state["pending_parsed"]
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debit_account = parsed["debit"]["account"]
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debit_type = parsed["debit"]["type"]
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amount = parsed["debit"]["amount"]
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if payment_method == "cash":
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credit_account, credit_type = "Cash", "Asset"
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elif payment_method == "bank":
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credit_account, credit_type = "Bank", "Asset"
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elif payment_method == "credit":
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credit_account, credit_type = "Accounts Payable", "Liability"
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state = {} # Clear state
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else:
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return {"error": "Please respond with 'cash', 'credit', or 'bank'."}, state
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else:
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# Parse new prompt
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for keyword, (account, acc_type) in account_mappings.items():
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if keyword in prompt_lower:
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if keyword in ["bought", "purchased"]:
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for asset in ["laptop", "inventory", "machinery", "building", "plant", "office supplies"]:
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if asset in prompt_lower:
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debit_account, debit_type = account_mappings[asset]
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break
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if not debit_account:
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debit_account, debit_type = account, acc_type
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elif keyword in ["rent", "salary", "office supplies"]:
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debit_account, debit_type = account, acc_type
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elif keyword in ["sold goods", "sales"]:
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debit_account, debit_type = "Accounts Receivable", "Asset"
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credit_account, credit_type = account, acc_type
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elif keyword == "owner's draw":
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debit_account, debit_type = "Drawings", "Equity"
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credit_account, credit_type = "Cash", "Asset"
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break
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if "cash" in prompt_lower:
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credit_account, credit_type = "Cash", "Asset"
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payment_method = "cash"
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elif "bank" in prompt_lower:
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credit_account, credit_type = "Bank", "Asset"
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payment_method = "bank"
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elif "credit" in prompt_lower:
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credit_account, credit_type = "Accounts Payable", "Liability"
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payment_method = "credit"
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elif debit_account and not credit_account:
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return {
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"status": "clarify",
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"message": "Was this bought on cash, credit, or bank?",
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"pending_parsed": {"debit": {"account": debit_account, "type": debit_type, "amount": amount}}
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}, {"pending_prompt": prompt, "pending_parsed": {"debit": {"account": debit_account, "type": debit_type, "amount": amount}}}
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if debit_account and credit_account:
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return {
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"debit": {"account": debit_account, "type": debit_type, "amount": amount},
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"credit": {"account": credit_account, "type": credit_type, "amount": amount},
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"payment_method": payment_method
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}, state
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return {"error": "Prompt not recognized. Try 'Bought a laptop for $200' or 'Paid rent $400'."}, state
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# Generate journal entry
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def generate_journal_entry(parsed, state):
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if "error" in parsed:
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return parsed["error"], state
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if parsed.get("status") == "clarify":
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return parsed["message"], state
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debit_account = parsed["debit"]["account"]
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amount = parsed["debit"]["amount"]
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credit_account = parsed["credit"]["account"]
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credit_type = parsed["credit"]["type"]
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# Validate accounts
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cursor.execute("SELECT account_id, account_type, allow_posting FROM chart_of_accounts WHERE account_name = ?", (debit_account,))
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credit_result = cursor.fetchone()
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if not debit_result or not credit_result:
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return "One or both accounts not found.", state
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if not debit_result[2] or not credit_result[2]:
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return "Posting not allowed for one or both accounts.", state
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if debit_result[1] != parsed["debit"]["type"] or credit_result[1] != credit_type:
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return "Account type mismatch.", state
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# Create journal entry
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entry_id = str(uuid.uuid4())
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date = datetime.datetime.now().isoformat()
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description = state.get("pending_prompt", "Transaction")
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cursor.execute("""
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INSERT INTO journal_entries (entry_id, date, debit_account_id, credit_account_id, amount, description)
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VALUES (?, ?, ?, ?, ?, ?)
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""", (entry_id, date, debit_result[0], credit_result[0], amount, description))
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conn.commit()
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logging.info(f"Journal entry created: Debit {debit_account} ${amount}, Credit {credit_account} ${amount}")
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return f"Journal Entry Created: Debit {debit_account} ${amount}, Credit {credit_account} ${amount}", {}
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# Generate T-account
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def generate_t_account(account_name):
|
|
|
305 |
|
306 |
return t_account
|
307 |
|
308 |
+
# Gradio chat function
|
309 |
+
def chat_function(message, history, state=None):
|
310 |
+
if state is None:
|
311 |
+
state = {}
|
312 |
+
|
313 |
+
# Initialize chart of accounts
|
314 |
initialize_chart_of_accounts()
|
|
|
315 |
|
316 |
+
# Handle T-account request
|
317 |
+
if message.lower().startswith("t-account "):
|
318 |
+
account_name = message[10:].strip()
|
319 |
+
if account_name:
|
320 |
+
return generate_t_account(account_name), state
|
321 |
+
return "Please specify an account name.", state
|
322 |
+
|
323 |
+
# Parse prompt and generate entry
|
324 |
+
parsed, state = parse_prompt(message, state)
|
325 |
+
response, state = generate_journal_entry(parsed, state)
|
326 |
+
|
327 |
+
return response, state
|
328 |
+
|
329 |
+
# Gradio interface
|
330 |
+
with gr.Blocks() as demo:
|
331 |
+
gr.Markdown("# AI ERP System")
|
332 |
+
gr.Markdown("Enter accounting prompts like 'Bought a laptop for $200' or 't-account Laptop'. The system will ask for clarification if needed.")
|
333 |
+
chatbot = gr.Chatbot()
|
334 |
+
msg = gr.Textbox(placeholder="Type your prompt here...")
|
335 |
+
clear = gr.Button("Clear")
|
336 |
+
|
337 |
+
# Maintain state
|
338 |
+
state = gr.State({})
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
339 |
|
340 |
+
msg.submit(chat_function, [msg, chatbot, state], [chatbot, state])
|
341 |
+
clear.click(lambda: None, None, chatbot, queue=False)
|
342 |
|
343 |
+
# Launch Gradio
|
344 |
if __name__ == "__main__":
|
345 |
+
demo.launch(server_name="0.0.0.0", server_port=7860)
|