Update app.py

app.py

@@ -9,30 +9,12 @@ import gradio as gr
 # Setup logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 
-# Attempt to import transformers
-try:
-    from transformers import AutoModelForCausalLM, AutoTokenizer
-    TRANSFORMERS_AVAILABLE = True
-except ImportError:
-    logging.warning("Transformers library not found. Using fallback parser.")
-    TRANSFORMERS_AVAILABLE = False
-    AutoModelForCausalLM = None
-    AutoTokenizer = None
-
-# Initialize AI model (t5-small for better accounting parsing; fallback to distilbert)
-model_name = "t5-small"  # Smaller model for free tier
-if TRANSFORMERS_AVAILABLE:
-    try:
-        tokenizer = AutoTokenizer.from_pretrained(model_name)
-        model = AutoModelForCausalLM.from_pretrained(model_name)
-        logging.info(f"Loaded model: {model_name}")
-    except Exception as e:
-        logging.error(f"Failed to load model {model_name}: {e}")
-        tokenizer = None
-        model = None
-else:
-    tokenizer = None
-    model = None
+# Disable model loading on free tier due to memory constraints
+TRANSFORMERS_AVAILABLE = False
+AutoModelForCausalLM = None
+AutoTokenizer = None
+tokenizer = None
+model = None
 
 # Database setup
 conn = sqlite3.connect("erp.db", check_same_thread=False)
@@ -110,6 +92,7 @@ def initialize_chart_of_accounts():
 
 # Enhanced fallback parser
 def parse_prompt(prompt, state):
+    logging.info(f"Parsing prompt: {prompt}")
     if model and tokenizer:
         try:
             input_text = f"""
@@ -124,7 +107,7 @@ def parse_prompt(prompt, state):
             response = tokenizer.decode(outputs[0], skip_special_tokens=True)
             return json.loads(response), state
         except Exception as e:
-            logging.warning(f"Model parsing failed: {e}. Using fallback parser.")
+            logging.error(f"Model parsing failed: {e}")
 
     # Fallback parser
     prompt_lower = prompt.lower().strip()
@@ -167,7 +150,7 @@ def parse_prompt(prompt, state):
     credit_type = None
     payment_method = None
 
-    # Check if this is a follow-up response
+    # Handle follow-up response
     if state.get("pending_prompt"):
         follow_up = prompt_lower
         if follow_up in ["cash", "credit", "bank"]:
@@ -205,15 +188,23 @@ def parse_prompt(prompt, state):
                 elif keyword == "owner's draw":
                     debit_account, debit_type = "Drawings", "Equity"
                     credit_account, credit_type = "Cash", "Asset"
+                elif keyword == "paid":
+                    if "rent" in prompt_lower:
+                        debit_account, debit_type = "Rent Expense", "Expense"
+                    elif "salary" in prompt_lower:
+                        debit_account, debit_type = "Salary Expense", "Expense"
+                    elif "office supplies" in prompt_lower:
+                        debit_account, debit_type = "Office Supplies", "Expense"
+                    credit_account, credit_type = "Cash", "Asset"
                 break
 
-        if "cash" in prompt_lower:
+        if "cash" in prompt_lower and not credit_account:
             credit_account, credit_type = "Cash", "Asset"
             payment_method = "cash"
-        elif "bank" in prompt_lower:
+        elif "bank" in prompt_lower and not credit_account:
             credit_account, credit_type = "Bank", "Asset"
             payment_method = "bank"
-        elif "credit" in prompt_lower:
+        elif "credit" in prompt_lower and not credit_account:
             credit_account, credit_type = "Accounts Payable", "Liability"
             payment_method = "credit"
         elif debit_account and not credit_account:
@@ -233,6 +224,7 @@ def parse_prompt(prompt, state):
 
 # Generate journal entry
 def generate_journal_entry(parsed, state):
+    logging.info(f"Generating journal entry with parsed: {parsed}")
     if "error" in parsed:
         return parsed["error"], state
     if parsed.get("status") == "clarify":
@@ -260,14 +252,18 @@ def generate_journal_entry(parsed, state):
     entry_id = str(uuid.uuid4())
     date = datetime.datetime.now().isoformat()
     description = state.get("pending_prompt", "Transaction")
-    cursor.execute("""
-    INSERT INTO journal_entries (entry_id, date, debit_account_id, credit_account_id, amount, description)
-    VALUES (?, ?, ?, ?, ?, ?)
-    """, (entry_id, date, debit_result[0], credit_result[0], amount, description))
-    conn.commit()
-    logging.info(f"Journal entry created: Debit {debit_account} ${amount}, Credit {credit_account} ${amount}")
+    try:
+        cursor.execute("""
+        INSERT INTO journal_entries (entry_id, date, debit_account_id, credit_account_id, amount, description)
+        VALUES (?, ?, ?, ?, ?, ?)
+        """, (entry_id, date, debit_result[0], credit_result[0], amount, description))
+        conn.commit()
+        logging.info(f"Journal entry created: Debit {debit_account} ${amount}, Credit {credit_account} ${amount}")
+    except sqlite3.Error as e:
+        logging.error(f"Database error: {e}")
+        return "Database error occurred.", state
 
-    return f"Journal Entry Created: Debit {debit_account} ${amount}, Credit {credit_account} ${amount}", {}
+    return f"Journal Entry Created: Debit {debit_account} ${amount}, Credit {credit_account} ${amount}", state
 
 # Generate T-account
 def generate_t_account(account_name):
@@ -309,9 +305,10 @@ def generate_t_account(account_name):
 def chat_function(message, history, state=None):
     if state is None:
         state = {}
+        initialize_chart_of_accounts()
+        logging.info("Initialized state and chart of accounts")
     
-    # Initialize chart of accounts
-    initialize_chart_of_accounts()
+    logging.info(f"Received message: {message}")
     
     # Handle T-account request
     if message.lower().startswith("t-account "):
@@ -324,6 +321,13 @@ def chat_function(message, history, state=None):
     parsed, state = parse_prompt(message, state)
     response, state = generate_journal_entry(parsed, state)
     
+    # Append to history
+    if history is not None:
+        history.append((message, response))
+    else:
+        history = [(message, response)]
+    
+    logging.info(f"Response: {response}")
     return response, state
 
 # Gradio interface
@@ -331,14 +335,14 @@ with gr.Blocks() as demo:
     gr.Markdown("# AI ERP System")
     gr.Markdown("Enter accounting prompts like 'Bought a laptop for $200' or 't-account Laptop'. The system will ask for clarification if needed.")
     chatbot = gr.Chatbot()
-    msg = gr.Textbox(placeholder="Type your prompt here...")
+    msg = gr.Textbox(placeholder="Type your prompt here...", lines=2)
     clear = gr.Button("Clear")
     
     # Maintain state
     state = gr.State({})
     
-    msg.submit(chat_function, [msg, chatbot, state], [chatbot, state])
-    clear.click(lambda: None, None, chatbot, queue=False)
+    msg.submit(chat_function, [msg, chatbot, state], [chatbot, state], _js="() => {return false;}")
+    clear.click(lambda: (None, []), None, [chatbot, state], queue=False)
 
 # Launch Gradio
 if __name__ == "__main__":