Update utility.py

utility.py

@@ -106,38 +106,76 @@ def generateResponse(prompt: str) -> str:
     if not model:
         return '{"error": "Model not available"}'
 
-    # --- CHANGE 1: Final, aggressive system prompt ---
+    # --- CORRECTED SYSTEM PROMPT ---
+    # This is the restored, comprehensive prompt that correctly classifies multiple transaction types.
     system_prompt = """
-    Analyze the user's request for business transaction management. Your goal is to extract structured information and output it as a valid JSON list.
-
-    **1. Critical Rule: Is it a Sale or a Service Definition?**
-    This is the most important rule. You must analyze the user's verb.
-    - A **SALE** is a **completed action**. If the user says they **did** something (e.g., "styled a client," "wired a house," "completed a project," "sold"), the `transaction_type` **MUST** be `sale`. You **MUST** also include a `quantity`, defaulting to `1` if not specified.
-    - A **SERVICE OFFERING** is a **statement of capability**. If the user says they **can do** something (e.g., "I offer styling," "add wiring to my services"), the `transaction_type` **MUST** be `service_offering`.
-
-    **2. Key Naming Conventions for `details`:**
-    - **Sales/Inventory:** Use `"item"`, `"quantity"`, and `"price"`.
-    - **Expenses:** Use `"amount"`, `"description"`.
-    - **Assets:** Use `"value"`, `"name"`.
-    - **Liabilities:** Use `"amount"`, `"creditor"`.
-
-    **3. Examples to Learn From:**
-
-    **Example A: Defining a Service (Inventory Update)**
-    - **Input:** "I now offer styling for $120"
-    - **Output:** `[{"intent": "create", "transaction_type": "service_offering", "details": {"item": "styling", "price": 120}}]`
-
-    **Example B: Selling a Service (Sale Event - No Price Mentioned)**
-    - **Input:** "I just styled a client"
-    - **Output:** `[{"intent": "create", "transaction_type": "sale", "details": {"item": "styling", "quantity": 1}}]`
-
-    **Example C: Selling a Service (Sale Event - With Price)**
-    - **Input:** "I wired a house for the new construction project for $2500"
-    - **Output:** `[{"intent": "create", "transaction_type": "sale", "details": {"item": "wiring", "quantity": 1, "price": 2500}}]`
-
-    **Example D: A Simple Query**
-    - **Input:** "what were my sales yesterday?"
-    - **Output:** `[{"intent": "read", "transaction_type": "query", "details": {"query": "what were my sales yesterday?"}}]`
+    Analyze the user's request for business transaction management. Your goal is to extract structured information about one or more transactions and output it as a valid JSON list.
+
+**1. Output Format:**
+You MUST output your response as a valid JSON list `[]` containing one or more transaction objects `{}`.
+
+**2. Transaction Object Structure:**
+Each transaction object MUST have the following keys:
+- `"intent"`: The user's goal (e.g., "create", "read", "update", "delete").
+- `"transaction_type"`: The category of the transaction (e.g., "sale", "purchase", "inventory", "expense", "asset", "liability", "query", "service_offering").
+- `"details"`: An object containing key-value pairs extracted from the request.
+
+**3. Key Naming Conventions for the `details` Object:**
+- **For Expenses:** Use `"amount"`, `"description"`, and `"category"`.
+- **For Assets:** Use `"value"` for the monetary worth and `"name"` for the item's name.
+- **For Liabilities:** Use `"amount"` and `"creditor"`.
+- **For Sales/Inventory:** Use `"item"`, `"quantity"`, and `"price"`.
+- **For all financial transactions:** If a currency symbol or code is present (e.g., $, £, €, ZAR, R), include a `"currency"` key.
+
+**4. Important Rules:**
+- **Rule for Queries:** For "read" intents or general questions, set `transaction_type` to "query" and the `details` object MUST contain a single key `"query"` with the user's full, original question as the value.
+- **Rule for Multiple Items:** If the user's request contains multiple distinct transactions (e.g., recording an expense AND an asset), create a separate JSON object for each one within the main list.
+- **Rule for Expense Normalization:** For "create" intents with `transaction_type` "expense", analyze the `description`. If it contains common keywords, normalize it to a single word. For example, if the description is "paid for fuel for the delivery truck", the normalized `description` in the JSON should be "fuel". If it's "office electricity bill", normalize it to "electricity".
+
+**5. Examples:**
+
+**Example 1: Simple Query**
+- **Input:** "what are my assets?"
+- **Output:**
+  [
+    {
+      "intent": "read",
+      "transaction_type": "query",
+      "details": {
+        "query": "what are my assets?"
+      }
+    }
+  ]
+
+**Example 2: Creating a Normalized Expense**
+- **Input:** "I paid R250 for fuel for work"
+- **Output:**
+  [
+    {
+      "intent": "create",
+      "transaction_type": "expense",
+      "details": {
+        "description": "fuel",
+        "amount": 250,
+        "currency": "R"
+      }
+    }
+  ]
+
+**Example 3: Creating an Asset**
+- **Input:** "just bought a new company laptop for $1500"
+- **Output:**
+  [
+    {
+      "intent": "create",
+      "transaction_type": "asset",
+      "details": {
+        "name": "new company laptop",
+        "value": 1500,
+        "currency": "$"
+      }
+    }
+  ]
     """
     try:
         full_prompt = [system_prompt, prompt]
@@ -180,7 +218,6 @@ def _get_canonical_info(user_phone: str, item_name: str) -> Dict[str, Any]:
     """
     Finds the canonical version of an item using an "exact match first" hybrid approach.
     """
-    # --- CHANGE 2: "Exact Match First" Fuzzy Logic ---
     inventory_ref = db.collection("users").document(user_phone).collection("inventory_and_services")
     name_lower = item_name.lower().strip()
 
@@ -208,7 +245,6 @@ def _get_canonical_info(user_phone: str, item_name: str) -> Dict[str, Any]:
         singular = name_lower
     
     return {'doc': None, 'name': singular}
-    # --- END OF CHANGE 2 ---
 
 
 def create_or_update_inventory_or_service_offering(user_phone: str, transaction_data: List[Dict]) -> tuple[bool, str]:
@@ -305,12 +341,10 @@ def create_sale(user_phone: str, transaction_data: List[Dict]) -> tuple[bool, st
                 elif last_selling_price is not None:
                     selling_price = last_selling_price
                 else:
-                    # For services sold without a price, we can default to 0 or another value
-                    # For goods, we must require a price.
                     if item_type == 'good':
                         return f"Sale failed for new item '{canonical_name}': You must specify a price for the first sale."
                     else:
-                        selling_price = 0 # Default price for services sold without one
+                        selling_price = 0
 
                 if not isinstance(selling_price, (int, float)): selling_price = 0
                 
@@ -555,7 +589,6 @@ def read_datalake(user_phone: str, query: str) -> str:
     """
     Handles queries with contextual pruning, temporal awareness, and robust error handling.
     """
-    # --- CHANGE 3: Definitive Temporal Fix and Conversational Flag ---
     try:
         all_dfs_with_names = _fetch_all_collections_as_dfs(user_phone)
         if not all_dfs_with_names:
@@ -588,7 +621,7 @@ def read_datalake(user_phone: str, query: str) -> str:
         lake = SmartDatalake(datalake_dfs, config={
             "llm": llm, "response_parser": FlaskResponse,
             "save_charts_path": user_defined_path, "enable_cache": False,
-            "conversational": True # Added conversational flag
+            "conversational": True
         })
         
         today_str = datetime.now(timezone.utc).strftime('%Y-%m-%d')