multiple outputs (map and data)

llm_api.py

@@ -74,7 +74,6 @@ google_api_key = os.getenv("GOOGLE_API_KEY")
 if not google_api_key:
     raise ValueError("GOOGLE_API_KEY not set. Please check your environment variables.")
 
-#TODO: make a format of the address in the prompt to the lm (street, building, city) and phone numbers
 def llm_parser(docs, model="gemini-2.0-flash-001"):
     llm = ChatGoogleGenerativeAI(model=model, temperature=0)
     parser = PydanticOutputParser(pydantic_object=InsuredDetails)
@@ -82,9 +81,38 @@ def llm_parser(docs, model="gemini-2.0-flash-001"):
     prompt = PromptTemplate(
         template="""
     Extract the insured business details from the following documents.
+    Make sure to extract the full address. If the address is spread across multiple lines
+    (e.g., "building number" and "street name" separately),
+    combine them to form a full address in the format: street name, building number, city.
+    The contact phone number format should be: 05xxxxxxxx (ten digits).
     
     {format_instructions}
-    
+
+    ### Examples:
+
+    Text:
+    כתובת מבוטח: 9, טבריה
+    הערות לכתובת המבוטח: תמר 9
+
+    Output:
+    business_name: null
+    business_address: תמר 9, טבריה
+    contact_name: null
+    contact_phone: null
+    ~~~~~~~~~~~~~~~~~~~~
+
+    Text:
+    Acme Corp is based at 123 Main St, Springfield. The contact person is Jane Doe, 055-123-4567.
+
+    Output:
+    business_name: Acme Corp
+    business_address: 123 Main St, Springfield
+    contact_name: Jane Doe
+    contact_phone: 0551234567
+    ~~~~~~~~~~~~~~~~~~~~
+
+    ### Now extract the details for the following document:
+
     Text:
     {input_text}
     """,