Update app.py

app.py

@@ -17,8 +17,11 @@ from langchain_core.messages import HumanMessage
 from langchain_openai import ChatOpenAI
 import base64
 from utils.mongoDB import MongoDBConnector
+from dags.utils.azure_blob import AzureBlob
 
 mongo = MongoDBConnector(os.getenv("mongo_db_conn"))
+azure_blob = AzureBlob(Variable.get("azure_blob_conn"))
+ab = azure_blob
 
 os.environ["AZURE_OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")
 os.environ["AZURE_OPENAI_API_VERSION"] = "2023-06-01-preview"
@@ -35,63 +38,65 @@ model = AzureChatOpenAI(
 
 def choose_table(question):
     try:
-        connection_string = f'postgresql+psycopg2://{db_user}:{db_password}@{db_host}/{db_name}'
-        engine = create_engine(connection_string)
-        capsuite_ref = 'foodBeverageSample1'
+        str_client_name = 'foodBeverageSample1'
+        df_data = pd.read_parquet(ab.get_latest_parquet('landing', str_client_name, 'sale', 'sol_'))
+        # connection_string = f'postgresql+psycopg2://{db_user}:{db_password}@{db_host}/{db_name}'
+        # engine = create_engine(connection_string)
+        # capsuite_ref = 'foodBeverageSample1'
 
 
-        model = AzureChatOpenAI(
-            deployment_name="CapSuiteGPT4omini",
-            openai_api_version=os.getenv("AZURE_OPENAI_API_VERSION"),
-        )
+        # model = AzureChatOpenAI(
+        #     deployment_name="CapSuiteGPT4omini",
+        #     openai_api_version=os.getenv("AZURE_OPENAI_API_VERSION"),
+        # )
         
-        table_format = """
-                1.table name:cdp_sale_order,
-                its columns:trxn_id,member_id,staff_id,subsidiary_name,staff_name,team_name,trxn_ref,trxn_channel,trxn_date,trxn_year,trxn_month,trxn_day,trxn_week,remark.
+        # table_format = """
+        #         1.table name:cdp_sale_order,
+        #         its columns:trxn_id,member_id,staff_id,subsidiary_name,staff_name,team_name,trxn_ref,trxn_channel,trxn_date,trxn_year,trxn_month,trxn_day,trxn_week,remark.
                 
-                2.table name:cdp_sale_order_line,
-                its columns:trxn_item_id,trxn_id,trxn_item_target_curr_unit_price,
-                trxn_item_qty,trxn_item_discount_amt,trxn_original_net_currency,trxn_date,trxn_channel,staff_name,staff_id,member_id,display_name,pord_sku,prod_category,prod_type,prod_name,
-                capsuite_ref.
+        #         2.table name:cdp_sale_order_line,
+        #         its columns:trxn_item_id,trxn_id,trxn_item_target_curr_unit_price,
+        #         trxn_item_qty,trxn_item_discount_amt,trxn_original_net_currency,trxn_date,trxn_channel,staff_name,staff_id,member_id,display_name,pord_sku,prod_category,prod_type,prod_name,
+        #         capsuite_ref.
                 
-                3.table name:cdp_stock_quant,
-                its columns:stock_quant_id,prod_id,location_id,stock_quantity,stock_quantity_reserved,stock_quant_create_date,capsuite_ref.
-                """
-
-        prompt = ChatPromptTemplate.from_template("Base on the question:{question},"
-                                                "And the following table format:{table_format},"
-                                                "Dont write a complex query. Only select statement like 'select * from table_name'."
-                                                "Dont add any condition or filter to the query. The query should be generic and should return all the data from the table."
-                                                "Select all the columns from the table. "
-                                                "Only output one SQL Query without any other information even the '''sql''' prefix. ")
-
-        chain = (
-                {"question": RunnablePassthrough(), "table_format": RunnablePassthrough()}
-                # {"table_format": RunnablePassthrough()}
-                | prompt
-                | model
-                | StrOutputParser()
-        )
-        # query = 'select * from cdp_membership_summary;'
-        query = chain.invoke({"question": question, "table_format": table_format})
-        query = query.replace(f"`", '')
-        query = query.replace(f"sql", '')
-        query = query.split(';')[0] + f' where capsuite_ref = \'{capsuite_ref}\';'
-        df_data = pd.read_sql(query, engine)
-        print(f'*'*50)
-        print(f"Query: {query}")
-
-        if 'cdp_sale_order_line' in query:
-            df_data['sales_amount'] = df_data['trxn_item_target_curr_unit_price'].astype(float) * df_data['trxn_item_qty'].astype(float)
-            df_data.rename(columns={'trxn_item_target_curr_unit_price':'unit_price'}, inplace=True)
-            df_data.rename(columns={'display_name':'customer_name'}, inplace=True)
-            df_data = df_data[['trxn_item_id','trxn_id','sales_amount','unit_price','trxn_item_qty','trxn_item_discount_amt','trxn_date','trxn_channel','staff_name','customer_name','prod_category','prod_type','prod_name','capsuite_ref']]
+        #         3.table name:cdp_stock_quant,
+        #         its columns:stock_quant_id,prod_id,location_id,stock_quantity,stock_quantity_reserved,stock_quant_create_date,capsuite_ref.
+        #         """
+
+        # prompt = ChatPromptTemplate.from_template("Base on the question:{question},"
+        #                                         "And the following table format:{table_format},"
+        #                                         "Dont write a complex query. Only select statement like 'select * from table_name'."
+        #                                         "Dont add any condition or filter to the query. The query should be generic and should return all the data from the table."
+        #                                         "Select all the columns from the table. "
+        #                                         "Only output one SQL Query without any other information even the '''sql''' prefix. ")
+
+        # chain = (
+        #         {"question": RunnablePassthrough(), "table_format": RunnablePassthrough()}
+        #         # {"table_format": RunnablePassthrough()}
+        #         | prompt
+        #         | model
+        #         | StrOutputParser()
+        # )
+        # # query = 'select * from cdp_membership_summary;'
+        # query = chain.invoke({"question": question, "table_format": table_format})
+        # query = query.replace(f"`", '')
+        # query = query.replace(f"sql", '')
+        # query = query.split(';')[0] + f' where capsuite_ref = \'{capsuite_ref}\';'
+        # df_data = pd.read_sql(query, engine)
+        # print(f'*'*50)
+        # print(f"Query: {query}")
+
+        # if 'cdp_sale_order_line' in query:
+        df_data['sales_amount'] = df_data['trxn_item_target_curr_unit_price'].astype(float) * df_data['trxn_item_qty'].astype(float)
+        df_data.rename(columns={'trxn_item_target_curr_unit_price':'unit_price'}, inplace=True)
+        df_data.rename(columns={'display_name':'customer_name'}, inplace=True)
+        df_data = df_data[['trxn_item_id','trxn_id','sales_amount','unit_price','trxn_item_qty','trxn_item_discount_amt','trxn_date','trxn_channel','staff_name','customer_name','prod_category','prod_type','prod_name','capsuite_ref']]
         
     except Exception as e:
         print(f"Error while: {e}")
 
     finally:
-        engine.dispose()
+        # engine.dispose()
         return df_data