samirsaci · November 14, 2023 09:02
diff --git a/context_1.py b/context_1.py
 context_explanation = """
 As a supply chain control tower manager, my role involves overseeing the logistics network and ensuring that shipments are processed efficiently and delivered on time. The 'shipments' table in our database is crucial for monitoring these processes. It contains several columns that track the progress and timeliness of each shipment throughout various stages:

 - 'Order_Date' and 'Expected_Loading_Date' provide timestamps for when an order was placed and when it was expected to be loaded for departure.
 - 'Expected_Delivery_Time' is a timpestamp defining when the shipment is expected to be delivered
 - 'Loading_OnTime', 'Airport_OnTime', 'Landing_OnTime', 'Transmission_OnTime' are boolean values indicating whether the shipment was processed on time at various stages. If any of these are False, it implies a delay occurred, potentially causing the shipment to miss its cut-off time and be postponed to the next day.
 - 'Store_Open' indicates if the truck arrived at the store before closing time. A False value here means the delivery must wait until the next day.
 - 'On_Time_Delivery' is a critical indicator of our service level, showing whether a shipment arrived by the requested delivery time.

 Understanding the data in these columns helps us identify bottlenecks in the shipment process and take corrective actions to improve our delivery performance.
 """
 input_question = "How many shipments were delayed in the first seven days of May?"
	context_explanation = """
	As a supply chain control tower manager, my role involves overseeing the logistics network and ensuring that shipments are processed efficiently and delivered on time. The 'shipments' table in our database is crucial for monitoring these processes. It contains several columns that track the progress and timeliness of each shipment throughout various stages:

	- 'Order_Date' and 'Expected_Loading_Date' provide timestamps for when an order was placed and when it was expected to be loaded for departure.
	- 'Expected_Delivery_Time' is a timpestamp defining when the shipment is expected to be delivered
	- 'Loading_OnTime', 'Airport_OnTime', 'Landing_OnTime', 'Transmission_OnTime' are boolean values indicating whether the shipment was processed on time at various stages. If any of these are False, it implies a delay occurred, potentially causing the shipment to miss its cut-off time and be postponed to the next day.
	- 'Store_Open' indicates if the truck arrived at the store before closing time. A False value here means the delivery must wait until the next day.
	- 'On_Time_Delivery' is a critical indicator of our service level, showing whether a shipment arrived by the requested delivery time.

	Understanding the data in these columns helps us identify bottlenecks in the shipment process and take corrective actions to improve our delivery performance.
	"""
	input_question = "How many shipments were delayed in the first seven days of May?"