This guide will teach you how to extract user-provided values (e.g., a name, a date, a query) from a user utterance and store them in context variables. You can then use these bot responses or follow-up logic.
The general syntax is the following:
# Comment with instructions on how to extract the value.
# Can span multiple lines.
$variable_name = ...
Note: ... is not a placeholder here; it is the actual syntax, i.e., ellipsis.
At any point in a flow, you can include a $variable_name = ..., instructing the LLM to compute the variable's value.
You can extract single values.
user provide name
# Extract the name of the user.
$name = ...
Or, you can also instruct the LLM to extract a list of values.
define flow add to cart
user request add items to cart
# Generate a list of the menu items that the user requested to be added to the cart
# e.g. ["french fries", "double protein burger", "lemonade"].
# If user specifies no menu items, just leave this empty, i.e. [].
$item_list = ...
If you extract the values for multiple variables from the same user input.
define user request book flight
"I want to book a flight."
"I want to fly from Bucharest to San Francisco."
"I want a flight to Paris."
define flow
user request book flight
# Extract the origin from the user's request. If not specified, say "unknown".
$origin_city = ...
# Extract the destination city from the user's request. If not specified, say "unknown".
$destination_city = ...
This mechanism can be applied to enable contextual queries. For example, let's assume you want to answer math questions using Wolfram Alpha and support a flow like the following:
user "What is the largest prime factor for 1024?"
bot "The largest prime factor is 2."
user "And its square root?"
bot "The square root for 1024 is 32"
To achieve this, you can use the following flow:
define flow
user ask math question
# Extract the math question from the user's input.
$math_query = ...
execute wolfram alpha request(query=$math_query)
bot respond to math question