Business Logic with Flows
Flows are part of Rasa's new Conversational AI with Language Models (CALM) approach
and available starting with version 3.7.0.
Overview
In CALM, the business logic of your AI assistant is implemented as a set of flows. Each flow describes the logical steps your AI assistant uses to complete a task. It describes the information you need from the user, data you need to retrieve from an API or a database, and branching logic based on the information collected.
A flow in Rasa only describes the logic your assistant follows, not all the potential paths conversations can take. If you're used to designing AI assistants by creating flow charts of how conversations should go, you'll see that flows in Rasa are much simpler. Check out Rasa Studio to build flows with a web interface.
To get familiar with how flows work, follow the tutorial. This page provides a reference of the format and properties of flows.
Hello World
A Flow is defined using YAML syntax. Here is an example of a simple flow:
flows:
  hello_world:
    description: A simple flow that greets the user
    steps:
      - action: utter_greet
Flow Properties
A flow is defined using the following properties:
flows:
  a_flow: # required id
    name: "A flow" # optional name
    description: "required description of what the flow does"
    always_include_in_prompt: false # optional boolean, defaults to false
    run_pattern_completed: true # optional boolean, defaults to true
    if: "condition" # optional flow guard
    nlu_trigger: # optional list of intents that can start a flow
     - intent: "starting_flow_intent"
    persisted_slots: [] # optional list of slots that should be persisted at the conversation level after the flow ends
    steps: [] # required list of steps
Flow ID
The id is required and uniquely identifies the flow among all flows. It allows only alphanumeric characters, underscores, and hyphens, with the restriction that the first character cannot be a hyphen.
Name
The name field is an optional human readable name for the flow.
Description
The description field is a summary of the flow. It is required, and should
describe what the flow does for the user.
Writing a clear description is important, because it is used by the
Dialogue Understanding component to decide when
to start this flow.
See Starting Flows for more details.
Additionally, for guidelines on how to write concise and clear descriptions
see the section provided here.
Always Include in Prompt
If always_include_in_prompt field is set to true and the flow guard
defined in the if field evaluates to true, the flow will be
always be included in the prompt
NLU Trigger property
The nlu_trigger field is used to add intents that can start the flow.
Run Pattern Completed
The run_pattern_completed field is used to determine if the
pattern_completed flow
should be run when the conversation is finished.
This field is only applicable to the parent flows which are not called by other flows.
If property
The if field is used to add flow guards.
Persisted Slots
By default, slots set in a collect and set_slot step are reset when the flow ends.
To change this behavior, you can add these slots to the persisted_slots field.
The persisted_slots field is used to specify a list of slots whose value should be persisted after the flow ends.
These slots have to be filled in either a collect or set_slots step in the flow.
flows:
  transfer_money:
    description: This flow lets users send money to friends and family.
    persisted_slots:
      - recipient
      - amount
    steps:
      - collect: recipient
      - id: ask_amount
        collect: amount
        description: the number of US dollars to send
      - action: action_check_sufficient_funds
        next:
          - if: not has_sufficient_funds
            then:
              - action: utter_insufficient_funds
              - set_slots:
                  - amount: null
                next: ask_amount
          - else: final_confirmation
Validation Rules for persisted_slots property
During training, Rasa implements the following strict validation checks for the persisted_slots property:
- 
The
persisted_slotsproperty cannot be simultaneously used with thereset_after_flow_endsproperty of thecollectstep in a flow.A validation error will be thrown by Rasa during training if both properties are used in a flow. Only one of the two properties can be used in a flow, not both.
 - 
The
persisted_slotsproperty should only contain slots that are filled in either acollectorset_slotsstep in the flow.A validation error will be thrown by Rasa during training if a slot that is not set in a
collectorset_slotsstep is added to thepersisted_slotsproperty.Please note, slots set in custom actions are automatically persistent by default and should not be added to the
persisted_slotsproperty. Attempting to do so will also result in a validation error. 
Steps
The steps field is required and lists the flow steps.
For details please refer to Flow Steps.
Examples
A basic flow with branching
flows:
  basic_flow_with_branching:
    description: a flow with a branch
    steps:
      - action: utter_greet
      - collect: age
        next:
          - if: slots.age < 18
            then: too_young_step
          - else: old_enough_step
      - id: too_young_step
        action: utter_too_young
      - id: old_enough_step
        action: utter_old_enough
The example shows a flow that branches based on the age slot collected from a user message.
Linking multiple flows
flows:
  transfer_money:
    description: Send money to another individual
    steps:
      - collect: recipient_name
      - collect: amount_of_money
      - action: execute_transfer
      - action: utter_transfer_complete
      - link: collect_feedback
  collect_feedback:
    description: Collect feedback from user on their experience talking to the assistant
    steps:
      - collect: ask_rating
      - action: utter_thankyou
This example demonstrates how the link step in flows enables the start of
another flow as a follow-up flow. Specifically, the flow collect_feedback is
initiated as a follow up flow after transfer_money is terminated at the link step.
Embedding a flow inside another flow
Let's assume a financial assistant needs to serve two use cases:
- Transferring money to another individual
 - Adding a new recipient for transferring money
 
It's possible that an end user talking to the assistant wants to initiate a money transfer
to an existing recipient, hence not needing the second use case. However, it is also possible
that the user wants to transfer money to a new recipient in which case both the use cases need
to be combined. This is exactly where a call step lets you accomplish both the
possibilities without needing to create redundant flows. To accomplish the above use cases,
you can leverage the call step in your flows as shown below:
flows:
  collect_recipient_details:
    description: Details of a money transfer recipient should be collected here
    if: False
    steps:
      - collect: recipient_name
        description: Name of a recipient who should be sent money
      - collect: recipient_iban
        description: IBAN of a recipient who should be sent money.
      - collect: recipient_phone_number
        description: Phone number of a recipient who should be sent money.
  add_recipient:
    description: User wants to add a new recipient for transferring money
    steps:
      - call: collect_recipient_details
      - action: add_new_recipient
  transfer_money:
    description: User wants to transfer money to a new or existing recipient
    steps:
      - action: show_existing_recipients
      - collect: need_new_recipient
        next:
          - if: slots.need_new_recipient
            then:
              - call: add_recipient
                next: get_confirmation
          - else:
              - call: collect_recipient_details
                next: get_confirmation
      - id: get_confirmation
        collect: transfer_confirmation
        ask_before_filling: true
      - action: execute_transfer
For the above flow structure, the LLM's prompt would contain the following flow definition:
add_recipient: User wants to add a new recipient to transfer money
    slot: recipient_name (Name of a recipient who should be sent money)
    slot: recipient_iban (IBAN of a recipient who should be sent money)
    slot: recipient_phone_number (Phone number of a recipient who should be sent money)
transfer_money: User wants to transfer money to a new or existing recipient
    slot: need_new_recipient ((True/False))
    slot: recipient_name (Name of a recipient who should be sent money)
    slot: recipient_iban (IBAN of a recipient who should be sent money)
    slot: recipient_phone_number (Phone number of a recipient who should be sent money)
    slot: transfer_confirmation ((True/False))
Each of the above flows are quite self-contained, accomplishing a single purpose and reused effectively to accomplish combinations of multiple use cases in a single conversation. This enhances the modularity and maintainability of flows. Also, note that no slot of a child flow is overlapping with slot of its parent flow in terms of the information they capture. This is important for the command generator's LLM to not get confused at filling such slots.
Optionally ask for information
Imagine a dress shopping AI assistant created to help users find and purchase dresses. This AI assistant includes two types of features: primary features (i.e., dress type, size) and optional features (i.e., color, material, price range, etc.). The assistant should ask for the primary features and avoid asking for the optional features, unless the user specifically requests them. This approach is key to avoid asking too many questions and overwhelming the user.
You can achieve this by setting the ask_before_filling property to false on the collect step and setting an
initial_value for the slot in the domain file.
flows:
  purchase_dress:
    name: purchase dress
    description: present options to the user and purchase the dress
    steps:
      - collect: dress_type
      - collect: dress_size
      - collect: dress_color
        ask_before_filling: false
      - collect: dress_material
        ask_before_filling: false
        next:
          - if: slots.dress_material = "cotton"
            then:
              - action: action_present_cotton_dresses
                next: END
          - if: slots.dress_material = "silk"
            then:
              - action: action_present_silk_dresses
                next: END
          - else:
              - action: action_present_all_dresses
                next: END
slots:
  dress_type:
    type: categorical
    values:
      - "shirt"
      - "pants"
      - "jacket"
  dress_size:
    type: categorical
    values:
      - "small"
      - "medium"
      - "large"
  dress_color:
    type: text
    initial_value: "unspecified"
  dress_material:
    type: categorical
    initial_value: "any"
    values:
      - "cotton"
      - "silk"
      - "polyester"
      - "any"
With ask_before_filling set to false and given that the slots (dress_color and dress_material) already have initial values,
the corresponding collect steps will not be asked. Instead, the assistant will move to the next step.
If the user explicitly provides a value for a slot, this new value will overwrite the initial one.