# Fallback Actions

Sometimes you want to revert to a fallback action, such as replying,  
“Sorry, I didn’t understand that”. You can handle fallback cases by adding  
either the `FallbackPolicy` or the `TwoStageFallbackPolicy` to your  
policy ensemble.

## Fallback Policy

The `FallbackPolicy` has one fallback action, which will  
be executed if the intent recognition has a confidence below `nlu_threshold`  
or if none of the dialogue policies predict an action with  
confidence higher than `core_threshold`.

The thresholds and fallback action can be adjusted in the policy configuration  
file as parameters of the `FallbackPolicy`.

```yaml
policies:
  - name: "FallbackPolicy"
    nlu_threshold: 0.4
    core_threshold: 0.3
    fallback_action_name: "action_default_fallback"
```

`action_default_fallback` is a default action in Rasa Core which sends the  
`utter_default` response to the user. Make sure to specify  
the `utter_default` in your domain file. It will also revert back to the  
state of the conversation before the user message that caused the  
fallback, so that it will not influence the prediction of future actions.  
You can take a look at the source of the action below:

_class_`rasa.core.actions.action.` `ActionDefaultFallback`

Executes the fallback action and goes back to the previous state  
of the dialogue

You can also create your own custom action to use as a fallback (see  
[custom actions](https://legacy-docs-v1.rasa.com/1.10.9/core/actions/#custom-actions) for more info on custom actions). If you  
do, make sure to pass the custom fallback action to `FallbackPolicy` inside  
your policy configuration file. For example:

```yaml
policies:
  - name: "FallbackPolicy"
    nlu_threshold: 0.4
    core_threshold: 0.3
    fallback_action_name: "my_fallback_action"
```

**Note**  
If your custom fallback action does not return a `UserUtteranceReverted` event,  
the next predictions of your bot may become inaccurate, as it is very likely that  
the fallback action is not present in your stories.

If you have a specific intent, let’s say it’s called `out_of_scope`, that  
should always trigger the fallback action, you should add this as a story:

```yaml
## fallback story
* out_of_scope
  - action_default_fallback
```

## Two-stage Fallback Policy

The `TwoStageFallbackPolicy` handles low NLU confidence in multiple stages  
by trying to disambiguate the user input (low core confidence is handled in  
the same manner as the `FallbackPolicy`).

- If a NLU prediction has a low confidence score, the user is asked to affirm  
the classification of the intent. (Default action: `action_default_ask_affirmation`)

- If they affirm, the story continues as if the intent was classified  
  with high confidence from the beginning.
  
  - If they deny, the user is asked to rephrase their message.
  
- Rephrasing (default action: `action_default_ask_rephrase`)

- If the classification of the rephrased intent was confident, the story  
continues as if the user had this intent from the beginning.
  
  - If the rephrased intent was not classified with high confidence, the user  
is asked to affirm the classified intent.

- Second affirmation (default action: `action_default_ask_affirmation`)

- If the user affirms the intent, the story continues as if the user had  
  this intent from the beginning.
  
  - If the user denies, the original intent is classified as the specified  
  `deny_suggestion_intent_name`, and an ultimate fallback action  
  `fallback_nlu_action_name` is triggered (e.g. a handoff to a human).

Rasa Core provides the default implementations of  
`action_default_ask_affirmation` and `action_default_ask_rephrase`.  
The default implementation of `action_default_ask_rephrase` action utters  
the response `utter_ask_rephrase`, so be sure to specify this  
response in your domain file.

You can specify the core fallback action as well as the ultimate NLU  
fallback action as parameters to `TwoStageFallbackPolicy` in your  
policy configuration file.

```yaml
policies:
  - name: TwoStageFallbackPolicy
    nlu_threshold: 0.3
    core_threshold: 0.3
    fallback_core_action_name: "action_default_fallback"
    fallback_nlu_action_name: "action_default_fallback"
    deny_suggestion_intent_name: "out_of_scope"
```