Using Rasa custom actions¶

awesome-project
|- .botfront
|- actions
|- botfront-db
|- models

- User: We want to book a room for 2 adults and 2 kids
- Bot: You are 4 in total and that is an even number

- User: We want to book a room for 2 adults and 2 kids
- Bot: Ok

## faq
* faq OR faq{"intent":"any"}
  - action_faq

## Inform guests 
* inform_guests
  - utter_ok

### 3. Train Core on your story
Open a new tab in your terminal and run `./train_core.sh` from the root project folder.
When Core has restarted after the training (it may take a minute), verify that the story works by typing `/inform_guests`

::: tip
Note that we prefixed the intent with `/`. Since there is no training data for that intent, we can't use natural language yet. The `/` allows us to invoke the intent directly.
:::

The bot should reply with `utter_ok`.

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  <source src="../../../videos/core_simple_story.mp4" type="video/mp4">
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In the next sections we'll make the interaction more natural.

### 4. Add training data to `inform_guests`

Add the following examples to the `inform_guests` intent of your NLU model **and re-train it**:

::: tip Note
We're assuming you still have the training data from the Quick Start guide. If not, make sure you have at least data for 2 intents. You can always add some from the Chit Chat.
:::

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  <source src="../../../videos/nlu_insert_many.mp4" type="video/mp4">
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### 5. Add a bot response and test your bot

Finally, let's create a bot response for the `utter_ok` template we put in the story.

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::: tip
You just created a sequence of messages. The bot will utter 2 messages even if your story only had one action following `* inform_guests`
:::

## Custom Actions

Let's just remind ourselves our end goal:

We need the following changes:
1. Add Duckling to our NLU pipeline to extract the numbers
2. Create a custom action to sum all the numbers found in the utterance and tell if it's an odd or even number.

### 1. Add Duckling to the NLU pipeline

[Duckling](https://github.com/facebook/duckling) is an open source package by Facebook to extract structured entities such as numbers, dates, amounts of money, weights, volumes and so on.

Duckling is integrated in your project as a container (see the `docker-compose.yml` file in the project's root folder).

_Adding Duckling to the NLU pipeline_ means that we are going to use Duckling to extract numbers from user utterances ("2 adults and 2 kids").

::: tip NOTE
`components.botfront.duckling_http_extractor.DucklingHTTPExtractor` provides the same functionality as `ner_http_duckling` and adds the possiblity to append the user `timezone` and `reftime` to the query string for better personalization of the user experience. More in the **Training Data > API** tab.
:::

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  <source src="../../../videos/add_duckling.mp4" type="video/mp4">
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### 2. Create a custom action

Open the `actions/custom_actions/` and add a new file called `my_actions.py` and paste the following content:

```python
import logging
from functools import reduce
from rasa_core_sdk import Action
from rasa_core_sdk.events import SlotSet, ReminderScheduled

logging.basicConfig(level="DEBUG")
logger = logging.getLogger()

class GuestsAction(Action):

    def name(self):
        return 'action_guests'

    def run(self, dispatcher, tracker, domain):
        entities = tracker.latest_message.get('entities', [])

        # Only keep 'number' entities
        numbers = list(filter(lambda e: e.get('entity') == 'number', entities))

        # Stop here if no numbers found
        if not len(numbers):
            dispatcher.utter_message("How many are you?")
            return []

        # Compute the sum of all 'number' entity values
        number_of_guests = reduce(lambda x, y: x + y, map(lambda e:e.get('value'), numbers))

        is_even = number_of_guests % 2 == 0 

        message = 'You are {number_of_guests} in total and that is an {is_even} number'.format(
            number_of_guests=number_of_guests, 
            is_even='even' if is_even else 'odd')

        dispatcher.utter_message(message)
        return []

INFO:rasa_core_sdk.executor:Registered function for 'action_faq'.
INFO:rasa_core_sdk.executor:Registered function for 'action_guests'.

## faq
* faq OR faq{"intent":"any"}
  - action_faq

## Inform guests 
* inform_guests
  - action_guests