# Response Selector Bot

This example bot extends the `moodbot` example to show how you can use retrieval actions with Response Selector to
handle single-turn interactions better.

## What’s inside this example?

This example contains some training data and the main files needed to build an
assistant on your local machine.

- **data/nlu.yml** contains training examples for the NLU model
- **data/stories.yml** contains training stories for the Core model
- **data/rules.yml** contains rule based behaviour
- **data/responses.yml** contains the response templates for retrieval intents
- **config.yml** contains the model configuration
- **domain.yml** contains the domain of the assistant
- **credentials.yml** contains credentials for the different channels

## How to use this example?

Using this example you can build an actual assistant and chat with it on
different channels. To do so execute the following steps:

1. Train a Rasa model containing the Rasa NLU and Rasa Core models by running:
    ```
    rasa train
    ```
    The model will be stored in the `/models` directory as a zipped file.

2. Run a Rasa server that connects, for example, to Facebook:
    ```
    rasa run -m models -p 5002 --connector facebook --credentials credentials.yml
    ```
    If you want to connect to a different channel, replace `facebook` with the name of the
    desired channel.
    All available channels are listed in the `credentials.yml` file.
    For more information on the different channels read our
    [documentation](http://x-docs.rasa.com/docs/rasa/messaging-and-voice-channels)

    If you don't want to use any channel, you can chat with your bot
    on the command line, using the following command:
    ```
    rasa shell
    ```

For more information about the individual commands, please check out our
[documentation](http://rasa.com/docs/rasa/command-line-interface).

## Encountered any issues?
Let us know about it by posting on [Rasa Community Forum](https://forum.rasa.com)!
