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:

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.
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

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.

Encountered any issues?

Let us know about it by posting on Rasa Community Forum!