Using the CLI

cli basics

When you start the cli, you will be greated with something like the following:

>>>

At it’s core the cli is stripped down python interactive interpreter. Similar to if you just ran python on your terminal. There are some notable differences:

• The presence of a msa_api object which is used for interacting with the daemon.
• Some “meta-commands” for the cli that allow special functionality within the cli. This includes recording scripts and saving them.

Intro to meta-commands

Meta-commands are executed within the cli and do not directly touch the daemon.

Available meta commands can be listed by typing # help in the cli e.g.:

>>> # help
MSA Interpreter Help:
 Availiable Commands:
  # help: Show this help text
  # record <file name>: Begin recording commands to a script.
  # record stop: stop recording commands, save the script, and open to review.

Note: the result of this help meta-command is subject to change as meta-commands are added or removed.

See below for an example using meta-commands to record a script interactively and sending it to the daemon to run periodically.

Intro to the msa_api object

When you start the cli a msa_api object is inserted into scope to facilitate interaction with the daemon process. The msa_api object can be used to interface with the daemon process.

Basic usage

Below you can find a list of methods available on msa_api.

The methods marked async below need to be prefixed with await. For example:

>>> await msa_api.talk("hello")

Recording and uploading scripts

One of the meta-commands available in the cli is the # record command.

As in the following example, it is possible to record an commands and save them as a script which can then be uploaded to the daemon.

$ moe-serifu-agent
>>> # record test.py                                                                                                                                                                                                                  
>>> await msa_api.talk("Hello, how are you?")                                                                                                                                     
I am well thank you. What can I do for you?
>>> await msa_api.talk("Please turn on the livingroom light")
I am afraid I don't know what to say.
>>> # record stop                                                                                                                                                                                                                     
Opening test.py

Now if we ls the current directory, we should see a new file test.py has been created, containing the following:

await msa_api.talk("Hello, how are you?")
await msa_api.talk("Please turn on the livingroom light.")

We can also upload the script to the daemon and schedule it to run every so often.

>>> await msa_api.upload_script("demo_script", crontab="* * * * *", file_name="test.py")
demo_script was sucessfully uploaded

The test script we uploaded should run once every minute. Unfortunately this is not very useful as we cannot see the conversation response from MSA because the daemon doesn’t know where to send the response. Future tutorials will walk through some more interesting uses for uploaded scripts such as triggering events.

One final note on uploading scripts is that they are saved to MSA’s database and are reloaded at startup.

msa_api Reference

class msa_api

check_connection(self)

Raises an exception if the cli cannot contact the daemon.

Async: Returns:None

check_version(self, quiet=False)

Called automatically at startup, ensures that the cli version and the daemon versions match.

Async: Parameters:quiet (bool) – Print’s the response of True. Returns:None

get_version(self)

Fetches the daemon’s version.

Async: Returns:None

ping(self, quiet=False)

Send’s a ping to the daemon. If the ping succeeds, you should see a pong response.

Async: Parameters:quiet (bool) – Print’s the response of True. Returns:None