Merge pull request #19 from RasaHQ/add-tests

- Decided against testing the makefile, since we are not likely to make dramatic changes to the way we parse arguments from the command line.  It would also involve training another model which would increase build time.
- Since this starter pack is made for newcomers, we would like to keep obfuscation low and a `dev-requirements.txt` would hinder this, so no `pycodestyle` testing either

.travis.yml

@@ -0,0 +1,19 @@
+language: python
+sudo: enabled
+cache:
+ directories:
+ - $HOME/.cache/pip
+ - /tmp/cached/
+python:
+- '3.5'
+- '3.6'
+install:
+- pip install -r requirements.txt
+- pip install pytest==3.5.1
+- pip install rasa_nlu --upgrade
+- pip install rasa_core --upgrade
+- pip install rasa_core_sdk --upgrade
+- python -m spacy download en_core_web_md
+- python -m spacy link en_core_web_md en
+script:
+- py.test test_stack.py

actions.py

@@ -19,7 +19,7 @@ def name(self):
 
  def run(self, dispatcher, tracker, domain):
  # what your action should do
- request = json.loads(requests.get('https://api.chucknorris.io/jokes/random').text) #make an apie call
- joke = request['value'] #extract a joke from returned json response
- dispatcher.utter_message(joke) #send the message back to the user
+ request = json.loads(requests.get('https://api.chucknorris.io/jokes/random').text)  # make an api call
+ joke = request['value']  # extract a joke from returned json response
+ dispatcher.utter_message(joke)  # send the message back to the user
  return []

nlu_config.yml

@@ -1,4 +1,3 @@
 language: "en"
 
 pipeline: spacy_sklearn
-

test_stack.py

@@ -0,0 +1,57 @@
+from rasa_core.policies import FallbackPolicy, KerasPolicy, MemoizationPolicy
+from rasa_core.agent import Agent
+
+from rasa_nlu.training_data import load_data
+from rasa_nlu.model import Trainer
+from rasa_nlu import config as nlu_config
+
+from rasa_core import config as core_config
+from rasa_core.trackers import DialogueStateTracker
+from rasa_core.domain import Domain
+from rasa_core.dispatcher import Dispatcher
+from rasa_core.channels import CollectingOutputChannel
+from rasa_core.nlg import TemplatedNaturalLanguageGenerator
+from actions import ActionJoke
+import uuid
+
+
+def test_nlu_interpreter():
+ training_data = load_data("data/nlu_data.md")
+ trainer = Trainer(nlu_config.load("nlu_config.yml"))
+ interpreter = trainer.train(training_data)
+ test_interpreter_dir = trainer.persist("./models/nlu", fixed_model_name="test")
+ parsing = interpreter.parse('hello')
+
+ assert parsing['intent']['name'] == 'greet'
+ assert test_interpreter_dir
+
+
+def test_agent_and_persist():
+ policies = core_config.load('policies.yml')
+ policies[0] = KerasPolicy(epochs=2) # Keep training times low
+
+ agent = Agent('domain.yml', policies=policies)
+ training_data = agent.load_data('data/stories.md')
+ agent.train(training_data, validation_split=0.0)
+ agent.persist('models/dialogue')
+
+ loaded = Agent.load('models/dialogue')
+
+ assert agent.handle_text('/greet') is not None
+ assert loaded.domain.action_names == agent.domain.action_names
+ assert loaded.domain.intents == agent.domain.intents
+ assert loaded.domain.entities == agent.domain.entities
+ assert loaded.domain.templates == agent.domain.templates
+
+
+def test_action():
+ domain = Domain.load('domain.yml')
+ nlg = TemplatedNaturalLanguageGenerator(domain.templates)
+ dispatcher = Dispatcher("my-sender", CollectingOutputChannel(), nlg)
+ uid = str(uuid.uuid1())
+ tracker = DialogueStateTracker(uid, domain.slots)
+
+ action = ActionJoke()
+ action.run(dispatcher, tracker, domain)
+
+ assert dispatcher.output_channel.latest_output() is not None