def test_core(
model: Optional[Text] = None,
stories: Optional[Text] = None,
endpoints: Optional[Text] = None,
output: Text = DEFAULT_RESULTS_PATH,
model_path: Optional[Text] = None,
kwargs: Optional[Dict] = None,
):
import rasa.core.test
import rasa.core.utils as core_utils
from rasa.nlu import utils as nlu_utils
from rasa.model import get_model
from rasa.core.interpreter import NaturalLanguageInterpreter
from rasa.core.agent import Agent
_endpoints = core_utils.AvailableEndpoints.read_endpoints(endpoints)
if kwargs is None:
kwargs = {}
if output:
nlu_utils.create_dir(output)
if os.path.isfile(model):
model_path = get_model(model)
if model_path:
# Single model: Normal evaluation
loop = asyncio.get_event_loop()
model_path = get_model(model)
core_path, nlu_path = get_model_subdirectories(model_path)
if os.path.exists(core_path) and os.path.exists(nlu_path):
_interpreter = NaturalLanguageInterpreter.create(nlu_path, _endpoints.nlu)
_agent = Agent.load(core_path, interpreter=_interpreter)
kwargs = minimal_kwargs(kwargs, rasa.core.test, ["stories", "agent"])
loop.run_until_complete(
rasa.core.test(stories, _agent, out_directory=output, **kwargs)
)
else:
logger.warning(
"Not able to test. Make sure both models, core and "
"nlu, are available."
)
else:
from rasa.core.test import compare, plot_curve
compare(model, stories, output)
story_n_path = os.path.join(model, "num_stories.json")
number_of_stories = core_utils.read_json_file(story_n_path)
plot_curve(output, number_of_stories)
def test_core(model: Text,
stories: Text,
endpoints: Text = None,
output: Text = DEFAULT_RESULTS_PATH,
model_path: Text = None,
**kwargs: Dict):
import rasa.core.test
import rasa.core.utils as core_utils
from rasa_nlu import utils as nlu_utils
from rasa.model import get_model
from rasa.core.interpreter import NaturalLanguageInterpreter
from rasa.core.agent import Agent
_endpoints = core_utils.AvailableEndpoints.read_endpoints(endpoints)
if output:
nlu_utils.create_dir(output)
if os.path.isfile(model):
model_path = get_model(model)
if model_path:
# Single model: Normal evaluation
loop = asyncio.get_event_loop()
model_path = get_model(model)
core_path, nlu_path = get_model_subdirectories(model_path)
_interpreter = NaturalLanguageInterpreter.create(
nlu_path, _endpoints.nlu)
_agent = Agent.load(core_path, interpreter=_interpreter)
kwargs = minimal_kwargs(kwargs, rasa.core.test)
loop.run_until_complete(
rasa.core.test(stories, _agent, out_directory=output, **kwargs))
else:
from rasa.core.test import compare, plot_curve
compare(model, stories, output)
story_n_path = os.path.join(model, 'num_stories.json')
number_of_stories = core_utils.read_json_file(story_n_path)
plot_curve(output, number_of_stories)
def test_compare_core(models: List[Text], stories: Text, output: Text):
from rasa.core.test import compare, plot_core_results
import rasa.utils.io
model_directory = copy_models_to_compare(models)
loop = asyncio.get_event_loop()
loop.run_until_complete(compare(model_directory, stories, output))
story_n_path = os.path.join(model_directory, "num_stories.json")
number_of_stories = rasa.utils.io.read_json_file(story_n_path)
plot_core_results(output, number_of_stories)
