def test_graph_persistence(default_domain, tmpdir):
from os.path import isfile
from networkx.drawing import nx_pydot
import io
from rasa_core.training.dsl import StoryFileReader
from rasa_core.interpreter import RegexInterpreter
story_steps = StoryFileReader.read_from_file(
"data/test_stories/stories.md",
default_domain,
interpreter=RegexInterpreter())
out_file = tmpdir.join("graph.html").strpath
generated_graph = visualization.visualize_stories(story_steps,
default_domain,
output_file=out_file,
max_history=3,
should_merge_nodes=False)
generated_graph = nx_pydot.to_pydot(generated_graph)
assert isfile(out_file)
with io.open(out_file, 'r') as graph_file:
content = graph_file.read()
assert 'isClient = true' in content
assert "graph = `{}`".format(generated_graph.to_string()) in content
def extract_story_graph_from_file(
filename, # type: Text
domain, # type: Domain
interpreter=RegexInterpreter() # type: NaturalLanguageInterpreter
):
# type: (...) -> StoryGraph
story_steps = StoryFileReader.read_from_file(filename, domain, interpreter)
return StoryGraph(story_steps)
def test_story_visualization_with_merging(default_domain):
story_steps = StoryFileReader.read_from_file(
"data/test_stories/stories.md", default_domain,
interpreter=RegexInterpreter())
generated_graph = visualize_stories(story_steps, default_domain,
output_file=None,
max_history=3,
should_merge_nodes=True)
assert 15 < len(generated_graph.nodes()) < 33
assert 20 < len(generated_graph.edges()) < 33
def test_story_visualization_with_merging(default_domain):
story_steps = StoryFileReader.read_from_file(
"data/test_stories/stories.md", default_domain,
interpreter=RegexInterpreter())
generated_graph = visualize_stories(story_steps, default_domain,
output_file=None,
max_history=3,
should_merge_nodes=True)
assert 15 < len(generated_graph.nodes()) < 33
assert 20 < len(generated_graph.edges()) < 33
def test_story_visualization(default_domain, tmpdir):
story_steps = StoryFileReader.read_from_file(
"data/test_stories/stories.md", default_domain,
interpreter=RegexInterpreter())
out_file = tmpdir.join("graph.html").strpath
generated_graph = visualize_stories(story_steps, default_domain,
output_file=out_file,
max_history=3,
should_merge_nodes=False)
assert len(generated_graph.nodes()) == 51
assert len(generated_graph.edges()) == 56
def test_story_visualization(default_domain, tmpdir):
story_steps = StoryFileReader.read_from_file(
"data/test_stories/stories.md", default_domain,
interpreter=RegexInterpreter())
out_file = tmpdir.join("graph.png").strpath
generated_graph = visualize_stories(story_steps, default_domain,
output_file=out_file,
max_history=3,
should_merge_nodes=False)
assert len(generated_graph.nodes()) == 51
assert len(generated_graph.edges()) == 56
def extract_story_graph(
resource_name, # type: Text
domain, # type: Domain
interpreter=None # type: Optional[NaturalLanguageInterpreter]
):
# type: (...) -> StoryGraph
from rasa_core.interpreter import RegexInterpreter
from rasa_core.training.dsl import StoryFileReader
from rasa_core.training.structures import StoryGraph
if not interpreter:
interpreter = RegexInterpreter()
story_steps = StoryFileReader.read_from_folder(resource_name, domain,
interpreter)
return StoryGraph(story_steps)
def extract_story_graph(
resource_name, # type: Text
domain, # type: Domain
interpreter=None # type: Optional[NaturalLanguageInterpreter]
):
# type: (...) -> StoryGraph
from rasa_core.interpreter import RegexInterpreter
from rasa_core.training.dsl import StoryFileReader
from rasa_core.training.structures import StoryGraph
if not interpreter:
interpreter = RegexInterpreter()
story_steps = StoryFileReader.read_from_folder(resource_name,
domain, interpreter)
return StoryGraph(story_steps)
def visualize(self,
resource_name, # type: Text
output_file, # type: Text
max_history, # type: int
nlu_training_data=None, # type: Optional[Text]
should_merge_nodes=True, # type: bool
fontsize=12 # type: int
):
# type: (...) -> None
from rasa_core.training.visualization import visualize_stories
from rasa_core.training.dsl import StoryFileReader
"""Visualize the loaded training data from the resource."""
story_steps = StoryFileReader.read_from_folder(resource_name,
self.domain)
visualize_stories(story_steps, self.domain, output_file, max_history,
self.interpreter, nlu_training_data,
should_merge_nodes, fontsize)
def visualize(self,
resource_name, # type: Text
output_file, # type: Text
max_history, # type: int
nlu_training_data=None, # type: Optional[Text]
should_merge_nodes=True, # type: bool
fontsize=12 # type: int
):
# type: (...) -> None
from rasa_core.training.visualization import visualize_stories
from rasa_core.training.dsl import StoryFileReader
"""Visualize the loaded training data from the resource."""
story_steps = StoryFileReader.read_from_folder(resource_name,
self.domain)
visualize_stories(story_steps, self.domain, output_file, max_history,
self.interpreter, nlu_training_data,
should_merge_nodes, fontsize)
def extract_story_graph(
resource_name: Text,
domain: 'Domain',
interpreter: Optional['NaturalLanguageInterpreter'] = None,
use_e2e: bool = False,
exclusion_percentage: int = None
) -> 'StoryGraph':
from rasa_core.interpreter import RegexInterpreter
from rasa_core.training.dsl import StoryFileReader
from rasa_core.training.structures import StoryGraph
if not interpreter:
interpreter = RegexInterpreter()
story_steps = StoryFileReader.read_from_folder(
resource_name,
domain, interpreter,
use_e2e=use_e2e,
exclusion_percentage=exclusion_percentage)
return StoryGraph(story_steps)
def visualize(self,
resource_name: Text,
output_file: Text,
max_history: Optional[int] = None,
nlu_training_data: Optional[Text] = None,
should_merge_nodes: bool = True,
fontsize: int = 12) -> None:
from rasa_core.training.visualization import visualize_stories
from rasa_core.training.dsl import StoryFileReader
"""Visualize the loaded training data from the resource."""
# if the user doesn't provide a max history, we will use the
# largest value from any policy
max_history = max_history or self._max_history()
story_steps = StoryFileReader.read_from_folder(resource_name,
self.domain)
visualize_stories(story_steps, self.domain, output_file, max_history,
self.interpreter, nlu_training_data,
should_merge_nodes, fontsize)
def extract_story_graph(
resource_name, # type: Text
domain, # type: Domain
interpreter=None, # type: Optional[NaturalLanguageInterpreter]
use_e2e=False, # type: bool
exclusion_percentage=None # type: int
):
# type: (...) -> StoryGraph
from rasa_core.interpreter import RegexInterpreter
from rasa_core.training.dsl import StoryFileReader
from rasa_core.training.structures import StoryGraph
if not interpreter:
interpreter = RegexInterpreter()
story_steps = StoryFileReader.read_from_folder(
resource_name,
domain,
interpreter,
use_e2e=use_e2e,
exclusion_percentage=exclusion_percentage)
return StoryGraph(story_steps)
def get_no_of_stories(stories, domain):
"""Get number of stories in a file."""
no_stories = len(
StoryFileReader.read_from_folder(stories, TemplateDomain.load(domain)))
return no_stories
