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