def test_persist_and_read_test_story(tmpdir, default_domain):
graph = training.extract_story_graph("data/test_stories/stories.md",
default_domain)
out_path = tmpdir.join("persisted_story.md")
Story(graph.story_steps).dump_to_file(out_path.strpath)
recovered_trackers = training.load_data(
out_path.strpath,
default_domain,
use_story_concatenation=False,
tracker_limit=1000,
remove_duplicates=False
)
existing_trackers = training.load_data(
"data/test_stories/stories.md",
default_domain,
use_story_concatenation=False,
tracker_limit=1000,
remove_duplicates=False
)
existing_stories = {t.export_stories() for t in existing_trackers}
for t in recovered_trackers:
story_str = t.export_stories()
assert story_str in existing_stories
existing_stories.discard(story_str)
def export_stories(self):
from rasa_core.training.structures import StoryStep, Story
story_step = StoryStep()
for event in self._applied_events():
story_step.add_event(event)
story = Story([story_step])
return story.as_story_string(flat=True)
def export_stories(self):
# type: () -> Text
"""Dump the tracker as a story in the Rasa Core story format.
Returns the dumped tracker as a string."""
from rasa_core.training.structures import StoryStep, Story
story_step = StoryStep()
for event in self._applied_events():
story_step.add_event(event)
story = Story([story_step])
return story.as_story_string(flat=True)
def test_persist_and_read_test_story(tmpdir, default_domain):
graph = extract_story_graph_from_file("data/test_stories/stories.md",
default_domain)
out_path = tmpdir.join("persisted_story.md")
Story(graph.story_steps).dump_to_file(out_path.strpath)
recovered_trackers = extract_trackers_from_file(out_path.strpath,
default_domain,
BinaryFeaturizer())
existing_trackers = extract_trackers_from_file(
"data/test_stories/stories.md", default_domain, BinaryFeaturizer())
existing_stories = {t.export_stories() for t in existing_trackers}
for t in recovered_trackers:
story_str = t.export_stories()
assert story_str in existing_stories
existing_stories.discard(story_str)