AUTO docusaurus 20230808

docs/docs/sources/rasa_interactive___help.txt

@@ -39,7 +39,7 @@ options:
   --conversation-id CONVERSATION_ID
                         Specify the id of the conversation the messages are
                         in. Defaults to a UUID that will be randomly
-                        generated. (default: de04d0f298734aeabe093213937197d3)
+                        generated. (default: d1e32dd965814ad3be8eb506bf4e281c)
   --endpoints ENDPOINTS
                         Configuration file for the model server and the
                         connectors as a yml file. (default: endpoints.yml)

docs/docs/sources/rasa_shell___help.txt

@@ -30,7 +30,7 @@ options:
   -h, --help            show this help message and exit
   --conversation-id CONVERSATION_ID
                         Set the conversation ID. (default:
-                        1fdbcdaf73d348a7aea93a95065c1262)
+                        2e227e84f7224337975b25bbe79bd32a)
   -m MODEL, --model MODEL
                         Path to a trained Rasa model. If a directory is
                         specified, it will use the latest model in this

rasa/shared/core/training_data/visualization.py

@@ -533,17 +533,17 @@ def _remove_auxiliary_nodes(
 
     graph.remove_node(TMP_NODE_ID)
 
-    if not len(list(graph.predecessors(END_NODE_ID))):
+    if not graph.predecessors(END_NODE_ID):
         graph.remove_node(END_NODE_ID)
 
     # remove duplicated "..." nodes after merging
-    ps = set()
+    predecessors_seen = set()
     for i in range(special_node_idx + 1, TMP_NODE_ID):
-        for pred in list(graph.predecessors(i)):
-            if pred in ps:
+        predecessors = graph.predecessors(i)
+        for pred in predecessors:
+            if pred in predecessors_seen:
                 graph.remove_node(i)
-            else:
-                ps.add(pred)
+        predecessors_seen.update(predecessors)
 
 
 def visualize_stories(

tests/shared/core/training_data/test_visualization.py

@@ -10,6 +10,8 @@
 from rasa.shared.nlu.training_data.message import Message
 from rasa.shared.nlu.training_data.training_data import TrainingData
 
+import pytest
+
 
 def test_style_transfer():
     r = visualization._transfer_style({"class": "dashed great"}, {"class": "myclass"})
@@ -188,3 +190,42 @@ def test_story_visualization_with_merging(domain: Domain):
     assert 15 < len(generated_graph.nodes()) < 33
 
     assert 20 < len(generated_graph.edges()) < 33
+
+
+@pytest.mark.parametrize(
+    "input_nodes, input_edges, remove_count, expected_nodes, expected_edges",
+    [
+        (
+            [-2, -1, 0, 1, 2, 3, 4, 5],
+            [(-2, 0), (-1, 0), (0, 1), (1, 2), (2, 3), (3, 4), (4, 5)],
+            3,
+            set([0, 1, 2, 3, 4, 5, -1]),
+            [(-1, 0), (0, 1), (1, 2), (2, 3), (3, 4), (4, 5)],
+        ),
+        (
+            [-3, -2, -1, 0, 1, 2, 3, 4, 5],
+            [(-3, -2), (-2, -1), (-1, 0), (0, 1), (1, 2), (2, 3), (3, 4), (4, 5)],
+            4,
+            set([-3, -1, 0, 1, 2, 3, 4, 5]),
+            [(-1, 0), (0, 1), (1, 2), (2, 3), (3, 4), (4, 5)],
+        ),
+    ],
+)
+def test_remove_auxiliary_nodes(
+    input_nodes, input_edges, remove_count, expected_nodes, expected_edges
+):
+    import networkx as nx
+
+    # Create a sample graph
+    graph = nx.MultiDiGraph()
+    graph.add_nodes_from(input_nodes)
+    graph.add_edges_from(input_edges)
+
+    # Call the method to remove auxiliary nodes
+    visualization._remove_auxiliary_nodes(graph, remove_count)
+
+    # Check if the expected nodes are removed
+    assert set(graph.nodes()) == expected_nodes, "Nodes mismatch"
+
+    # Check if the edges are updated correctly
+    assert list(graph.edges()) == expected_edges, "Edges mismatch"