Merge branch 'main' into 8569-drop-py36-support

.github/workflows/ci-model-regression-on-schedule.yml

@@ -442,6 +442,7 @@ jobs:
 
           OUTPUT="${OUTPUT//$'\n'/'%0A'}"
           OUTPUT="${OUTPUT//$'\r'/'%0D'}"
+          OUTPUT="$(echo $OUTPUT | sed 's|`|\\`|g')"
           echo "::set-output name=report_description::${OUTPUT}"
 
           IS_DROPPED=false
@@ -493,12 +494,17 @@ jobs:
           # do not use GITHUB_TOKEN here because it wouldn't trigger subsequent workflows
           github-token: ${{ secrets.RASABOT_GITHUB_TOKEN }}
           script: |
+            // Prepare issue body
+            let issue_body = '*This PR is automatically created by the Scheduled Model Regression Test workflow. Checkout the Github Action Run [here](https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}).* <br> --- <br> **Description of Problem:** <br>  Some test performance scores **decreased**. Please look at the following table for more details. <br>'
+            issue_body += `${{ steps.performance.outputs.report_description }}`
+
+            // Open issue
             var issue = await github.issues.create({
               owner: context.repo.owner,
               repo: context.repo.repo,
               title: '${{ env.GITHUB_ISSUE_TITLE }}',
               labels: ${{ env.GITHUB_ISSUE_LABELS }},
-              body: '"*This PR is automatically created by the Scheduled Model Regression Test workflow. Checkout the Github Action Run [here](https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}).* <br> --- <br> **Description of Problem:** <br>  Some test performance scores **decreased**. Please look at the following table for more details. <br> ${{ steps.performance.outputs.report_description }}"'
+              body: issue_body
             })
             return issue.data.number
 

changelog/9193.improvement.md

@@ -0,0 +1 @@
+Added debug message that logs when a response condition is used.

rasa/core/nlg/response.py

@@ -102,7 +102,17 @@ def _random_response_for(
             )
 
             if suitable_responses:
-                return np.random.choice(suitable_responses)
+                selected_response = np.random.choice(suitable_responses)
+                condition = selected_response.get(RESPONSE_CONDITION)
+                if condition:
+                    formatted_response_conditions = self._format_response_conditions(
+                        condition
+                    )
+                    logger.debug(
+                        "Selecting response variation with conditions:"
+                        f"{formatted_response_conditions}"
+                    )
+                return selected_response
             else:
                 return None
         else:
@@ -177,3 +187,18 @@ def _response_variables(
         response_vars = filled_slots.copy()
         response_vars.update(kwargs)
         return response_vars
+
+    @staticmethod
+    def _format_response_conditions(response_conditions: List[Dict[Text, Any]]) -> Text:
+        formatted_response_conditions = [""]
+        for index, condition in enumerate(response_conditions):
+            constraints = []
+            constraints.append(f"type: {str(condition['type'])}")
+            constraints.append(f"name: {str(condition['name'])}")
+            constraints.append(f"value: {str(condition['value'])}")
+
+            condition_message = " | ".join(constraints)
+            formatted_condition = f"[condition {str(index + 1)}] {condition_message}"
+            formatted_response_conditions.append(formatted_condition)
+
+        return "\n".join(formatted_response_conditions)

tests/core/nlg/test_response.py

@@ -1,6 +1,8 @@
 from typing import Text, Any
 
+import logging
 import pytest
+from _pytest.logging import LogCaptureFixture
 
 from rasa.core.nlg.response import TemplatedNaturalLanguageGenerator
 from rasa.shared.core.domain import Domain
@@ -398,3 +400,44 @@ async def test_nlg_conditional_edgecases(slots, channel, expected_response):
     tracker = DialogueStateTracker(sender_id="test", slots=slots)
     r = await t.generate("utter_action", tracker, channel)
     assert r.get("text") == expected_response
+
+
+async def test_nlg_conditional_response_variations_condition_logging(
+    caplog: LogCaptureFixture,
+):
+    domain = Domain.from_yaml(
+        """
+        version: "2.0"
+        responses:
+           utter_action:
+             - text: "example"
+               condition:
+                - type: slot
+                  name: test_A
+                  value: A
+                - type: slot
+                  name: test_B
+                  value: B
+             - text: "default"
+        """
+    )
+    t = TemplatedNaturalLanguageGenerator(domain.responses)
+    slot_A = TextSlot(name="test_A", initial_value="A", influence_conversation=False)
+    slot_B = TextSlot(name="test_B", initial_value="B", influence_conversation=False)
+    tracker = DialogueStateTracker(sender_id="test", slots=[slot_A, slot_B])
+
+    with caplog.at_level(logging.DEBUG):
+        await t.generate("utter_action", tracker=tracker, output_channel="")
+
+    assert any(
+        "Selecting response variation with conditions:" in message
+        for message in caplog.messages
+    )
+    assert any(
+        "[condition 1] type: slot | name: test_A | value: A" in message
+        for message in caplog.messages
+    )
+    assert any(
+        "[condition 2] type: slot | name: test_B | value: B" in message
+        for message in caplog.messages
+    )