fixes for pr

deeppavlov · Dec 25, 2023 · a88a0be · a88a0be
1 parent 9656c40
commit a88a0be
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Showing 2 changed files with 4 additions and 4 deletions.
diff --git a/annotators/speech_function_classifier/models.py b/annotators/speech_function_classifier/models.py
@@ -6,14 +6,14 @@
 
 def check_sfs(predicted_sf, previous_sf, current_speaker, previous_speaker):
     if predicted_sf == "Command":
-        if ("Open" in previous_sf or previous_sf is "") and current_speaker == previous_speaker:
+        if ("Open" in previous_sf or previous_sf == "") and current_speaker == previous_speaker:
             return "Open.Command"
         elif current_speaker == previous_speaker:
             return "Sustain.Continue.Command"
         else:
             return "React.Respond.Command"
     elif predicted_sf == "Engage":
-        if previous_sf is "":
+        if previous_sf == "":
             return "Open.Attend"
         else:
             return "React.Respond.Support.Engage"

diff --git a/response_selectors/ranking_and_sf_based_response_selector/server.py b/response_selectors/ranking_and_sf_based_response_selector/server.py
@@ -102,7 +102,7 @@ def select_response(dialog_context: List[str], hypotheses: List[dict], last_huma
     human_entities = get_entities(last_human_ann_uttr, only_named=False, with_labels=False)
 
     _human_is_switch_topic_request = is_switch_topic(last_human_ann_uttr)
-    _human_is_any_question = is_any_question_sentence_in_utterance(last_human_ann_uttr)
+    # _human_is_any_question = is_any_question_sentence_in_utterance(last_human_ann_uttr)
     # if user utterance contains any question AND requires some intent by socialbot
     _human_wants_to_chat_about_topic = (
         if_chat_about_particular_topic(last_human_ann_uttr) and "about it" not in last_human_ann_uttr["text"].lower()
@@ -123,7 +123,7 @@ def select_response(dialog_context: List[str], hypotheses: List[dict], last_huma
             speech_predictor_hyps = [v["prediction"] for v in speech_predictor]
             speech_predictor_scores = [v["confidence"] for v in speech_predictor]
         except TypeError:
-            logger.error(f"Warning! The speech_predictor_classifier data is either empty or corrupt.")
+            logger.error("Warning! The speech_predictor_classifier data is either empty or corrupt.")
             return
         try:
             speech_index = speech_predictor_hyps.index(speech_annotation)