corrected annotations

dialogy/plugins/text/dob_plugin/__init__.py

@@ -123,7 +123,8 @@ def get_transcripts_from_utterances(utterances: List[Utterance], func_transcript
     output: 
     best_transcript,
     """
-    result_dict = {}
+    result_dict: Dict[str, float] = {}
+    result: str = ""
     for utterance_set in utterances:
         for utterance in utterance_set:
             transcript = utterance.get('transcript')
@@ -139,7 +140,7 @@ def get_transcripts_from_utterances(utterances: List[Utterance], func_transcript
                 result_dict[result] = confidence
 
     # Sort the result_dict based on confidence in descending order
-    sorted_result = {k: v for k, v in sorted(result_dict.items(), key=lambda item: item[1], reverse=True)}
+    sorted_result: Dict[str, float] = {k: v for k, v in sorted(result_dict.items(), key=lambda item: item[1], reverse=True)}
     transcripts = sorted(sorted_result, key=lambda x: sorted_result[x], reverse=True)
 
     return transcripts
@@ -185,8 +186,7 @@ def __init__(
             **kwargs
         )
 
-    async def utility(self, input: Input, _: Output) -> Any:
-        # return input.best_transcript
+    async def utility(self, input: Input, _: Output) -> List[str]:
         return get_dob(input.utterances)
 
     async def transform(self, training_data: pd.DataFrame) -> pd.DataFrame:

tests/plugin/text/test_dob_plugin/test_dob_plugin.py

@@ -15,12 +15,7 @@
 get_dob = DOBPlugin(
     dest="input.transcripts", use_transform=True, input_column="data"
 )
-"""
-Checker function in test: 
-input: expected, all transcripts
-Description: for each transcript, check if duckling(transcript)==duckling(expected)
-Output: true/false, %increase in correctness
-"""
+
 def checker(transcripts: List[str], expected: str) -> Union[int, None]:
     """
     input: transcripts- a list of strings; expected- a string