Parameterize open_question to allow the user to change the labels `…

…Question` and `Answer`.

PiperOrigin-RevId: 657531076
Change-Id: I90e7f40bf63b51db07a6e4aa0acd61ed28edeb74

concordia/components/agent/v2/concat_act_component.py

@@ -127,6 +127,7 @@ def get_action_attempt(
           # after the end of a directly spoken response, since it normally
           # puts a space after a quotation mark only in these cases.
           terminators=('" ', '\n'),
+          question_label='Exercise',
       )
       self._log(output, prompt)
       return output

concordia/components/agent/v2/legacy_act_component.py

@@ -128,6 +128,7 @@ def get_action_attempt(
           # after the end of a directly spoken response, since it normally
           # puts a space after a quotation mark only in these cases.
           terminators=('" ', '\n'),
+          question_label='Exercise',
       )
       self._log(output, prompt)
       return output

concordia/document/interactive_document.py

@@ -147,6 +147,8 @@ def open_question(
       answer_suffix: str = '',
       max_tokens: int = DEFAULT_MAX_TOKENS,
       terminators: Collection[str] = ('\n',),
+      question_label: str = 'Question',
+      answer_label: str = 'Answer',
   ) -> str:
     """Asks the agent an open question and appends it to the document.
 
@@ -160,12 +162,14 @@ def open_question(
       max_tokens: the maximum number of tokens to sample from the model.
       terminators: strings that must not be present in the model's response. If
         emitted by the model the response will be truncated before them.
+      question_label: the label to use for the question, typically "Question".
+      answer_label: the label to use for the answer, typically "Answer".
 
     Returns:
       The agents truncated response (or `forced_response` is provided).
     """
-    self._question(f'Question: {question}\n')
-    self._response(f'Answer: {answer_prefix}')
+    self._question(f'{question_label}: {question}\n')
+    self._response(f'{answer_label}: {answer_prefix}')
     if forced_response is None:
       response = self._model.sample_text(
           prompt=self._model_view.text(),