Add class attribute "return_generated_question" to class "BaseConversationalRetrievalChain" (#5749)

<!--
Thank you for contributing to LangChain! Your PR will appear in our
release under the title you set. Please make sure it highlights your
valuable contribution.

Replace this with a description of the change, the issue it fixes (if
applicable), and relevant context. List any dependencies required for
this change.

After you're done, someone will review your PR. They may suggest
improvements. If no one reviews your PR within a few days, feel free to
@-mention the same people again, as notifications can get lost.

Finally, we'd love to show appreciation for your contribution - if you'd
like us to shout you out on Twitter, please also include your handle!
-->

Adding a class attribute "return_generated_question" to class
"BaseConversationalRetrievalChain". If set to `True`, the chain's output
has a key "generated_question" with the question generated by the
sub-chain `question_generator` as the value. This way the generated
question can be logged.

<!-- If you're adding a new integration, please include:

1. a test for the integration - favor unit tests that does not rely on
network access.
2. an example notebook showing its use


See contribution guidelines for more information on how to write tests,
lint
etc:


https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md
-->

#### Who can review?

<!-- For a quicker response, figure out the right person to tag with @

  @hwchase17 - project lead

  Tracing / Callbacks
  - @agola11

  Async
  - @agola11

  DataLoaders
  - @eyurtsev

  Models
  - @hwchase17
  - @agola11

  Agents / Tools / Toolkits
  - @vowelparrot

  VectorStores / Retrievers / Memory
  - @dev2049

 -->
@dev2049 @vowelparrot

langchain/chains/conversational_retrieval/base.py

@@ -56,6 +56,7 @@ class BaseConversationalRetrievalChain(Chain):
     question_generator: LLMChain
     output_key: str = "answer"
     return_source_documents: bool = False
+    return_generated_question: bool = False
     get_chat_history: Optional[Callable[[CHAT_TURN_TYPE], str]] = None
     """Return the source documents."""
 
@@ -80,6 +81,8 @@ class BaseConversationalRetrievalChain(Chain):
         _output_keys = [self.output_key]
         if self.return_source_documents:
             _output_keys = _output_keys + ["source_documents"]
+        if self.return_generated_question:
+            _output_keys = _output_keys + ["generated_question"]
         return _output_keys
 
     @abstractmethod
@@ -110,10 +113,12 @@ class BaseConversationalRetrievalChain(Chain):
         answer = self.combine_docs_chain.run(
             input_documents=docs, callbacks=_run_manager.get_child(), **new_inputs
         )
+        output: Dict[str, Any] = {self.output_key: answer}
         if self.return_source_documents:
-            return {self.output_key: answer, "source_documents": docs}
-        else:
-            return {self.output_key: answer}
+            output["source_documents"] = docs
+        if self.return_generated_question:
+            output["generated_question"] = new_question
+        return output
 
     @abstractmethod
     async def _aget_docs(self, question: str, inputs: Dict[str, Any]) -> List[Document]:
@@ -142,10 +147,12 @@ class BaseConversationalRetrievalChain(Chain):
         answer = await self.combine_docs_chain.arun(
             input_documents=docs, callbacks=_run_manager.get_child(), **new_inputs
         )
+        output: Dict[str, Any] = {self.output_key: answer}
         if self.return_source_documents:
-            return {self.output_key: answer, "source_documents": docs}
-        else:
-            return {self.output_key: answer}
+            output["source_documents"] = docs
+        if self.return_generated_question:
+            output["generated_question"] = new_question
+        return output
 
     def save(self, file_path: Union[Path, str]) -> None:
         if self.get_chat_history: