Add class attribute "return_generated_question" to class "BaseConvers…

…ationalRetrievalChain" (langchain-ai#5749)

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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.

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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 @@ def output_keys(self) -> List[str]:
         _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 @@ def _call(
         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 @@ async def _acall(
         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: