fixed follow up logging

code/main.py

@@ -395,11 +395,20 @@ class Chatbot:
 
         if self.config["llm_params"]["generate_follow_up"]:
             start_time = time.time()
-            list_of_questions = self.question_generator.generate_questions(
+            config = {
+                "callbacks": (
+                    [cl.LangchainCallbackHandler()]
+                    if cl_data._data_layer and self.config["chat_logging"]["callbacks"]
+                    else None
+                )
+            }
+
+            list_of_questions = await self.question_generator.generate_questions(
                 query=user_query_dict["input"],
                 response=answer,
                 chat_history=res.get("chat_history"),
                 context=res.get("context"),
+                config=config,
             )
 
             for question in list_of_questions:

code/modules/chat/langchain/langchain_rag.py

@@ -100,8 +100,8 @@ class QuestionGenerator:
     def __init__(self):
         pass
 
-    def generate_questions(self, query, response, chat_history, context):
-        questions = return_questions(query, response, chat_history, context)
+    def generate_questions(self, query, response, chat_history, context, config):
+        questions = return_questions(query, response, chat_history, context, config)
         return questions
 
 
@@ -204,7 +204,7 @@ class Langchain_RAG_V2(BaseRAG):
                     is_shared=True,
                 ),
             ],
-        )
+        ).with_config(run_name="Langchain_RAG_V2")
 
         if callbacks is not None:
             self.rag_chain = self.rag_chain.with_config(callbacks=callbacks)

code/modules/chat/langchain/utils.py

@@ -280,7 +280,8 @@ def create_retrieval_chain(
     return retrieval_chain
 
 
-def return_questions(query, response, chat_history_str, context):
+# TODO: Remove Hard-coded values
+async def return_questions(query, response, chat_history_str, context, config):
 
     system = (
         "You are someone that suggests a question based on the student's input and chat history. "
@@ -303,13 +304,17 @@ def return_questions(query, response, chat_history_str, context):
     )
     llm = ChatOpenAI(model="gpt-4o-mini", temperature=0)
     question_generator = prompt | llm | StrOutputParser()
-    new_questions = question_generator.invoke(
+    question_generator = question_generator.with_config(
+        run_name="follow_up_question_generator"
+    )
+    new_questions = await question_generator.ainvoke(
         {
             "chat_history_str": chat_history_str,
             "context": context,
             "query": query,
             "response": response,
-        }
+        },
+        config=config,
     )
 
     list_of_questions = new_questions.split("...")