diff --git a/langchain/chains/conversational_retrieval/base.py b/langchain/chains/conversational_retrieval/base.py
index baa3f6dd..396f2092 100644
--- a/langchain/chains/conversational_retrieval/base.py
+++ b/langchain/chains/conversational_retrieval/base.py
@@ -12,6 +12,7 @@ from langchain.base_language import BaseLanguageModel
 from langchain.callbacks.manager import (
     AsyncCallbackManagerForChainRun,
     CallbackManagerForChainRun,
+    Callbacks,
 )
 from langchain.chains.base import Chain
 from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
@@ -204,6 +205,7 @@ class ConversationalRetrievalChain(BaseConversationalRetrievalChain):
         verbose: bool = False,
         condense_question_llm: Optional[BaseLanguageModel] = None,
         combine_docs_chain_kwargs: Optional[Dict] = None,
+        callbacks: Callbacks = None,
         **kwargs: Any,
     ) -> BaseConversationalRetrievalChain:
         """Load chain from LLM."""
@@ -212,17 +214,22 @@ class ConversationalRetrievalChain(BaseConversationalRetrievalChain):
             llm,
             chain_type=chain_type,
             verbose=verbose,
+            callbacks=callbacks,
             **combine_docs_chain_kwargs,
         )
 
         _llm = condense_question_llm or llm
         condense_question_chain = LLMChain(
-            llm=_llm, prompt=condense_question_prompt, verbose=verbose
+            llm=_llm,
+            prompt=condense_question_prompt,
+            verbose=verbose,
+            callbacks=callbacks,
         )
         return cls(
             retriever=retriever,
             combine_docs_chain=doc_chain,
             question_generator=condense_question_chain,
+            callbacks=callbacks,
             **kwargs,
         )
 
@@ -264,6 +271,7 @@ class ChatVectorDBChain(BaseConversationalRetrievalChain):
         condense_question_prompt: BasePromptTemplate = CONDENSE_QUESTION_PROMPT,
         chain_type: str = "stuff",
         combine_docs_chain_kwargs: Optional[Dict] = None,
+        callbacks: Callbacks = None,
         **kwargs: Any,
     ) -> BaseConversationalRetrievalChain:
         """Load chain from LLM."""
@@ -271,12 +279,16 @@ class ChatVectorDBChain(BaseConversationalRetrievalChain):
         doc_chain = load_qa_chain(
             llm,
             chain_type=chain_type,
+            callbacks=callbacks,
             **combine_docs_chain_kwargs,
         )
-        condense_question_chain = LLMChain(llm=llm, prompt=condense_question_prompt)
+        condense_question_chain = LLMChain(
+            llm=llm, prompt=condense_question_prompt, callbacks=callbacks
+        )
         return cls(
             vectorstore=vectorstore,
             combine_docs_chain=doc_chain,
             question_generator=condense_question_chain,
+            callbacks=callbacks,
             **kwargs,
         )
diff --git a/langchain/chains/question_answering/__init__.py b/langchain/chains/question_answering/__init__.py
index 95c24f0a..107415cd 100644
--- a/langchain/chains/question_answering/__init__.py
+++ b/langchain/chains/question_answering/__init__.py
@@ -3,6 +3,7 @@ from typing import Any, Mapping, Optional, Protocol
 
 from langchain.base_language import BaseLanguageModel
 from langchain.callbacks.base import BaseCallbackManager
+from langchain.callbacks.manager import Callbacks
 from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
 from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
 from langchain.chains.combine_documents.map_rerank import MapRerankDocumentsChain
@@ -35,10 +36,15 @@ def _load_map_rerank_chain(
     rank_key: str = "score",
     answer_key: str = "answer",
     callback_manager: Optional[BaseCallbackManager] = None,
+    callbacks: Callbacks = None,
     **kwargs: Any,
 ) -> MapRerankDocumentsChain:
     llm_chain = LLMChain(
-        llm=llm, prompt=prompt, verbose=verbose, callback_manager=callback_manager
+        llm=llm,
+        prompt=prompt,
+        verbose=verbose,
+        callback_manager=callback_manager,
+        callbacks=callbacks,
     )
     return MapRerankDocumentsChain(
         llm_chain=llm_chain,
@@ -57,11 +63,16 @@ def _load_stuff_chain(
     document_variable_name: str = "context",
     verbose: Optional[bool] = None,
     callback_manager: Optional[BaseCallbackManager] = None,
+    callbacks: Callbacks = None,
     **kwargs: Any,
 ) -> StuffDocumentsChain:
     _prompt = prompt or stuff_prompt.PROMPT_SELECTOR.get_prompt(llm)
     llm_chain = LLMChain(
-        llm=llm, prompt=_prompt, verbose=verbose, callback_manager=callback_manager
+        llm=llm,
+        prompt=_prompt,
+        verbose=verbose,
+        callback_manager=callback_manager,
+        callbacks=callbacks,
     )
     # TODO: document prompt
     return StuffDocumentsChain(
@@ -84,6 +95,7 @@ def _load_map_reduce_chain(
     collapse_llm: Optional[BaseLanguageModel] = None,
     verbose: Optional[bool] = None,
     callback_manager: Optional[BaseCallbackManager] = None,
+    callbacks: Callbacks = None,
     **kwargs: Any,
 ) -> MapReduceDocumentsChain:
     _question_prompt = (
@@ -97,6 +109,7 @@ def _load_map_reduce_chain(
         prompt=_question_prompt,
         verbose=verbose,
         callback_manager=callback_manager,
+        callbacks=callbacks,
     )
     _reduce_llm = reduce_llm or llm
     reduce_chain = LLMChain(
@@ -104,6 +117,7 @@ def _load_map_reduce_chain(
         prompt=_combine_prompt,
         verbose=verbose,
         callback_manager=callback_manager,
+        callbacks=callbacks,
     )
     # TODO: document prompt
     combine_document_chain = StuffDocumentsChain(
@@ -111,6 +125,7 @@ def _load_map_reduce_chain(
         document_variable_name=combine_document_variable_name,
         verbose=verbose,
         callback_manager=callback_manager,
+        callbacks=callbacks,
     )
     if collapse_prompt is None:
         collapse_chain = None
@@ -127,6 +142,7 @@ def _load_map_reduce_chain(
                 prompt=collapse_prompt,
                 verbose=verbose,
                 callback_manager=callback_manager,
+                callbacks=callbacks,
             ),
             document_variable_name=combine_document_variable_name,
             verbose=verbose,
@@ -139,6 +155,7 @@ def _load_map_reduce_chain(
         collapse_document_chain=collapse_chain,
         verbose=verbose,
         callback_manager=callback_manager,
+        callbacks=callbacks,
         **kwargs,
     )
 
@@ -152,6 +169,7 @@ def _load_refine_chain(
     refine_llm: Optional[BaseLanguageModel] = None,
     verbose: Optional[bool] = None,
     callback_manager: Optional[BaseCallbackManager] = None,
+    callbacks: Callbacks = None,
     **kwargs: Any,
 ) -> RefineDocumentsChain:
     _question_prompt = (
@@ -165,6 +183,7 @@ def _load_refine_chain(
         prompt=_question_prompt,
         verbose=verbose,
         callback_manager=callback_manager,
+        callbacks=callbacks,
     )
     _refine_llm = refine_llm or llm
     refine_chain = LLMChain(
@@ -172,6 +191,7 @@ def _load_refine_chain(
         prompt=_refine_prompt,
         verbose=verbose,
         callback_manager=callback_manager,
+        callbacks=callbacks,
     )
     return RefineDocumentsChain(
         initial_llm_chain=initial_chain,