diff --git a/libs/langchain/langchain/agents/chat/base.py b/libs/langchain/langchain/agents/chat/base.py
index ffd36852e1e..0fda0a119ed 100644
--- a/libs/langchain/langchain/agents/chat/base.py
+++ b/libs/langchain/langchain/agents/chat/base.py
@@ -97,7 +97,7 @@ class ChatAgent(Agent):
         ]
         if input_variables is None:
             input_variables = ["input", "agent_scratchpad"]
-        return ChatPromptTemplate(input_variables=input_variables, messages=messages)
+        return ChatPromptTemplate(input_variables=input_variables, messages=messages)  # type: ignore[arg-type]
 
     @classmethod
     def from_llm_and_tools(
diff --git a/libs/langchain/langchain/agents/conversational_chat/base.py b/libs/langchain/langchain/agents/conversational_chat/base.py
index 8ee2218780b..a2f43a33f4d 100644
--- a/libs/langchain/langchain/agents/conversational_chat/base.py
+++ b/libs/langchain/langchain/agents/conversational_chat/base.py
@@ -88,7 +88,7 @@ class ConversationalChatAgent(Agent):
             HumanMessagePromptTemplate.from_template(final_prompt),
             MessagesPlaceholder(variable_name="agent_scratchpad"),
         ]
-        return ChatPromptTemplate(input_variables=input_variables, messages=messages)
+        return ChatPromptTemplate(input_variables=input_variables, messages=messages)  # type: ignore[arg-type]
 
     def _construct_scratchpad(
         self, intermediate_steps: List[Tuple[AgentAction, str]]
diff --git a/libs/langchain/langchain/agents/load_tools.py b/libs/langchain/langchain/agents/load_tools.py
index 5577c9178e1..f87d1b8c25e 100644
--- a/libs/langchain/langchain/agents/load_tools.py
+++ b/libs/langchain/langchain/agents/load_tools.py
@@ -406,7 +406,7 @@ def _get_eleven_labs_text2speech(**kwargs: Any) -> BaseTool:
 
 
 def _get_memorize(llm: BaseLanguageModel, **kwargs: Any) -> BaseTool:
-    return Memorize(llm=llm)
+    return Memorize(llm=llm)  # type: ignore[arg-type]
 
 
 def _get_google_cloud_texttospeech(**kwargs: Any) -> BaseTool:
diff --git a/libs/langchain/langchain/agents/openai_functions_agent/base.py b/libs/langchain/langchain/agents/openai_functions_agent/base.py
index 47e9b8d99fc..d96b924e298 100644
--- a/libs/langchain/langchain/agents/openai_functions_agent/base.py
+++ b/libs/langchain/langchain/agents/openai_functions_agent/base.py
@@ -201,7 +201,7 @@ class OpenAIFunctionsAgent(BaseSingleActionAgent):
                 MessagesPlaceholder(variable_name="agent_scratchpad"),
             ]
         )
-        return ChatPromptTemplate(messages=messages)
+        return ChatPromptTemplate(messages=messages)  # type: ignore[arg-type, call-arg]
 
     @classmethod
     def from_llm_and_tools(
@@ -220,7 +220,7 @@ class OpenAIFunctionsAgent(BaseSingleActionAgent):
             extra_prompt_messages=extra_prompt_messages,
             system_message=system_message,
         )
-        return cls(
+        return cls(  # type: ignore[call-arg]
             llm=llm,
             prompt=prompt,
             tools=tools,
diff --git a/libs/langchain/langchain/agents/openai_functions_multi_agent/base.py b/libs/langchain/langchain/agents/openai_functions_multi_agent/base.py
index 03d804c60fd..f59a751136f 100644
--- a/libs/langchain/langchain/agents/openai_functions_multi_agent/base.py
+++ b/libs/langchain/langchain/agents/openai_functions_multi_agent/base.py
@@ -279,7 +279,7 @@ class OpenAIMultiFunctionsAgent(BaseMultiActionAgent):
                 MessagesPlaceholder(variable_name="agent_scratchpad"),
             ]
         )
-        return ChatPromptTemplate(messages=messages)
+        return ChatPromptTemplate(messages=messages)  # type: ignore[arg-type, call-arg]
 
     @classmethod
     def from_llm_and_tools(
@@ -298,7 +298,7 @@ class OpenAIMultiFunctionsAgent(BaseMultiActionAgent):
             extra_prompt_messages=extra_prompt_messages,
             system_message=system_message,
         )
-        return cls(
+        return cls(  # type: ignore[call-arg]
             llm=llm,
             prompt=prompt,
             tools=tools,
diff --git a/libs/langchain/langchain/agents/structured_chat/base.py b/libs/langchain/langchain/agents/structured_chat/base.py
index 9054ef3f05e..735160f639d 100644
--- a/libs/langchain/langchain/agents/structured_chat/base.py
+++ b/libs/langchain/langchain/agents/structured_chat/base.py
@@ -103,7 +103,7 @@ class StructuredChatAgent(Agent):
             *_memory_prompts,
             HumanMessagePromptTemplate.from_template(human_message_template),
         ]
-        return ChatPromptTemplate(input_variables=input_variables, messages=messages)
+        return ChatPromptTemplate(input_variables=input_variables, messages=messages)  # type: ignore[arg-type]
 
     @classmethod
     def from_llm_and_tools(
diff --git a/libs/langchain/langchain/chains/graph_qa/cypher.py b/libs/langchain/langchain/chains/graph_qa/cypher.py
index 3376e567308..7682de853ad 100644
--- a/libs/langchain/langchain/chains/graph_qa/cypher.py
+++ b/libs/langchain/langchain/chains/graph_qa/cypher.py
@@ -199,10 +199,11 @@ class GraphCypherQAChain(Chain):
                 cypher_prompt if cypher_prompt is not None else CYPHER_GENERATION_PROMPT
             )
 
-        qa_chain = LLMChain(llm=qa_llm or llm, **use_qa_llm_kwargs)
+        qa_chain = LLMChain(llm=qa_llm or llm, **use_qa_llm_kwargs)  # type: ignore[arg-type]
 
         cypher_generation_chain = LLMChain(
-            llm=cypher_llm or llm, **use_cypher_llm_kwargs
+            llm=cypher_llm or llm,  # type: ignore[arg-type]
+            **use_cypher_llm_kwargs,  # type: ignore[arg-type]
         )
 
         if exclude_types and include_types:
diff --git a/libs/langchain/langchain/chains/graph_qa/neptune_sparql.py b/libs/langchain/langchain/chains/graph_qa/neptune_sparql.py
index 08a1cc249be..1a5b23f5874 100644
--- a/libs/langchain/langchain/chains/graph_qa/neptune_sparql.py
+++ b/libs/langchain/langchain/chains/graph_qa/neptune_sparql.py
@@ -135,7 +135,7 @@ class NeptuneSparqlQAChain(Chain):
             )
         sparql_generation_chain = LLMChain(llm=llm, prompt=sparql_prompt)
 
-        return cls(
+        return cls(  # type: ignore[call-arg]
             qa_chain=qa_chain,
             sparql_generation_chain=sparql_generation_chain,
             examples=examples,
diff --git a/libs/langchain/langchain/chains/llm_checker/base.py b/libs/langchain/langchain/chains/llm_checker/base.py
index 1d9166364e6..c5d96859be3 100644
--- a/libs/langchain/langchain/chains/llm_checker/base.py
+++ b/libs/langchain/langchain/chains/llm_checker/base.py
@@ -54,7 +54,7 @@ def _load_question_to_checked_assertions_chain(
         revised_answer_chain,
     ]
     question_to_checked_assertions_chain = SequentialChain(
-        chains=chains,
+        chains=chains,  # type: ignore[arg-type]
         input_variables=["question"],
         output_variables=["revised_statement"],
         verbose=True,
diff --git a/libs/langchain/langchain/chains/loading.py b/libs/langchain/langchain/chains/loading.py
index 0fc3da3f499..a5c3e458188 100644
--- a/libs/langchain/langchain/chains/loading.py
+++ b/libs/langchain/langchain/chains/loading.py
@@ -69,7 +69,9 @@ def _load_hyde_chain(config: dict, **kwargs: Any) -> HypotheticalDocumentEmbedde
     else:
         raise ValueError("`embeddings` must be present.")
     return HypotheticalDocumentEmbedder(
-        llm_chain=llm_chain, base_embeddings=embeddings, **config
+        llm_chain=llm_chain,  # type: ignore[arg-type]
+        base_embeddings=embeddings,
+        **config,  # type: ignore[arg-type]
     )
 
 
@@ -125,7 +127,7 @@ def _load_map_reduce_documents_chain(
 
     return MapReduceDocumentsChain(
         llm_chain=llm_chain,
-        reduce_documents_chain=reduce_documents_chain,
+        reduce_documents_chain=reduce_documents_chain,  # type: ignore[arg-type]
         **config,
     )
 
@@ -207,7 +209,7 @@ def _load_llm_bash_chain(config: dict, **kwargs: Any) -> Any:
     elif "prompt_path" in config:
         prompt = load_prompt(config.pop("prompt_path"))
     if llm_chain:
-        return LLMBashChain(llm_chain=llm_chain, prompt=prompt, **config)
+        return LLMBashChain(llm_chain=llm_chain, prompt=prompt, **config)  # type: ignore[arg-type]
     else:
         return LLMBashChain(llm=llm, prompt=prompt, **config)
 
@@ -250,10 +252,10 @@ def _load_llm_checker_chain(config: dict, **kwargs: Any) -> LLMCheckerChain:
         revised_answer_prompt = load_prompt(config.pop("revised_answer_prompt_path"))
     return LLMCheckerChain(
         llm=llm,
-        create_draft_answer_prompt=create_draft_answer_prompt,
-        list_assertions_prompt=list_assertions_prompt,
-        check_assertions_prompt=check_assertions_prompt,
-        revised_answer_prompt=revised_answer_prompt,
+        create_draft_answer_prompt=create_draft_answer_prompt,  # type: ignore[arg-type]
+        list_assertions_prompt=list_assertions_prompt,  # type: ignore[arg-type]
+        check_assertions_prompt=check_assertions_prompt,  # type: ignore[arg-type]
+        revised_answer_prompt=revised_answer_prompt,  # type: ignore[arg-type]
         **config,
     )
 
@@ -281,7 +283,7 @@ def _load_llm_math_chain(config: dict, **kwargs: Any) -> LLMMathChain:
     elif "prompt_path" in config:
         prompt = load_prompt(config.pop("prompt_path"))
     if llm_chain:
-        return LLMMathChain(llm_chain=llm_chain, prompt=prompt, **config)
+        return LLMMathChain(llm_chain=llm_chain, prompt=prompt, **config)  # type: ignore[arg-type]
     else:
         return LLMMathChain(llm=llm, prompt=prompt, **config)
 
@@ -296,7 +298,7 @@ def _load_map_rerank_documents_chain(
         llm_chain = load_chain(config.pop("llm_chain_path"))
     else:
         raise ValueError("One of `llm_chain` or `llm_chain_path` must be present.")
-    return MapRerankDocumentsChain(llm_chain=llm_chain, **config)
+    return MapRerankDocumentsChain(llm_chain=llm_chain, **config)  # type: ignore[arg-type]
 
 
 def _load_pal_chain(config: dict, **kwargs: Any) -> Any:
@@ -309,7 +311,7 @@ def _load_pal_chain(config: dict, **kwargs: Any) -> Any:
         llm_chain = load_chain(config.pop("llm_chain_path"))
     else:
         raise ValueError("One of `llm_chain` or `llm_chain_path` must be present.")
-    return PALChain(llm_chain=llm_chain, **config)
+    return PALChain(llm_chain=llm_chain, **config)  # type: ignore[arg-type]
 
 
 def _load_refine_documents_chain(config: dict, **kwargs: Any) -> RefineDocumentsChain:
@@ -337,8 +339,8 @@ def _load_refine_documents_chain(config: dict, **kwargs: Any) -> RefineDocuments
     elif "document_prompt_path" in config:
         document_prompt = load_prompt(config.pop("document_prompt_path"))
     return RefineDocumentsChain(
-        initial_llm_chain=initial_llm_chain,
-        refine_llm_chain=refine_llm_chain,
+        initial_llm_chain=initial_llm_chain,  # type: ignore[arg-type]
+        refine_llm_chain=refine_llm_chain,  # type: ignore[arg-type]
         document_prompt=document_prompt,
         **config,
     )
@@ -355,7 +357,7 @@ def _load_qa_with_sources_chain(config: dict, **kwargs: Any) -> QAWithSourcesCha
             "One of `combine_documents_chain` or "
             "`combine_documents_chain_path` must be present."
         )
-    return QAWithSourcesChain(combine_documents_chain=combine_documents_chain, **config)
+    return QAWithSourcesChain(combine_documents_chain=combine_documents_chain, **config)  # type: ignore[arg-type]
 
 
 def _load_sql_database_chain(config: dict, **kwargs: Any) -> Any:
@@ -368,7 +370,7 @@ def _load_sql_database_chain(config: dict, **kwargs: Any) -> Any:
     if "llm_chain" in config:
         llm_chain_config = config.pop("llm_chain")
         chain = load_chain_from_config(llm_chain_config)
-        return SQLDatabaseChain(llm_chain=chain, database=database, **config)
+        return SQLDatabaseChain(llm_chain=chain, database=database, **config)  # type: ignore[arg-type]
     if "llm" in config:
         llm_config = config.pop("llm")
         llm = load_llm_from_config(llm_config)
@@ -403,7 +405,7 @@ def _load_vector_db_qa_with_sources_chain(
             "`combine_documents_chain_path` must be present."
         )
     return VectorDBQAWithSourcesChain(
-        combine_documents_chain=combine_documents_chain,
+        combine_documents_chain=combine_documents_chain,  # type: ignore[arg-type]
         vectorstore=vectorstore,
         **config,
     )
@@ -425,7 +427,7 @@ def _load_retrieval_qa(config: dict, **kwargs: Any) -> RetrievalQA:
             "`combine_documents_chain_path` must be present."
         )
     return RetrievalQA(
-        combine_documents_chain=combine_documents_chain,
+        combine_documents_chain=combine_documents_chain,  # type: ignore[arg-type]
         retriever=retriever,
         **config,
     )
@@ -449,7 +451,7 @@ def _load_retrieval_qa_with_sources_chain(
             "`combine_documents_chain_path` must be present."
         )
     return RetrievalQAWithSourcesChain(
-        combine_documents_chain=combine_documents_chain,
+        combine_documents_chain=combine_documents_chain,  # type: ignore[arg-type]
         retriever=retriever,
         **config,
     )
@@ -471,7 +473,7 @@ def _load_vector_db_qa(config: dict, **kwargs: Any) -> VectorDBQA:
             "`combine_documents_chain_path` must be present."
         )
     return VectorDBQA(
-        combine_documents_chain=combine_documents_chain,
+        combine_documents_chain=combine_documents_chain,  # type: ignore[arg-type]
         vectorstore=vectorstore,
         **config,
     )
@@ -495,8 +497,8 @@ def _load_graph_cypher_chain(config: dict, **kwargs: Any) -> GraphCypherQAChain:
 
     return GraphCypherQAChain(
         graph=graph,
-        cypher_generation_chain=cypher_generation_chain,
-        qa_chain=qa_chain,
+        cypher_generation_chain=cypher_generation_chain,  # type: ignore[arg-type]
+        qa_chain=qa_chain,  # type: ignore[arg-type]
         **config,
     )
 
@@ -525,8 +527,8 @@ def _load_api_chain(config: dict, **kwargs: Any) -> APIChain:
     else:
         raise ValueError("`requests_wrapper` must be present.")
     return APIChain(
-        api_request_chain=api_request_chain,
-        api_answer_chain=api_answer_chain,
+        api_request_chain=api_request_chain,  # type: ignore[arg-type]
+        api_answer_chain=api_answer_chain,  # type: ignore[arg-type]
         requests_wrapper=requests_wrapper,
         **config,
     )
diff --git a/libs/langchain/langchain/chains/openai_functions/citation_fuzzy_match.py b/libs/langchain/langchain/chains/openai_functions/citation_fuzzy_match.py
index 29874420396..05bb27d7a9a 100644
--- a/libs/langchain/langchain/chains/openai_functions/citation_fuzzy_match.py
+++ b/libs/langchain/langchain/chains/openai_functions/citation_fuzzy_match.py
@@ -95,7 +95,7 @@ def create_citation_fuzzy_match_chain(llm: BaseLanguageModel) -> LLMChain:
             )
         ),
     ]
-    prompt = ChatPromptTemplate(messages=messages)
+    prompt = ChatPromptTemplate(messages=messages)  # type: ignore[arg-type, call-arg]
 
     chain = LLMChain(
         llm=llm,
diff --git a/libs/langchain/langchain/chains/openai_functions/qa_with_structure.py b/libs/langchain/langchain/chains/openai_functions/qa_with_structure.py
index feaec2e36d0..7f39e4dd5d7 100644
--- a/libs/langchain/langchain/chains/openai_functions/qa_with_structure.py
+++ b/libs/langchain/langchain/chains/openai_functions/qa_with_structure.py
@@ -82,7 +82,7 @@ def create_qa_with_structure_chain(
         HumanMessagePromptTemplate.from_template("Question: {question}"),
         HumanMessage(content="Tips: Make sure to answer in the correct format"),
     ]
-    prompt = prompt or ChatPromptTemplate(messages=messages)
+    prompt = prompt or ChatPromptTemplate(messages=messages)  # type: ignore[arg-type, call-arg]
 
     chain = LLMChain(
         llm=llm,
diff --git a/libs/langchain/langchain/chains/qa_with_sources/loading.py b/libs/langchain/langchain/chains/qa_with_sources/loading.py
index e1e63c0316b..0957d8012ad 100644
--- a/libs/langchain/langchain/chains/qa_with_sources/loading.py
+++ b/libs/langchain/langchain/chains/qa_with_sources/loading.py
@@ -59,12 +59,12 @@ def _load_stuff_chain(
     verbose: Optional[bool] = None,
     **kwargs: Any,
 ) -> StuffDocumentsChain:
-    llm_chain = LLMChain(llm=llm, prompt=prompt, verbose=verbose)
+    llm_chain = LLMChain(llm=llm, prompt=prompt, verbose=verbose)  # type: ignore[arg-type]
     return StuffDocumentsChain(
         llm_chain=llm_chain,
         document_variable_name=document_variable_name,
         document_prompt=document_prompt,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         **kwargs,
     )
 
@@ -83,14 +83,14 @@ def _load_map_reduce_chain(
     token_max: int = 3000,
     **kwargs: Any,
 ) -> MapReduceDocumentsChain:
-    map_chain = LLMChain(llm=llm, prompt=question_prompt, verbose=verbose)
+    map_chain = LLMChain(llm=llm, prompt=question_prompt, verbose=verbose)  # type: ignore[arg-type]
     _reduce_llm = reduce_llm or llm
-    reduce_chain = LLMChain(llm=_reduce_llm, prompt=combine_prompt, verbose=verbose)
+    reduce_chain = LLMChain(llm=_reduce_llm, prompt=combine_prompt, verbose=verbose)  # type: ignore[arg-type]
     combine_documents_chain = StuffDocumentsChain(
         llm_chain=reduce_chain,
         document_variable_name=combine_document_variable_name,
         document_prompt=document_prompt,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
     )
     if collapse_prompt is None:
         collapse_chain = None
@@ -105,7 +105,7 @@ def _load_map_reduce_chain(
             llm_chain=LLMChain(
                 llm=_collapse_llm,
                 prompt=collapse_prompt,
-                verbose=verbose,
+                verbose=verbose,  # type: ignore[arg-type]
             ),
             document_variable_name=combine_document_variable_name,
             document_prompt=document_prompt,
@@ -114,13 +114,13 @@ def _load_map_reduce_chain(
         combine_documents_chain=combine_documents_chain,
         collapse_documents_chain=collapse_chain,
         token_max=token_max,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
     )
     return MapReduceDocumentsChain(
         llm_chain=map_chain,
         reduce_documents_chain=reduce_documents_chain,
         document_variable_name=map_reduce_document_variable_name,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         **kwargs,
     )
 
@@ -136,16 +136,16 @@ def _load_refine_chain(
     verbose: Optional[bool] = None,
     **kwargs: Any,
 ) -> RefineDocumentsChain:
-    initial_chain = LLMChain(llm=llm, prompt=question_prompt, verbose=verbose)
+    initial_chain = LLMChain(llm=llm, prompt=question_prompt, verbose=verbose)  # type: ignore[arg-type]
     _refine_llm = refine_llm or llm
-    refine_chain = LLMChain(llm=_refine_llm, prompt=refine_prompt, verbose=verbose)
+    refine_chain = LLMChain(llm=_refine_llm, prompt=refine_prompt, verbose=verbose)  # type: ignore[arg-type]
     return RefineDocumentsChain(
         initial_llm_chain=initial_chain,
         refine_llm_chain=refine_chain,
         document_variable_name=document_variable_name,
         initial_response_name=initial_response_name,
         document_prompt=document_prompt,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         **kwargs,
     )
 
diff --git a/libs/langchain/langchain/chains/question_answering/__init__.py b/libs/langchain/langchain/chains/question_answering/__init__.py
index 34d6c917626..5e41e19f891 100644
--- a/libs/langchain/langchain/chains/question_answering/__init__.py
+++ b/libs/langchain/langchain/chains/question_answering/__init__.py
@@ -73,7 +73,7 @@ def _load_stuff_chain(
     llm_chain = LLMChain(
         llm=llm,
         prompt=_prompt,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         callback_manager=callback_manager,
         callbacks=callbacks,
     )
@@ -81,7 +81,7 @@ def _load_stuff_chain(
     return StuffDocumentsChain(
         llm_chain=llm_chain,
         document_variable_name=document_variable_name,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         callback_manager=callback_manager,
         callbacks=callbacks,
         **kwargs,
@@ -112,7 +112,7 @@ def _load_map_reduce_chain(
     map_chain = LLMChain(
         llm=llm,
         prompt=_question_prompt,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         callback_manager=callback_manager,
         callbacks=callbacks,
     )
@@ -120,7 +120,7 @@ def _load_map_reduce_chain(
     reduce_chain = LLMChain(
         llm=_reduce_llm,
         prompt=_combine_prompt,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         callback_manager=callback_manager,
         callbacks=callbacks,
     )
@@ -128,7 +128,7 @@ def _load_map_reduce_chain(
     combine_documents_chain = StuffDocumentsChain(
         llm_chain=reduce_chain,
         document_variable_name=combine_document_variable_name,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         callback_manager=callback_manager,
         callbacks=callbacks,
     )
@@ -145,12 +145,12 @@ def _load_map_reduce_chain(
             llm_chain=LLMChain(
                 llm=_collapse_llm,
                 prompt=collapse_prompt,
-                verbose=verbose,
+                verbose=verbose,  # type: ignore[arg-type]
                 callback_manager=callback_manager,
                 callbacks=callbacks,
             ),
             document_variable_name=combine_document_variable_name,
-            verbose=verbose,
+            verbose=verbose,  # type: ignore[arg-type]
             callback_manager=callback_manager,
         )
     reduce_documents_chain = ReduceDocumentsChain(
@@ -163,7 +163,7 @@ def _load_map_reduce_chain(
         llm_chain=map_chain,
         document_variable_name=map_reduce_document_variable_name,
         reduce_documents_chain=reduce_documents_chain,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         callback_manager=callback_manager,
         callbacks=callbacks,
         **kwargs,
@@ -191,7 +191,7 @@ def _load_refine_chain(
     initial_chain = LLMChain(
         llm=llm,
         prompt=_question_prompt,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         callback_manager=callback_manager,
         callbacks=callbacks,
     )
@@ -199,7 +199,7 @@ def _load_refine_chain(
     refine_chain = LLMChain(
         llm=_refine_llm,
         prompt=_refine_prompt,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         callback_manager=callback_manager,
         callbacks=callbacks,
     )
@@ -208,7 +208,7 @@ def _load_refine_chain(
         refine_llm_chain=refine_chain,
         document_variable_name=document_variable_name,
         initial_response_name=initial_response_name,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         callback_manager=callback_manager,
         callbacks=callbacks,
         **kwargs,
diff --git a/libs/langchain/langchain/chains/summarize/__init__.py b/libs/langchain/langchain/chains/summarize/__init__.py
index 3f6068a0f26..dcb7fb91e62 100644
--- a/libs/langchain/langchain/chains/summarize/__init__.py
+++ b/libs/langchain/langchain/chains/summarize/__init__.py
@@ -30,12 +30,12 @@ def _load_stuff_chain(
     verbose: Optional[bool] = None,
     **kwargs: Any,
 ) -> StuffDocumentsChain:
-    llm_chain = LLMChain(llm=llm, prompt=prompt, verbose=verbose)
+    llm_chain = LLMChain(llm=llm, prompt=prompt, verbose=verbose)  # type: ignore[arg-type]
     # TODO: document prompt
     return StuffDocumentsChain(
         llm_chain=llm_chain,
         document_variable_name=document_variable_name,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         **kwargs,
     )
 
@@ -57,17 +57,23 @@ def _load_map_reduce_chain(
     **kwargs: Any,
 ) -> MapReduceDocumentsChain:
     map_chain = LLMChain(
-        llm=llm, prompt=map_prompt, verbose=verbose, callbacks=callbacks
+        llm=llm,
+        prompt=map_prompt,
+        verbose=verbose,  # type: ignore[arg-type]
+        callbacks=callbacks,  # type: ignore[arg-type]
     )
     _reduce_llm = reduce_llm or llm
     reduce_chain = LLMChain(
-        llm=_reduce_llm, prompt=combine_prompt, verbose=verbose, callbacks=callbacks
+        llm=_reduce_llm,
+        prompt=combine_prompt,
+        verbose=verbose,  # type: ignore[arg-type]
+        callbacks=callbacks,  # type: ignore[arg-type]
     )
     # TODO: document prompt
     combine_documents_chain = StuffDocumentsChain(
         llm_chain=reduce_chain,
         document_variable_name=combine_document_variable_name,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         callbacks=callbacks,
     )
     if collapse_prompt is None:
@@ -83,7 +89,7 @@ def _load_map_reduce_chain(
             llm_chain=LLMChain(
                 llm=_collapse_llm,
                 prompt=collapse_prompt,
-                verbose=verbose,
+                verbose=verbose,  # type: ignore[arg-type]
                 callbacks=callbacks,
             ),
             document_variable_name=combine_document_variable_name,
@@ -92,7 +98,7 @@ def _load_map_reduce_chain(
         combine_documents_chain=combine_documents_chain,
         collapse_documents_chain=collapse_chain,
         token_max=token_max,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         callbacks=callbacks,
         collapse_max_retries=collapse_max_retries,
     )
@@ -100,7 +106,7 @@ def _load_map_reduce_chain(
         llm_chain=map_chain,
         reduce_documents_chain=reduce_documents_chain,
         document_variable_name=map_reduce_document_variable_name,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         callbacks=callbacks,
         **kwargs,
     )
@@ -116,15 +122,15 @@ def _load_refine_chain(
     verbose: Optional[bool] = None,
     **kwargs: Any,
 ) -> RefineDocumentsChain:
-    initial_chain = LLMChain(llm=llm, prompt=question_prompt, verbose=verbose)
+    initial_chain = LLMChain(llm=llm, prompt=question_prompt, verbose=verbose)  # type: ignore[arg-type]
     _refine_llm = refine_llm or llm
-    refine_chain = LLMChain(llm=_refine_llm, prompt=refine_prompt, verbose=verbose)
+    refine_chain = LLMChain(llm=_refine_llm, prompt=refine_prompt, verbose=verbose)  # type: ignore[arg-type]
     return RefineDocumentsChain(
         initial_llm_chain=initial_chain,
         refine_llm_chain=refine_chain,
         document_variable_name=document_variable_name,
         initial_response_name=initial_response_name,
-        verbose=verbose,
+        verbose=verbose,  # type: ignore[arg-type]
         **kwargs,
     )
 
diff --git a/libs/langchain/langchain/evaluation/agents/trajectory_eval_chain.py b/libs/langchain/langchain/evaluation/agents/trajectory_eval_chain.py
index 89b389340ea..0d31a6686a9 100644
--- a/libs/langchain/langchain/evaluation/agents/trajectory_eval_chain.py
+++ b/libs/langchain/langchain/evaluation/agents/trajectory_eval_chain.py
@@ -255,7 +255,7 @@ The following is the expected answer. Use this to measure correctness:
             prompt = TOOL_FREE_EVAL_CHAT_PROMPT
         eval_chain = LLMChain(llm=llm, prompt=prompt)
         return cls(
-            agent_tools=agent_tools,
+            agent_tools=agent_tools,  # type: ignore[arg-type]
             eval_chain=eval_chain,
             output_parser=output_parser or TrajectoryOutputParser(),
             **kwargs,
diff --git a/libs/langchain/langchain/evaluation/loading.py b/libs/langchain/langchain/evaluation/loading.py
index 4f9c3757d74..fbb17325854 100644
--- a/libs/langchain/langchain/evaluation/loading.py
+++ b/libs/langchain/langchain/evaluation/loading.py
@@ -131,7 +131,7 @@ def load_evaluator(
     evaluator_cls = _EVALUATOR_MAP[evaluator]
     if issubclass(evaluator_cls, LLMEvalChain):
         try:
-            llm = llm or ChatOpenAI(
+            llm = llm or ChatOpenAI(  # type: ignore[call-arg]
                 model="gpt-4", model_kwargs={"seed": 42}, temperature=0
             )
         except Exception as e:
diff --git a/libs/langchain/langchain/indexes/_api.py b/libs/langchain/langchain/indexes/_api.py
index 8dcf6e0c93a..01371c4b73f 100644
--- a/libs/langchain/langchain/indexes/_api.py
+++ b/libs/langchain/langchain/indexes/_api.py
@@ -109,8 +109,8 @@ class _HashedDocument(Document):
         cls, document: Document, *, uid: Optional[str] = None
     ) -> _HashedDocument:
         """Create a HashedDocument from a Document."""
-        return cls(
-            uid=uid,
+        return cls(  # type: ignore[call-arg]
+            uid=uid,  # type: ignore[arg-type]
             page_content=document.page_content,
             metadata=document.metadata,
         )
diff --git a/libs/langchain/langchain/indexes/_sql_record_manager.py b/libs/langchain/langchain/indexes/_sql_record_manager.py
index 76dfd967234..435f34e11cc 100644
--- a/libs/langchain/langchain/indexes/_sql_record_manager.py
+++ b/libs/langchain/langchain/indexes/_sql_record_manager.py
@@ -308,7 +308,7 @@ class SQLRecordManager(RecordManager):
                 pg_insert_stmt: PgInsertType = pg_insert(UpsertionRecord).values(
                     records_to_upsert
                 )
-                stmt = pg_insert_stmt.on_conflict_do_update(
+                stmt = pg_insert_stmt.on_conflict_do_update(  # type: ignore[assignment]
                     "uix_key_namespace",  # Name of constraint
                     set_=dict(
                         updated_at=pg_insert_stmt.excluded.updated_at,
@@ -387,7 +387,7 @@ class SQLRecordManager(RecordManager):
                 pg_insert_stmt: PgInsertType = pg_insert(UpsertionRecord).values(
                     records_to_upsert
                 )
-                stmt = pg_insert_stmt.on_conflict_do_update(
+                stmt = pg_insert_stmt.on_conflict_do_update(  # type: ignore[assignment]
                     "uix_key_namespace",  # Name of constraint
                     set_=dict(
                         updated_at=pg_insert_stmt.excluded.updated_at,
@@ -472,7 +472,7 @@ class SQLRecordManager(RecordManager):
         """List records in the SQLite database based on the provided date range."""
         session: AsyncSession
         async with self._amake_session() as session:
-            query: Query = select(UpsertionRecord.key).filter(
+            query: Query = select(UpsertionRecord.key).filter(  # type: ignore[assignment]
                 UpsertionRecord.namespace == self.namespace
             )
 
diff --git a/libs/langchain/langchain/retrievers/document_compressors/chain_extract.py b/libs/langchain/langchain/retrievers/document_compressors/chain_extract.py
index af8319f1ffc..6cfe45b2264 100644
--- a/libs/langchain/langchain/retrievers/document_compressors/chain_extract.py
+++ b/libs/langchain/langchain/retrievers/document_compressors/chain_extract.py
@@ -92,7 +92,7 @@ class LLMChainExtractor(BaseDocumentCompressor):
             if len(outputs[i]) == 0:
                 continue
             compressed_docs.append(
-                Document(page_content=outputs[i], metadata=doc.metadata)
+                Document(page_content=outputs[i], metadata=doc.metadata)  # type: ignore[arg-type]
             )
         return compressed_docs
 
@@ -108,4 +108,4 @@ class LLMChainExtractor(BaseDocumentCompressor):
         _prompt = prompt if prompt is not None else _get_default_chain_prompt()
         _get_input = get_input if get_input is not None else default_get_input
         llm_chain = LLMChain(llm=llm, prompt=_prompt, **(llm_chain_kwargs or {}))
-        return cls(llm_chain=llm_chain, get_input=_get_input)
+        return cls(llm_chain=llm_chain, get_input=_get_input)  # type: ignore[arg-type]
diff --git a/libs/langchain/langchain/retrievers/ensemble.py b/libs/langchain/langchain/retrievers/ensemble.py
index 34838f23fed..835faba78a4 100644
--- a/libs/langchain/langchain/retrievers/ensemble.py
+++ b/libs/langchain/langchain/retrievers/ensemble.py
@@ -238,7 +238,7 @@ class EnsembleRetriever(BaseRetriever):
         # Enforce that retrieved docs are Documents for each list in retriever_docs
         for i in range(len(retriever_docs)):
             retriever_docs[i] = [
-                Document(page_content=doc) if not isinstance(doc, Document) else doc
+                Document(page_content=doc) if not isinstance(doc, Document) else doc  # type: ignore[arg-type]
                 for doc in retriever_docs[i]
             ]
 
diff --git a/libs/langchain/langchain/retrievers/self_query/base.py b/libs/langchain/langchain/retrievers/self_query/base.py
index dbc53637fc4..f08038d0721 100644
--- a/libs/langchain/langchain/retrievers/self_query/base.py
+++ b/libs/langchain/langchain/retrievers/self_query/base.py
@@ -251,7 +251,7 @@ class SelfQueryRetriever(BaseRetriever):
         query_constructor = query_constructor.with_config(
             run_name=QUERY_CONSTRUCTOR_RUN_NAME
         )
-        return cls(
+        return cls(  # type: ignore[call-arg]
             query_constructor=query_constructor,
             vectorstore=vectorstore,
             use_original_query=use_original_query,
diff --git a/libs/langchain/langchain/smith/evaluation/config.py b/libs/langchain/langchain/smith/evaluation/config.py
index 202a94fddea..d73bba22624 100644
--- a/libs/langchain/langchain/smith/evaluation/config.py
+++ b/libs/langchain/langchain/smith/evaluation/config.py
@@ -178,7 +178,7 @@ class RunEvalConfig(BaseModel):
         def __init__(
             self, criteria: Optional[CRITERIA_TYPE] = None, **kwargs: Any
         ) -> None:
-            super().__init__(criteria=criteria, **kwargs)
+            super().__init__(criteria=criteria, **kwargs)  # type: ignore[call-arg]
 
     class LabeledCriteria(SingleKeyEvalConfig):
         """Configuration for a labeled (with references) criteria evaluator.
@@ -198,7 +198,7 @@ class RunEvalConfig(BaseModel):
         def __init__(
             self, criteria: Optional[CRITERIA_TYPE] = None, **kwargs: Any
         ) -> None:
-            super().__init__(criteria=criteria, **kwargs)
+            super().__init__(criteria=criteria, **kwargs)  # type: ignore[call-arg]
 
     class EmbeddingDistance(SingleKeyEvalConfig):
         """Configuration for an embedding distance evaluator.
@@ -370,7 +370,7 @@ class RunEvalConfig(BaseModel):
             normalize_by: Optional[float] = None,
             **kwargs: Any,
         ) -> None:
-            super().__init__(criteria=criteria, normalize_by=normalize_by, **kwargs)
+            super().__init__(criteria=criteria, normalize_by=normalize_by, **kwargs)  # type: ignore[call-arg]
 
     class LabeledScoreString(ScoreString):
         evaluator_type: EvaluatorType = EvaluatorType.LABELED_SCORE_STRING
diff --git a/libs/langchain/poetry.lock b/libs/langchain/poetry.lock
index 08d17198fb5..6a177bfb444 100644
--- a/libs/langchain/poetry.lock
+++ b/libs/langchain/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
 
 [[package]]
 name = "aiodns"
@@ -3072,6 +3072,7 @@ files = [
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@@ -4238,52 +4239,49 @@ para = ">=0.0.1"
 
 [[package]]
 name = "mypy"
-version = "0.991"
+version = "1.9.0"
 description = "Optional static typing for Python"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
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 install-types = ["pip"]
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 tutorials = ["matplotlib", "pandas", "tabulate", "torch"]
 
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 [[package]]
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 version = "2.43.0"
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 types-pyOpenSSL = "*"
 
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-[package.dependencies]
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 [[package]]
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 version = "2.31.0.20240311"
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 ]
 
-[[package]]
-name = "types-urllib3"
-version = "1.26.25.14"
-description = "Typing stubs for urllib3"
-optional = false
-python-versions = "*"
-files = [
-    {file = "types-urllib3-1.26.25.14.tar.gz", hash = "sha256:229b7f577c951b8c1b92c1bc2b2fdb0b49847bd2af6d1cc2a2e3dd340f3bda8f"},
-    {file = "types_urllib3-1.26.25.14-py3-none-any.whl", hash = "sha256:9683bbb7fb72e32bfe9d2be6e04875fbe1b3eeec3cbb4ea231435aa7fd6b4f0e"},
-]
-
 [[package]]
 name = "typing"
 version = "3.7.4.3"
@@ -8848,22 +8799,6 @@ files = [
 [package.extras]
 dev = ["flake8", "flake8-annotations", "flake8-bandit", "flake8-bugbear", "flake8-commas", "flake8-comprehensions", "flake8-continuation", "flake8-datetimez", "flake8-docstrings", "flake8-import-order", "flake8-literal", "flake8-modern-annotations", "flake8-noqa", "flake8-pyproject", "flake8-requirements", "flake8-typechecking-import", "flake8-use-fstring", "mypy", "pep8-naming", "types-PyYAML"]
 
-[[package]]
-name = "urllib3"
-version = "1.26.18"
-description = "HTTP library with thread-safe connection pooling, file post, and more."
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
-files = [
-    {file = "urllib3-1.26.18-py2.py3-none-any.whl", hash = "sha256:34b97092d7e0a3a8cf7cd10e386f401b3737364026c45e622aa02903dffe0f07"},
-    {file = "urllib3-1.26.18.tar.gz", hash = "sha256:f8ecc1bba5667413457c529ab955bf8c67b45db799d159066261719e328580a0"},
-]
-
-[package.extras]
-brotli = ["brotli (==1.0.9)", "brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"]
-secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"]
-socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
-
 [[package]]
 name = "urllib3"
 version = "2.2.1"
@@ -8891,6 +8826,23 @@ files = [
     {file = "uuid-1.30.tar.gz", hash = "sha256:1f87cc004ac5120466f36c5beae48b4c48cc411968eed0eaecd3da82aa96193f"},
 ]
 
+[[package]]
+name = "vcrpy"
+version = "4.3.0"
+description = "Automatically mock your HTTP interactions to simplify and speed up testing"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "vcrpy-4.3.0-py2.py3-none-any.whl", hash = "sha256:8fbd4be412e8a7f35f623dd61034e6380a1c8dbd0edf6e87277a3289f6e98093"},
+    {file = "vcrpy-4.3.0.tar.gz", hash = "sha256:49c270ce67e826dba027d83e20d25b67a5885487697e97bca6dbdf53d750a0ac"},
+]
+
+[package.dependencies]
+PyYAML = "*"
+six = ">=1.5"
+wrapt = "*"
+yarl = "*"
+
 [[package]]
 name = "vcrpy"
 version = "6.0.1"
@@ -8903,7 +8855,6 @@ files = [
 
 [package.dependencies]
 PyYAML = "*"
-urllib3 = {version = "<2", markers = "platform_python_implementation == \"PyPy\" or python_version < \"3.10\""}
 wrapt = "*"
 yarl = "*"
 
@@ -9456,4 +9407,4 @@ text-helpers = ["chardet"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<4.0"
-content-hash = "6e4b150a47dc6c9cf098b56fef8b53ec711f20e75336eb2d421fe3bbb930906c"
+content-hash = "1faf186ad3d0918b4df6c06c5db9963aa077260fc3ca3a946dd0690939e57e34"
diff --git a/libs/langchain/pyproject.toml b/libs/langchain/pyproject.toml
index 758b57d2ee1..7d17fc687ea 100644
--- a/libs/langchain/pyproject.toml
+++ b/libs/langchain/pyproject.toml
@@ -184,7 +184,7 @@ ruff = "^0.1.5"
 optional = true
 
 [tool.poetry.group.typing.dependencies]
-mypy = "^0.991"
+mypy = "^1"
 types-pyyaml = "^6.0.12.2"
 types-requests = "^2.28.11.5"
 types-toml = "^0.10.8.1"
diff --git a/libs/langchain/tests/integration_tests/chains/test_ontotext_graphdb_qa.py b/libs/langchain/tests/integration_tests/chains/test_ontotext_graphdb_qa.py
index 4f46559585c..77b3c26a5cf 100644
--- a/libs/langchain/tests/integration_tests/chains/test_ontotext_graphdb_qa.py
+++ b/libs/langchain/tests/integration_tests/chains/test_ontotext_graphdb_qa.py
@@ -374,7 +374,9 @@ def test_chain(model_name: str, question: str) -> None:
         "FROM <https://swapi.co/ontology/> WHERE {?s ?p ?o}",
     )
     chain = OntotextGraphDBQAChain.from_llm(
-        ChatOpenAI(temperature=0, model_name=model_name), graph=graph, verbose=True
+        ChatOpenAI(temperature=0, model_name=model_name),
+        graph=graph,
+        verbose=True,  # type: ignore[call-arg]
     )
     try:
         chain.invoke({chain.input_key: question})
diff --git a/libs/langchain/tests/integration_tests/chains/test_react.py b/libs/langchain/tests/integration_tests/chains/test_react.py
index 1615872bac8..b577b778711 100644
--- a/libs/langchain/tests/integration_tests/chains/test_react.py
+++ b/libs/langchain/tests/integration_tests/chains/test_react.py
@@ -8,7 +8,7 @@ from langchain.docstore.wikipedia import Wikipedia
 
 def test_react() -> None:
     """Test functionality on a prompt."""
-    llm = OpenAI(temperature=0, model_name="gpt-3.5-turbo-instruct")
+    llm = OpenAI(temperature=0, model_name="gpt-3.5-turbo-instruct")  # type: ignore[call-arg]
     react = ReActChain(llm=llm, docstore=Wikipedia())
     question = (
         "Author David Chanoff has collaborated with a U.S. Navy admiral "
diff --git a/libs/langchain/tests/integration_tests/memory/test_elasticsearch.py b/libs/langchain/tests/integration_tests/memory/test_elasticsearch.py
index 75c486e6163..38a5d0635dc 100644
--- a/libs/langchain/tests/integration_tests/memory/test_elasticsearch.py
+++ b/libs/langchain/tests/integration_tests/memory/test_elasticsearch.py
@@ -23,7 +23,7 @@ To run against Elastic Cloud, set the following environment variables:
 
 class TestElasticsearch:
     @pytest.fixture(scope="class", autouse=True)
-    def elasticsearch_connection(self) -> Union[dict, Generator[dict, None, None]]:
+    def elasticsearch_connection(self) -> Union[dict, Generator[dict, None, None]]:  # type: ignore[return]
         # Run this integration test against Elasticsearch on localhost,
         # or an Elastic Cloud instance
         from elasticsearch import Elasticsearch
diff --git a/libs/langchain/tests/integration_tests/retrievers/document_compressors/test_embeddings_filter.py b/libs/langchain/tests/integration_tests/retrievers/document_compressors/test_embeddings_filter.py
index 7f0cf64c74a..b433d57bf2b 100644
--- a/libs/langchain/tests/integration_tests/retrievers/document_compressors/test_embeddings_filter.py
+++ b/libs/langchain/tests/integration_tests/retrievers/document_compressors/test_embeddings_filter.py
@@ -35,7 +35,7 @@ def test_embeddings_filter_with_state() -> None:
     state = {"embedded_doc": np.zeros(len(embedded_query))}
     docs = [_DocumentWithState(page_content=t, state=state) for t in texts]
     docs[-1].state = {"embedded_doc": embedded_query}
-    relevant_filter = EmbeddingsFilter(
+    relevant_filter = EmbeddingsFilter(  # type: ignore[call-arg]
         embeddings=embeddings, similarity_threshold=0.75, return_similarity_scores=True
     )
     actual = relevant_filter.compress_documents(docs, query)
diff --git a/libs/langchain/tests/integration_tests/test_dalle.py b/libs/langchain/tests/integration_tests/test_dalle.py
index 9b765827889..6498cfb79c5 100644
--- a/libs/langchain/tests/integration_tests/test_dalle.py
+++ b/libs/langchain/tests/integration_tests/test_dalle.py
@@ -4,6 +4,6 @@ from langchain_community.utilities.dalle_image_generator import DallEAPIWrapper
 
 def test_call() -> None:
     """Test that call returns a URL in the output."""
-    search = DallEAPIWrapper()
+    search = DallEAPIWrapper()  # type: ignore[call-arg]
     output = search.run("volcano island")
     assert "https://oaidalleapi" in output
diff --git a/libs/langchain/tests/unit_tests/agents/test_agent.py b/libs/langchain/tests/unit_tests/agents/test_agent.py
index 5eb571c91bb..5ce9def9092 100644
--- a/libs/langchain/tests/unit_tests/agents/test_agent.py
+++ b/libs/langchain/tests/unit_tests/agents/test_agent.py
@@ -457,7 +457,7 @@ async def test_runnable_agent() -> None:
         return AgentFinish(return_values={"foo": "meow"}, log="hard-coded-message")
 
     agent = template | model | fake_parse
-    executor = AgentExecutor(agent=agent, tools=[])
+    executor = AgentExecutor(agent=agent, tools=[])  # type: ignore[arg-type]
 
     # Invoke
     result = executor.invoke({"question": "hello"})
@@ -573,7 +573,7 @@ async def test_runnable_agent_with_function_calls() -> None:
         return "Spying from under the bed."
 
     agent = template | model | fake_parse
-    executor = AgentExecutor(agent=agent, tools=[find_pet])
+    executor = AgentExecutor(agent=agent, tools=[find_pet])  # type: ignore[arg-type, list-item]
 
     # Invoke
     result = executor.invoke({"question": "hello"})
@@ -685,7 +685,7 @@ async def test_runnable_with_multi_action_per_step() -> None:
         return "purrrr"
 
     agent = template | model | fake_parse
-    executor = AgentExecutor(agent=agent, tools=[find_pet])
+    executor = AgentExecutor(agent=agent, tools=[find_pet])  # type: ignore[arg-type, list-item]
 
     # Invoke
     result = executor.invoke({"question": "hello"})
@@ -819,7 +819,7 @@ async def test_openai_agent_with_streaming() -> None:
         [find_pet],  # type: ignore[list-item]
         template,
     )
-    executor = AgentExecutor(agent=agent, tools=[find_pet])
+    executor = AgentExecutor(agent=agent, tools=[find_pet])  # type: ignore[arg-type, list-item]
 
     # Invoke
     result = executor.invoke({"question": "hello"})
@@ -994,7 +994,7 @@ async def test_openai_agent_tools_agent() -> None:
         [find_pet],  # type: ignore[list-item]
         template,
     )
-    executor = AgentExecutor(agent=agent, tools=[find_pet])
+    executor = AgentExecutor(agent=agent, tools=[find_pet])  # type: ignore[arg-type, list-item]
 
     # Invoke
     result = executor.invoke({"question": "hello"})
diff --git a/libs/langchain/tests/unit_tests/chains/test_conversation_retrieval.py b/libs/langchain/tests/unit_tests/chains/test_conversation_retrieval.py
index e2e62e006a2..1198c27085c 100644
--- a/libs/langchain/tests/unit_tests/chains/test_conversation_retrieval.py
+++ b/libs/langchain/tests/unit_tests/chains/test_conversation_retrieval.py
@@ -14,7 +14,7 @@ async def test_simplea() -> None:
     answer = "I know the answer!"
     llm = FakeListLLM(responses=[answer])
     retriever = SequentialRetriever(sequential_responses=[[]])
-    memory = ConversationBufferMemory(
+    memory = ConversationBufferMemory(  # type: ignore[call-arg]
         k=1, output_key="answer", memory_key="chat_history", return_messages=True
     )
     qa_chain = ConversationalRetrievalChain.from_llm(
@@ -38,7 +38,7 @@ async def test_fixed_message_response_when_docs_founda() -> None:
     retriever = SequentialRetriever(
         sequential_responses=[[Document(page_content=answer)]]
     )
-    memory = ConversationBufferMemory(
+    memory = ConversationBufferMemory(  # type: ignore[call-arg]
         k=1, output_key="answer", memory_key="chat_history", return_messages=True
     )
     qa_chain = ConversationalRetrievalChain.from_llm(
@@ -60,7 +60,7 @@ def test_fixed_message_response_when_no_docs_found() -> None:
     answer = "I know the answer!"
     llm = FakeListLLM(responses=[answer])
     retriever = SequentialRetriever(sequential_responses=[[]])
-    memory = ConversationBufferMemory(
+    memory = ConversationBufferMemory(  # type: ignore[call-arg]
         k=1, output_key="answer", memory_key="chat_history", return_messages=True
     )
     qa_chain = ConversationalRetrievalChain.from_llm(
@@ -84,7 +84,7 @@ def test_fixed_message_response_when_docs_found() -> None:
     retriever = SequentialRetriever(
         sequential_responses=[[Document(page_content=answer)]]
     )
-    memory = ConversationBufferMemory(
+    memory = ConversationBufferMemory(  # type: ignore[call-arg]
         k=1, output_key="answer", memory_key="chat_history", return_messages=True
     )
     qa_chain = ConversationalRetrievalChain.from_llm(
diff --git a/libs/langchain/tests/unit_tests/chains/test_sequential.py b/libs/langchain/tests/unit_tests/chains/test_sequential.py
index ca2ff78e7aa..5b6c4e36302 100644
--- a/libs/langchain/tests/unit_tests/chains/test_sequential.py
+++ b/libs/langchain/tests/unit_tests/chains/test_sequential.py
@@ -58,7 +58,7 @@ def test_sequential_usage_single_inputs() -> None:
     """Test sequential on single input chains."""
     chain_1 = FakeChain(input_variables=["foo"], output_variables=["bar"])
     chain_2 = FakeChain(input_variables=["bar"], output_variables=["baz"])
-    chain = SequentialChain(chains=[chain_1, chain_2], input_variables=["foo"])
+    chain = SequentialChain(chains=[chain_1, chain_2], input_variables=["foo"])  # type: ignore[call-arg]
     output = chain({"foo": "123"})
     expected_output = {"baz": "123foofoo", "foo": "123"}
     assert output == expected_output
@@ -68,7 +68,7 @@ def test_sequential_usage_multiple_inputs() -> None:
     """Test sequential on multiple input chains."""
     chain_1 = FakeChain(input_variables=["foo", "test"], output_variables=["bar"])
     chain_2 = FakeChain(input_variables=["bar", "foo"], output_variables=["baz"])
-    chain = SequentialChain(chains=[chain_1, chain_2], input_variables=["foo", "test"])
+    chain = SequentialChain(chains=[chain_1, chain_2], input_variables=["foo", "test"])  # type: ignore[call-arg]
     output = chain({"foo": "123", "test": "456"})
     expected_output = {
         "baz": "123 456foo 123foo",
@@ -83,7 +83,7 @@ def test_sequential_usage_memory() -> None:
     memory = SimpleMemory(memories={"zab": "rab"})
     chain_1 = FakeChain(input_variables=["foo"], output_variables=["bar"])
     chain_2 = FakeChain(input_variables=["bar"], output_variables=["baz"])
-    chain = SequentialChain(
+    chain = SequentialChain(  # type: ignore[call-arg]
         memory=memory, chains=[chain_1, chain_2], input_variables=["foo"]
     )
     output = chain({"foo": "123"})
@@ -93,7 +93,7 @@ def test_sequential_usage_memory() -> None:
     chain_1 = FakeChain(input_variables=["foo"], output_variables=["bar"])
     chain_2 = FakeChain(input_variables=["bar"], output_variables=["baz"])
     with pytest.raises(ValueError):
-        SequentialChain(
+        SequentialChain(  # type: ignore[call-arg]
             memory=memory, chains=[chain_1, chain_2], input_variables=["foo"]
         )
 
@@ -106,7 +106,7 @@ def test_sequential_internal_chain_use_memory() -> None:
         input_variables=["foo", "bla"], output_variables=["bar"], memory=memory
     )
     chain_2 = FakeChain(input_variables=["bar"], output_variables=["baz"])
-    chain = SequentialChain(chains=[chain_1, chain_2], input_variables=["foo"])
+    chain = SequentialChain(chains=[chain_1, chain_2], input_variables=["foo"])  # type: ignore[call-arg]
     output = chain({"foo": "123"})
     print("HEYYY OUTPUT", output)  # noqa: T201
     expected_output = {"foo": "123", "baz": "123 Human: yo\nAI: yafoofoo"}
@@ -117,7 +117,7 @@ def test_sequential_usage_multiple_outputs() -> None:
     """Test sequential usage on multiple output chains."""
     chain_1 = FakeChain(input_variables=["foo"], output_variables=["bar", "test"])
     chain_2 = FakeChain(input_variables=["bar", "foo"], output_variables=["baz"])
-    chain = SequentialChain(chains=[chain_1, chain_2], input_variables=["foo"])
+    chain = SequentialChain(chains=[chain_1, chain_2], input_variables=["foo"])  # type: ignore[call-arg]
     output = chain({"foo": "123"})
     expected_output = {
         "baz": "123foo 123foo",
@@ -132,7 +132,7 @@ def test_sequential_missing_inputs() -> None:
     chain_2 = FakeChain(input_variables=["bar", "test"], output_variables=["baz"])
     with pytest.raises(ValueError):
         # Also needs "test" as an input
-        SequentialChain(chains=[chain_1, chain_2], input_variables=["foo"])
+        SequentialChain(chains=[chain_1, chain_2], input_variables=["foo"])  # type: ignore[call-arg]
 
 
 def test_sequential_bad_outputs() -> None:
@@ -168,7 +168,7 @@ def test_sequential_overlapping_inputs() -> None:
     chain_2 = FakeChain(input_variables=["bar"], output_variables=["baz"])
     with pytest.raises(ValueError):
         # "test" is specified as an input, but also is an output of one step
-        SequentialChain(chains=[chain_1, chain_2], input_variables=["foo", "test"])
+        SequentialChain(chains=[chain_1, chain_2], input_variables=["foo", "test"])  # type: ignore[call-arg]
 
 
 def test_simple_sequential_functionality() -> None:
diff --git a/libs/langchain/tests/unit_tests/chains/test_transform.py b/libs/langchain/tests/unit_tests/chains/test_transform.py
index a4a1cd08ff8..054b8468fe8 100644
--- a/libs/langchain/tests/unit_tests/chains/test_transform.py
+++ b/libs/langchain/tests/unit_tests/chains/test_transform.py
@@ -17,7 +17,7 @@ def dummy_transform(inputs: Dict[str, str]) -> Dict[str, str]:
 
 def test_transform_chain() -> None:
     """Test basic transform chain."""
-    transform_chain = TransformChain(
+    transform_chain = TransformChain(  # type: ignore[call-arg]
         input_variables=["first_name", "last_name"],
         output_variables=["greeting"],
         transform=dummy_transform,
@@ -30,7 +30,7 @@ def test_transform_chain() -> None:
 
 def test_transform_chain_bad_inputs() -> None:
     """Test basic transform chain."""
-    transform_chain = TransformChain(
+    transform_chain = TransformChain(  # type: ignore[call-arg]
         input_variables=["first_name", "last_name"],
         output_variables=["greeting"],
         transform=dummy_transform,
diff --git a/libs/langchain/tests/unit_tests/indexes/test_hashed_document.py b/libs/langchain/tests/unit_tests/indexes/test_hashed_document.py
index ff0121967ca..6c79fe6624a 100644
--- a/libs/langchain/tests/unit_tests/indexes/test_hashed_document.py
+++ b/libs/langchain/tests/unit_tests/indexes/test_hashed_document.py
@@ -5,7 +5,7 @@ from langchain.indexes._api import _HashedDocument
 
 
 def test_hashed_document_hashing() -> None:
-    hashed_document = _HashedDocument(
+    hashed_document = _HashedDocument(  # type: ignore[call-arg]
         uid="123", page_content="Lorem ipsum dolor sit amet", metadata={"key": "value"}
     )
     assert isinstance(hashed_document.hash_, str)
@@ -21,7 +21,7 @@ def test_hashing_with_missing_content() -> None:
 
 def test_uid_auto_assigned_to_hash() -> None:
     """Test uid is auto-assigned to the hashed_document hash."""
-    hashed_document = _HashedDocument(
+    hashed_document = _HashedDocument(  # type: ignore[call-arg]
         page_content="Lorem ipsum dolor sit amet", metadata={"key": "value"}
     )
     assert hashed_document.uid == hashed_document.hash_
@@ -29,7 +29,7 @@ def test_uid_auto_assigned_to_hash() -> None:
 
 def test_to_document() -> None:
     """Test to_document method."""
-    hashed_document = _HashedDocument(
+    hashed_document = _HashedDocument(  # type: ignore[call-arg]
         page_content="Lorem ipsum dolor sit amet", metadata={"key": "value"}
     )
     doc = hashed_document.to_document()
diff --git a/libs/langchain/tests/unit_tests/load/test_dump.py b/libs/langchain/tests/unit_tests/load/test_dump.py
index 5989f609d26..e3e1003d30e 100644
--- a/libs/langchain/tests/unit_tests/load/test_dump.py
+++ b/libs/langchain/tests/unit_tests/load/test_dump.py
@@ -79,7 +79,7 @@ def test_typeerror() -> None:
 @pytest.mark.requires("openai")
 def test_serialize_openai_llm(snapshot: Any) -> None:
     with patch.dict(os.environ, {"LANGCHAIN_API_KEY": "test-api-key"}):
-        llm = OpenAI(
+        llm = OpenAI(  # type: ignore[call-arg]
             model="davinci",
             temperature=0.5,
             openai_api_key="hello",
@@ -92,7 +92,7 @@ def test_serialize_openai_llm(snapshot: Any) -> None:
 
 @pytest.mark.requires("openai")
 def test_serialize_llmchain(snapshot: Any) -> None:
-    llm = OpenAI(model="davinci", temperature=0.5, openai_api_key="hello")
+    llm = OpenAI(model="davinci", temperature=0.5, openai_api_key="hello")  # type: ignore[call-arg]
     prompt = PromptTemplate.from_template("hello {name}!")
     chain = LLMChain(llm=llm, prompt=prompt)
     assert dumps(chain, pretty=True) == snapshot
@@ -100,7 +100,7 @@ def test_serialize_llmchain(snapshot: Any) -> None:
 
 @pytest.mark.requires("openai")
 def test_serialize_llmchain_env() -> None:
-    llm = OpenAI(model="davinci", temperature=0.5, openai_api_key="hello")
+    llm = OpenAI(model="davinci", temperature=0.5, openai_api_key="hello")  # type: ignore[call-arg]
     prompt = PromptTemplate.from_template("hello {name}!")
     chain = LLMChain(llm=llm, prompt=prompt)
 
@@ -110,7 +110,7 @@ def test_serialize_llmchain_env() -> None:
     if not has_env:
         os.environ["OPENAI_API_KEY"] = "env_variable"
 
-    llm_2 = OpenAI(model="davinci", temperature=0.5)
+    llm_2 = OpenAI(model="davinci", temperature=0.5)  # type: ignore[call-arg]
     prompt_2 = PromptTemplate.from_template("hello {name}!")
     chain_2 = LLMChain(llm=llm_2, prompt=prompt_2)
 
@@ -122,7 +122,7 @@ def test_serialize_llmchain_env() -> None:
 
 @pytest.mark.requires("openai")
 def test_serialize_llmchain_chat(snapshot: Any) -> None:
-    llm = ChatOpenAI(model="davinci", temperature=0.5, openai_api_key="hello")
+    llm = ChatOpenAI(model="davinci", temperature=0.5, openai_api_key="hello")  # type: ignore[call-arg]
     prompt = ChatPromptTemplate.from_messages(
         [HumanMessagePromptTemplate.from_template("hello {name}!")]
     )
@@ -135,7 +135,7 @@ def test_serialize_llmchain_chat(snapshot: Any) -> None:
     if not has_env:
         os.environ["OPENAI_API_KEY"] = "env_variable"
 
-    llm_2 = ChatOpenAI(model="davinci", temperature=0.5)
+    llm_2 = ChatOpenAI(model="davinci", temperature=0.5)  # type: ignore[call-arg]
     prompt_2 = ChatPromptTemplate.from_messages(
         [HumanMessagePromptTemplate.from_template("hello {name}!")]
     )
@@ -149,7 +149,7 @@ def test_serialize_llmchain_chat(snapshot: Any) -> None:
 
 @pytest.mark.requires("openai")
 def test_serialize_llmchain_with_non_serializable_arg(snapshot: Any) -> None:
-    llm = OpenAI(
+    llm = OpenAI(  # type: ignore[call-arg]
         model="davinci",
         temperature=0.5,
         openai_api_key="hello",
@@ -206,7 +206,7 @@ class TestClass(Serializable):
 
 
 def test_aliases_hidden() -> None:
-    test_class = TestClass(my_favorite_secret="hello", my_other_secret="world")
+    test_class = TestClass(my_favorite_secret="hello", my_other_secret="world")  # type: ignore[call-arg]
     dumped = json.loads(dumps(test_class, pretty=True))
     expected_dump = {
         "lc": 1,
@@ -226,11 +226,11 @@ def test_aliases_hidden() -> None:
     with patch.dict(
         os.environ, {"MY_FAVORITE_SECRET": "hello", "MY_OTHER_SECRET": "world"}
     ):
-        test_class = TestClass()
+        test_class = TestClass()  # type: ignore[call-arg]
         dumped = json.loads(dumps(test_class, pretty=True))
 
     # Check by alias
-    test_class = TestClass(my_favorite_secret_alias="hello", my_other_secret="world")
+    test_class = TestClass(my_favorite_secret_alias="hello", my_other_secret="world")  # type: ignore[call-arg]
     dumped = json.loads(dumps(test_class, pretty=True))
     expected_dump = {
         "lc": 1,
diff --git a/libs/langchain/tests/unit_tests/load/test_load.py b/libs/langchain/tests/unit_tests/load/test_load.py
index 4266c3f45bf..1fd22bbaa86 100644
--- a/libs/langchain/tests/unit_tests/load/test_load.py
+++ b/libs/langchain/tests/unit_tests/load/test_load.py
@@ -17,7 +17,7 @@ class NotSerializable:
 def test_loads_openai_llm() -> None:
     from langchain_openai import OpenAI
 
-    llm = CommunityOpenAI(model="davinci", temperature=0.5, openai_api_key="hello")
+    llm = CommunityOpenAI(model="davinci", temperature=0.5, openai_api_key="hello")  # type: ignore[call-arg]
     llm_string = dumps(llm)
     llm2 = loads(llm_string, secrets_map={"OPENAI_API_KEY": "hello"})
 
@@ -31,7 +31,7 @@ def test_loads_openai_llm() -> None:
 def test_loads_llmchain() -> None:
     from langchain_openai import OpenAI
 
-    llm = CommunityOpenAI(model="davinci", temperature=0.5, openai_api_key="hello")
+    llm = CommunityOpenAI(model="davinci", temperature=0.5, openai_api_key="hello")  # type: ignore[call-arg]
     prompt = PromptTemplate.from_template("hello {name}!")
     chain = LLMChain(llm=llm, prompt=prompt)
     chain_string = dumps(chain)
@@ -54,7 +54,7 @@ def test_loads_llmchain_env() -> None:
     if not has_env:
         os.environ["OPENAI_API_KEY"] = "env_variable"
 
-    llm = OpenAI(model="davinci", temperature=0.5)
+    llm = OpenAI(model="davinci", temperature=0.5)  # type: ignore[call-arg]
     prompt = PromptTemplate.from_template("hello {name}!")
     chain = LLMChain(llm=llm, prompt=prompt)
     chain_string = dumps(chain)
@@ -72,7 +72,7 @@ def test_loads_llmchain_env() -> None:
 
 @pytest.mark.requires("openai")
 def test_loads_llmchain_with_non_serializable_arg() -> None:
-    llm = CommunityOpenAI(
+    llm = CommunityOpenAI(  # type: ignore[call-arg]
         model="davinci",
         temperature=0.5,
         openai_api_key="hello",
@@ -89,7 +89,7 @@ def test_loads_llmchain_with_non_serializable_arg() -> None:
 def test_load_openai_llm() -> None:
     from langchain_openai import OpenAI
 
-    llm = CommunityOpenAI(model="davinci", temperature=0.5, openai_api_key="hello")
+    llm = CommunityOpenAI(model="davinci", temperature=0.5, openai_api_key="hello")  # type: ignore[call-arg]
     llm_obj = dumpd(llm)
     llm2 = load(llm_obj, secrets_map={"OPENAI_API_KEY": "hello"})
 
@@ -102,7 +102,7 @@ def test_load_openai_llm() -> None:
 def test_load_llmchain() -> None:
     from langchain_openai import OpenAI
 
-    llm = CommunityOpenAI(model="davinci", temperature=0.5, openai_api_key="hello")
+    llm = CommunityOpenAI(model="davinci", temperature=0.5, openai_api_key="hello")  # type: ignore[call-arg]
     prompt = PromptTemplate.from_template("hello {name}!")
     chain = LLMChain(llm=llm, prompt=prompt)
     chain_obj = dumpd(chain)
@@ -125,7 +125,7 @@ def test_load_llmchain_env() -> None:
     if not has_env:
         os.environ["OPENAI_API_KEY"] = "env_variable"
 
-    llm = CommunityOpenAI(model="davinci", temperature=0.5)
+    llm = CommunityOpenAI(model="davinci", temperature=0.5)  # type: ignore[call-arg]
     prompt = PromptTemplate.from_template("hello {name}!")
     chain = LLMChain(llm=llm, prompt=prompt)
     chain_obj = dumpd(chain)
@@ -143,7 +143,7 @@ def test_load_llmchain_env() -> None:
 
 @pytest.mark.requires("openai")
 def test_load_llmchain_with_non_serializable_arg() -> None:
-    llm = CommunityOpenAI(
+    llm = CommunityOpenAI(  # type: ignore[call-arg]
         model="davinci",
         temperature=0.5,
         openai_api_key="hello",
diff --git a/libs/langchain/tests/unit_tests/retrievers/test_ensemble.py b/libs/langchain/tests/unit_tests/retrievers/test_ensemble.py
index 8b9cbbed115..c4eb6397cc0 100644
--- a/libs/langchain/tests/unit_tests/retrievers/test_ensemble.py
+++ b/libs/langchain/tests/unit_tests/retrievers/test_ensemble.py
@@ -18,7 +18,7 @@ def test_ensemble_retriever_get_relevant_docs() -> None:
     dummy_retriever = BM25Retriever.from_texts(doc_list)
     dummy_retriever.k = 1
 
-    ensemble_retriever = EnsembleRetriever(
+    ensemble_retriever = EnsembleRetriever(  # type: ignore[call-arg]
         retrievers=[dummy_retriever, dummy_retriever]
     )
     docs = ensemble_retriever.get_relevant_documents("I like apples")
diff --git a/libs/langchain/tests/unit_tests/retrievers/test_multi_vector.py b/libs/langchain/tests/unit_tests/retrievers/test_multi_vector.py
index 648d8252141..e35244c77d4 100644
--- a/libs/langchain/tests/unit_tests/retrievers/test_multi_vector.py
+++ b/libs/langchain/tests/unit_tests/retrievers/test_multi_vector.py
@@ -19,7 +19,7 @@ class InMemoryVectorstoreWithSearch(InMemoryVectorStore):
 
 def test_multi_vector_retriever_initialization() -> None:
     vectorstore = InMemoryVectorstoreWithSearch()
-    retriever = MultiVectorRetriever(
+    retriever = MultiVectorRetriever(  # type: ignore[call-arg]
         vectorstore=vectorstore, docstore=InMemoryStore(), doc_id="doc_id"
     )
     documents = [Document(page_content="test document", metadata={"doc_id": "1"})]
@@ -32,7 +32,7 @@ def test_multi_vector_retriever_initialization() -> None:
 
 async def test_multi_vector_retriever_initialization_async() -> None:
     vectorstore = InMemoryVectorstoreWithSearch()
-    retriever = MultiVectorRetriever(
+    retriever = MultiVectorRetriever(  # type: ignore[call-arg]
         vectorstore=vectorstore, docstore=InMemoryStore(), doc_id="doc_id"
     )
     documents = [Document(page_content="test document", metadata={"doc_id": "1"})]
diff --git a/libs/langchain/tests/unit_tests/smith/evaluation/test_runner_utils.py b/libs/langchain/tests/unit_tests/smith/evaluation/test_runner_utils.py
index ddbe4af7e02..702d626fac1 100644
--- a/libs/langchain/tests/unit_tests/smith/evaluation/test_runner_utils.py
+++ b/libs/langchain/tests/unit_tests/smith/evaluation/test_runner_utils.py
@@ -172,7 +172,7 @@ def test_run_llm_or_chain_with_input_mapper() -> None:
         assert "the right input" in inputs
         return {"output": "2"}
 
-    mock_chain = TransformChain(
+    mock_chain = TransformChain(  # type: ignore[call-arg]
         input_variables=["the right input"],
         output_variables=["output"],
         transform=run_val,