[Bug]: TypeError: create() got an unexpected keyword argument 'tags' when using LCEL

[aditya624]

Current Behavior

If I use LangChain Expression Language (LCEL) an error occurs TypeError: create() got an unexpected keyword argument 'tags'

llm = ChatOpenAI(temperature=0)
llm_cache = LangChainChat(chat=llm)

sql_response = (
    RunnablePassthrough.assign(
            table_info=get_schema,
            dialect=get_dialect,
            few_shot_examples=lambda x: get_similar_data(x["input"]),
            history=RunnableLambda(memory_zep.load_memory_variables) | itemgetter("history"),
        )
    | prompt
    | llm.bind(stop=["\nSQLResult:"])
    | StrOutputParser()
)

full_chain = (
    RunnablePassthrough.assign(query=sql_response).assign(
        table_info=get_schema,
        response=lambda x: db.run(x["query"]),
    )
    | prompt_reponse
    | llm_cache
)

full_chain.invoke({"input":"..."})

Expected Behavior

The hope is that there will be no such errors when using LCEL.

Steps To Reproduce

No response

Environment

langchain                             0.1.5
langchain-community                   0.0.19
langchain-core                        0.1.21
langchain-experimental                0.0.50
langchain-openai                      0.0.5
langchainhub                          0.1.14
gptcache                              0.1.43
openai                                1.11.1

TypeError                                 Traceback (most recent call last)
Cell In[49], line 2
      1 # response = full_chain.invoke(inputs, config={'callbacks': [ConsoleCallbackHandler()]})
----> 2 response = full_chain.invoke(inputs, config={'callbacks': [ConsoleCallbackHandler()]})

File /opt/conda/envs/agent/lib/python3.9/site-packages/langchain_core/runnables/base.py:2053, in RunnableSequence.invoke(self, input, config)
   2051 try:
   2052     for i, step in enumerate(self.steps):
-> 2053         input = step.invoke(
   2054             input,
   2055             # mark each step as a child run
   2056             patch_config(
   2057                 config, callbacks=run_manager.get_child(f"seq:step:{i+1}")
   2058             ),
   2059         )
   2060 # finish the root run
   2061 except BaseException as e:

File /opt/conda/envs/agent/lib/python3.9/site-packages/langchain_core/language_models/chat_models.py:166, in BaseChatModel.invoke(self, input, config, stop, **kwargs)
    155 def invoke(
    156     self,
    157     input: LanguageModelInput,
   (...)
    161     **kwargs: Any,
    162 ) -> BaseMessage:
    163     config = ensure_config(config)
    164     return cast(
    165         ChatGeneration,
--> 166         self.generate_prompt(
    167             [self._convert_input(input)],
    168             stop=stop,
    169             callbacks=config.get("callbacks"),
    170             tags=config.get("tags"),
    171             metadata=config.get("metadata"),
    172             run_name=config.get("run_name"),
    173             **kwargs,
    174         ).generations[0][0],
    175     ).message

File /opt/conda/envs/agent/lib/python3.9/site-packages/langchain_core/language_models/chat_models.py:544, in BaseChatModel.generate_prompt(self, prompts, stop, callbacks, **kwargs)
    536 def generate_prompt(
    537     self,
    538     prompts: List[PromptValue],
   (...)
    541     **kwargs: Any,
    542 ) -> LLMResult:
    543     prompt_messages = [p.to_messages() for p in prompts]
--> 544     return self.generate(prompt_messages, stop=stop, callbacks=callbacks, **kwargs)

File /opt/conda/envs/agent/lib/python3.9/site-packages/gptcache/adapter/langchain_models.py:213, in LangChainChat.generate(self, messages, stop, callbacks, **kwargs)
    205 def generate(
    206     self,
    207     messages: List[List[BaseMessage]],
   (...)
    210     **kwargs,
    211 ) -> LLMResult:
    212     self.tmp_args = kwargs
--> 213     return super().generate(messages, stop=stop, callbacks=callbacks)

File /opt/conda/envs/agent/lib/python3.9/site-packages/langchain_core/language_models/chat_models.py:408, in BaseChatModel.generate(self, messages, stop, callbacks, tags, metadata, run_name, **kwargs)
    406         if run_managers:
    407             run_managers[i].on_llm_error(e, response=LLMResult(generations=[]))
--> 408         raise e
    409 flattened_outputs = [
    410     LLMResult(generations=[res.generations], llm_output=res.llm_output)
    411     for res in results
    412 ]
    413 llm_output = self._combine_llm_outputs([res.llm_output for res in results])

File /opt/conda/envs/agent/lib/python3.9/site-packages/langchain_core/language_models/chat_models.py:398, in BaseChatModel.generate(self, messages, stop, callbacks, tags, metadata, run_name, **kwargs)
    395 for i, m in enumerate(messages):
    396     try:
    397         results.append(
--> 398             self._generate_with_cache(
    399                 m,
    400                 stop=stop,
    401                 run_manager=run_managers[i] if run_managers else None,
    402                 **kwargs,
    403             )
    404         )
    405     except BaseException as e:
    406         if run_managers:

File /opt/conda/envs/agent/lib/python3.9/site-packages/langchain_core/language_models/chat_models.py:577, in BaseChatModel._generate_with_cache(self, messages, stop, run_manager, **kwargs)
    573     raise ValueError(
    574         "Asked to cache, but no cache found at `langchain.cache`."
    575     )
    576 if new_arg_supported:
--> 577     return self._generate(
    578         messages, stop=stop, run_manager=run_manager, **kwargs
    579     )
    580 else:
    581     return self._generate(messages, stop=stop, **kwargs)

File /opt/conda/envs/agent/lib/python3.9/site-packages/gptcache/adapter/langchain_models.py:169, in LangChainChat._generate(self, messages, stop, run_manager)
    163 session = (
    164     self.session
    165     if "session" not in self.tmp_args
    166     else self.tmp_args.pop("session")
    167 )
    168 cache_obj = self.tmp_args.pop("cache_obj", cache)
--> 169 return adapt(
    170     self.chat._generate,
    171     _cache_msg_data_convert,
    172     _update_cache_msg_callback,
    173     messages=messages,
    174     stop=stop,
    175     cache_obj=cache_obj,
    176     session=session,
    177     run_manager=run_manager,
    178     **self.tmp_args,
    179 )

File /opt/conda/envs/agent/lib/python3.9/site-packages/gptcache/adapter/adapter.py:241, in adapt(llm_handler, cache_data_convert, update_cache_callback, *args, **kwargs)
    238     if search_only_flag:
    239         # cache miss
    240         return None
--> 241     llm_data = time_cal(
    242         llm_handler, func_name="llm_request", report_func=chat_cache.report.llm
    243     )(*args, **kwargs)
    245 if not llm_data:
    246     return None

File /opt/conda/envs/agent/lib/python3.9/site-packages/gptcache/utils/time.py:9, in time_cal.<locals>.inner(*args, **kwargs)
      7 def inner(*args, **kwargs):
      8     time_start = time.time()
----> 9     res = func(*args, **kwargs)
     10     delta_time = time.time() - time_start
     11     if cache.config.log_time_func:

File /opt/conda/envs/agent/lib/python3.9/site-packages/langchain_community/chat_models/openai.py:435, in ChatOpenAI._generate(self, messages, stop, run_manager, stream, **kwargs)
    429 message_dicts, params = self._create_message_dicts(messages, stop)
    430 params = {
    431     **params,
    432     **({"stream": stream} if stream is not None else {}),
    433     **kwargs,
    434 }
--> 435 response = self.completion_with_retry(
    436     messages=message_dicts, run_manager=run_manager, **params
    437 )
    438 return self._create_chat_result(response)

File /opt/conda/envs/agent/lib/python3.9/site-packages/langchain_community/chat_models/openai.py:352, in ChatOpenAI.completion_with_retry(self, run_manager, **kwargs)
    350 """Use tenacity to retry the completion call."""
    351 if is_openai_v1():
--> 352     return self.client.create(**kwargs)
    354 retry_decorator = _create_retry_decorator(self, run_manager=run_manager)
    356 @retry_decorator
    357 def _completion_with_retry(**kwargs: Any) -> Any:

File /opt/conda/envs/agent/lib/python3.9/site-packages/openai/_utils/_utils.py:271, in required_args.<locals>.inner.<locals>.wrapper(*args, **kwargs)
    269             msg = f"Missing required argument: {quote(missing[0])}"
    270     raise TypeError(msg)
--> 271 return func(*args, **kwargs)

TypeError: create() got an unexpected keyword argument 'tags'

Anything else?

No response