### Checked other resources

- [X] I added a very descriptive title to this issue.
- [X] I searched the LangChain documentation with the integrated search.
- [X] I used the GitHub search to find a similar question and didn't find it.
- [X] I am sure that this is a bug in LangChain rather than my code.
- [X] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package).

### Example Code

```
from langchain_core.prompts import ChatPromptTemplate
from langchain.llms import OpenAI
from langchain.schema.output_parser import StrOutputParser


model = OpenAI(model_name='gpt-4o')
prompt = ChatPromptTemplate.from_template('tell me a joke: {question}')
question = "a funny one"

async def get_question(query):
    return 'tell me a joke'
    

chain = (
    {
        "question": get_question,
    }
    | prompt
    | model
    | StrOutputParser()
)

# Define a function to invoke the chain
async def invoke_chain(question):
    result = await chain.ainvoke(question)
    return result

# Example usage


# Run the async function and get the result
result = await invoke_chain(question)
print(result)
```


### Error Message and Stack Trace (if applicable)


```
---> 32 result = await invoke_chain(question)
     33 print(result)

Cell In[13], line 25, in invoke_chain(question)
     24 async def invoke_chain(question):
---> 25     result = await chain.ainvoke(question)
     26     return result

File ~/dev/sparkai-chatbot/venv/lib/python3.11/site-packages/langchain_core/runnables/base.py:2436, in RunnableSequence.ainvoke(self, input, config, **kwargs)
   2434 try:
   2435     for i, step in enumerate(self.steps):
-> 2436         input = await step.ainvoke(
   2437             input,
   2438             # mark each step as a child run
   2439             patch_config(
   2440                 config, callbacks=run_manager.get_child(f"seq:step:{i+1}")
   2441             ),
   2442         )
   2443 # finish the root run
   2444 except BaseException as e:

File ~/dev/sparkai-chatbot/venv/lib/python3.11/site-packages/langchain_core/language_models/llms.py:299, in BaseLLM.ainvoke(self, input, config, stop, **kwargs)
    290 async def ainvoke(
    291     self,
    292     input: LanguageModelInput,
   (...)
    296     **kwargs: Any,
    297 ) -> str:
    298     config = ensure_config(config)
--> 299     llm_result = await self.agenerate_prompt(
    300         [self._convert_input(input)],
    301         stop=stop,
    302         callbacks=config.get("callbacks"),
    303         tags=config.get("tags"),
    304         metadata=config.get("metadata"),
    305         run_name=config.get("run_name"),
    306         run_id=config.pop("run_id", None),
    307         **kwargs,
    308     )
    309     return llm_result.generations[0][0].text

File ~/dev/sparkai-chatbot/venv/lib/python3.11/site-packages/langchain_core/language_models/llms.py:643, in BaseLLM.agenerate_prompt(self, prompts, stop, callbacks, **kwargs)
    635 async def agenerate_prompt(
    636     self,
    637     prompts: List[PromptValue],
   (...)
    640     **kwargs: Any,
    641 ) -> LLMResult:
    642     prompt_strings = [p.to_string() for p in prompts]
--> 643     return await self.agenerate(
    644         prompt_strings, stop=stop, callbacks=callbacks, **kwargs
    645     )

File ~/dev/sparkai-chatbot/venv/lib/python3.11/site-packages/langchain_core/language_models/llms.py:1018, in BaseLLM.agenerate(self, prompts, stop, callbacks, tags, metadata, run_name, run_id, **kwargs)
   1001     run_managers = await asyncio.gather(
   1002         *[
   1003             callback_manager.on_llm_start(
   (...)
   1015         ]
   1016     )
   1017     run_managers = [r[0] for r in run_managers]  # type: ignore[misc]
-> 1018     output = await self._agenerate_helper(
   1019         prompts,
   1020         stop,
   1021         run_managers,  # type: ignore[arg-type]
   1022         bool(new_arg_supported),
   1023         **kwargs,  # type: ignore[arg-type]
   1024     )
   1025     return output
   1026 if len(missing_prompts) > 0:

File ~/dev/sparkai-chatbot/venv/lib/python3.11/site-packages/langchain_core/language_models/llms.py:882, in BaseLLM._agenerate_helper(self, prompts, stop, run_managers, new_arg_supported, **kwargs)
    875 except BaseException as e:
    876     await asyncio.gather(
    877         *[
    878             run_manager.on_llm_error(e, response=LLMResult(generations=[]))
    879             for run_manager in run_managers
    880         ]
    881     )
--> 882     raise e
    883 flattened_outputs = output.flatten()
    884 await asyncio.gather(
    885     *[
    886         run_manager.on_llm_end(flattened_output)
   (...)
    890     ]
    891 )

File ~/dev/sparkai-chatbot/venv/lib/python3.11/site-packages/langchain_core/language_models/llms.py:866, in BaseLLM._agenerate_helper(self, prompts, stop, run_managers, new_arg_supported, **kwargs)
    856 async def _agenerate_helper(
    857     self,
    858     prompts: List[str],
   (...)
    862     **kwargs: Any,
    863 ) -> LLMResult:
    864     try:
    865         output = (
--> 866             await self._agenerate(
    867                 prompts,
    868                 stop=stop,
    869                 run_manager=run_managers[0] if run_managers else None,
    870                 **kwargs,
    871             )
    872             if new_arg_supported
    873             else await self._agenerate(prompts, stop=stop)
    874         )
    875     except BaseException as e:
    876         await asyncio.gather(
    877             *[
    878                 run_manager.on_llm_error(e, response=LLMResult(generations=[]))
    879                 for run_manager in run_managers
    880             ]
    881         )

File ~/dev/sparkai-chatbot/venv/lib/python3.11/site-packages/langchain_community/llms/openai.py:1194, in OpenAIChat._agenerate(self, prompts, stop, run_manager, **kwargs)
   1192 messages, params = self._get_chat_params(prompts, stop)
   1193 params = {**params, **kwargs}
-> 1194 full_response = await acompletion_with_retry(
   1195     self, messages=messages, run_manager=run_manager, **params
   1196 )
   1197 if not isinstance(full_response, dict):
   1198     full_response = full_response.dict()

File ~/dev/sparkai-chatbot/venv/lib/python3.11/site-packages/langchain_community/llms/openai.py:133, in acompletion_with_retry(llm, run_manager, **kwargs)
    131 """Use tenacity to retry the async completion call."""
    132 if is_openai_v1():
--> 133     return await llm.async_client.create(**kwargs)
    135 retry_decorator = _create_retry_decorator(llm, run_manager=run_manager)
    137 @retry_decorator
    138 async def _completion_with_retry(**kwargs: Any) -> Any:
    139     # Use OpenAI's async api https://github.com/openai/openai-python#async-api

AttributeError: 'NoneType' object has no attribute 'create'

```

### Description

Doing async calls to langchain seem to break when I update OpenAI package to version >=1.0

### System Info

latest version from github or any other version is affected
Langchain using chain.ainvoke for async breaks with OpenAI>=1.0: AttributeError: 'NoneType' object has no attribute 'create
This is a GitHub Issue
repo:langchain
owner:hwchase17
Title : Langchain using chain.ainvoke for async breaks with OpenAI>=1.0: AttributeError: 'NoneType' object has no attribute 'create
Issue date:

--- start body ---
### Checked other resources

- [X] I added a very descriptive title to this issue.
- [X] I searched the LangChain documentation with the integrated search.
- [X] I used the GitHub search to find a similar question and didn't find it.
- [X] I am sure that this is a bug in LangChain rather than my code.
- [X] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package).

### Example Code

```
from langchain_core.prompts import ChatPromptTemplate
from langchain.llms import OpenAI
from langchain.schema.output_parser import StrOutputParser


model = OpenAI(model_name='gpt-4o')
prompt = ChatPromptTemplate.from_template('tell me a joke: {question}')
question = "a funny one"

async def get_question(query):
    return 'tell me a joke'
    

chain = (
    {
        "question": get_question,
    }
    | prompt
    | model
    | StrOutputParser()
)

# Define a function to invoke the chain
async def invoke_chain(question):
    result = await chain.ainvoke(question)
    return result

# Example usage


# Run the async function and get the result
result = await invoke_chain(question)
print(result)
```


### Error Message and Stack Trace (if applicable)


```
---> 32 result = await invoke_chain(question)
     33 print(result)

Cell In[13], line 25, in invoke_chain(question)
     24 async def invoke_chain(question):
---> 25     result = await chain.ainvoke(question)
     26     return result

File ~/dev/sparkai-chatbot/venv/lib/python3.11/site-packages/langchain_core/runnables/base.py:2436, in RunnableSequence.ainvoke(self, input, config, **kwargs)
   2434 try:
   2435     for i, step in enumerate(self.steps):
-> 2436         input = await step.ainvoke(
   2437             input,
   2438             # mark each step as a child run
   2439             patch_config(
   2440                 config, callbacks=run_manager.get_child(f"seq:step:{i+1}")
   2441             ),
   2442         )
   2443 # finish the root run
   2444 except BaseException as e:

File ~/dev/sparkai-chatbot/venv/lib/python3.11/site-packages/langchain_core/language_models/llms.py:299, in BaseLLM.ainvoke(self, input, config, stop, **kwargs)
    290 async def ainvoke(
    291     self,
    292     input: LanguageModelInput,
   (...)
    296     **kwargs: Any,
    297 ) -> str:
    298     config = ensure_config(config)
--> 299     llm_result = await self.agenerate_prompt(
    300         [self._convert_input(input)],
    301         stop=stop,
    302         callbacks=config.get("callbacks"),
    303         tags=config.get("tags"),
    304         metadata=config.get("metadata"),
    305         run_name=config.get("run_name"),
    306         run_id=config.pop("run_id", None),
    307         **kwargs,
    308     )
    309     return llm_result.generations[0][0].text

File ~/dev/sparkai-chatbot/venv/lib/python3.11/site-packages/langchain_core/language_models/llms.py:643, in BaseLLM.agenerate_prompt(self, prompts, stop, callbacks, **kwargs)
    635 async def agenerate_prompt(
    636     self,
    637     prompts: List[PromptValue],
   (...)
    640     **kwargs: Any,
    641 ) -> LLMResult:
    642     prompt_strings = [p.to_string() for p in prompts]
--> 643     return await self.agenerate(
    644         prompt_strings, stop=stop, callbacks=callbacks, **kwargs
    645     )

File ~/dev/sparkai-chatbot/venv/lib/python3.11/site-packages/langchain_core/language_models/llms.py:1018, in BaseLLM.agenerate(self, prompts, stop, callbacks, tags, metadata, run_name, run_id, **kwargs)
   1001     run_managers = await asyncio.gather(
   1002         *[
   1003             callback_manager.on_llm_start(
   (...)
   1015         ]
   1016     )
   1017     run_managers = [r[0] for r in run_managers]  # type: ignore[misc]
-> 1018     output = await self._agenerate_helper(
   1019         prompts,
   1020         stop,
   1021         run_managers,  # type: ignore[arg-type]
   1022         bool(new_arg_supported),
   1023         **kwargs,  # type: ignore[arg-type]
   1024     )
   1025     return output
   1026 if len(missing_prompts) > 0:

File ~/dev/sparkai-chatbot/venv/lib/python3.11/site-packages/langchain_core/language_models/llms.py:882, in BaseLLM._agenerate_helper(self, prompts, stop, run_managers, new_arg_supported, **kwargs)
    875 except BaseException as e:
    876     await asyncio.gather(
    877         *[
    878             run_manager.on_llm_error(e, response=LLMResult(generations=[]))
    879             for run_manager in run_managers
    880         ]
    881     )
--> 882     raise e
    883 flattened_outputs = output.flatten()
    884 await asyncio.gather(
    885     *[
    886         run_manager.on_llm_end(flattened_output)
   (...)
    890     ]
    891 )

File ~/dev/sparkai-chatbot/venv/lib/python3.11/site-packages/langchain_core/language_models/llms.py:866, in BaseLLM._agenerate_helper(self, prompts, stop, run_managers, new_arg_supported, **kwargs)
    856 async def _agenerate_helper(
    857     self,
    858     prompts: List[str],
   (...)
    862     **kwargs: Any,
    863 ) -> LLMResult:
    864     try:
    865         output = (
--> 866             await self._agenerate(
    867                 prompts,
    868                 stop=stop,
    869                 run_manager=run_managers[0] if run_managers else None,
    870                 **kwargs,
    871             )
    872             if new_arg_supported
    873             else await self._agenerate(prompts, stop=stop)
    874         )
    875     except BaseException as e:
    876         await asyncio.gather(
    877             *[
    878                 run_manager.on_llm_error(e, response=LLMResult(generations=[]))
    879                 for run_manager in run_managers
    880             ]
    881         )

File ~/dev/sparkai-chatbot/venv/lib/python3.11/site-packages/langchain_community/llms/openai.py:1194, in OpenAIChat._agenerate(self, prompts, stop, run_manager, **kwargs)
   1192 messages, params = self._get_chat_params(prompts, stop)
   1193 params = {**params, **kwargs}
-> 1194 full_response = await acompletion_with_retry(
   1195     self, messages=messages, run_manager=run_manager, **params
   1196 )
   1197 if not isinstance(full_response, dict):
   1198     full_response = full_response.dict()

File ~/dev/sparkai-chatbot/venv/lib/python3.11/site-packages/langchain_community/llms/openai.py:133, in acompletion_with_retry(llm, run_manager, **kwargs)
    131 """Use tenacity to retry the async completion call."""
    132 if is_openai_v1():
--> 133     return await llm.async_client.create(**kwargs)
    135 retry_decorator = _create_retry_decorator(llm, run_manager=run_manager)
    137 @retry_decorator
    138 async def _completion_with_retry(**kwargs: Any) -> Any:
    139     # Use OpenAI's async api https://github.com/openai/openai-python#async-api

AttributeError: 'NoneType' object has no attribute 'create'

```

### Description

Doing async calls to langchain seem to break when I update OpenAI package to version >=1.0

### System Info

latest version from github or any other version is affected
--- end body ---
