Requests to the Embeddings_Create Operation under Azure OpenAI API version 2023-07-01-preview have exceeded call rate limit of your current OpenAI S0 pricing tier
Labels: name: area: embeddings, name: auto:bug

### System Info

Python 3.11.4
LangChain 0.0.321

Platform info (WSL2):
DISTRIB_ID=Ubuntu
DISTRIB_RELEASE=20.04
DISTRIB_CODENAME=focal
DISTRIB_DESCRIPTION="Ubuntu 20.04.6 LTS"

### Who can help?

_No response_

### Information

- [ ] The official example notebooks/scripts
- [X] My own modified scripts

### Related Components

- [ ] LLMs/Chat Models
- [X] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async

### Reproduction

I'm trying to embed a few documents as shown in the code below:

```python

# Pass the state object as a parameter
@retry(
    retry=retry_if_exception_type(RateLimitError),
    wait=wait_exponential(multiplier=1, min=60, max=60),
    stop=stop_after_attempt(10),
    before_sleep=before_sleep_log(logger, logging.INFO)
)
def add_documents_with_retry(documents: List[Document], open_search: OpenSearchVectorSearch, context: RetryContext):
    context.increment_attempts()
    logger.info(f"API call attempt #{context.attempts}")
    try:
        open_search.add_documents(documents=documents)
        context.increment_successful_calls()
        logger.info(f"API call #{context.attempts} successful. Total successful calls: {context.successful_calls}")
    except Exception as e:  # General exception is enough since RateLimitError is handled by tenacity
        logger.error(f"Unexpected error occurred: {e}")
        raise  # Re-raise the exception to be handled by the retry decorator

add_documents_with_retry(documents=texts, open_search=open_search, context=retry_context)
```

But I get the rate limit error:

```
WARNING:langchain.embeddings.openai:Warning: model not found. Using cl100k_base encoding.
 67%|██████▋   | 2/3 [00:00<00:00,  5.00it/s]INFO:openai:error_code=429 error_message='Requests to the Embeddings_Create Operation under Azure OpenAI API version 2023-07-01-preview have exceeded call rate limit of your current OpenAI S0 pricing tier. Please retry after 60 seconds. Please go here: https://aka.ms/oai/quotaincrease if you would like to further increase the default rate limit.' error_param=None error_type=None message='OpenAI API error received' stream_error=False
WARNING:langchain.embeddings.openai:Retrying langchain.embeddings.openai.embed_with_retry.<locals>._embed_with_retry in 4.0 seconds as it raised RateLimitError: Requests to the Embeddings_Create Operation under Azure OpenAI API version 2023-07-01-preview have exceeded call rate limit of your current OpenAI S0 pricing tier. Please retry after 60 seconds. Please go here: https://aka.ms/oai/quotaincrease if you would like to further increase the default rate limit..
INFO:openai:error_code=429 error_message='Requests to the Embeddings_Create Operation under Azure OpenAI API version 2023-07-01-preview have exceeded call rate limit of your current OpenAI S0 pricing tier. Please retry after 56 seconds. Please go here: https://aka.ms/oai/quotaincrease if you would like to further increase the default rate limit.' error_param=None error_type=None message='OpenAI API error received' stream_error=False
```



### Expected behavior

It should embed documents instead of indefinitely blocking the embedding because of "rate limit".. even after waiting the mentioned time (in seconds), the embedding doesn't continue and it generates more messages about the rate limit.. Not sure if this is due to the type of tier of the Azure OpenAI instance or something else