OpenAI compatible server returns empty chat completion

# Prerequisites

Please answer the following questions for yourself before submitting an issue.

- [x] I am running the latest code. Development is very rapid so there are no tagged versions as of now.
- [ x I carefully followed the [README.md](https://github.com/abetlen/llama-cpp-python/blob/main/README.md).
- [ x I [searched using keywords relevant to my issue](https://docs.github.com/en/issues/tracking-your-work-with-issues/filtering-and-searching-issues-and-pull-requests) to make sure that I am creating a new issue that is not already open (or closed).
- [x] I reviewed the [Discussions](https://github.com/abetlen/llama-cpp-python/discussions), and have a new bug or useful enhancement to share.

# Expected Behavior

Running llama_cpp.server with a Mixtral model can respond to chat completion.

# Current Behavior

Running llama_cpp.server with a Mixtral model does not return any content, it stops immediately.

# Failure Information (for bugs)

I dig some digging and this seems to be caused by the result.stop in function chat_formatter_to_chat_completion_handler.

Here is the value of result:
```
ChatFormatterResponse(prompt='<|im_start|>user\nTranslate this sentence from English to French. I love programming.<|im_end|>\n<|im_start|>user\nTranslate this sentence from English to French. I love programming.<|im_end|>\n<|im_start|>assistant\n', stop=[''])
```

As you can see stop contains an empty string, this seems to be the cause of the issue. When I force stop to None after calling the chat_formatter it solves the issue and I get a proper response.

Also when running with verbose we can see that bos_token and eos_token are empty:
```
Model metadata: {'general.quantization_version': '2', 'tokenizer.chat_template': "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}", 'tokenizer.ggml.add_eos_token': 'false', 'tokenizer.ggml.add_bos_token': 'true', 'tokenizer.ggml.padding_token_id': '0', 'tokenizer.ggml.eos_token_id': '32000', 'tokenizer.ggml.bos_token_id': '1', 'llama.attention.head_count_kv': '8', 'llama.context_length': '32768', 'llama.attention.head_count': '32', 'llama.rope.freq_base': '1000000.000000', 'llama.rope.dimension_count': '128', 'tokenizer.ggml.model': 'llama', 'llama.expert_used_count': '2', 'general.file_type': '15', 'llama.feed_forward_length': '14336', 'llama.embedding_length': '4096', 'llama.expert_count': '8', 'llama.block_count': '32', 'general.name': 'ehartford_dolphin-2.5-mixtral-8x7b', 'llama.attention.layer_norm_rms_epsilon': '0.000010', 'general.architecture': 'llama'}
Using chat template: {% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '
' + message['content'] + '<|im_end|>' + '
'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
' }}{% endif %}
Using chat eos_token:
Using chat bos_token:
```

# Steps to Reproduce

1) Run llama_cpp.server with any Mixtral model.
2) Make a chat completion request to the server.
3) Server response is empty.