Stop strings

[robertgshaw2-neuralmagic]

FILL IN THE PR DESCRIPTION HERE

FIX #xxxx (link existing issues this PR will resolve)

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[varun-sundar-rabindranath]

@njhill I believe this can result in a KeyError sometimes. This can happen when the LLMEngineCore runs ahead before it gets to process the abort request. What do you think ?

[njhill]

@varun-sundar-rabindranath good catch! I think all that's needed here though is to ignore the case where we no longer have an entry (the request is already completed from our pov and we can discard residual outputs from the engine).

[varun-sundar-rabindranath]

Is it better to decouple stop-string check and the making of request outputs into different classes ?

[njhill]

@varun-sundar-rabindranath I think the incremental detokenization + stop string handling naturally fits together given the possible buffering / truncation required by the latter.

We could decouple the request output construction (I do agree with the idea of keeping the detokenizer "generic"), but I think we would want to output something quite similar to Optional[RequestOutput] from the add_tokens method anyhow I think?

At a minimum we could split that part into a sub-method

[varun-sundar-rabindranath]

@njhill I agree that all three belong together, but they could be different components called one after the other. like the sub-methods you are hinting at.

Concretely, I was thinking we could refactor it like this,

class OutputProcessor:
  def __init__(request):
     self.stop : List[str] = request.sampling_params.stop
     self.include_stop_str: str = request.sampling_params.include_stop_str
     self.detokenizer = IncrementalDetokenizer(request)
     self.generated_text: str = ""
     self.streamed_text_index: int = 0 # text from generted_text has been streamed until streamed_text_index

   def check_stop_strings() -> Optional[str]:
       """
       if a stop string is identified, return the identified stop string.
      """
      ...

  def make_request_output(engine_core_output, stop_str) -> Optional[RequestOutput]:
     """
     make a request output based on RequestOutputKind
     """    

   def step(engine_core_output) -> Tuple[RequestOutput, bool]:
         """
           Process the engine core output and return,
           1. request output if the request finished / request output kind delta is enabled
           2. to abort request or not to abort requset 
         """
         new_text = self.Detokenizer(engine_core_output)
         self.generated_text += new_text

         stop_str = check_stop_strings()
         if stop_str:
             # this request must be aborted
             return self.make_request_output(engine_core_output, stop_str), True

        return self.make_request_output(engine_core_output), False
         

[njhill]

Thanks @varun-sundar-rabindranath I agree and had similar thought re the OutputProcessor naming. I just think it might still make sense to keep the stop string handling in the incrementaldetokenizer for now (we can still reevaluate that later)