[Frontend][Core] Move guided decoding params into sampling params (#8252)

Signed-off-by: Joe Runde <Joseph.Runde@ibm.com>
Co-authored-by: Nick Hill <nickhill@us.ibm.com>

vllm/engine/llm_engine.py

@@ -25,6 +25,7 @@ from vllm.engine.output_processor.interfaces import (
     SequenceGroupOutputProcessor)
 from vllm.engine.output_processor.stop_checker import StopChecker
 from vllm.engine.output_processor.util import create_output_by_sequence_group
+from vllm.entrypoints.openai.logits_processors import get_logits_processors
 from vllm.executor.executor_base import ExecutorBase
 from vllm.executor.gpu_executor import GPUExecutor
 from vllm.executor.ray_utils import initialize_ray_cluster
@@ -33,6 +34,8 @@ from vllm.inputs import (INPUT_REGISTRY, EncoderDecoderLLMInputs,
 from vllm.inputs.preprocess import InputPreprocessor
 from vllm.logger import init_logger
 from vllm.lora.request import LoRARequest
+from vllm.model_executor.guided_decoding import (
+    get_local_guided_decoding_logits_processor)
 from vllm.model_executor.layers.sampler import SamplerOutput
 from vllm.outputs import (EmbeddingRequestOutput, RequestOutput,
                           RequestOutputFactory)
@@ -843,6 +846,9 @@ class LLMEngine:
             raise ValueError(f"Cannot request more than "
                              f"{max_logprobs} logprobs.")
 
+        sampling_params = self._build_logits_processors(
+            sampling_params, lora_request)
+
         # Defensive copy of SamplingParams, which are used by the sampler,
         # this doesn't deep-copy LogitsProcessor objects
         sampling_params = sampling_params.clone()
@@ -1895,3 +1901,51 @@ class LLMEngine:
             # TODO: Find out how many placeholder tokens are there so we can
             # check that chunked prefill does not truncate them
             # max_batch_len = self.scheduler_config.max_num_batched_tokens
+
+    def _build_logits_processors(
+            self, sampling_params: SamplingParams,
+            lora_request: Optional[LoRARequest]) -> SamplingParams:
+        """Constructs logits processors based on the guided_decoding,
+        logits_bias, and allowed_token_ids fields in sampling_params. Deletes
+        those fields and adds the constructed logits processors to the
+        logits_processors field. Returns the modified sampling params."""
+
+        logits_processors = []
+        if (guided_decoding := sampling_params.guided_decoding) is not None:
+
+            logger.debug(
+                "Building guided decoding logits processor in "
+                "LLMEngine. Params: %s", guided_decoding)
+
+            tokenizer = self.get_tokenizer(lora_request=lora_request)
+            guided_decoding.backend = guided_decoding.backend or \
+                self.decoding_config.guided_decoding_backend
+
+            processor = get_local_guided_decoding_logits_processor(
+                guided_params=guided_decoding, tokenizer=tokenizer)
+            if processor:
+                logits_processors.append(processor)
+
+            # Unset so this doesn't get passed down to the model
+            sampling_params.guided_decoding = None
+
+        if (sampling_params.logit_bias or sampling_params.allowed_token_ids):
+            tokenizer = self.get_tokenizer(lora_request=lora_request)
+
+            processors = get_logits_processors(
+                logit_bias=sampling_params.logit_bias,
+                allowed_token_ids=sampling_params.allowed_token_ids,
+                tokenizer=tokenizer)
+            logits_processors.extend(processors)
+
+            # Unset so these don't get passed down to the model
+            sampling_params.logit_bias = None
+            sampling_params.allowed_token_ids = None
+
+        if logits_processors:
+            if sampling_params.logits_processors is None:
+                sampling_params.logits_processors = logits_processors
+            else:
+                sampling_params.logits_processors.extend(logits_processors)
+
+        return sampling_params