[Core][Performance] Add XGrammar support for guided decoding and set it as default (#10785)

Signed-off-by: Aaron Pham <contact@aarnphm.xyz>
Signed-off-by: mgoin <michael@neuralmagic.com>
Co-authored-by: mgoin <michael@neuralmagic.com>

vllm/engine/async_llm_engine.py

@@ -1,4 +1,5 @@
 import asyncio
+import copy
 import time
 import weakref
 from functools import partial
@@ -507,7 +508,8 @@ class _AsyncLLMEngine(LLMEngine):
                 sampling_params=params,
                 tokenizer=await self.get_tokenizer_async(lora_request),
                 default_guided_backend=self.decoding_config.
-                guided_decoding_backend)
+                guided_decoding_backend,
+                model_config=self.model_config)
 
         self._add_processed_request(
             request_id=request_id,
@@ -528,22 +530,30 @@ class _AsyncLLMEngine(LLMEngine):
 
 async def build_guided_decoding_logits_processor_async(
         sampling_params: SamplingParams, tokenizer: AnyTokenizer,
-        default_guided_backend: str) -> SamplingParams:
+        default_guided_backend: str,
+        model_config: ModelConfig) -> 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. Modifies sampling params in-place and returns
     the modified sampling params."""
-    if (guided_decoding := sampling_params.guided_decoding) is None:
+    if sampling_params.guided_decoding is None:
         return sampling_params
 
+    # Defensively copy sampling params since guided decoding logits
+    # processors can have different state for each request
+    sampling_params = copy.copy(sampling_params)
+    guided_decoding = sampling_params.guided_decoding
+
     logger.debug("Building guided decoding logits processor. "
                  "Params: %s", guided_decoding)
 
     guided_decoding.backend = guided_decoding.backend or default_guided_backend
 
     processor = await get_guided_decoding_logits_processor(
-        guided_params=guided_decoding, tokenizer=tokenizer)
+        guided_params=guided_decoding,
+        tokenizer=tokenizer,
+        model_config=model_config)
 
     if processor:
         if sampling_params.logits_processors is None: