Fix dependency and error message for xgrammar (#2024)

python/sglang/srt/constrained/base_grammar_backend.py

@@ -13,7 +13,7 @@ See the License for the specific language governing permissions and
 limitations under the License.
 """
 
-"""The baseclass of backends for grammar-guided constrained decoding."""
+"""The baseclass of a backend for grammar-guided constrained decoding."""
 
 from concurrent.futures import Future, ThreadPoolExecutor
 from dataclasses import dataclass

python/sglang/srt/constrained/outlines_backend.py

@@ -22,7 +22,9 @@ from typing import Dict, List, Optional, Tuple, Union
 import interegular
 import torch
 from outlines.fsm.guide import RegexGuide
+from outlines.fsm.json_schema import build_regex_from_schema
 from outlines.models.transformers import TransformerTokenizer
+from pydantic import BaseModel
 
 from sglang.srt.constrained.base_grammar_backend import (
     BaseGrammarBackend,
@@ -33,26 +35,6 @@ from sglang.srt.constrained.outlines_jump_forward import OutlinesJumpForwardMap
 logger = logging.getLogger(__name__)
 
 
-try:
-    from outlines.fsm.json_schema import build_regex_from_object
-except ImportError:
-    # Since outlines 0.0.32, build_regex_from_object is replaced by build_regex_from_schema,
-    # which only accepts string schema as input.
-    from outlines.fsm.json_schema import build_regex_from_schema
-    from pydantic import BaseModel
-
-    def build_regex_from_object(
-        object: Union[str, BaseModel, Dict], whitespace_pattern: Optional[str] = None
-    ):
-        if isinstance(object, type(BaseModel)):
-            schema = json.dumps(object.model_json_schema())
-        elif isinstance(object, Dict):
-            schema = json.dumps(object)
-        else:
-            schema = object
-        return build_regex_from_schema(schema, whitespace_pattern)
-
-
 class OutlinesGrammar(BaseGrammarObject):
     def __init__(
         self,
@@ -169,3 +151,15 @@ class OutlinesGrammarBackend(BaseGrammarBackend):
         else:
             jump_forward_map = None
         return OutlinesGrammar(guide, jump_forward_map)
+
+
+def build_regex_from_object(
+    object: Union[str, BaseModel, Dict], whitespace_pattern: Optional[str] = None
+):
+    if isinstance(object, type(BaseModel)):
+        schema = json.dumps(object.model_json_schema())
+    elif isinstance(object, Dict):
+        schema = json.dumps(object)
+    else:
+        schema = object
+    return build_regex_from_schema(schema, whitespace_pattern)

python/sglang/srt/constrained/xgrammar_backend.py

@@ -19,7 +19,16 @@ import logging
 from typing import List, Tuple
 
 import torch
-from xgrammar import CachedGrammarCompiler, CompiledGrammar, GrammarMatcher
+
+try:
+    from xgrammar import CachedGrammarCompiler, CompiledGrammar, GrammarMatcher
+
+    import_error = None
+except ImportError as e:
+    CachedGrammarCompiler = CompiledGrammar = GrammarMatcher = TokenizerInfo = (
+        ImportError
+    )
+    import_error = e
 
 from sglang.srt.constrained.base_grammar_backend import (
     BaseGrammarBackend,
@@ -95,10 +104,21 @@ class XGrammarGrammarBackend(BaseGrammarBackend):
         vocab_size: int,
     ):
         super().__init__()
+
+        if import_error:
+            logger.warning(
+                f"Ignore import error for the grammar backend: {import_error}"
+            )
+            self.grammar_cache = None
+            return
+
         self.grammar_cache = CachedGrammarCompiler(tokenizer_or_vocab=tokenizer)
         self.vocab_size = vocab_size
 
     def init_value_impl(self, key: Tuple[str, str]) -> XGrammarGrammar:
+        if import_error:
+            raise import_error
+
         key_type, key_string = key
         if key_type == "json":
             try:
@@ -126,4 +146,5 @@ class XGrammarGrammarBackend(BaseGrammarBackend):
         return XGrammarGrammar(matcher, self.vocab_size, ctx)
 
     def reset(self):
-        self.grammar_cache.clear()
+        if self.grammar_cache:
+            self.grammar_cache.clear()