Rename Spark3 to Spark2.5 (#36416)

python/sglang/srt/configs/__init__.py

@@ -57,7 +57,7 @@ from sglang.srt.configs.qwen3_5 import (
 )
 from sglang.srt.configs.qwen3_asr import Qwen3ASRConfig
 from sglang.srt.configs.qwen3_next import Qwen3NextConfig
-from sglang.srt.configs.spark3 import Spark3Config
+from sglang.srt.configs.spark2_5 import Spark2_5Config
 from sglang.srt.configs.step3_vl import (
     Step3TextConfig,
     Step3VisionEncoderConfig,
@@ -118,7 +118,7 @@ __all__ = [
     "MiniCPMHybridConfig",
     "Step3p5Config",
     "MiniMaxM3VLConfig",
-    "Spark3Config",
+    "Spark2_5Config",
     "Step3p7Config",
     "Qwen3ASRConfig",
     "InklingAudioConfig",

python/sglang/srt/configs/spark2_5.py

@@ -3,9 +3,9 @@ from typing import Any, Optional
 from transformers.configuration_utils import PretrainedConfig
 
 
-class Spark3Config(PretrainedConfig):
+class Spark2_5Config(PretrainedConfig):
-    model_type = "spark3"
+    model_type = "spark2_5"
-    architectures = ["Spark3ForCausalLM"]
+    architectures = ["Spark2_5ForCausalLM"]
 
     def __init__(
         self,

python/sglang/srt/function_call/function_call_parser.py

@@ -43,7 +43,7 @@ from sglang.srt.function_call.poolside_v1_detector import PoolsideV1Detector
 from sglang.srt.function_call.pythonic_detector import PythonicDetector
 from sglang.srt.function_call.qwen3_coder_detector import Qwen3CoderDetector
 from sglang.srt.function_call.qwen25_detector import Qwen25Detector
-from sglang.srt.function_call.spark3_detector import Spark3Detector
+from sglang.srt.function_call.spark25_detector import Spark25Detector
 from sglang.srt.function_call.step3_detector import Step3Detector
 from sglang.srt.function_call.trinity_detector import TrinityDetector
 from sglang.srt.function_call.utils import (
@@ -88,7 +88,7 @@ class FunctionCallParser:
         "qwen": Qwen25Detector,
         "qwen25": Qwen25Detector,
         "qwen3_coder": Qwen3CoderDetector,
-        "spark": Spark3Detector,
+        "spark25": Spark25Detector,
         "step3": Step3Detector,
         "step3p5": Qwen3CoderDetector,
         "minimax-m2": MinimaxM2Detector,

python/sglang/srt/function_call/spark25_detector.py

@@ -26,7 +26,7 @@ ARG_PAIR_PATTERN = re.compile(
 
 
 @dataclass(frozen=True)
-class _Spark3ToolCall:
+class _Spark2_5ToolCall:
     name: str
     arguments: dict[str, Any]
 
@@ -57,7 +57,7 @@ def _get_param_type(tools: list[Tool], function_name: str, param_name: str) -> s
 
 
 def _convert_value(value: str, param_type: str) -> Any:
-    """Convert Spark3 XML text according to the model's tool protocol."""
+    """Convert Spark2_5 XML text according to the model's tool protocol."""
     if value.lower() == "null":
         return None
 
@@ -83,7 +83,7 @@ def _convert_value(value: str, param_type: str) -> Any:
             return value
 
 
-def _parse_tool_call_xml(tool_xml: str, tools: list[Tool]) -> _Spark3ToolCall | None:
+def _parse_tool_call_xml(tool_xml: str, tools: list[Tool]) -> _Spark2_5ToolCall | None:
     if not tool_xml.startswith(TOOL_CALL_BEGIN) or not tool_xml.endswith(TOOL_CALL_END):
         return None
 
@@ -102,7 +102,7 @@ def _parse_tool_call_xml(tool_xml: str, tools: list[Tool]) -> _Spark3ToolCall |
             raw_value,
             _get_param_type(tools, function_name, key),
         )
-    return _Spark3ToolCall(name=function_name, arguments=arguments)
+    return _Spark2_5ToolCall(name=function_name, arguments=arguments)
 
 
 def _partial_marker_suffix_length(text: str, marker: str) -> int:
@@ -113,8 +113,8 @@ def _partial_marker_suffix_length(text: str, marker: str) -> int:
     return 0
 
 
-class Spark3Detector(BaseFormatDetector):
+class Spark25Detector(BaseFormatDetector):
-    """Detector for Spark3's XML-KV tool-call format.
+    """Detector for Spark2_5's XML-KV tool-call format.
 
     Wire format::
 
@@ -137,7 +137,7 @@ class Spark3Detector(BaseFormatDetector):
 
     def _build_item(
         self,
-        parsed: _Spark3ToolCall,
+        parsed: _Spark2_5ToolCall,
         tools: list[Tool],
         tool_index: int,
     ) -> ToolCallItem | None:
@@ -153,7 +153,7 @@ class Spark3Detector(BaseFormatDetector):
         )
 
     def _record_streamed_item(
-        self, parsed: _Spark3ToolCall, item: ToolCallItem
+        self, parsed: _Spark2_5ToolCall, item: ToolCallItem
     ) -> None:
         self.prev_tool_call_arr.append(
             {"name": parsed.name, "arguments": parsed.arguments}
@@ -259,5 +259,5 @@ class Spark3Detector(BaseFormatDetector):
 
     def structure_info(self) -> _GetInfoFunc:
         raise NotImplementedError(
-            "Spark3 XML arguments cannot be represented by legacy structural tags"
+            "Spark2_5 XML arguments cannot be represented by legacy structural tags"
         )

python/sglang/srt/models/spark2_5.py

@@ -31,7 +31,7 @@ from sglang.srt.platforms import current_platform
 from sglang.srt.runtime_context import get_parallel
 from sglang.srt.utils import add_prefix, make_layers
 
-Spark3Config = None
+Spark2_5Config = None
 
 logger = logging.getLogger(__name__)
 
@@ -42,7 +42,7 @@ def _get_attention_sliding_window_size(config):
     return config.sliding_window - 1
 
 
-class Spark3MLP(nn.Module):
+class Spark2_5MLP(nn.Module):
     def __init__(
         self,
         hidden_size: int,
@@ -80,7 +80,7 @@ class Spark3MLP(nn.Module):
         return x
 
 
-class Spark3Attention(nn.Module):
+class Spark2_5Attention(nn.Module):
     def __init__(
         self,
         hidden_size: int,
@@ -169,7 +169,7 @@ class Spark3Attention(nn.Module):
             is_neox_style=True,
         )
         if layer_type not in ("sliding_attention", "full_attention"):
-            raise ValueError(f"Unsupported Spark3 layer_type: {layer_type}")
+            raise ValueError(f"Unsupported Spark2_5 layer_type: {layer_type}")
         sliding_window_size = (
             sliding_window if layer_type == "sliding_attention" else -1
         )
@@ -209,7 +209,7 @@ class Spark3Attention(nn.Module):
         return output
 
 
-class Spark3DecoderLayer(nn.Module):
+class Spark2_5DecoderLayer(nn.Module):
     """A single transformer layer.
 
     Transformer layer takes input with size [s, b, h] and returns an
@@ -218,7 +218,7 @@ class Spark3DecoderLayer(nn.Module):
 
     def __init__(
         self,
-        config: Spark3Config,
+        config: Spark2_5Config,
         layer_id: int = 0,
         quant_config: Optional[QuantizationConfig] = None,
         prefix: str = "",
@@ -234,7 +234,7 @@ class Spark3DecoderLayer(nn.Module):
         if partial_rotary_factor is None:
             partial_rotary_factor = 1.0
 
-        self.self_attn = Spark3Attention(
+        self.self_attn = Spark2_5Attention(
             hidden_size=config.hidden_size,
             num_heads=config.num_attention_heads,
             num_kv_heads=config.num_key_value_heads,
@@ -253,7 +253,7 @@ class Spark3DecoderLayer(nn.Module):
         )
 
         # MLP
-        self.mlp = Spark3MLP(
+        self.mlp = Spark2_5MLP(
             config.hidden_size,
             intermediate_size=config.intermediate_size,
             quant_config=quant_config,
@@ -290,10 +290,10 @@ class Spark3DecoderLayer(nn.Module):
         return hidden_states, residual
 
 
-class Spark3Model(nn.Module):
+class Spark2_5Model(nn.Module):
     def __init__(
         self,
-        config: Spark3Config,
+        config: Spark2_5Config,
         quant_config: Optional[QuantizationConfig] = None,
         prefix: str = "",
     ) -> None:
@@ -315,7 +315,7 @@ class Spark3Model(nn.Module):
 
         self.layers, self.start_layer, self.end_layer = make_layers(
             config.num_hidden_layers,
-            lambda idx, prefix: Spark3DecoderLayer(
+            lambda idx, prefix: Spark2_5DecoderLayer(
                 layer_id=idx,
                 config=config,
                 quant_config=quant_config,
@@ -377,10 +377,10 @@ class Spark3Model(nn.Module):
         return hidden_states
 
 
-class Spark3ForCausalLM(nn.Module):
+class Spark2_5ForCausalLM(nn.Module):
     def __init__(
         self,
-        config: Spark3Config,
+        config: Spark2_5Config,
         quant_config: Optional[QuantizationConfig] = None,
         prefix: str = "",
     ) -> None:
@@ -388,7 +388,7 @@ class Spark3ForCausalLM(nn.Module):
         self.pp_group = get_pp_group()
         self.config = config
         self.quant_config = quant_config
-        self.model = Spark3Model(
+        self.model = Spark2_5Model(
             config, quant_config=quant_config, prefix=add_prefix("model", prefix)
         )
 
@@ -561,4 +561,4 @@ class Spark3ForCausalLM(nn.Module):
         return _get_attention_sliding_window_size(self.config)
 
 
-EntryClass = [Spark3ForCausalLM]
+EntryClass = [Spark2_5ForCausalLM]

python/sglang/srt/utils/hf_transformers/common.py

@@ -66,7 +66,7 @@ from sglang.srt.configs import (
     Qwen3_5MoeTextConfig,
     Qwen3_5TextConfig,
     Qwen3NextConfig,
-    Spark3Config,
+    Spark2_5Config,
     Step3p5Config,
     Step3p7Config,
     Step3VLConfig,
@@ -103,7 +103,7 @@ _CONFIG_REGISTRY: Dict[str, Type[PretrainedConfig]] = {
         LocateAnythingConfig,
         InternVLChatConfig,
         LagunaConfig,
-        Spark3Config,
+        Spark2_5Config,
         Step3VLConfig,
         LongcatFlashConfig,
         Olmo3Config,

test/registered/unit/function_call/test_spark25_detector.py

@@ -1,4 +1,4 @@
-"""Unit tests for Spark3Detector - no server, no model loading."""
+"""Unit tests for Spark25Detector - no server, no model loading."""
 
 import json
 import unittest
@@ -6,7 +6,7 @@ import unittest
 from sglang.srt.entrypoints.openai.protocol import Function, Tool
 from sglang.srt.environ import envs
 from sglang.srt.function_call.function_call_parser import FunctionCallParser
-from sglang.srt.function_call.spark3_detector import Spark3Detector
+from sglang.srt.function_call.spark25_detector import Spark25Detector
 from sglang.test.ci.ci_register import register_cpu_ci
 from sglang.test.test_utils import CustomTestCase
 
@@ -50,13 +50,13 @@ def _tools():
     ]
 
 
-class TestSpark3DetectorDetectAndParse(CustomTestCase):
+class TestSpark25DetectorDetectAndParse(CustomTestCase):
     def setUp(self):
         self.tools = _tools()
-        self.detector = Spark3Detector()
+        self.detector = Spark25Detector()
 
-    def test_spark3_parser_is_registered(self):
+    def test_spark25_parser_is_registered(self):
-        self.assertIs(FunctionCallParser.ToolCallParserEnum["spark"], Spark3Detector)
+        self.assertIs(FunctionCallParser.ToolCallParserEnum["spark25"], Spark25Detector)
 
     def test_nonstream_parses_multiple_calls_and_preserves_normal_text(self):
         text = (
@@ -95,7 +95,7 @@ class TestSpark3DetectorDetectAndParse(CustomTestCase):
         )
         self.assertEqual(json.loads(result.calls[1].parameters), {})
 
-    def test_null_and_conversion_fallbacks_match_spark3_protocol(self):
+    def test_null_and_conversion_fallbacks_match_spark2_5_protocol(self):
         text = _xml(
             "set_state",
             [
@@ -139,7 +139,7 @@ class TestSpark3DetectorDetectAndParse(CustomTestCase):
         self.assertEqual(result.normal_text, "plain")
         self.assertEqual(self.detector.finish(self.tools).normal_text, "<tool_")
 
-        truncated = Spark3Detector()
+        truncated = Spark25Detector()
         result = truncated.parse_streaming_increment(
             "plain<tool_call>set_state<arg_key>count</arg_key>", self.tools
         )
@@ -156,7 +156,7 @@ class TestSpark3DetectorDetectAndParse(CustomTestCase):
         )
 
 
-class TestSpark3DetectorStreaming(CustomTestCase):
+class TestSpark25DetectorStreaming(CustomTestCase):
     def setUp(self):
         self.tools = _tools()
 
@@ -167,7 +167,7 @@ class TestSpark3DetectorStreaming(CustomTestCase):
             + _xml("now", [])
             + "done"
         )
-        detector = Spark3Detector()
+        detector = Spark25Detector()
         normal_parts = []
         calls = []