Introduce naming convention in io_struct and base sglang io classes. (#10133)

python/sglang/srt/entrypoints/grpc_request_manager.py

@@ -22,8 +22,8 @@ import zmq.asyncio
 from sglang.srt.managers.disagg_service import start_disagg_service
 from sglang.srt.managers.io_struct import (
     AbortReq,
-    BatchEmbeddingOut,
+    BatchEmbeddingOutput,
-    BatchTokenIDOut,
+    BatchTokenIDOutput,
     HealthCheckOutput,
     TokenizedEmbeddingReqInput,
     TokenizedGenerateReqInput,
@@ -467,9 +467,9 @@ class GrpcRequestManager:
                         await self.is_pause_cond.wait()
 
                 # Handle different output types
-                if isinstance(recv_obj, BatchTokenIDOut):
+                if isinstance(recv_obj, BatchTokenIDOutput):
                     await self._handle_batch_output(recv_obj)
-                elif isinstance(recv_obj, BatchEmbeddingOut):
+                elif isinstance(recv_obj, BatchEmbeddingOutput):
                     await self._handle_embedding_output(recv_obj)
                 elif isinstance(recv_obj, HealthCheckOutput):
                     await self._handle_health_check_output(recv_obj)
@@ -498,7 +498,7 @@ class GrpcRequestManager:
     def _convert_logprob_style(
         self,
         state: GrpcReqState,
-        batch_out: BatchTokenIDOut,
+        batch_out: BatchTokenIDOutput,
         batch_index: int,
     ):
         """
@@ -545,7 +545,7 @@ class GrpcRequestManager:
                 batch_out.output_top_logprobs_idx[batch_index]
             )
 
-    async def _handle_batch_output(self, batch_out: BatchTokenIDOut):
+    async def _handle_batch_output(self, batch_out: BatchTokenIDOutput):
         """Handle batch generation output from scheduler."""
         # Process each request in the batch
         for i, rid in enumerate(batch_out.rids):
@@ -666,7 +666,7 @@ class GrpcRequestManager:
 
                 asyncio.create_task(cleanup())
 
-    async def _handle_embedding_output(self, batch_out: BatchEmbeddingOut):
+    async def _handle_embedding_output(self, batch_out: BatchEmbeddingOutput):
         """Handle batch embedding output from scheduler."""
         for i, rid in enumerate(batch_out.rids):
             if rid not in self.rid_to_state:

python/sglang/srt/entrypoints/http_server.py

@@ -94,8 +94,8 @@ from sglang.srt.managers.io_struct import (
     VertexGenerateReqInput,
 )
 from sglang.srt.managers.multi_tokenizer_mixin import (
-    MultiTokenizerManager,
     MultiTokenizerRouter,
+    TokenizerWorker,
     get_main_process_id,
     monkey_patch_uvicorn_multiprocessing,
     read_from_shared_memory,
@@ -127,9 +127,7 @@ HEALTH_CHECK_TIMEOUT = int(os.getenv("SGLANG_HEALTH_CHECK_TIMEOUT", 20))
 # Store global states
 @dataclasses.dataclass
 class _GlobalState:
-    tokenizer_manager: Union[
+    tokenizer_manager: Union[TokenizerManager, MultiTokenizerRouter, TokenizerWorker]
-        TokenizerManager, MultiTokenizerRouter, MultiTokenizerManager
-    ]
     template_manager: TemplateManager
     scheduler_info: Dict
 
@@ -164,7 +162,7 @@ async def init_multi_tokenizer() -> ServerArgs:
     )
 
     # Launch multi-tokenizer manager process
-    tokenizer_manager = MultiTokenizerManager(server_args, port_args)
+    tokenizer_manager = TokenizerWorker(server_args, port_args)
     template_manager = TemplateManager()
     template_manager.initialize_templates(
         tokenizer_manager=tokenizer_manager,

python/sglang/srt/lora/lora_manager.py

@@ -35,7 +35,7 @@ from sglang.srt.lora.utils import (
     get_normalized_target_modules,
     get_target_module_name,
 )
-from sglang.srt.managers.io_struct import LoRAUpdateResult
+from sglang.srt.managers.io_struct import LoRAUpdateOutput
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch
 from sglang.srt.server_args import ServerArgs
 from sglang.srt.utils import replace_submodule
@@ -107,8 +107,8 @@ class LoRAManager:
 
     def create_lora_update_result(
         self, success: bool, error_message: str = ""
-    ) -> LoRAUpdateResult:
+    ) -> LoRAUpdateOutput:
-        return LoRAUpdateResult(
+        return LoRAUpdateOutput(
             success=success,
             error_message=error_message,
             loaded_adapters={
@@ -117,7 +117,7 @@ class LoRAManager:
             },
         )
 
-    def load_lora_adapter(self, lora_ref: LoRARef) -> LoRAUpdateResult:
+    def load_lora_adapter(self, lora_ref: LoRARef) -> LoRAUpdateOutput:
         """
         Load a single LoRA adapter from the specified path.
 
@@ -174,7 +174,7 @@ class LoRAManager:
                 "`--max-loras-per-batch` or load it as unpinned LoRA adapters."
             )
 
-    def unload_lora_adapter(self, lora_ref: LoRARef) -> LoRAUpdateResult:
+    def unload_lora_adapter(self, lora_ref: LoRARef) -> LoRAUpdateOutput:
         """
         Unload LoRA adapters by their names. This will remove the adapters from the memory pool and
         delete the corresponding LoRA modules.

python/sglang/srt/managers/detokenizer_manager.py

@@ -26,11 +26,11 @@ import zmq
 
 from sglang.srt.hf_transformers_utils import get_tokenizer
 from sglang.srt.managers.io_struct import (
-    BatchEmbeddingOut,
+    BatchEmbeddingOutput,
     BatchMultimodalDecodeReq,
-    BatchMultimodalOut,
+    BatchMultimodalOutput,
-    BatchStrOut,
+    BatchStrOutput,
-    BatchTokenIDOut,
+    BatchTokenIDOutput,
     FreezeGCReq,
     MultiTokenizerRegisterReq,
 )
@@ -101,8 +101,8 @@ class DetokenizerManager(MultiHttpWorkerDetokenizerMixin):
 
         self._request_dispatcher = TypeBasedDispatcher(
             [
-                (BatchEmbeddingOut, self.handle_batch_embedding_out),
+                (BatchEmbeddingOutput, self.handle_batch_embedding_out),
-                (BatchTokenIDOut, self.handle_batch_token_id_out),
+                (BatchTokenIDOutput, self.handle_batch_token_id_out),
                 (BatchMultimodalDecodeReq, self.handle_multimodal_decode_req),
                 (MultiTokenizerRegisterReq, lambda x: x),
                 (FreezeGCReq, self.handle_freeze_gc_req),
@@ -145,11 +145,11 @@ class DetokenizerManager(MultiHttpWorkerDetokenizerMixin):
             return output[:-1]
         return output
 
-    def handle_batch_embedding_out(self, recv_obj: BatchEmbeddingOut):
+    def handle_batch_embedding_out(self, recv_obj: BatchEmbeddingOutput):
         # If it is embedding model, no detokenization is needed.
         return recv_obj
 
-    def handle_batch_token_id_out(self, recv_obj: BatchTokenIDOut):
+    def handle_batch_token_id_out(self, recv_obj: BatchTokenIDOutput):
         bs = len(recv_obj.rids)
 
         # Initialize decode status
@@ -224,7 +224,7 @@ class DetokenizerManager(MultiHttpWorkerDetokenizerMixin):
             s.sent_offset = len(output_str)
             output_strs.append(incremental_output)
 
-        return BatchStrOut(
+        return BatchStrOutput(
             rids=recv_obj.rids,
             finished_reasons=recv_obj.finished_reasons,
             output_strs=output_strs,
@@ -252,7 +252,7 @@ class DetokenizerManager(MultiHttpWorkerDetokenizerMixin):
 
     def handle_multimodal_decode_req(self, recv_obj: BatchMultimodalDecodeReq):
         outputs = self.tokenizer.detokenize(recv_obj)
-        return BatchMultimodalOut(
+        return BatchMultimodalOutput(
             rids=recv_obj.rids,
             finished_reasons=recv_obj.finished_reasons,
             outputs=outputs,

python/sglang/srt/managers/io_struct.py

@@ -18,6 +18,7 @@ processes (TokenizerManager, DetokenizerManager, Scheduler).
 
 import copy
 import uuid
+from abc import ABC
 from dataclasses import dataclass, field
 from enum import Enum
 from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
@@ -36,10 +37,32 @@ else:
 
 
 # Parameters for a session
+@dataclass
+class BaseReq(ABC):
+    rid: Optional[Union[str, List[str]]] = field(default=None, kw_only=True)
+
+    def regenerate_rid(self):
+        """Generate a new request ID and return it."""
+        if isinstance(self.rid, list):
+            self.rid = [uuid.uuid4().hex for _ in range(len(self.rid))]
+        else:
+            self.rid = uuid.uuid4().hex
+        return self.rid
+
+
+@dataclass
+class BaseBatchReq(ABC):
+    rids: Optional[List[str]] = field(default=None, kw_only=True)
+
+    def regenerate_rids(self):
+        """Generate new request IDs and return them."""
+        self.rids = [uuid.uuid4().hex for _ in range(len(self.rids))]
+        return self.rids
+
+
 @dataclass
 class SessionParams:
     id: Optional[str] = None
-    rid: Optional[str] = None
     offset: Optional[int] = None
     replace: Optional[bool] = None
     drop_previous_output: Optional[bool] = None
@@ -63,7 +86,7 @@ MultimodalDataInputFormat = Union[
 
 
 @dataclass
-class GenerateReqInput:
+class GenerateReqInput(BaseReq):
     # The input prompt. It can be a single prompt or a batch of prompts.
     text: Optional[Union[List[str], str]] = None
     # The token ids for text; one can specify either text or input_ids
@@ -83,8 +106,6 @@ class GenerateReqInput:
     audio_data: Optional[MultimodalDataInputFormat] = None
     # The sampling_params. See descriptions below.
     sampling_params: Optional[Union[List[Dict], Dict]] = None
-    # The request id.
-    rid: Optional[Union[List[str], str]] = None
     # Whether to return logprobs.
     return_logprob: Optional[Union[List[bool], bool]] = None
     # If return logprobs, the start location in the prompt for returning logprobs.
@@ -491,11 +512,6 @@ class GenerateReqInput:
             ):
                 raise ValueError("Session params must be a dict or a list of dicts.")
 
-    def regenerate_rid(self):
-        """Generate a new request ID and return it."""
-        self.rid = uuid.uuid4().hex
-        return self.rid
-
     def __getitem__(self, i):
         return GenerateReqInput(
             text=self.text[i] if self.text is not None else None,
@@ -558,9 +574,7 @@ class GenerateReqInput:
 
 
 @dataclass
-class TokenizedGenerateReqInput:
+class TokenizedGenerateReqInput(BaseReq):
-    # The request id
-    rid: str
     # The input text
     input_text: str
     # The input token ids
@@ -625,7 +639,7 @@ class TokenizedGenerateReqInput:
 
 
 @dataclass
-class BatchTokenizedGenerateReqInput:
+class BatchTokenizedGenerateReqInput(BaseBatchReq):
     # The batch of tokenized requests
     batch: List[TokenizedGenerateReqInput]
 
@@ -640,7 +654,7 @@ class BatchTokenizedGenerateReqInput:
 
 
 @dataclass
-class EmbeddingReqInput:
+class EmbeddingReqInput(BaseReq):
     # The input prompt. It can be a single prompt or a batch of prompts.
     text: Optional[Union[List[List[str]], List[str], str]] = None
     # The image input. It can be an image instance, file name, URL, or base64 encoded string.
@@ -656,8 +670,6 @@ class EmbeddingReqInput:
     audio_data: Optional[MultimodalDataInputFormat] = None
     # The token ids for text; one can either specify text or input_ids.
     input_ids: Optional[Union[List[List[int]], List[int]]] = None
-    # The request id.
-    rid: Optional[Union[List[str], str]] = None
     # Dummy sampling params for compatibility
     sampling_params: Optional[Union[List[Dict], Dict]] = None
     # Dummy input embeds for compatibility
@@ -728,10 +740,6 @@ class EmbeddingReqInput:
             for i in range(self.batch_size):
                 self.sampling_params[i]["max_new_tokens"] = 0
 
-    def regenerate_rid(self):
-        self.rid = uuid.uuid4().hex
-        return self.rid
-
     def contains_mm_input(self) -> bool:
         return (
             has_valid_data(self.image_data)
@@ -760,9 +768,7 @@ class EmbeddingReqInput:
 
 
 @dataclass
-class TokenizedEmbeddingReqInput:
+class TokenizedEmbeddingReqInput(BaseReq):
-    # The request id
-    rid: str
     # The input text
     input_text: str
     # The input token ids
@@ -780,7 +786,7 @@ class TokenizedEmbeddingReqInput:
 
 
 @dataclass
-class BatchTokenizedEmbeddingReqInput:
+class BatchTokenizedEmbeddingReqInput(BaseBatchReq):
     # The batch of tokenized embedding requests
     batch: List[TokenizedEmbeddingReqInput]
 
@@ -795,9 +801,7 @@ class BatchTokenizedEmbeddingReqInput:
 
 
 @dataclass
-class BatchTokenIDOut:
+class BatchTokenIDOutput(BaseBatchReq):
-    # The request id
-    rids: List[str]
     # The finish reason
     finished_reasons: List[BaseFinishReason]
     # For incremental decoding
@@ -842,7 +846,7 @@ class BatchTokenIDOut:
 
 
 @dataclass
-class BatchMultimodalDecodeReq:
+class BatchMultimodalDecodeReq(BaseBatchReq):
     decoded_ids: List[int]
     input_token_logprobs_val: List[float]
     input_token_logprobs_idx: List[int]
@@ -854,8 +858,6 @@ class BatchMultimodalDecodeReq:
     image_resolutions: List[List[int]]
     resize_image_resolutions: List[List[int]]
 
-    # The request id
-    rids: List[str]
     finished_reasons: List[BaseFinishReason]
 
     # Token counts
@@ -871,9 +873,7 @@ class BatchMultimodalDecodeReq:
 
 
 @dataclass
-class BatchStrOut:
+class BatchStrOutput(BaseBatchReq):
-    # The request id
-    rids: List[str]
     # The finish reason
     finished_reasons: List[dict]
     # The output decoded strings
@@ -909,9 +909,7 @@ class BatchStrOut:
 
 
 @dataclass
-class BatchMultimodalOut:
+class BatchMultimodalOutput(BaseBatchReq):
-    # The request id
-    rids: List[str]
     # The finish reason
     finished_reasons: List[dict]
     decoded_ids: List[List[int]]
@@ -936,9 +934,7 @@ class BatchMultimodalOut:
 
 
 @dataclass
-class BatchEmbeddingOut:
+class BatchEmbeddingOutput(BaseBatchReq):
-    # The request id
-    rids: List[str]
     # The finish reason
     finished_reasons: List[BaseFinishReason]
     # The output embedding
@@ -952,27 +948,27 @@ class BatchEmbeddingOut:
 
 
 @dataclass
-class ClearHiCacheReqInput:
+class ClearHiCacheReqInput(BaseReq):
     pass
 
 
 @dataclass
-class ClearHiCacheReqOutput:
+class ClearHiCacheReqOutput(BaseReq):
     success: bool
 
 
 @dataclass
-class FlushCacheReqInput:
+class FlushCacheReqInput(BaseReq):
     pass
 
 
 @dataclass
-class FlushCacheReqOutput:
+class FlushCacheReqOutput(BaseReq):
     success: bool
 
 
 @dataclass
-class UpdateWeightFromDiskReqInput:
+class UpdateWeightFromDiskReqInput(BaseReq):
     # The model path with the new weights
     model_path: str
     # The format to load the weights
@@ -990,7 +986,7 @@ class UpdateWeightFromDiskReqInput:
 
 
 @dataclass
-class UpdateWeightFromDiskReqOutput:
+class UpdateWeightFromDiskReqOutput(BaseReq):
     success: bool
     message: str
     # Number of paused requests during weight sync.
@@ -998,7 +994,7 @@ class UpdateWeightFromDiskReqOutput:
 
 
 @dataclass
-class UpdateWeightsFromDistributedReqInput:
+class UpdateWeightsFromDistributedReqInput(BaseReq):
     names: List[str]
     dtypes: List[str]
     shapes: List[List[int]]
@@ -1013,13 +1009,13 @@ class UpdateWeightsFromDistributedReqInput:
 
 
 @dataclass
-class UpdateWeightsFromDistributedReqOutput:
+class UpdateWeightsFromDistributedReqOutput(BaseReq):
     success: bool
     message: str
 
 
 @dataclass
-class UpdateWeightsFromTensorReqInput:
+class UpdateWeightsFromTensorReqInput(BaseReq):
     """Update model weights from tensor input.
 
     - Tensors are serialized for transmission
@@ -1038,13 +1034,13 @@ class UpdateWeightsFromTensorReqInput:
 
 
 @dataclass
-class UpdateWeightsFromTensorReqOutput:
+class UpdateWeightsFromTensorReqOutput(BaseReq):
     success: bool
     message: str
 
 
 @dataclass
-class InitWeightsSendGroupForRemoteInstanceReqInput:
+class InitWeightsSendGroupForRemoteInstanceReqInput(BaseReq):
     # The master address
     master_address: str
     # The ports for each rank's communication group
@@ -1060,13 +1056,13 @@ class InitWeightsSendGroupForRemoteInstanceReqInput:
 
 
 @dataclass
-class InitWeightsSendGroupForRemoteInstanceReqOutput:
+class InitWeightsSendGroupForRemoteInstanceReqOutput(BaseReq):
     success: bool
     message: str
 
 
 @dataclass
-class SendWeightsToRemoteInstanceReqInput:
+class SendWeightsToRemoteInstanceReqInput(BaseReq):
     # The master address
     master_address: str
     # The ports for each rank's communication group
@@ -1076,13 +1072,13 @@ class SendWeightsToRemoteInstanceReqInput:
 
 
 @dataclass
-class SendWeightsToRemoteInstanceReqOutput:
+class SendWeightsToRemoteInstanceReqOutput(BaseReq):
     success: bool
     message: str
 
 
 @dataclass
-class InitWeightsUpdateGroupReqInput:
+class InitWeightsUpdateGroupReqInput(BaseReq):
     # The master address
     master_address: str
     # The master port
@@ -1098,24 +1094,24 @@ class InitWeightsUpdateGroupReqInput:
 
 
 @dataclass
-class InitWeightsUpdateGroupReqOutput:
+class InitWeightsUpdateGroupReqOutput(BaseReq):
     success: bool
     message: str
 
 
 @dataclass
-class DestroyWeightsUpdateGroupReqInput:
+class DestroyWeightsUpdateGroupReqInput(BaseReq):
     group_name: str = "weight_update_group"
 
 
 @dataclass
-class DestroyWeightsUpdateGroupReqOutput:
+class DestroyWeightsUpdateGroupReqOutput(BaseReq):
     success: bool
     message: str
 
 
 @dataclass
-class UpdateWeightVersionReqInput:
+class UpdateWeightVersionReqInput(BaseReq):
     # The new weight version
     new_version: str
     # Whether to abort all running requests before updating
@@ -1123,89 +1119,87 @@ class UpdateWeightVersionReqInput:
 
 
 @dataclass
-class GetWeightsByNameReqInput:
+class GetWeightsByNameReqInput(BaseReq):
     name: str
     truncate_size: int = 100
 
 
 @dataclass
-class GetWeightsByNameReqOutput:
+class GetWeightsByNameReqOutput(BaseReq):
     parameter: list
 
 
 @dataclass
-class ReleaseMemoryOccupationReqInput:
+class ReleaseMemoryOccupationReqInput(BaseReq):
     # Optional tags to identify the memory region, which is primarily used for RL
     # Currently we only support `weights` and `kv_cache`
     tags: Optional[List[str]] = None
 
 
 @dataclass
-class ReleaseMemoryOccupationReqOutput:
+class ReleaseMemoryOccupationReqOutput(BaseReq):
     pass
 
 
 @dataclass
-class ResumeMemoryOccupationReqInput:
+class ResumeMemoryOccupationReqInput(BaseReq):
     # Optional tags to identify the memory region, which is primarily used for RL
     # Currently we only support `weights` and `kv_cache`
     tags: Optional[List[str]] = None
 
 
 @dataclass
-class ResumeMemoryOccupationReqOutput:
+class ResumeMemoryOccupationReqOutput(BaseReq):
     pass
 
 
 @dataclass
-class SlowDownReqInput:
+class SlowDownReqInput(BaseReq):
     forward_sleep_time: Optional[float]
 
 
 @dataclass
-class SlowDownReqOutput:
+class SlowDownReqOutput(BaseReq):
     pass
 
 
 @dataclass
-class AbortReq:
+class AbortReq(BaseReq):
-    # The request id
-    rid: str = ""
     # Whether to abort all requests
     abort_all: bool = False
     # The finished reason data
     finished_reason: Optional[Dict[str, Any]] = None
     abort_reason: Optional[str] = None
-    # used in MultiTokenzierManager mode
-    rids: Optional[Union[List[str], str]] = None
 
     def __post_init__(self):
-        self.rids = self.rid
+        # FIXME: This is a hack to keep the same with the old code
+        if self.rid is None:
+            self.rid = ""
 
 
 @dataclass
-class GetInternalStateReq:
+class GetInternalStateReq(BaseReq):
     pass
 
 
 @dataclass
-class GetInternalStateReqOutput:
+class GetInternalStateReqOutput(BaseReq):
     internal_state: Dict[Any, Any]
 
 
 @dataclass
-class SetInternalStateReq:
+class SetInternalStateReq(BaseReq):
     server_args: Dict[str, Any]
 
 
 @dataclass
-class SetInternalStateReqOutput:
+class SetInternalStateReqOutput(BaseReq):
     updated: bool
     server_args: Dict[str, Any]
 
 
 @dataclass
-class ProfileReqInput:
+class ProfileReqInput(BaseReq):
     # The output directory
     output_dir: Optional[str] = None
     # If set, it profile as many as this number of steps.
@@ -1225,7 +1219,7 @@ class ProfileReqType(Enum):
 
 
 @dataclass
-class ProfileReq:
+class ProfileReq(BaseReq):
     type: ProfileReqType
     output_dir: Optional[str] = None
     start_step: Optional[int] = None
@@ -1238,18 +1232,18 @@ class ProfileReq:
 
 
 @dataclass
-class ProfileReqOutput:
+class ProfileReqOutput(BaseReq):
     success: bool
     message: str
 
 
 @dataclass
-class FreezeGCReq:
+class FreezeGCReq(BaseReq):
     pass
 
 
 @dataclass
-class ConfigureLoggingReq:
+class ConfigureLoggingReq(BaseReq):
     log_requests: Optional[bool] = None
     log_requests_level: Optional[int] = None
     dump_requests_folder: Optional[str] = None
@@ -1258,35 +1252,39 @@ class ConfigureLoggingReq:
 
 
 @dataclass
-class OpenSessionReqInput:
+class OpenSessionReqInput(BaseReq):
     capacity_of_str_len: int
     session_id: Optional[str] = None
 
 
 @dataclass
-class CloseSessionReqInput:
+class CloseSessionReqInput(BaseReq):
     session_id: str
 
 
 @dataclass
-class OpenSessionReqOutput:
+class OpenSessionReqOutput(BaseReq):
     session_id: Optional[str]
     success: bool
 
 
 @dataclass
-class HealthCheckOutput:
+class HealthCheckOutput(BaseReq):
     pass
 
 
-class ExpertDistributionReq(Enum):
+class ExpertDistributionReqType(Enum):
     START_RECORD = 1
     STOP_RECORD = 2
     DUMP_RECORD = 3
 
 
+class ExpertDistributionReq(BaseReq):
+    action: ExpertDistributionReqType
+
+
 @dataclass
-class ExpertDistributionReqOutput:
+class ExpertDistributionReqOutput(BaseReq):
     pass
 
 
@@ -1304,7 +1302,7 @@ class Tool:
 
 
 @dataclass
-class ParseFunctionCallReq:
+class ParseFunctionCallReq(BaseReq):
     text: str  # The text to parse.
     tools: List[Tool] = field(
         default_factory=list
@@ -1315,31 +1313,31 @@ class ParseFunctionCallReq:
 
 
 @dataclass
-class SeparateReasoningReqInput:
+class SeparateReasoningReqInput(BaseReq):
     text: str  # The text to parse.
     reasoning_parser: str  # Specify the parser type, e.g., "deepseek-r1".
 
 
 @dataclass
-class VertexGenerateReqInput:
+class VertexGenerateReqInput(BaseReq):
     instances: List[dict]
     parameters: Optional[dict] = None
 
 
 @dataclass
-class RpcReqInput:
+class RpcReqInput(BaseReq):
     method: str
     parameters: Optional[Dict] = None
 
 
 @dataclass
-class RpcReqOutput:
+class RpcReqOutput(BaseReq):
     success: bool
     message: str
 
 
 @dataclass
-class LoadLoRAAdapterReqInput:
+class LoadLoRAAdapterReqInput(BaseReq):
     # The name of the lora module to newly loaded.
     lora_name: str
     # The path of loading.
@@ -1359,7 +1357,7 @@ class LoadLoRAAdapterReqInput:
 
 
 @dataclass
-class UnloadLoRAAdapterReqInput:
+class UnloadLoRAAdapterReqInput(BaseReq):
     # The name of lora module to unload.
     lora_name: str
     # The unique identifier for the LoRA adapter, which automatically generated in the `TokenizerManager`.
@@ -1373,23 +1371,23 @@ class UnloadLoRAAdapterReqInput:
 
 
 @dataclass
-class LoRAUpdateResult:
+class LoRAUpdateOutput(BaseReq):
     success: bool
     error_message: Optional[str] = None
     loaded_adapters: Optional[Dict[str, LoRARef]] = None
 
 
-LoadLoRAAdapterReqOutput = UnloadLoRAAdapterReqOutput = LoRAUpdateResult
+LoadLoRAAdapterReqOutput = UnloadLoRAAdapterReqOutput = LoRAUpdateOutput
 
 
 @dataclass
-class MultiTokenizerRegisterReq:
+class MultiTokenizerRegisterReq(BaseBatchReq):
-    rids: Optional[Union[List[str], str]] = None
     ipc_name: Optional[str] = None
 
 
 @dataclass
 class MultiTokenizerWrapper:
+    # FIXME(lsyin): remove this
     worker_id: int
     obj: Optional[Any] = None
 
@@ -1400,17 +1398,17 @@ class BlockReqType(Enum):
 
 
 @dataclass
-class BlockReqInput:
+class BlockReqInput(BaseReq):
     type: BlockReqType
 
 
 @dataclass
-class GetLoadReqInput:
+class GetLoadReqInput(BaseReq):
     pass
 
 
 @dataclass
-class GetLoadReqOutput:
+class GetLoadReqOutput(BaseReq):
     dp_rank: int
     num_reqs: int
     num_waiting_reqs: int
@@ -1418,5 +1416,31 @@ class GetLoadReqOutput:
 
 
 @dataclass
-class WatchLoadUpdateReq:
+class WatchLoadUpdateReq(BaseReq):
     loads: List[GetLoadReqOutput]
+
+
+def _check_all_req_types():
+    """A helper function to check all request types are defined in this file."""
+    import inspect
+    import sys
+
+    all_classes = inspect.getmembers(sys.modules[__name__], inspect.isclass)
+    for class_type in all_classes:
+        # check its name
+        name = class_type[0]
+        is_io_struct = (
+            name.endswith("Req") or name.endswith("Input") or name.endswith("Output")
+        )
+        is_base_req = issubclass(class_type[1], BaseReq) or issubclass(
+            class_type[1], BaseBatchReq
+        )
+        if is_io_struct and not is_base_req:
+            raise ValueError(f"{name} is not a subclass of BaseReq or BaseBatchReq.")
+        if is_base_req and not is_io_struct:
+            raise ValueError(
+                f"{name} is a subclass of BaseReq but not follow the naming convention."
+            )
+
+
+_check_all_req_types()

python/sglang/srt/managers/multi_tokenizer_mixin.py

@@ -11,7 +11,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ==============================================================================
-"""MultiTokenizerMixin is a class that provides nesscary methods for MultiTokenizerManager and DetokenizerManager."""
+"""Mixin class and utils for multi-http-worker mode"""
 import asyncio
 import logging
 import multiprocessing as multiprocessing
@@ -30,10 +30,10 @@ import zmq.asyncio
 from sglang.srt.disaggregation.utils import DisaggregationMode, TransferBackend
 from sglang.srt.managers.disagg_service import start_disagg_service
 from sglang.srt.managers.io_struct import (
-    BatchEmbeddingOut,
+    BatchEmbeddingOutput,
-    BatchMultimodalOut,
+    BatchMultimodalOutput,
-    BatchStrOut,
+    BatchStrOutput,
-    BatchTokenIDOut,
+    BatchTokenIDOutput,
     MultiTokenizerRegisterReq,
     MultiTokenizerWrapper,
 )
@@ -83,8 +83,8 @@ class SocketMapping:
 
 def _handle_output_by_index(output, i):
     """NOTE: A maintainable method is better here."""
-    if isinstance(output, BatchTokenIDOut):
+    if isinstance(output, BatchTokenIDOutput):
-        new_output = BatchTokenIDOut(
+        new_output = BatchTokenIDOutput(
             rids=[output.rids[i]],
             finished_reasons=(
                 [output.finished_reasons[i]]
@@ -198,8 +198,8 @@ def _handle_output_by_index(output, i):
             placeholder_tokens_idx=None,
             placeholder_tokens_val=None,
         )
-    elif isinstance(output, BatchEmbeddingOut):
+    elif isinstance(output, BatchEmbeddingOutput):
-        new_output = BatchEmbeddingOut(
+        new_output = BatchEmbeddingOutput(
             rids=[output.rids[i]],
             finished_reasons=(
                 [output.finished_reasons[i]]
@@ -216,8 +216,8 @@ def _handle_output_by_index(output, i):
             placeholder_tokens_idx=None,
             placeholder_tokens_val=None,
         )
-    elif isinstance(output, BatchStrOut):
+    elif isinstance(output, BatchStrOutput):
-        new_output = BatchStrOut(
+        new_output = BatchStrOutput(
             rids=[output.rids[i]],
             finished_reasons=(
                 [output.finished_reasons[i]]
@@ -314,8 +314,8 @@ def _handle_output_by_index(output, i):
             placeholder_tokens_idx=None,
             placeholder_tokens_val=None,
         )
-    elif isinstance(output, BatchMultimodalOut):
+    elif isinstance(output, BatchMultimodalOutput):
-        new_output = BatchMultimodalOut(
+        new_output = BatchMultimodalOutput(
             rids=[output.rids[i]],
             finished_reasons=(
                 [output.finished_reasons[i]]
@@ -343,7 +343,7 @@ def _handle_output_by_index(output, i):
 
 
 class MultiHttpWorkerDetokenizerMixin:
-    """Mixin class for MultiTokenizerManager and DetokenizerManager"""
+    """Mixin class for DetokenizerManager"""
 
     def get_worker_ids_from_req_rids(self, rids):
         if isinstance(rids, list):
@@ -386,7 +386,7 @@ class MultiHttpWorkerDetokenizerMixin:
 
 
 class MultiTokenizerRouter:
-    """A router to receive requests from MultiTokenizerManager"""
+    """A router to receive requests from TokenizerWorker"""
 
     def __init__(
         self,
@@ -454,8 +454,8 @@ class MultiTokenizerRouter:
                 self.socket_mapping.send_output(worker_id, new_recv_obj)
 
 
-class MultiTokenizerManager(TokenizerManager):
+class TokenizerWorker(TokenizerManager):
-    """Multi Process Tokenizer Manager that tokenizes the text."""
+    """Tokenizer Worker in multi-http-worker mode"""
 
     def __init__(
         self,

python/sglang/srt/managers/scheduler.py

@@ -78,6 +78,7 @@ from sglang.srt.managers.io_struct import (
     DestroyWeightsUpdateGroupReqInput,
     ExpertDistributionReq,
     ExpertDistributionReqOutput,
+    ExpertDistributionReqType,
     FlushCacheReqInput,
     FlushCacheReqOutput,
     FreezeGCReq,
@@ -1487,12 +1488,12 @@ class Scheduler(
                 req.priority = -sys.maxsize - 1
         elif not self.enable_priority_scheduling and req.priority is not None:
             abort_req = AbortReq(
-                req.rid,
                 finished_reason={
                     "type": "abort",
                     "status_code": HTTPStatus.SERVICE_UNAVAILABLE,
                     "message": "Using priority is disabled for this server. Please send a new request without a priority.",
                 },
+                rid=req.rid,
             )
             self.send_to_tokenizer.send_pyobj(abort_req)
 
@@ -1528,12 +1529,12 @@ class Scheduler(
 
         self.send_to_tokenizer.send_pyobj(
             AbortReq(
-                req_to_abort.rid,
                 finished_reason={
                     "type": "abort",
                     "status_code": HTTPStatus.SERVICE_UNAVAILABLE,
                     "message": message,
                 },
+                rid=req_to_abort.rid,
             )
         )
         return req_to_abort.rid == recv_req.rid
@@ -2005,7 +2006,7 @@ class Scheduler(
             self.new_token_ratio = new_token_ratio
             for req in reqs_to_abort:
                 self.send_to_tokenizer.send_pyobj(
-                    AbortReq(req.rid, abort_reason=req.to_abort_message)
+                    AbortReq(abort_reason=req.to_abort_message, rid=req.rid)
                 )
 
             logger.info(
@@ -2575,7 +2576,7 @@ class Scheduler(
             if self.enable_hicache_storage:
                 # to release prefetch events associated with the request
                 self.tree_cache.release_aborted_request(req.rid)
-            self.send_to_tokenizer.send_pyobj(AbortReq(req.rid))
+            self.send_to_tokenizer.send_pyobj(AbortReq(rid=req.rid))
             # For disaggregation decode mode, the request in the waiting queue has KV cache allocated.
             if self.disaggregation_mode == DisaggregationMode.DECODE:
                 self.tree_cache.cache_finished_req(req)
@@ -2687,11 +2688,12 @@ class Scheduler(
         return SlowDownReqOutput()
 
     def expert_distribution_handle(self, recv_req: ExpertDistributionReq):
-        if recv_req == ExpertDistributionReq.START_RECORD:
+        action = recv_req.action
+        if action == ExpertDistributionReqType.START_RECORD:
             get_global_expert_distribution_recorder().start_record()
-        elif recv_req == ExpertDistributionReq.STOP_RECORD:
+        elif action == ExpertDistributionReqType.STOP_RECORD:
             get_global_expert_distribution_recorder().stop_record()
-        elif recv_req == ExpertDistributionReq.DUMP_RECORD:
+        elif action == ExpertDistributionReqType.DUMP_RECORD:
             get_global_expert_distribution_recorder().dump_record()
         else:
             raise ValueError(f"Unrecognized ExpertDistributionReq value: {recv_req=}")
@@ -2774,7 +2776,8 @@ class IdleSleeper:
 
 
 def is_health_check_generate_req(recv_req):
-    return getattr(recv_req, "rid", "").startswith("HEALTH_CHECK")
+    rid = getattr(recv_req, "rid", None)
+    return rid is not None and rid.startswith("HEALTH_CHECK")
 
 
 def is_work_request(recv_req):

python/sglang/srt/managers/scheduler_output_processor_mixin.py

@@ -9,7 +9,11 @@ import torch
 
 from sglang.srt.disaggregation.utils import DisaggregationMode
 from sglang.srt.layers.logits_processor import LogitsProcessorOutput
-from sglang.srt.managers.io_struct import AbortReq, BatchEmbeddingOut, BatchTokenIDOut
+from sglang.srt.managers.io_struct import (
+    AbortReq,
+    BatchEmbeddingOutput,
+    BatchTokenIDOutput,
+)
 from sglang.srt.managers.schedule_batch import BaseFinishReason, Req, ScheduleBatch
 
 if TYPE_CHECKING:
@@ -140,7 +144,7 @@ class SchedulerOutputProcessorMixin:
                             logger.error(
                                 f"Grammar accept_token failed for req {req.rid} with token {next_token_id}: {e}"
                             )
-                            self.abort_request(AbortReq(req.rid))
+                            self.abort_request(AbortReq(rid=req.rid))
                         req.grammar.finished = req.finished()
                 else:
                     # being chunked reqs' prefill is not finished
@@ -292,7 +296,7 @@ class SchedulerOutputProcessorMixin:
                     logger.error(
                         f"Grammar accept_token failed for req {req.rid} with token {next_token_id}: {e}"
                     )
-                    self.abort_request(AbortReq(req.rid))
+                    self.abort_request(AbortReq(rid=req.rid))
                 req.grammar.finished = req.finished()
 
         self.set_next_batch_sampling_info_done(batch)
@@ -714,8 +718,7 @@ class SchedulerOutputProcessorMixin:
                 return
 
             self.send_to_detokenizer.send_pyobj(
-                BatchTokenIDOut(
+                BatchTokenIDOutput(
-                    rids,
                     finished_reasons,
                     decoded_texts,
                     decode_ids_list,
@@ -741,6 +744,7 @@ class SchedulerOutputProcessorMixin:
                     output_token_ids_logprobs_val,
                     output_token_ids_logprobs_idx,
                     output_hidden_states,
+                    rids=rids,
                     placeholder_tokens_idx=None,
                     placeholder_tokens_val=None,
                 )
@@ -761,12 +765,12 @@ class SchedulerOutputProcessorMixin:
                 prompt_tokens.append(len(req.origin_input_ids))
                 cached_tokens.append(req.cached_tokens)
         self.send_to_detokenizer.send_pyobj(
-            BatchEmbeddingOut(
+            BatchEmbeddingOutput(
-                rids,
                 finished_reasons,
                 embeddings,
                 prompt_tokens,
                 cached_tokens,
+                rids=rids,
                 placeholder_tokens_idx=None,
                 placeholder_tokens_val=None,
             )

python/sglang/srt/managers/tokenizer_communicator_mixin.py

@@ -30,6 +30,7 @@ from sglang.srt.managers.io_struct import (
     DestroyWeightsUpdateGroupReqOutput,
     ExpertDistributionReq,
     ExpertDistributionReqOutput,
+    ExpertDistributionReqType,
     FlushCacheReqInput,
     FlushCacheReqOutput,
     GetInternalStateReq,
@@ -44,7 +45,7 @@ from sglang.srt.managers.io_struct import (
     InitWeightsUpdateGroupReqOutput,
     LoadLoRAAdapterReqInput,
     LoadLoRAAdapterReqOutput,
-    LoRAUpdateResult,
+    LoRAUpdateOutput,
     MultiTokenizerWrapper,
     OpenSessionReqInput,
     ProfileReq,
@@ -276,7 +277,7 @@ class TokenizerCommunicatorMixin:
                     self.expert_distribution_communicator.handle_recv,
                 ),
                 (
-                    LoRAUpdateResult,
+                    LoRAUpdateOutput,
                     self.update_lora_adapter_communicator.handle_recv,
                 ),
                 (
@@ -335,15 +336,18 @@ class TokenizerCommunicatorMixin:
 
     async def start_expert_distribution_record(self: TokenizerManager):
         self.auto_create_handle_loop()
-        await self.expert_distribution_communicator(ExpertDistributionReq.START_RECORD)
+        req = ExpertDistributionReq(action=ExpertDistributionReqType.START_RECORD)
+        await self.expert_distribution_communicator(req)
 
     async def stop_expert_distribution_record(self: TokenizerManager):
         self.auto_create_handle_loop()
-        await self.expert_distribution_communicator(ExpertDistributionReq.STOP_RECORD)
+        req = ExpertDistributionReq(action=ExpertDistributionReqType.STOP_RECORD)
+        await self.expert_distribution_communicator(req)
 
     async def dump_expert_distribution_record(self: TokenizerManager):
         self.auto_create_handle_loop()
-        await self.expert_distribution_communicator(ExpertDistributionReq.DUMP_RECORD)
+        req = ExpertDistributionReq(action=ExpertDistributionReqType.DUMP_RECORD)
+        await self.expert_distribution_communicator(req)
 
     async def init_weights_update_group(
         self: TokenizerManager,

python/sglang/srt/managers/tokenizer_manager.py

@@ -48,18 +48,17 @@ from sglang.srt.hf_transformers_utils import (
     get_tokenizer,
     get_tokenizer_from_processor,
 )
-from sglang.srt.lora.lora_registry import LoRARef, LoRARegistry
+from sglang.srt.lora.lora_registry import LoRARegistry
 from sglang.srt.managers.async_dynamic_batch_tokenizer import AsyncDynamicbatchTokenizer
 from sglang.srt.managers.disagg_service import start_disagg_service
 from sglang.srt.managers.io_struct import (
     AbortReq,
-    BatchEmbeddingOut,
+    BatchEmbeddingOutput,
-    BatchMultimodalOut,
+    BatchMultimodalOutput,
-    BatchStrOut,
+    BatchStrOutput,
-    BatchTokenIDOut,
+    BatchTokenIDOutput,
     BatchTokenizedEmbeddingReqInput,
     BatchTokenizedGenerateReqInput,
-    CloseSessionReqInput,
     ConfigureLoggingReq,
     EmbeddingReqInput,
     FreezeGCReq,
@@ -67,7 +66,6 @@ from sglang.srt.managers.io_struct import (
     GetLoadReqInput,
     HealthCheckOutput,
     MultiTokenizerWrapper,
-    OpenSessionReqInput,
     OpenSessionReqOutput,
     SessionParams,
     TokenizedEmbeddingReqInput,
@@ -341,10 +339,10 @@ class TokenizerManager(TokenizerCommunicatorMixin):
             [
                 (
                     (
-                        BatchStrOut,
+                        BatchStrOutput,
-                        BatchEmbeddingOut,
+                        BatchEmbeddingOutput,
-                        BatchTokenIDOut,
+                        BatchTokenIDOutput,
-                        BatchMultimodalOut,
+                        BatchMultimodalOutput,
                     ),
                     self._handle_batch_output,
                 ),
@@ -716,7 +714,6 @@ class TokenizerManager(TokenizerCommunicatorMixin):
             )
 
             tokenized_obj = TokenizedGenerateReqInput(
-                obj.rid,
                 input_text,
                 input_ids,
                 mm_inputs,
@@ -726,6 +723,7 @@ class TokenizerManager(TokenizerCommunicatorMixin):
                 obj.top_logprobs_num,
                 obj.token_ids_logprob,
                 obj.stream,
+                rid=obj.rid,
                 bootstrap_host=obj.bootstrap_host,
                 bootstrap_port=obj.bootstrap_port,
                 bootstrap_room=obj.bootstrap_room,
@@ -740,12 +738,12 @@ class TokenizerManager(TokenizerCommunicatorMixin):
             )
         elif isinstance(obj, EmbeddingReqInput):
             tokenized_obj = TokenizedEmbeddingReqInput(
-                obj.rid,
                 input_text,
                 input_ids,
                 mm_inputs,
                 token_type_ids,
                 sampling_params,
+                rid=obj.rid,
                 priority=obj.priority,
             )
 
@@ -1038,7 +1036,7 @@ class TokenizerManager(TokenizerCommunicatorMixin):
     def abort_request(self, rid: str = "", abort_all: bool = False):
         if not abort_all and rid not in self.rid_to_state:
             return
-        req = AbortReq(rid, abort_all)
+        req = AbortReq(rid=rid, abort_all=abort_all)
         self.send_to_scheduler.send_pyobj(req)
         if self.enable_metrics:
             # TODO: also use custom_labels from the request
@@ -1303,7 +1301,10 @@ class TokenizerManager(TokenizerCommunicatorMixin):
     def _handle_batch_output(
         self,
         recv_obj: Union[
-            BatchStrOut, BatchEmbeddingOut, BatchMultimodalOut, BatchTokenIDOut
+            BatchStrOutput,
+            BatchEmbeddingOutput,
+            BatchMultimodalOutput,
+            BatchTokenIDOutput,
         ],
     ):
         for i, rid in enumerate(recv_obj.rids):
@@ -1337,7 +1338,7 @@ class TokenizerManager(TokenizerCommunicatorMixin):
                     i,
                 )
 
-            if not isinstance(recv_obj, BatchEmbeddingOut):
+            if not isinstance(recv_obj, BatchEmbeddingOutput):
                 meta_info.update(
                     {
                         "completion_tokens": recv_obj.completion_tokens[i],
@@ -1348,7 +1349,7 @@ class TokenizerManager(TokenizerCommunicatorMixin):
             if getattr(recv_obj, "output_hidden_states", None):
                 meta_info["hidden_states"] = recv_obj.output_hidden_states[i]
 
-            if isinstance(recv_obj, BatchStrOut):
+            if isinstance(recv_obj, BatchStrOutput):
                 state.text += recv_obj.output_strs[i]
                 if state.obj.stream:
                     state.output_ids.extend(recv_obj.output_ids[i])
@@ -1363,7 +1364,7 @@ class TokenizerManager(TokenizerCommunicatorMixin):
                     "output_ids": output_token_ids,
                     "meta_info": meta_info,
                 }
-            elif isinstance(recv_obj, BatchTokenIDOut):
+            elif isinstance(recv_obj, BatchTokenIDOutput):
                 if self.server_args.stream_output and state.obj.stream:
                     state.output_ids.extend(recv_obj.output_ids[i])
                     output_token_ids = state.output_ids[state.last_output_offset :]
@@ -1376,10 +1377,10 @@ class TokenizerManager(TokenizerCommunicatorMixin):
                     "output_ids": output_token_ids,
                     "meta_info": meta_info,
                 }
-            elif isinstance(recv_obj, BatchMultimodalOut):
+            elif isinstance(recv_obj, BatchMultimodalOutput):
                 raise NotImplementedError("BatchMultimodalOut not implemented")
             else:
-                assert isinstance(recv_obj, BatchEmbeddingOut)
+                assert isinstance(recv_obj, BatchEmbeddingOutput)
                 out_dict = {
                     "embedding": recv_obj.embeddings[i],
                     "meta_info": meta_info,
@@ -1418,7 +1419,7 @@ class TokenizerManager(TokenizerCommunicatorMixin):
         top_logprobs_num: int,
         token_ids_logprob: List[int],
         return_text_in_logprobs: bool,
-        recv_obj: BatchStrOut,
+        recv_obj: BatchStrOutput,
         recv_obj_index: int,
     ):
         if recv_obj.input_token_logprobs_val is None:
@@ -1536,7 +1537,7 @@ class TokenizerManager(TokenizerCommunicatorMixin):
                 ret.append(None)
         return ret
 
-    def collect_metrics(self, state: ReqState, recv_obj: BatchStrOut, i: int):
+    def collect_metrics(self, state: ReqState, recv_obj: BatchStrOutput, i: int):
         completion_tokens = (
             recv_obj.completion_tokens[i]
             if getattr(recv_obj, "completion_tokens", None)
@@ -1632,7 +1633,7 @@ class TokenizerManager(TokenizerCommunicatorMixin):
 
         asyncio.create_task(asyncio.to_thread(background_task))
 
-    def _handle_abort_req(self, recv_obj):
+    def _handle_abort_req(self, recv_obj: AbortReq):
         if is_health_check_generate_req(recv_obj):
             return
         state = self.rid_to_state[recv_obj.rid]