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[router][refactor] Clean up protobuf fields (#10923)

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This commit is contained in:
Chang Su
2025-09-25 17:48:47 -07:00
committed by GitHub
parent f7bab41a29
commit 7dcd689b47
5 changed files with 102 additions and 109 deletions
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15
python/sglang/srt/entrypoints/grpc_server.py
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@@ -266,7 +266,6 @@ class SGLangSchedulerServicer(sglang_scheduler_pb2_grpc.SglangSchedulerServicer)
prompt_tokens=result.get("prompt_tokens", 0),
cached_tokens=0,
embedding_dim=len(result["embedding"]),
generation_time=time.time() - self.start_time,
),
)
@@ -477,16 +476,14 @@ class SGLangSchedulerServicer(sglang_scheduler_pb2_grpc.SglangSchedulerServicer)
self, request_id: str, output: Dict
) -> sglang_scheduler_pb2.GenerateResponse:
"""Create a streaming chunk response."""
meta_info = output.get("meta_info", {})
return sglang_scheduler_pb2.GenerateResponse(
request_id=request_id,
chunk=sglang_scheduler_pb2.GenerateStreamChunk(
token_id=output["token_ids"][-1] if output.get("token_ids") else 0,
text=output.get("text", ""),
prompt_tokens=0,
completion_tokens=len(output.get("token_ids", [])),
prompt_tokens=meta_info.get("prompt_tokens", 0),
completion_tokens=meta_info.get("completion_tokens", 0),
cached_tokens=0,
generation_time=time.time() - self.start_time,
queue_time=0.0,
),
)
@@ -507,8 +504,12 @@ class SGLangSchedulerServicer(sglang_scheduler_pb2_grpc.SglangSchedulerServicer)
request_id=request_id,
complete=sglang_scheduler_pb2.GenerateComplete(
output_ids=output.get("token_ids", []),
output_text=output.get("text", ""),
finish_reason=finish_reason,
prompt_tokens=meta_info.get("prompt_tokens", 0),
completion_tokens=meta_info.get(
"completion_tokens", len(output.get("token_ids", []))
),
cached_tokens=meta_info.get("cached_tokens", 0),
),
)

30
python/sglang/srt/grpc/sglang_scheduler.proto
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@@ -165,28 +165,22 @@ message GenerateResponse {
message GenerateStreamChunk {
// Generated token
int32 token_id = 1;
string text = 2;
// Cumulative counts
int32 prompt_tokens = 3;
int32 completion_tokens = 4;
int32 cached_tokens = 5;
int32 prompt_tokens = 2;
int32 completion_tokens = 3;
int32 cached_tokens = 4;
// Logprobs (if requested)
LogProbs logprobs = 6;
LogProbs logprobs = 5;
// Hidden states (if requested)
repeated float hidden_states = 7;
// Metadata
float generation_time = 8; // Time to generate this token
int32 queue_time = 9; // Time spent in queue
repeated float hidden_states = 6;
}
message GenerateComplete {
// Final output
repeated int32 output_ids = 1;
string output_text = 2;
// Finish reason
enum FinishReason {
@@ -201,13 +195,18 @@ message GenerateComplete {
// The request was aborted by the user or system.
ABORT = 4;
}
FinishReason finish_reason = 3;
FinishReason finish_reason = 2;
// Token usage counts
int32 prompt_tokens = 3;
int32 completion_tokens = 4;
int32 cached_tokens = 5;
// All logprobs if requested
repeated LogProbs all_logprobs = 11;
repeated LogProbs all_logprobs = 6;
// All hidden states if requested
repeated HiddenStates all_hidden_states = 12;
repeated HiddenStates all_hidden_states = 7;
}
message GenerateError {
@@ -285,10 +284,9 @@ message EmbedComplete {
// Additional metadata
int32 embedding_dim = 4;
float generation_time = 5;
// For batch embeddings
repeated Embedding batch_embeddings = 6;
repeated Embedding batch_embeddings = 5;
}
message Embedding {

108
python/sglang/srt/grpc/sglang_scheduler_pb2.py
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File diff suppressed because one or more lines are too long

28
python/sglang/srt/grpc/sglang_scheduler_pb2.pyi
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@@ -161,29 +161,23 @@ class GenerateResponse(_message.Message):
def __init__(self, request_id: _Optional[str] = ..., chunk: _Optional[_Union[GenerateStreamChunk, _Mapping]] = ..., complete: _Optional[_Union[GenerateComplete, _Mapping]] = ..., error: _Optional[_Union[GenerateError, _Mapping]] = ...) -> None: ...
class GenerateStreamChunk(_message.Message):
__slots__ = ("token_id", "text", "prompt_tokens", "completion_tokens", "cached_tokens", "logprobs", "hidden_states", "generation_time", "queue_time")
__slots__ = ("token_id", "prompt_tokens", "completion_tokens", "cached_tokens", "logprobs", "hidden_states")
TOKEN_ID_FIELD_NUMBER: _ClassVar[int]
TEXT_FIELD_NUMBER: _ClassVar[int]
PROMPT_TOKENS_FIELD_NUMBER: _ClassVar[int]
COMPLETION_TOKENS_FIELD_NUMBER: _ClassVar[int]
CACHED_TOKENS_FIELD_NUMBER: _ClassVar[int]
LOGPROBS_FIELD_NUMBER: _ClassVar[int]
HIDDEN_STATES_FIELD_NUMBER: _ClassVar[int]
GENERATION_TIME_FIELD_NUMBER: _ClassVar[int]
QUEUE_TIME_FIELD_NUMBER: _ClassVar[int]
token_id: int
text: str
prompt_tokens: int
completion_tokens: int
cached_tokens: int
logprobs: LogProbs
hidden_states: _containers.RepeatedScalarFieldContainer[float]
generation_time: float
queue_time: int
def __init__(self, token_id: _Optional[int] = ..., text: _Optional[str] = ..., prompt_tokens: _Optional[int] = ..., completion_tokens: _Optional[int] = ..., cached_tokens: _Optional[int] = ..., logprobs: _Optional[_Union[LogProbs, _Mapping]] = ..., hidden_states: _Optional[_Iterable[float]] = ..., generation_time: _Optional[float] = ..., queue_time: _Optional[int] = ...) -> None: ...
def __init__(self, token_id: _Optional[int] = ..., prompt_tokens: _Optional[int] = ..., completion_tokens: _Optional[int] = ..., cached_tokens: _Optional[int] = ..., logprobs: _Optional[_Union[LogProbs, _Mapping]] = ..., hidden_states: _Optional[_Iterable[float]] = ...) -> None: ...
class GenerateComplete(_message.Message):
__slots__ = ("output_ids", "output_text", "finish_reason", "all_logprobs", "all_hidden_states")
__slots__ = ("output_ids", "finish_reason", "prompt_tokens", "completion_tokens", "cached_tokens", "all_logprobs", "all_hidden_states")
class FinishReason(int, metaclass=_enum_type_wrapper.EnumTypeWrapper):
__slots__ = ()
STOP: _ClassVar[GenerateComplete.FinishReason]
@@ -197,16 +191,20 @@ class GenerateComplete(_message.Message):
STOP_STR: GenerateComplete.FinishReason
ABORT: GenerateComplete.FinishReason
OUTPUT_IDS_FIELD_NUMBER: _ClassVar[int]
OUTPUT_TEXT_FIELD_NUMBER: _ClassVar[int]
FINISH_REASON_FIELD_NUMBER: _ClassVar[int]
PROMPT_TOKENS_FIELD_NUMBER: _ClassVar[int]
COMPLETION_TOKENS_FIELD_NUMBER: _ClassVar[int]
CACHED_TOKENS_FIELD_NUMBER: _ClassVar[int]
ALL_LOGPROBS_FIELD_NUMBER: _ClassVar[int]
ALL_HIDDEN_STATES_FIELD_NUMBER: _ClassVar[int]
output_ids: _containers.RepeatedScalarFieldContainer[int]
output_text: str
finish_reason: GenerateComplete.FinishReason
prompt_tokens: int
completion_tokens: int
cached_tokens: int
all_logprobs: _containers.RepeatedCompositeFieldContainer[LogProbs]
all_hidden_states: _containers.RepeatedCompositeFieldContainer[HiddenStates]
def __init__(self, output_ids: _Optional[_Iterable[int]] = ..., output_text: _Optional[str] = ..., finish_reason: _Optional[_Union[GenerateComplete.FinishReason, str]] = ..., all_logprobs: _Optional[_Iterable[_Union[LogProbs, _Mapping]]] = ..., all_hidden_states: _Optional[_Iterable[_Union[HiddenStates, _Mapping]]] = ...) -> None: ...
def __init__(self, output_ids: _Optional[_Iterable[int]] = ..., finish_reason: _Optional[_Union[GenerateComplete.FinishReason, str]] = ..., prompt_tokens: _Optional[int] = ..., completion_tokens: _Optional[int] = ..., cached_tokens: _Optional[int] = ..., all_logprobs: _Optional[_Iterable[_Union[LogProbs, _Mapping]]] = ..., all_hidden_states: _Optional[_Iterable[_Union[HiddenStates, _Mapping]]] = ...) -> None: ...
class GenerateError(_message.Message):
__slots__ = ("message", "http_status_code", "details")
@@ -283,20 +281,18 @@ class EmbedResponse(_message.Message):
def __init__(self, request_id: _Optional[str] = ..., complete: _Optional[_Union[EmbedComplete, _Mapping]] = ..., error: _Optional[_Union[EmbedError, _Mapping]] = ...) -> None: ...
class EmbedComplete(_message.Message):
__slots__ = ("embedding", "prompt_tokens", "cached_tokens", "embedding_dim", "generation_time", "batch_embeddings")
__slots__ = ("embedding", "prompt_tokens", "cached_tokens", "embedding_dim", "batch_embeddings")
EMBEDDING_FIELD_NUMBER: _ClassVar[int]
PROMPT_TOKENS_FIELD_NUMBER: _ClassVar[int]
CACHED_TOKENS_FIELD_NUMBER: _ClassVar[int]
EMBEDDING_DIM_FIELD_NUMBER: _ClassVar[int]
GENERATION_TIME_FIELD_NUMBER: _ClassVar[int]
BATCH_EMBEDDINGS_FIELD_NUMBER: _ClassVar[int]
embedding: _containers.RepeatedScalarFieldContainer[float]
prompt_tokens: int
cached_tokens: int
embedding_dim: int
generation_time: float
batch_embeddings: _containers.RepeatedCompositeFieldContainer[Embedding]
def __init__(self, embedding: _Optional[_Iterable[float]] = ..., prompt_tokens: _Optional[int] = ..., cached_tokens: _Optional[int] = ..., embedding_dim: _Optional[int] = ..., generation_time: _Optional[float] = ..., batch_embeddings: _Optional[_Iterable[_Union[Embedding, _Mapping]]] = ...) -> None: ...
def __init__(self, embedding: _Optional[_Iterable[float]] = ..., prompt_tokens: _Optional[int] = ..., cached_tokens: _Optional[int] = ..., embedding_dim: _Optional[int] = ..., batch_embeddings: _Optional[_Iterable[_Union[Embedding, _Mapping]]] = ...) -> None: ...
class Embedding(_message.Message):
__slots__ = ("values", "index")