refactor: replace local proto compilation with smg-grpc-proto package (#18682)
This commit is contained in:
@@ -21,11 +21,11 @@ from google.protobuf.struct_pb2 import Struct
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from google.protobuf.timestamp_pb2 import Timestamp
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from grpc_health.v1 import health_pb2_grpc
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from grpc_reflection.v1alpha import reflection
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from smg_grpc_proto import sglang_scheduler_pb2, sglang_scheduler_pb2_grpc
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import sglang
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from sglang.srt.configs.model_config import ModelConfig
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from sglang.srt.disaggregation.utils import FAKE_BOOTSTRAP_HOST, DisaggregationMode
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from sglang.srt.grpc import sglang_scheduler_pb2, sglang_scheduler_pb2_grpc
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from sglang.srt.grpc.grpc_request_manager import GrpcRequestManager
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from sglang.srt.grpc.health_servicer import SGLangHealthServicer
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from sglang.srt.grpc.scheduler_launcher import launch_scheduler_process_only
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@@ -1,248 +0,0 @@
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#!/usr/bin/env python3
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"""
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Compile protobuf files for SGLang gRPC server.
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This script compiles .proto files to Python code using grpc_tools.protoc.
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It generates:
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- *_pb2.py (protobuf message classes)
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- *_pb2_grpc.py (gRPC service classes)
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- *_pb2.pyi (type hints for mypy/IDEs)
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Usage:
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python compile_proto.py [--check] [--proto-file PROTO_FILE]
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Options:
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--check Check if regeneration is needed (exit 1 if needed)
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--proto-file Specify proto file (default: sglang_scheduler.proto)
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### Install Dependencies
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pip install "grpcio==1.75.1" "grpcio-tools==1.75.1"
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Please make sure to use the same version of grpcio and grpcio-tools specified in pyproject.toml
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otherwise update the versions specified in pyproject.toml
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### Run Script
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cd python/sglang/srt/grpc
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python compile_proto.py
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"""
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import argparse
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import subprocess
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import sys
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from importlib.metadata import version
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from pathlib import Path
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GRPC_VERSION = "1.75.1"
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def get_file_mtime(path: Path) -> float:
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"""Get file modification time, return 0 if file doesn't exist."""
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try:
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return path.stat().st_mtime
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except FileNotFoundError:
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return 0.0
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def check_regeneration_needed(proto_file: Path, output_dir: Path) -> bool:
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"""Check if proto files are newer than generated files."""
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proto_mtime = get_file_mtime(proto_file)
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generated_files = [
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output_dir / f"{proto_file.stem}_pb2.py",
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output_dir / f"{proto_file.stem}_pb2_grpc.py",
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output_dir / f"{proto_file.stem}_pb2.pyi",
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]
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for gen_file in generated_files:
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if get_file_mtime(gen_file) < proto_mtime:
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return True
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return False
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def compile_proto(proto_file: Path, output_dir: Path, verbose: bool = True) -> bool:
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"""Compile the protobuf file to Python."""
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if not proto_file.exists():
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print(f"Error: Proto file not found: {proto_file}")
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return False
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if verbose:
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print(f"Found proto file: {proto_file}")
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# Check if grpc_tools is available
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try:
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import grpc_tools.protoc # noqa: F401
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except ImportError:
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print("Error: grpcio-tools not installed")
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print(
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f'Install with: pip install "grpcio-tools=={GRPC_VERSION}" "grpcio=={GRPC_VERSION}"'
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)
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return False
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grpc_tools_version = version("grpcio-tools")
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grpc_version = version("grpcio")
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if grpc_tools_version != GRPC_VERSION or grpc_version != GRPC_VERSION:
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raise RuntimeError(
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f"Error: grpcio-tools version {grpc_tools_version} and grpcio version {grpc_version} detected, but {GRPC_VERSION} is required."
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)
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# Compile command
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cmd = [
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sys.executable,
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"-m",
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"grpc_tools.protoc",
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f"-I{proto_file.parent}",
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f"--python_out={output_dir}",
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f"--grpc_python_out={output_dir}",
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f"--pyi_out={output_dir}", # Generate type stubs
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str(proto_file.name),
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]
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if verbose:
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print(f"Running: {' '.join(cmd)}")
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# Run protoc
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result = subprocess.run(cmd, capture_output=True, text=True, cwd=proto_file.parent)
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if result.returncode != 0:
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print(f"Error compiling proto:")
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print(result.stderr)
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if result.stdout:
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print(result.stdout)
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return False
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# Verify generated files exist
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generated_files = [
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f"{proto_file.stem}_pb2.py",
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f"{proto_file.stem}_pb2_grpc.py",
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f"{proto_file.stem}_pb2.pyi",
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]
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missing_files = []
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for gen_file in generated_files:
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if not (output_dir / gen_file).exists():
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missing_files.append(gen_file)
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if missing_files:
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print(f"Error: Expected generated files not found: {missing_files}")
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return False
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if verbose:
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print("Successfully compiled protobuf files:")
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for gen_file in generated_files:
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print(f" - {output_dir}/{gen_file}")
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# Fix imports in generated files
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fix_imports(output_dir, proto_file.stem, verbose)
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return True
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def fix_imports(output_dir: Path, proto_stem: str, verbose: bool = True) -> None:
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"""Fix imports in generated files to use relative imports."""
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grpc_file = output_dir / f"{proto_stem}_pb2_grpc.py"
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if grpc_file.exists():
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content = grpc_file.read_text()
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# Change absolute import to relative import
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old_import = f"import {proto_stem}_pb2"
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new_import = f"from . import {proto_stem}_pb2"
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if old_import in content:
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content = content.replace(old_import, new_import)
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grpc_file.write_text(content)
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if verbose:
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print("Fixed imports in generated files")
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def add_generation_header(output_dir: Path, proto_stem: str) -> None:
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"""Add header to generated files indicating they are auto-generated."""
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header = """# This file is auto-generated. Do not edit manually.
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# Regenerate with: python compile_proto.py
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"""
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files_to_update = [f"{proto_stem}_pb2.py", f"{proto_stem}_pb2_grpc.py"]
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for filename in files_to_update:
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file_path = output_dir / filename
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if file_path.exists():
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content = file_path.read_text()
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if not content.startswith("# This file is auto-generated"):
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file_path.write_text(header + content)
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def main():
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"""Main entry point."""
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parser = argparse.ArgumentParser(
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description="Compile protobuf files for SGLang gRPC server",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog=__doc__,
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)
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parser.add_argument(
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"--check",
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action="store_true",
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help="Check if regeneration is needed (exit 1 if needed)",
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)
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parser.add_argument(
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"--proto-file",
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type=str,
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default="sglang_scheduler.proto",
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help="Proto file to compile (default: sglang_scheduler.proto)",
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)
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parser.add_argument(
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"-v",
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"--verbose",
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action="store_true",
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default=True,
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help="Verbose output (default: True)",
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)
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parser.add_argument(
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"-q", "--quiet", action="store_true", help="Quiet mode (overrides verbose)"
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)
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args = parser.parse_args()
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# Handle verbosity
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verbose = args.verbose and not args.quiet
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# Get paths
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script_dir = Path(__file__).parent
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proto_file = script_dir / args.proto_file
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output_dir = script_dir
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# Check mode
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if args.check:
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if check_regeneration_needed(proto_file, output_dir):
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if verbose:
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print("Proto files need regeneration")
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sys.exit(1)
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else:
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if verbose:
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print("Generated files are up to date")
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sys.exit(0)
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# Compile mode
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success = compile_proto(proto_file, output_dir, verbose)
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if success:
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# Add generation headers
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add_generation_header(output_dir, proto_file.stem)
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if verbose:
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print("\n✅ Protobuf compilation successful!")
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print("Generated files are ready for use")
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else:
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if verbose:
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print("\n❌ Protobuf compilation failed!")
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sys.exit(1)
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if __name__ == "__main__":
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main()
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@@ -1,566 +0,0 @@
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syntax = "proto3";
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package sglang.grpc.scheduler;
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import "google/protobuf/timestamp.proto";
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import "google/protobuf/struct.proto";
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// Service definition for SGLang scheduler communication
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// This protocol bridges the Rust router and Python scheduler
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service SglangScheduler {
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// Submit a generation request (supports streaming)
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rpc Generate(GenerateRequest) returns (stream GenerateResponse);
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// Submit an embedding request
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rpc Embed(EmbedRequest) returns (EmbedResponse);
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// Health check and metrics
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rpc HealthCheck(HealthCheckRequest) returns (HealthCheckResponse);
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// Abort a running request
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rpc Abort(AbortRequest) returns (AbortResponse);
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// Get model information
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rpc GetModelInfo(GetModelInfoRequest) returns (GetModelInfoResponse);
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// Get server information
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rpc GetServerInfo(GetServerInfoRequest) returns (GetServerInfoResponse);
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// Get comprehensive load metrics
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rpc GetLoads(GetLoadsRequest) returns (GetLoadsResponse);
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}
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// =====================
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// Common Types
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// =====================
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// Sampling parameters matching SGLang's SamplingParams
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//
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// IMPORTANT: Do not use SamplingParams::default() directly!
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// The proto3 defaults (0 for numeric fields) do NOT match the semantic defaults
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// (temperature=1.0, top_p=1.0, top_k=-1, etc.). Always construct with explicit values
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// or use the conversion functions in sglang_scheduler.rs / grpc_server.py.
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message SamplingParams {
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float temperature = 1;
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float top_p = 2;
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int32 top_k = 3;
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float min_p = 4;
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float frequency_penalty = 5;
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float presence_penalty = 6;
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float repetition_penalty = 7;
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optional int32 max_new_tokens = 8;
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repeated string stop = 9;
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repeated uint32 stop_token_ids = 10;
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bool skip_special_tokens = 11;
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bool spaces_between_special_tokens = 12;
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// Structured generation
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oneof constraint {
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string regex = 13;
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string json_schema = 14;
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string ebnf_grammar = 15;
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string structural_tag = 16;
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}
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// Speculative decoding
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int32 n = 17; // Number of samples
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// Additional parameters
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int32 min_new_tokens = 18;
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bool ignore_eos = 19;
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bool no_stop_trim = 20;
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optional int32 stream_interval = 21;
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map<string, float> logit_bias = 22;
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// Custom parameters for extensibility
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google.protobuf.Struct custom_params = 23;
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}
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// Disaggregated serving parameters
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message DisaggregatedParams {
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string bootstrap_host = 1;
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int32 bootstrap_port = 2;
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int32 bootstrap_room = 3;
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}
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// =====================
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// Generate Request
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// =====================
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message GenerateRequest {
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string request_id = 1;
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// Input must be tokenized (no raw text)
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TokenizedInput tokenized = 2;
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// Multimodal inputs
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MultimodalInputs mm_inputs = 3;
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// Generation parameters
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SamplingParams sampling_params = 4;
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// Return options
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bool return_logprob = 5;
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int32 logprob_start_len = 6;
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int32 top_logprobs_num = 7;
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repeated uint32 token_ids_logprob = 8;
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bool return_hidden_states = 9;
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// For disaggregated serving
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DisaggregatedParams disaggregated_params = 10;
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// Custom logit processor (serialized)
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string custom_logit_processor = 11;
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// Request metadata
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google.protobuf.Timestamp timestamp = 12;
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bool log_metrics = 13;
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// Input embeddings (alternative to text/tokens)
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repeated float input_embeds = 14;
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// LoRA adapter ID (if pre-loaded)
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string lora_id = 15;
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// Data parallel routing
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int32 data_parallel_rank = 16;
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// Whether client wants streaming response
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bool stream = 17;
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}
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message TokenizedInput {
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string original_text = 1; // For reference
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repeated uint32 input_ids = 2;
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}
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message MultimodalInputs {
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// Simplified multimodal handling - actual data processed by tokenizer
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repeated string image_urls = 1;
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repeated string video_urls = 2;
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repeated string audio_urls = 3;
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// Pre-processed multimodal features (if available)
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google.protobuf.Struct processed_features = 4;
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// Raw data for direct processing
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repeated bytes image_data = 5;
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repeated bytes video_data = 6;
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repeated bytes audio_data = 7;
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// Modality metadata
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repeated string modalities = 8;
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}
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// =====================
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// Generate Response
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// =====================
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message GenerateResponse {
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string request_id = 1;
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// Response type
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oneof response {
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GenerateStreamChunk chunk = 2;
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GenerateComplete complete = 3;
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GenerateError error = 4;
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}
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}
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message GenerateStreamChunk {
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// Generated tokens (incremental chunk)
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repeated uint32 token_ids = 1;
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// Cumulative counts
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int32 prompt_tokens = 2;
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int32 completion_tokens = 3;
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int32 cached_tokens = 4;
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// Output logprobs (if requested) - incremental for streaming
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OutputLogProbs output_logprobs = 5;
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// Hidden states (if requested)
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repeated float hidden_states = 6;
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// Input logprobs (if requested) - only in first chunk
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InputLogProbs input_logprobs = 7;
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// Index for ordering when n>1 (for parallel request multiplexing)
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uint32 index = 8;
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}
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message GenerateComplete {
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// Final output
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repeated uint32 output_ids = 1;
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// Finish reason as OpenAI-compatible string ("stop", "length", "abort")
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string finish_reason = 2;
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// Token usage counts
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int32 prompt_tokens = 3;
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int32 completion_tokens = 4;
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int32 cached_tokens = 5;
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// Output logprobs if requested (cumulative)
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OutputLogProbs output_logprobs = 6;
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// All hidden states if requested
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repeated HiddenStates all_hidden_states = 7;
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// Matched stop information (for stop sequences)
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oneof matched_stop {
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uint32 matched_token_id = 8;
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string matched_stop_str = 9;
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}
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// Input logprobs if requested (for prompt tokens)
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InputLogProbs input_logprobs = 10;
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// Index for ordering when n>1 (for parallel request multiplexing)
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uint32 index = 11;
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}
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message GenerateError {
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string message = 1;
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string http_status_code = 2;
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string details = 3;
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}
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// Output logprobs - all values are present (no None)
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message OutputLogProbs {
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repeated float token_logprobs = 1;
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repeated int32 token_ids = 2;
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// Top logprobs at each position
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repeated TopLogProbs top_logprobs = 3;
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}
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// Input logprobs - first token has no logprob (None)
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message InputLogProbs {
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repeated InputTokenLogProb token_logprobs = 1;
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repeated int32 token_ids = 2;
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// Top logprobs at each position
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repeated TopLogProbs top_logprobs = 3;
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}
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// Wrapper to represent optional logprob (first input token has no logprob)
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message InputTokenLogProb {
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optional float value = 1;
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}
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message TopLogProbs {
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repeated float values = 1;
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repeated int32 token_ids = 2;
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}
|
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|
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message HiddenStates {
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repeated float values = 1;
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int32 layer = 2;
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int32 position = 3;
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||||
}
|
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|
||||
// =====================
|
||||
// Embedding Request
|
||||
// =====================
|
||||
|
||||
message EmbedRequest {
|
||||
string request_id = 1;
|
||||
|
||||
// Input must be tokenized (no raw text)
|
||||
TokenizedInput tokenized = 2;
|
||||
|
||||
// Multimodal inputs
|
||||
MultimodalInputs mm_inputs = 4;
|
||||
|
||||
// Dummy sampling params for compatibility
|
||||
// EmbedRequest doesn't use sampling_params
|
||||
SamplingParams sampling_params = 5;
|
||||
|
||||
bool log_metrics = 6;
|
||||
|
||||
// Token type IDs for models that require them
|
||||
repeated int32 token_type_ids = 7;
|
||||
|
||||
// Data parallel routing
|
||||
int32 data_parallel_rank = 8;
|
||||
|
||||
// For cross-encoder requests
|
||||
bool is_cross_encoder = 9;
|
||||
repeated string texts = 10; // For cross-encoder batch
|
||||
}
|
||||
|
||||
message EmbedResponse {
|
||||
string request_id = 1;
|
||||
|
||||
oneof response {
|
||||
EmbedComplete complete = 2;
|
||||
EmbedError error = 3;
|
||||
}
|
||||
}
|
||||
|
||||
message EmbedComplete {
|
||||
repeated float embedding = 1;
|
||||
int32 prompt_tokens = 2;
|
||||
int32 cached_tokens = 3;
|
||||
|
||||
// Additional metadata
|
||||
int32 embedding_dim = 4;
|
||||
|
||||
// For batch embeddings
|
||||
repeated Embedding batch_embeddings = 5;
|
||||
}
|
||||
|
||||
message Embedding {
|
||||
repeated float values = 1;
|
||||
int32 index = 2;
|
||||
}
|
||||
|
||||
message EmbedError {
|
||||
string message = 1;
|
||||
string code = 2;
|
||||
string details = 3;
|
||||
}
|
||||
|
||||
// =====================
|
||||
// Management Operations
|
||||
// =====================
|
||||
|
||||
message HealthCheckRequest {}
|
||||
|
||||
message HealthCheckResponse {
|
||||
bool healthy = 1;
|
||||
string message = 2;
|
||||
}
|
||||
|
||||
message AbortRequest {
|
||||
string request_id = 1;
|
||||
string reason = 2;
|
||||
}
|
||||
|
||||
message AbortResponse {
|
||||
bool success = 1;
|
||||
string message = 2;
|
||||
}
|
||||
|
||||
|
||||
// =====================
|
||||
// Additional Operations (Future)
|
||||
// =====================
|
||||
|
||||
// Load LoRA adapter
|
||||
message LoadLoRARequest {
|
||||
string adapter_id = 1;
|
||||
string adapter_path = 2;
|
||||
int32 rank = 3;
|
||||
}
|
||||
|
||||
message LoadLoRAResponse {
|
||||
bool success = 1;
|
||||
string adapter_id = 2;
|
||||
string message = 3;
|
||||
}
|
||||
|
||||
// Unload LoRA adapter
|
||||
message UnloadLoRARequest {
|
||||
string adapter_id = 1;
|
||||
}
|
||||
|
||||
message UnloadLoRAResponse {
|
||||
bool success = 1;
|
||||
string message = 2;
|
||||
}
|
||||
|
||||
// Update weights
|
||||
message UpdateWeightsRequest {
|
||||
oneof source {
|
||||
string disk_path = 1;
|
||||
bytes tensor_data = 2;
|
||||
string remote_url = 3;
|
||||
}
|
||||
string weight_name = 4;
|
||||
}
|
||||
|
||||
message UpdateWeightsResponse {
|
||||
bool success = 1;
|
||||
string message = 2;
|
||||
}
|
||||
|
||||
// Get internal state for debugging
|
||||
message GetInternalStateRequest {
|
||||
repeated string state_keys = 1;
|
||||
}
|
||||
|
||||
message GetInternalStateResponse {
|
||||
google.protobuf.Struct state = 1;
|
||||
}
|
||||
|
||||
// Set internal state for testing
|
||||
message SetInternalStateRequest {
|
||||
google.protobuf.Struct state = 1;
|
||||
}
|
||||
|
||||
message SetInternalStateResponse {
|
||||
bool success = 1;
|
||||
string message = 2;
|
||||
}
|
||||
|
||||
// =====================
|
||||
// Model and Server Info
|
||||
// =====================
|
||||
|
||||
// Get model information
|
||||
message GetModelInfoRequest {}
|
||||
|
||||
message GetModelInfoResponse {
|
||||
string model_path = 1;
|
||||
string tokenizer_path = 2;
|
||||
bool is_generation = 3;
|
||||
string preferred_sampling_params = 4; // JSON string or empty
|
||||
string weight_version = 5;
|
||||
string served_model_name = 6;
|
||||
int32 max_context_length = 7;
|
||||
int32 vocab_size = 8;
|
||||
bool supports_vision = 9;
|
||||
string model_type = 10;
|
||||
repeated int32 eos_token_ids = 11;
|
||||
int32 pad_token_id = 12;
|
||||
int32 bos_token_id = 13;
|
||||
int32 max_req_input_len = 14;
|
||||
repeated string architectures = 15;
|
||||
|
||||
// Classification model support (from HuggingFace config.json)
|
||||
// id2label maps class indices to label names, e.g., {"0": "negative", "1": "positive"}
|
||||
string id2label_json = 16;
|
||||
// Number of classification labels (0 if not a classifier)
|
||||
int32 num_labels = 17;
|
||||
}
|
||||
|
||||
// Get server information
|
||||
message GetServerInfoRequest {}
|
||||
|
||||
message GetServerInfoResponse {
|
||||
// Server configuration (as structured data)
|
||||
google.protobuf.Struct server_args = 1;
|
||||
|
||||
// Scheduler metrics (from scheduler initialization)
|
||||
google.protobuf.Struct scheduler_info = 2;
|
||||
|
||||
// Runtime state
|
||||
int32 active_requests = 3;
|
||||
bool is_paused = 4;
|
||||
double last_receive_timestamp = 5;
|
||||
double uptime_seconds = 6;
|
||||
|
||||
// Version info
|
||||
string sglang_version = 7;
|
||||
|
||||
// Server metadata
|
||||
string server_type = 8; // "grpc"
|
||||
google.protobuf.Timestamp start_time = 9;
|
||||
|
||||
// Note: internal_states not provided in gRPC mode
|
||||
// Scheduler-side metrics (memory usage, throughput) require
|
||||
// bidirectional communicator infrastructure not available in gRPC.
|
||||
// Use HTTP /get_server_info if scheduler internal state is needed.
|
||||
}
|
||||
|
||||
// =====================
|
||||
// Load Metrics (v1/loads)
|
||||
// =====================
|
||||
|
||||
message GetLoadsRequest {
|
||||
// Optional: filter to specific DP rank
|
||||
optional int32 dp_rank = 1;
|
||||
|
||||
// Sections to include: core, memory, spec, lora, disagg, queues, all
|
||||
repeated string include = 2;
|
||||
}
|
||||
|
||||
message GetLoadsResponse {
|
||||
// ISO 8601 timestamp
|
||||
string timestamp = 1;
|
||||
|
||||
// SGLang version
|
||||
string version = 2;
|
||||
|
||||
// Number of DP ranks
|
||||
int32 dp_rank_count = 3;
|
||||
|
||||
// Per-DP-rank load metrics
|
||||
repeated SchedulerLoad loads = 4;
|
||||
|
||||
// Aggregate metrics across all DP ranks
|
||||
AggregateMetrics aggregate = 5;
|
||||
}
|
||||
|
||||
message SchedulerLoad {
|
||||
int32 dp_rank = 1;
|
||||
|
||||
// Core metrics (always included)
|
||||
int32 num_running_reqs = 2;
|
||||
int32 num_waiting_reqs = 3;
|
||||
int32 num_total_reqs = 4;
|
||||
int32 num_used_tokens = 5;
|
||||
int32 max_total_num_tokens = 6;
|
||||
double token_usage = 7;
|
||||
double gen_throughput = 8;
|
||||
double cache_hit_rate = 9;
|
||||
double utilization = 10;
|
||||
int32 max_running_requests = 11;
|
||||
|
||||
// Optional sections
|
||||
optional MemoryMetrics memory = 12;
|
||||
optional SpeculativeMetrics speculative = 13;
|
||||
optional LoRAMetrics lora = 14;
|
||||
optional DisaggregationMetrics disaggregation = 15;
|
||||
optional QueueMetrics queues = 16;
|
||||
}
|
||||
|
||||
message MemoryMetrics {
|
||||
double weight_gb = 1;
|
||||
double kv_cache_gb = 2;
|
||||
double graph_gb = 3;
|
||||
int32 token_capacity = 4;
|
||||
}
|
||||
|
||||
message SpeculativeMetrics {
|
||||
double accept_length = 1;
|
||||
double accept_rate = 2;
|
||||
}
|
||||
|
||||
message LoRAMetrics {
|
||||
int32 slots_used = 1;
|
||||
int32 slots_total = 2;
|
||||
double utilization = 3;
|
||||
}
|
||||
|
||||
message DisaggregationMetrics {
|
||||
string mode = 1; // "prefill", "decode", or "null"
|
||||
int32 prefill_prealloc_queue_reqs = 2;
|
||||
int32 prefill_inflight_queue_reqs = 3;
|
||||
int32 decode_prealloc_queue_reqs = 4;
|
||||
int32 decode_transfer_queue_reqs = 5;
|
||||
int32 decode_retracted_queue_reqs = 6;
|
||||
double kv_transfer_speed_gb_s = 7;
|
||||
double kv_transfer_latency_ms = 8;
|
||||
}
|
||||
|
||||
message QueueMetrics {
|
||||
int32 waiting = 1;
|
||||
int32 grammar = 2;
|
||||
int32 paused = 3;
|
||||
int32 retracted = 4;
|
||||
}
|
||||
|
||||
message AggregateMetrics {
|
||||
int32 total_running_reqs = 1;
|
||||
int32 total_waiting_reqs = 2;
|
||||
int32 total_reqs = 3;
|
||||
double avg_token_usage = 4;
|
||||
double avg_throughput = 5;
|
||||
double avg_utilization = 6;
|
||||
}
|
||||
Reference in New Issue
Block a user