Minor improvements of TokenizerManager / health check (#6327)

.github/workflows/pr-test-amd.yml

@@ -4,14 +4,16 @@ on:
   push:
     branches: [ main ]
     paths:
-      - "python/sglang/**"
+      - "python/**"
+      - "scripts/**"
       - "test/**"
       - "sgl-kernel/**"
       - ".github/workflows/pr-test-amd.yml"
   pull_request:
     branches: [ main ]
     paths:
-      - "python/sglang/**"
+      - "python/**"
+      - "scripts/**"
       - "test/**"
       - "sgl-kernel/**"
       - ".github/workflows/pr-test-amd.yml"

python/pyproject.toml

@@ -96,12 +96,14 @@ anthropic = ["anthropic>=0.20.0"]
 litellm = ["litellm>=1.0.0"]
 torch_memory_saver = ["torch_memory_saver>=0.0.4"]
 test = [
+    "accelerate",
+    "torchaudio",
     "jsonlines",
     "matplotlib",
     "pandas",
-    "sentence_transformers",
-    "accelerate",
     "peft",
+    "timm",
+    "sentence_transformers",
 ]
 all = ["sglang[srt]", "sglang[openai]", "sglang[anthropic]", "sglang[litellm]", "sglang[torch_memory_saver]"]
 all_hip = ["sglang[srt_hip]", "sglang[openai]", "sglang[anthropic]", "sglang[litellm]"]

python/sglang/srt/disaggregation/utils.py

@@ -13,6 +13,8 @@ import torch.distributed as dist
 
 from sglang.srt.utils import get_ip
 
+FakeBootstrapHost = "2.2.2.2"
+
 
 class DisaggregationMode(Enum):
     NULL = "null"
@@ -20,9 +22,6 @@ class DisaggregationMode(Enum):
     DECODE = "decode"
 
 
-FakeBootstrapHost = "2.2.2.2"
-
-
 def poll_and_all_reduce(pollers, gloo_group):
     polls = [int(poller.poll()) for poller in pollers]
     tensor_to_reduce = torch.tensor(polls, dtype=torch.uint8, device="cpu")

python/sglang/srt/entrypoints/http_server.py

@@ -189,6 +189,7 @@ async def health_generate(request: Request) -> Response:
         if _global_state.tokenizer_manager.last_receive_tstamp > tic:
             task.cancel()
             _global_state.tokenizer_manager.rid_to_state.pop(rid, None)
+            _global_state.tokenizer_manager.health_check_failed = False
             return Response(status_code=200)
 
     task.cancel()
@@ -202,6 +203,7 @@ async def health_generate(request: Request) -> Response:
         f"last_heartbeat time: {last_receive_time}"
     )
     _global_state.tokenizer_manager.rid_to_state.pop(rid, None)
+    _global_state.tokenizer_manager.health_check_failed = True
     return Response(status_code=503)
 
 

python/sglang/srt/hf_transformers_utils.py

@@ -19,7 +19,6 @@ import warnings
 from pathlib import Path
 from typing import Dict, Optional, Type, Union
 
-import transformers
 from huggingface_hub import snapshot_download
 from transformers import (
     AutoConfig,

python/sglang/srt/managers/scheduler.py

@@ -129,7 +129,6 @@ from sglang.srt.utils import (
     DynamicGradMode,
     broadcast_pyobj,
     configure_logger,
-    crash_on_warnings,
     disable_request_logging,
     get_bool_env_var,
     get_zmq_socket,

python/sglang/srt/managers/tokenizer_manager.py

@@ -16,6 +16,7 @@
 import asyncio
 import copy
 import dataclasses
+import json
 import logging
 import os
 import pickle
@@ -90,6 +91,8 @@ from sglang.srt.managers.io_struct import (
     ResumeMemoryOccupationReqInput,
     ResumeMemoryOccupationReqOutput,
     SessionParams,
+    SetInternalStateReq,
+    SetInternalStateReqOutput,
     SlowDownReqInput,
     SlowDownReqOutput,
     TokenizedEmbeddingReqInput,
@@ -169,6 +172,11 @@ class TokenizerManager:
         self.enable_metrics = server_args.enable_metrics
         self.log_requests = server_args.log_requests
         self.log_requests_level = server_args.log_requests_level
+        self.preferred_sampling_params = (
+            json.loads(server_args.preferred_sampling_params)
+            if server_args.preferred_sampling_params
+            else None
+        )
 
         # Init inter-process communication
         context = zmq.asyncio.Context(2)
@@ -228,6 +236,7 @@ class TokenizerManager:
         # Store states
         self.no_create_loop = False
         self.rid_to_state: Dict[str, ReqState] = {}
+        self.health_check_failed = False
         self.gracefully_exit = False
         self.last_receive_tstamp = 0
         self.dump_requests_folder = ""  # By default do not dump
@@ -255,6 +264,10 @@ class TokenizerManager:
                     "model_name": self.server_args.served_model_name,
                     # TODO: Add lora name/path in the future,
                 },
+                bucket_time_to_first_token=self.server_args.bucket_time_to_first_token,
+                bucket_e2e_request_latency=self.server_args.bucket_e2e_request_latency,
+                bucket_inter_token_latency=self.server_args.bucket_inter_token_latency,
+                collect_tokens_histogram=self.server_args.collect_tokens_histogram,
             )
 
         # Communicators
@@ -285,9 +298,13 @@ class TokenizerManager:
         self.start_profile_communicator = _Communicator(
             self.send_to_scheduler, server_args.dp_size
         )
+        self.health_check_communitcator = _Communicator(self.send_to_scheduler, 1)
         self.get_internal_state_communicator = _Communicator(
             self.send_to_scheduler, server_args.dp_size
         )
+        self.set_internal_state_communicator = _Communicator(
+            self.send_to_scheduler, server_args.dp_size
+        )
         self.expert_distribution_communicator = _Communicator(
             self.send_to_scheduler, server_args.dp_size
         )
@@ -349,6 +366,10 @@ class TokenizerManager:
                     GetInternalStateReqOutput,
                     self.get_internal_state_communicator.handle_recv,
                 ),
+                (
+                    SetInternalStateReqOutput,
+                    self.set_internal_state_communicator.handle_recv,
+                ),
                 (
                     ExpertDistributionReqOutput,
                     self.expert_distribution_communicator.handle_recv,
@@ -508,7 +529,14 @@ class TokenizerManager:
                     "Please set `--enable-custom-logits-processor` to enable this feature."
                 )
 
-        sampling_params = SamplingParams(**obj.sampling_params)
+        # Parse sampling parameters
+        # Note: if there are preferred sampling params, we use them if they are not
+        # explicitly passed in sampling_params
+        if self.preferred_sampling_params:
+            sampling_kwargs = {**self.preferred_sampling_params, **obj.sampling_params}
+        else:
+            sampling_kwargs = obj.sampling_params
+        sampling_params = SamplingParams(**sampling_kwargs)
         sampling_params.normalize(self.tokenizer)
         sampling_params.verify()
 
@@ -667,7 +695,6 @@ class TokenizerManager:
 
         generators = []
         rids = []
-
         if getattr(obj, "parallel_sample_num", 1) == 1:
             if self.server_args.enable_tokenizer_batch_encode:
                 # Validate batch tokenization constraints
@@ -857,7 +884,7 @@ class TokenizerManager:
         self.auto_create_handle_loop()
         assert (
             self.server_args.dp_size == 1
-        ), "dp_size must be for update weights from distributed"
+        ), "dp_size must be 1 for update weights from distributed"
 
         # This means that weight sync
         # cannot run while requests are in progress.
@@ -946,6 +973,14 @@ class TokenizerManager:
         # Many DP ranks
         return [res.internal_state for res in responses]
 
+    async def set_internal_state(
+        self, obj: SetInternalStateReq
+    ) -> SetInternalStateReqOutput:
+        responses: List[SetInternalStateReqOutput] = (
+            await self.set_internal_state_communicator(obj)
+        )
+        return [res.internal_state for res in responses]
+
     def get_log_request_metadata(self):
         max_length = None
         skip_names = None
@@ -1015,11 +1050,17 @@ class TokenizerManager:
             loop.create_task(print_exception_wrapper(self.handle_loop))
         )
 
+        self.event_loop = loop
+
         # We cannot add signal handler when the tokenizer manager is not in
         # the main thread due to the CPython limitation.
         if threading.current_thread() is threading.main_thread():
             signal_handler = SignalHandler(self)
-            loop.add_signal_handler(signal.SIGTERM, signal_handler.signal_handler)
+            loop.add_signal_handler(signal.SIGTERM, signal_handler.sigterm_handler)
+            # Update the signal handler for the process. It overrides the sigquit handler in the launch phase.
+            loop.add_signal_handler(
+                signal.SIGQUIT, signal_handler.running_phase_sigquit_handler
+            )
         else:
             logger.warning(
                 "Signal handler is not added because the tokenizer manager is "
@@ -1037,6 +1078,15 @@ class TokenizerManager:
         # Drain requests
         while True:
             remain_num_req = len(self.rid_to_state)
+
+            if self.health_check_failed:
+                # if health check failed, we should exit immediately
+                logger.error(
+                    "Signal SIGTERM received while health check failed. Exiting... remaining number of requests: %d",
+                    remain_num_req,
+                )
+                break
+
             logger.info(
                 f"Gracefully exiting... remaining number of requests {remain_num_req}"
             )
@@ -1120,7 +1170,16 @@ class TokenizerManager:
                     "meta_info": meta_info,
                 }
             elif isinstance(recv_obj, BatchMultimodalOut):
-                raise NotImplementedError()
+                if isinstance(recv_obj.outputs[i], str):
+                    out_dict = {
+                        "text": recv_obj.outputs[i],
+                        "meta_info": meta_info,
+                    }
+                else:
+                    out_dict = {
+                        "outputs": json.dumps(recv_obj.outputs[i]),
+                        "meta_info": meta_info,
+                    }
             else:
                 assert isinstance(recv_obj, BatchEmbeddingOut)
                 out_dict = {
@@ -1366,12 +1425,18 @@ class SignalHandler:
     def __init__(self, tokenizer_manager: TokenizerManager):
         self.tokenizer_manager = tokenizer_manager
 
-    def signal_handler(self, signum=None, frame=None):
+    def sigterm_handler(self, signum=None, frame=None):
         logger.warning(
             f"SIGTERM received. {signum=} {frame=}. Draining requests and shutting down..."
         )
         self.tokenizer_manager.gracefully_exit = True
 
+    def running_phase_sigquit_handler(self, signum=None, frame=None):
+        logger.error(
+            "Received sigquit from a child process. It usually means the child failed."
+        )
+        kill_process_tree(os.getpid())
+
 
 T = TypeVar("T")
 

python/sglang/srt/server_args.py

@@ -46,7 +46,6 @@ class ServerArgs:
     tokenizer_path: Optional[str] = None
     tokenizer_mode: str = "auto"
     skip_tokenizer_init: bool = False
-    enable_tokenizer_batch_encode: bool = False
     load_format: str = "auto"
     trust_remote_code: bool = False
     dtype: str = "auto"
@@ -59,6 +58,7 @@ class ServerArgs:
     chat_template: Optional[str] = None
     completion_template: Optional[str] = None
     is_embedding: bool = False
+    enable_multimodal: Optional[bool] = None
     revision: Optional[str] = None
 
     # Port for the HTTP server
@@ -97,6 +97,10 @@ class ServerArgs:
     log_requests_level: int = 0
     show_time_cost: bool = False
     enable_metrics: bool = False
+    bucket_time_to_first_token: Optional[List[float]] = None
+    bucket_e2e_request_latency: Optional[List[float]] = None
+    bucket_inter_token_latency: Optional[List[float]] = None
+    collect_tokens_histogram: bool = False
     decode_log_interval: int = 40
     enable_request_time_stats_logging: bool = False
 
@@ -120,6 +124,7 @@ class ServerArgs:
 
     # Model override args in JSON
     json_model_override_args: str = "{}"
+    preferred_sampling_params: Optional[str] = None
 
     # LoRA
     lora_paths: Optional[List[str]] = None
@@ -154,9 +159,9 @@ class ServerArgs:
     disable_cuda_graph: bool = False
     disable_cuda_graph_padding: bool = False
     enable_nccl_nvls: bool = False
+    enable_tokenizer_batch_encode: bool = False
     disable_outlines_disk_cache: bool = False
     disable_custom_all_reduce: bool = False
-    enable_multimodal: Optional[bool] = None
     disable_overlap_schedule: bool = False
     enable_mixed_chunk: bool = False
     enable_dp_attention: bool = False
@@ -474,11 +479,6 @@ class ServerArgs:
             action="store_true",
             help="If set, skip init tokenizer and pass input_ids in generate request.",
         )
-        parser.add_argument(
-            "--enable-tokenizer-batch-encode",
-            action="store_true",
-            help="Enable batch tokenization for improved performance when processing multiple text inputs. Do not use with image inputs, pre-tokenized input_ids, or input_embeds.",
-        )
         parser.add_argument(
             "--load-format",
             type=str,
@@ -603,6 +603,12 @@ class ServerArgs:
             action="store_true",
             help="Whether to use a CausalLM as an embedding model.",
         )
+        parser.add_argument(
+            "--enable-multimodal",
+            default=ServerArgs.enable_multimodal,
+            action="store_true",
+            help="Enable the multimodal functionality for the served model. If the model being served is not multimodal, nothing will happen",
+        )
         parser.add_argument(
             "--revision",
             type=str,
@@ -780,6 +786,33 @@ class ServerArgs:
             action="store_true",
             help="Enable log prometheus metrics.",
         )
+        parser.add_argument(
+            "--bucket-time-to-first-token",
+            type=float,
+            nargs="+",
+            default=ServerArgs.bucket_time_to_first_token,
+            help="The buckets of time to first token, specified as a list of floats.",
+        )
+        parser.add_argument(
+            "--bucket-inter-token-latency",
+            type=float,
+            nargs="+",
+            default=ServerArgs.bucket_inter_token_latency,
+            help="The buckets of inter-token latency, specified as a list of floats.",
+        )
+        parser.add_argument(
+            "--bucket-e2e-request-latency",
+            type=float,
+            nargs="+",
+            default=ServerArgs.bucket_e2e_request_latency,
+            help="The buckets of end-to-end request latency, specified as a list of floats.",
+        )
+        parser.add_argument(
+            "--collect-tokens-histogram",
+            action="store_true",
+            default=ServerArgs.collect_tokens_histogram,
+            help="Collect prompt/generation tokens histogram.",
+        )
         parser.add_argument(
             "--decode-log-interval",
             type=int,
@@ -868,6 +901,11 @@ class ServerArgs:
             help="A dictionary in JSON string format used to override default model configurations.",
             default=ServerArgs.json_model_override_args,
         )
+        parser.add_argument(
+            "--preferred-sampling-params",
+            type=str,
+            help="json-formatted sampling settings that will be returned in /get_model_info",
+        )
 
         # LoRA
         parser.add_argument(
@@ -1043,6 +1081,11 @@ class ServerArgs:
             action="store_true",
             help="Enable NCCL NVLS for prefill heavy requests when available.",
         )
+        parser.add_argument(
+            "--enable-tokenizer-batch-encode",
+            action="store_true",
+            help="Enable batch tokenization for improved performance when processing multiple text inputs. Do not use with image inputs, pre-tokenized input_ids, or input_embeds.",
+        )
         parser.add_argument(
             "--disable-outlines-disk-cache",
             action="store_true",
@@ -1053,12 +1096,6 @@ class ServerArgs:
             action="store_true",
             help="Disable the custom all-reduce kernel and fall back to NCCL.",
         )
-        parser.add_argument(
-            "--enable-multimodal",
-            default=ServerArgs.enable_multimodal,
-            action="store_true",
-            help="Enable the multimodal functionality for the served model. If the model being served is not multimodal, nothing will happen",
-        )
         parser.add_argument(
             "--disable-overlap-schedule",
             action="store_true",

scripts/ci_install_dependency.sh

@@ -2,6 +2,7 @@
 # Install the dependency in CI.
 set -euxo pipefail
 
+# Kill existing processes
 SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
 bash "${SCRIPT_DIR}/killall_sglang.sh"
 
@@ -16,13 +17,10 @@ rm -rf /usr/local/lib/python3.10/dist-packages/flashinfer*
 rm -rf /usr/local/lib/python3.10/dist-packages/sgl_kernel*
 
 # Install the main package
-pip install -e "python[all]"
+pip install -e "python[dev]"
 
 # Install additional dependencies
-pip install transformers==4.51.0 timm torchaudio==2.6.0 sentence_transformers accelerate peft pandas datasets mooncake-transfer-engine==0.3.0
-
-# For compiling xgrammar kernels
-pip install cuda-python nvidia-cuda-nvrtc-cu12
+pip install mooncake-transfer-engine==0.3.0 nvidia-cuda-nvrtc-cu12
 
 # For lmms_evals evaluating MMMU
 git clone --branch v0.3.3 --depth 1 https://github.com/EvolvingLMMs-Lab/lmms-eval.git