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deepseek multinode and no logging #696

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2 changes: 1 addition & 1 deletion model-engine/model_engine_server/api/v2/chat_completion.py
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Original file line number Diff line number Diff line change
Expand Up @@ -263,7 +263,7 @@ async def chat_completion(
)
else:
logger.info(
f"POST /v2/chat/completion ({('stream' if request.stream else 'sync')}) with {request} to endpoint {model_endpoint_name} for {auth}"
f"POST /v2/chat/completion ({('stream' if request.stream else 'sync')}) with to endpoint {model_endpoint_name} for {auth}"
)

if request.stream:
Expand Down
2 changes: 1 addition & 1 deletion model-engine/model_engine_server/api/v2/completion.py
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Original file line number Diff line number Diff line change
Expand Up @@ -262,7 +262,7 @@ async def completion(
)
else:
logger.info(
f"POST /v2/completion ({('stream' if request.stream else 'sync')}) with {request} to endpoint {model_endpoint_name} for {auth}"
f"POST /v2/completion ({('stream' if request.stream else 'sync')}) with to endpoint {model_endpoint_name} for {auth}"
)

if request.stream:
Expand Down
120 changes: 108 additions & 12 deletions model-engine/model_engine_server/domain/use_cases/llm_model_endpoint_use_cases.py
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Original file line number Diff line number Diff line change
Expand Up @@ -377,6 +377,88 @@ def check_docker_image_exists_for_image_tag(
tag=framework_image_tag,
)

async def create_sglang_multinode_bundle(
self,
user: User,
model_name: str,
framework_image_tag: str,
endpoint_unique_name: str,
num_shards: int,
nodes_per_worker: int,
quantize: Optional[Quantization],
checkpoint_path: Optional[str],
chat_template_override: Optional[str],
additional_args: Optional[SGLangEndpointAdditionalArgs] = None,
):
leader_command = [
"python3",
"/root/sglang-startup-script.py",
"--model",
"deepseek-ai/DeepSeek-R1",
"--nnodes",
"2",
"--node-rank",
"0"
"--worker-port",
"5005",
"--leader-port",
"5002"
]

worker_command = [
"python3",
"/root/sglang-startup-script.py",
"--model",
"deepseek-ai/DeepSeek-R1",
"--nnodes",
"2",
"--node-rank",
"1",
"--worker-port",
"5005",
"--leader-port",
"5002"
]

# NOTE: the most important env var SGLANG_HOST_IP is already established in the sglang startup script

common_sglang_envs = { # these are for debugging
"NCCL_SOCKET_IFNAME": "eth0",
"GLOO_SOCKET_IFNAME": "eth0",
}

# This is same as VLLM multinode bundle
create_model_bundle_v2_request = CreateModelBundleV2Request(
name=endpoint_unique_name,
schema_location="TBA",
flavor=StreamingEnhancedRunnableImageFlavor(
flavor=ModelBundleFlavorType.STREAMING_ENHANCED_RUNNABLE_IMAGE,
repository=hmi_config.sglang_repository,
tag=framework_image_tag,
command=leader_command,
streaming_command=leader_command,
protocol="http",
readiness_initial_delay_seconds=10,
healthcheck_route="/health",
predict_route="/predict",
streaming_predict_route="/stream",
extra_routes=[OPENAI_CHAT_COMPLETION_PATH, OPENAI_COMPLETION_PATH],
env=common_sglang_envs,
worker_command=worker_command,
worker_env=common_sglang_envs,
),
metadata={},
)

return (
await self.create_model_bundle_use_case.execute(
user,
create_model_bundle_v2_request,
do_auth_check=False,
)
).model_bundle_id


async def execute(
self,
user: User,
Expand All @@ -400,7 +482,7 @@ async def execute(
self.check_docker_image_exists_for_image_tag(
framework_image_tag, INFERENCE_FRAMEWORK_REPOSITORY[framework]
)
if multinode and framework != LLMInferenceFramework.VLLM:
if multinode and framework not in [LLMInferenceFramework.VLLM, LLMInferenceFramework.SGLANG]:
raise ObjectHasInvalidValueException(
f"Multinode is not supported for framework {framework}."
)
Expand Down Expand Up @@ -481,16 +563,30 @@ async def execute(
if additional_args
else None
)
bundle_id = await self.create_sglang_bundle(
user,
model_name,
framework_image_tag,
endpoint_name,
num_shards,
checkpoint_path,
chat_template_override,
additional_args=additional_sglang_args,
)
if multinode:
bundle_id = await self.create_sglang_multinode_bundle(
user,
model_name,
framework_image_tag,
endpoint_name,
num_shards,
nodes_per_worker,
quantize,
checkpoint_path,
chat_template_override,
additional_args=additional_sglang_args,
)
else:
bundle_id = await self.create_sglang_bundle(
user,
model_name,
framework_image_tag,
endpoint_name,
num_shards,
checkpoint_path,
chat_template_override,
additional_args=additional_sglang_args,
)
case _:
assert_never(framework)
raise ObjectHasInvalidValueException(
Expand Down Expand Up @@ -1323,7 +1419,7 @@ async def execute(

if (
request.nodes_per_worker > 1
and not request.inference_framework == LLMInferenceFramework.VLLM
and not request.inference_framework in [LLMInferenceFramework.VLLM, LLMInferenceFramework.SGLANG]
):
raise ObjectHasInvalidValueException(
"Multinode endpoints are only supported for VLLM models."
Expand Down
6 changes: 3 additions & 3 deletions model-engine/model_engine_server/inference/forwarding/http_forwarder.py
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Original file line number Diff line number Diff line change
Expand Up @@ -90,7 +90,7 @@ async def predict(
)
return response
except Exception:
logger.error(f"Failed to decode payload from: {request}")
logger.error(f"Failed to decode payload from: ")
raise


Expand All @@ -103,10 +103,10 @@ async def stream(
try:
payload = request.model_dump()
except Exception:
logger.error(f"Failed to decode payload from: {request}")
logger.error(f"Failed to decode payload from: ")
raise
else:
logger.debug(f"Received request: {payload}")
logger.debug(f"Received request:")

responses = forwarder.forward(payload)
# We fetch the first response to check if upstream request was successful
Expand Down
29 changes: 29 additions & 0 deletions model-engine/model_engine_server/inference/sglang/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -163,6 +163,35 @@ GIT_SHA="$(git rev-parse HEAD)-rcX" SETENV=prod LOCAL=true AWS_PROFILE=ml-servin
4. Send a `POST` request to `http://localhost:5001/v1/llm/model-endpoints` with the following body:

```json
# do i need to set borrowing to false?
{
"name": "deepseek-r1-0528",
"model_name": "deepseek-r1-0528",
"endpoint_type": "streaming",
"cpus": 160,
"memory": "800Gi",
"min_workers": 1,
"max_workers": 1,
"gpus": 8,
"gpu_type": "nvidia-hopper-h100",
"storage": "900Gi",
"per_worker": 1,
"num_shards": 8,
"nodes_per_worker": 2,
"labels": {
"team": "infra",
"product": "inference.llm_model_zoo"
},
"inference_framework": "sglang",
"inference_framework_image_tag": "multinode-latest-2", # TODO change this?
"high_priority": true,
"metadata": {
"_llm":
{"source": "hugging_face", "quantize": null, "model_name": "deepseek-r1-0528", "num_shards": 8, "checkpoint_path": "s3://scale-ml/models/hf-synced-weights/deepseek-ai/DeepSeek-R1-0528", "inference_framework": "sglang", "chat_template_override": null, "inference_framework_image_tag": "multinode-latest-2"} # TODO change this?
}
}


{
"name": "deepseek-r1",
"model_name": "deepseek-r1",
Expand Down