vllm/tests/entrypoints/sagemaker/test_sagemaker_middleware_integration.py
Zuyi Zhao bca74e32b7
[Frontend] Add sagemaker_standards dynamic lora adapter and stateful session management decorators to vLLM OpenAI API server (#27892)
Signed-off-by: Zuyi Zhao <zhaozuy@amazon.com>
Signed-off-by: Shen Teng <sheteng@amazon.com>
Co-authored-by: Shen Teng <sheteng@amazon.com>
Co-authored-by: Robert Shaw <114415538+robertgshaw2-redhat@users.noreply.github.com>
2025-11-11 04:57:01 +00:00

347 lines
12 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""Integration test for middleware loader functionality.
Tests that customer middlewares get called correctly with a vLLM server.
"""
import os
import tempfile
import pytest
import requests
from ...utils import RemoteOpenAIServer
from .conftest import (
MODEL_NAME_SMOLLM,
)
class TestMiddlewareIntegration:
"""Integration test for middleware with vLLM server."""
def setup_method(self):
"""Setup for each test - simulate fresh server startup."""
self._clear_caches()
def _clear_caches(self):
"""Clear middleware registry and function loader cache."""
try:
from model_hosting_container_standards.common.fastapi.middleware import (
middleware_registry,
)
from model_hosting_container_standards.common.fastapi.middleware.source.decorator_loader import ( # noqa: E501
decorator_loader,
)
from model_hosting_container_standards.sagemaker.sagemaker_loader import (
SageMakerFunctionLoader,
)
middleware_registry.clear_middlewares()
decorator_loader.clear()
SageMakerFunctionLoader._default_function_loader = None
except ImportError:
pytest.skip("model-hosting-container-standards not available")
@pytest.mark.asyncio
async def test_customer_middleware_with_vllm_server(self):
"""Test that customer middlewares work with actual vLLM server.
Tests decorator-based middlewares (@custom_middleware, @input_formatter,
@output_formatter)
on multiple endpoints (chat/completions, invocations).
"""
try:
from model_hosting_container_standards.sagemaker.config import (
SageMakerEnvVars,
)
except ImportError:
pytest.skip("model-hosting-container-standards not available")
# Customer writes a middleware script with multiple decorators
with tempfile.NamedTemporaryFile(mode="w", suffix=".py", delete=False) as f:
f.write(
"""
from model_hosting_container_standards.common.fastapi.middleware import (
custom_middleware, input_formatter, output_formatter
)
# Global flag to track if input formatter was called
_input_formatter_called = False
@input_formatter
async def customer_input_formatter(request):
# Process input - mark that input formatter was called
global _input_formatter_called
_input_formatter_called = True
return request
@custom_middleware("throttle")
async def customer_throttle_middleware(request, call_next):
response = await call_next(request)
response.headers["X-Customer-Throttle"] = "applied"
order = response.headers.get("X-Middleware-Order", "")
response.headers["X-Middleware-Order"] = order + "throttle,"
return response
@output_formatter
async def customer_output_formatter(response):
global _input_formatter_called
response.headers["X-Customer-Processed"] = "true"
# Since input_formatter and output_formatter are combined into
# pre_post_process middleware,
# if output_formatter is called, input_formatter should have been called too
if _input_formatter_called:
response.headers["X-Input-Formatter-Called"] = "true"
order = response.headers.get("X-Middleware-Order", "")
response.headers["X-Middleware-Order"] = order + "output_formatter,"
return response
"""
)
script_path = f.name
try:
script_dir = os.path.dirname(script_path)
script_name = os.path.basename(script_path)
# Set environment variables to point to customer script
env_vars = {
SageMakerEnvVars.SAGEMAKER_MODEL_PATH: script_dir,
SageMakerEnvVars.CUSTOM_SCRIPT_FILENAME: script_name,
}
args = [
"--dtype",
"bfloat16",
"--max-model-len",
"2048",
"--enforce-eager",
"--max-num-seqs",
"32",
]
with RemoteOpenAIServer(
MODEL_NAME_SMOLLM, args, env_dict=env_vars
) as server:
# Test 1: Middlewares applied to chat/completions endpoint
chat_response = requests.post(
server.url_for("v1/chat/completions"),
json={
"model": MODEL_NAME_SMOLLM,
"messages": [{"role": "user", "content": "Hello"}],
"max_tokens": 5,
"temperature": 0.0,
},
)
assert chat_response.status_code == 200
# Verify all middlewares were executed
assert "X-Customer-Throttle" in chat_response.headers
assert chat_response.headers["X-Customer-Throttle"] == "applied"
assert "X-Customer-Processed" in chat_response.headers
assert chat_response.headers["X-Customer-Processed"] == "true"
# Verify input formatter was called
assert "X-Input-Formatter-Called" in chat_response.headers
assert chat_response.headers["X-Input-Formatter-Called"] == "true"
# Verify middleware execution order
execution_order = chat_response.headers.get(
"X-Middleware-Order", ""
).rstrip(",")
order_parts = execution_order.split(",") if execution_order else []
assert "throttle" in order_parts
assert "output_formatter" in order_parts
# Test 2: Middlewares applied to invocations endpoint
invocations_response = requests.post(
server.url_for("invocations"),
json={
"model": MODEL_NAME_SMOLLM,
"messages": [{"role": "user", "content": "Hello"}],
"max_tokens": 5,
"temperature": 0.0,
},
)
assert invocations_response.status_code == 200
# Verify all middlewares were executed
assert "X-Customer-Throttle" in invocations_response.headers
assert invocations_response.headers["X-Customer-Throttle"] == "applied"
assert "X-Customer-Processed" in invocations_response.headers
assert invocations_response.headers["X-Customer-Processed"] == "true"
# Verify input formatter was called
assert "X-Input-Formatter-Called" in invocations_response.headers
assert (
invocations_response.headers["X-Input-Formatter-Called"] == "true"
)
finally:
os.unlink(script_path)
@pytest.mark.asyncio
async def test_middleware_with_ping_endpoint(self):
"""Test that middlewares work with SageMaker ping endpoint."""
try:
from model_hosting_container_standards.sagemaker.config import (
SageMakerEnvVars,
)
except ImportError:
pytest.skip("model-hosting-container-standards not available")
# Customer writes a middleware script
with tempfile.NamedTemporaryFile(mode="w", suffix=".py", delete=False) as f:
f.write(
"""
from model_hosting_container_standards.common.fastapi.middleware import (
custom_middleware
)
@custom_middleware("pre_post_process")
async def ping_tracking_middleware(request, call_next):
response = await call_next(request)
if request.url.path == "/ping":
response.headers["X-Ping-Tracked"] = "true"
return response
"""
)
script_path = f.name
try:
script_dir = os.path.dirname(script_path)
script_name = os.path.basename(script_path)
env_vars = {
SageMakerEnvVars.SAGEMAKER_MODEL_PATH: script_dir,
SageMakerEnvVars.CUSTOM_SCRIPT_FILENAME: script_name,
}
args = [
"--dtype",
"bfloat16",
"--max-model-len",
"2048",
"--enforce-eager",
"--max-num-seqs",
"32",
]
with RemoteOpenAIServer(
MODEL_NAME_SMOLLM, args, env_dict=env_vars
) as server:
# Test ping endpoint with middleware
response = requests.get(server.url_for("ping"))
assert response.status_code == 200
assert "X-Ping-Tracked" in response.headers
assert response.headers["X-Ping-Tracked"] == "true"
finally:
os.unlink(script_path)
@pytest.mark.asyncio
async def test_middleware_env_var_override(self):
"""Test middleware environment variable overrides."""
try:
from model_hosting_container_standards.common.fastapi.config import (
FastAPIEnvVars,
)
from model_hosting_container_standards.sagemaker.config import (
SageMakerEnvVars,
)
except ImportError:
pytest.skip("model-hosting-container-standards not available")
# Create a script with middleware functions specified via env vars
with tempfile.NamedTemporaryFile(mode="w", suffix=".py", delete=False) as f:
f.write(
"""
from fastapi import Request
# Global flag to track if pre_process was called
_pre_process_called = False
async def env_throttle_middleware(request, call_next):
response = await call_next(request)
response.headers["X-Env-Throttle"] = "applied"
return response
async def env_pre_process(request: Request) -> Request:
# Mark that pre_process was called
global _pre_process_called
_pre_process_called = True
return request
async def env_post_process(response):
global _pre_process_called
if hasattr(response, 'headers'):
response.headers["X-Env-Post-Process"] = "applied"
# Since pre_process and post_process are combined into
# pre_post_process middleware,
# if post_process is called, pre_process should have been called too
if _pre_process_called:
response.headers["X-Pre-Process-Called"] = "true"
return response
"""
)
script_path = f.name
try:
script_dir = os.path.dirname(script_path)
script_name = os.path.basename(script_path)
# Set environment variables for middleware
# Use script_name with .py extension as per plugin example
env_vars = {
SageMakerEnvVars.SAGEMAKER_MODEL_PATH: script_dir,
SageMakerEnvVars.CUSTOM_SCRIPT_FILENAME: script_name,
FastAPIEnvVars.CUSTOM_FASTAPI_MIDDLEWARE_THROTTLE: (
f"{script_name}:env_throttle_middleware"
),
FastAPIEnvVars.CUSTOM_PRE_PROCESS: f"{script_name}:env_pre_process",
FastAPIEnvVars.CUSTOM_POST_PROCESS: f"{script_name}:env_post_process",
}
args = [
"--dtype",
"bfloat16",
"--max-model-len",
"2048",
"--enforce-eager",
"--max-num-seqs",
"32",
]
with RemoteOpenAIServer(
MODEL_NAME_SMOLLM, args, env_dict=env_vars
) as server:
response = requests.get(server.url_for("ping"))
assert response.status_code == 200
# Check if environment variable middleware was applied
headers = response.headers
# Verify that env var middlewares were applied
assert "X-Env-Throttle" in headers, (
"Throttle middleware should be applied via env var"
)
assert headers["X-Env-Throttle"] == "applied"
assert "X-Env-Post-Process" in headers, (
"Post-process middleware should be applied via env var"
)
assert headers["X-Env-Post-Process"] == "applied"
# Verify that pre_process was called
assert "X-Pre-Process-Called" in headers, (
"Pre-process should be called via env var"
)
assert headers["X-Pre-Process-Called"] == "true"
finally:
os.unlink(script_path)