async def init_pooling_state(
engine_client: "EngineClient", state: "State", args: "Namespace"
):
from vllm.entrypoints.chat_utils import load_chat_template
from vllm.entrypoints.logger import RequestLogger
from vllm.entrypoints.pooling.classify.serving import ServingClassification
from vllm.entrypoints.pooling.embed.serving import OpenAIServingEmbedding
from vllm.entrypoints.pooling.pooling.serving import OpenAIServingPooling
from vllm.entrypoints.pooling.score.serving import ServingScores
from vllm.tasks import POOLING_TASKS
supported_tasks = await engine_client.get_supported_tasks()
resolved_chat_template = load_chat_template(args.chat_template)
if args.enable_log_requests:
request_logger = RequestLogger(max_log_len=args.max_log_len)
else:
request_logger = None
state.openai_serving_pooling = (
(
OpenAIServingPooling(
engine_client,
state.openai_serving_models,
supported_tasks=supported_tasks,
request_logger=request_logger,
chat_template=resolved_chat_template,
chat_template_content_format=args.chat_template_content_format,
trust_request_chat_template=args.trust_request_chat_template,
log_error_stack=args.log_error_stack,
)
)
if any(task in POOLING_TASKS for task in supported_tasks)
else None
)
state.openai_serving_embedding = (
OpenAIServingEmbedding(
engine_client,
state.openai_serving_models,
request_logger=request_logger,
chat_template=resolved_chat_template,
chat_template_content_format=args.chat_template_content_format,
trust_request_chat_template=args.trust_request_chat_template,
log_error_stack=args.log_error_stack,
)
if "embed" in supported_tasks
else None
)
state.openai_serving_classification = (
ServingClassification(
engine_client,
state.openai_serving_models,
request_logger=request_logger,
chat_template=resolved_chat_template,
chat_template_content_format=args.chat_template_content_format,
trust_request_chat_template=args.trust_request_chat_template,
log_error_stack=args.log_error_stack,
)
if "classify" in supported_tasks
else None
)
state.openai_serving_scores = (
ServingScores(
engine_client,
state.openai_serving_models,
request_logger=request_logger,
score_template=resolved_chat_template,
log_error_stack=args.log_error_stack,
)
if ("embed" in supported_tasks or "score" in supported_tasks)
else None
)