289 lines
11 KiB
Python
289 lines
11 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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from asyncio import Lock
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from collections import defaultdict
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from dataclasses import dataclass
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from http import HTTPStatus
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from typing import Optional, Union
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from vllm.config import ModelConfig
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from vllm.engine.protocol import EngineClient
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from vllm.entrypoints.openai.protocol import (ErrorInfo, ErrorResponse,
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LoadLoRAAdapterRequest,
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ModelCard, ModelList,
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ModelPermission,
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UnloadLoRAAdapterRequest)
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from vllm.logger import init_logger
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from vllm.lora.request import LoRARequest
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from vllm.lora.resolver import LoRAResolver, LoRAResolverRegistry
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from vllm.utils import AtomicCounter
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logger = init_logger(__name__)
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@dataclass
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class BaseModelPath:
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name: str
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model_path: str
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@dataclass
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class LoRAModulePath:
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name: str
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path: str
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base_model_name: Optional[str] = None
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class OpenAIServingModels:
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"""Shared instance to hold data about the loaded base model(s) and adapters.
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Handles the routes:
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- /v1/models
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- /v1/load_lora_adapter
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- /v1/unload_lora_adapter
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"""
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def __init__(
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self,
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engine_client: EngineClient,
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model_config: ModelConfig,
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base_model_paths: list[BaseModelPath],
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*,
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lora_modules: Optional[list[LoRAModulePath]] = None,
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):
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super().__init__()
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self.base_model_paths = base_model_paths
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self.max_model_len = model_config.max_model_len
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self.engine_client = engine_client
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self.model_config = model_config
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self.static_lora_modules = lora_modules
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self.lora_requests: dict[str, LoRARequest] = {}
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self.lora_id_counter = AtomicCounter(0)
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self.lora_resolvers: list[LoRAResolver] = []
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for lora_resolver_name in LoRAResolverRegistry.get_supported_resolvers(
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):
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self.lora_resolvers.append(
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LoRAResolverRegistry.get_resolver(lora_resolver_name))
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self.lora_resolver_lock: dict[str, Lock] = defaultdict(Lock)
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async def init_static_loras(self):
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"""Loads all static LoRA modules.
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Raises if any fail to load"""
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if self.static_lora_modules is None:
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return
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for lora in self.static_lora_modules:
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load_request = LoadLoRAAdapterRequest(lora_path=lora.path,
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lora_name=lora.name)
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load_result = await self.load_lora_adapter(
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request=load_request, base_model_name=lora.base_model_name)
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if isinstance(load_result, ErrorResponse):
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raise ValueError(load_result.error.message)
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def is_base_model(self, model_name) -> bool:
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return any(model.name == model_name for model in self.base_model_paths)
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def model_name(self, lora_request: Optional[LoRARequest] = None) -> str:
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"""Returns the appropriate model name depending on the availability
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and support of the LoRA or base model.
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Parameters:
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- lora: LoRARequest that contain a base_model_name.
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Returns:
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- str: The name of the base model or the first available model path.
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"""
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if lora_request is not None:
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return lora_request.lora_name
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return self.base_model_paths[0].name
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async def show_available_models(self) -> ModelList:
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"""Show available models. This includes the base model and all
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adapters"""
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model_cards = [
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ModelCard(id=base_model.name,
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max_model_len=self.max_model_len,
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root=base_model.model_path,
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permission=[ModelPermission()])
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for base_model in self.base_model_paths
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]
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lora_cards = [
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ModelCard(id=lora.lora_name,
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root=lora.local_path,
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parent=lora.base_model_name if lora.base_model_name else
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self.base_model_paths[0].name,
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permission=[ModelPermission()])
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for lora in self.lora_requests.values()
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]
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model_cards.extend(lora_cards)
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return ModelList(data=model_cards)
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async def load_lora_adapter(
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self,
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request: LoadLoRAAdapterRequest,
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base_model_name: Optional[str] = None
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) -> Union[ErrorResponse, str]:
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lora_name = request.lora_name
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# Ensure atomicity based on the lora name
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async with self.lora_resolver_lock[lora_name]:
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error_check_ret = await self._check_load_lora_adapter_request(
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request)
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if error_check_ret is not None:
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return error_check_ret
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lora_path = request.lora_path
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unique_id = self.lora_id_counter.inc(1)
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lora_request = LoRARequest(lora_name=lora_name,
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lora_int_id=unique_id,
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lora_path=lora_path)
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if base_model_name is not None and self.is_base_model(
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base_model_name):
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lora_request.base_model_name = base_model_name
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# Validate that the adapter can be loaded into the engine
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# This will also pre-load it for incoming requests
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try:
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await self.engine_client.add_lora(lora_request)
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except Exception as e:
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error_type = "BadRequestError"
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status_code = HTTPStatus.BAD_REQUEST
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if "No adapter found" in str(e):
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error_type = "NotFoundError"
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status_code = HTTPStatus.NOT_FOUND
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return create_error_response(message=str(e),
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err_type=error_type,
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status_code=status_code)
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self.lora_requests[lora_name] = lora_request
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logger.info("Loaded new LoRA adapter: name '%s', path '%s'",
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lora_name, lora_path)
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return f"Success: LoRA adapter '{lora_name}' added successfully."
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async def unload_lora_adapter(
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self,
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request: UnloadLoRAAdapterRequest) -> Union[ErrorResponse, str]:
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lora_name = request.lora_name
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# Ensure atomicity based on the lora name
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async with self.lora_resolver_lock[lora_name]:
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error_check_ret = await self._check_unload_lora_adapter_request(
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request)
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if error_check_ret is not None:
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return error_check_ret
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# Safe to delete now since we hold the lock
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del self.lora_requests[lora_name]
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logger.info("Removed LoRA adapter: name '%s'", lora_name)
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return f"Success: LoRA adapter '{lora_name}' removed successfully."
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async def _check_load_lora_adapter_request(
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self, request: LoadLoRAAdapterRequest) -> Optional[ErrorResponse]:
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# Check if both 'lora_name' and 'lora_path' are provided
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if not request.lora_name or not request.lora_path:
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return create_error_response(
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message="Both 'lora_name' and 'lora_path' must be provided.",
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err_type="InvalidUserInput",
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status_code=HTTPStatus.BAD_REQUEST)
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# Check if the lora adapter with the given name already exists
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if request.lora_name in self.lora_requests:
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return create_error_response(
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message=
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f"The lora adapter '{request.lora_name}' has already been "
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"loaded.",
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err_type="InvalidUserInput",
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status_code=HTTPStatus.BAD_REQUEST)
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return None
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async def _check_unload_lora_adapter_request(
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self,
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request: UnloadLoRAAdapterRequest) -> Optional[ErrorResponse]:
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# Check if 'lora_name' is not provided return an error
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if not request.lora_name:
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return create_error_response(
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message=
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"'lora_name' needs to be provided to unload a LoRA adapter.",
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err_type="InvalidUserInput",
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status_code=HTTPStatus.BAD_REQUEST)
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# Check if the lora adapter with the given name exists
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if request.lora_name not in self.lora_requests:
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return create_error_response(
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message=
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f"The lora adapter '{request.lora_name}' cannot be found.",
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err_type="NotFoundError",
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status_code=HTTPStatus.NOT_FOUND)
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return None
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async def resolve_lora(
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self, lora_name: str) -> Union[LoRARequest, ErrorResponse]:
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"""Attempt to resolve a LoRA adapter using available resolvers.
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Args:
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lora_name: Name/identifier of the LoRA adapter
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Returns:
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LoRARequest if found and loaded successfully.
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ErrorResponse (404) if no resolver finds the adapter.
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ErrorResponse (400) if adapter(s) are found but none load.
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"""
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async with self.lora_resolver_lock[lora_name]:
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# First check if this LoRA is already loaded
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if lora_name in self.lora_requests:
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return self.lora_requests[lora_name]
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base_model_name = self.model_config.model
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unique_id = self.lora_id_counter.inc(1)
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found_adapter = False
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# Try to resolve using available resolvers
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for resolver in self.lora_resolvers:
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lora_request = await resolver.resolve_lora(
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base_model_name, lora_name)
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if lora_request is not None:
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found_adapter = True
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lora_request.lora_int_id = unique_id
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try:
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await self.engine_client.add_lora(lora_request)
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self.lora_requests[lora_name] = lora_request
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logger.info(
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"Resolved and loaded LoRA adapter '%s' using %s",
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lora_name, resolver.__class__.__name__)
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return lora_request
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except BaseException as e:
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logger.warning(
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"Failed to load LoRA '%s' resolved by %s: %s. "
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"Trying next resolver.", lora_name,
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resolver.__class__.__name__, e)
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continue
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if found_adapter:
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# An adapter was found, but all attempts to load it failed.
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return create_error_response(
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message=(f"LoRA adapter '{lora_name}' was found "
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"but could not be loaded."),
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err_type="BadRequestError",
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status_code=HTTPStatus.BAD_REQUEST)
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else:
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# No adapter was found
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return create_error_response(
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message=f"LoRA adapter {lora_name} does not exist",
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err_type="NotFoundError",
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status_code=HTTPStatus.NOT_FOUND)
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def create_error_response(
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message: str,
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err_type: str = "BadRequestError",
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status_code: HTTPStatus = HTTPStatus.BAD_REQUEST) -> ErrorResponse:
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return ErrorResponse(error=ErrorInfo(
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message=message, type=err_type, code=status_code.value))
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