Merge pull request #121 from sven-knoblauch/lora-modules

add changes for lora adapter support and /v1/models endpoint
This commit is contained in:
Marut Pandya
2024-10-31 15:07:02 -04:00
committed by GitHub
+15 -6
View File
@@ -11,7 +11,8 @@ from vllm import AsyncLLMEngine
from vllm.entrypoints.openai.serving_chat import OpenAIServingChat
from vllm.entrypoints.openai.serving_completion import OpenAIServingCompletion
from vllm.entrypoints.openai.protocol import ChatCompletionRequest, CompletionRequest, ErrorResponse
from vllm.entrypoints.openai.serving_engine import BaseModelPath
from vllm.entrypoints.openai.serving_engine import BaseModelPath, LoRAModulePath
from utils import DummyRequest, JobInput, BatchSize, create_error_response
from constants import DEFAULT_MAX_CONCURRENCY, DEFAULT_BATCH_SIZE, DEFAULT_BATCH_SIZE_GROWTH_FACTOR, DEFAULT_MIN_BATCH_SIZE
@@ -128,13 +129,24 @@ class OpenAIvLLMEngine(vLLMEngine):
self.base_model_paths = [
BaseModelPath(name=self.engine_args.model, model_path=self.engine_args.model)
]
lora_modules = os.getenv('LORA_MODULES', None)
if lora_modules is not None:
try:
lora_modules = json.loads(lora_modules)
lora_modules = [LoRAModulePath(**lora_modules)]
except:
lora_modules = None
self.chat_engine = OpenAIServingChat(
engine_client=self.llm,
model_config=self.model_config,
base_model_paths=self.base_model_paths,
response_role=self.response_role,
chat_template=self.tokenizer.tokenizer.chat_template,
lora_modules=None,
lora_modules=lora_modules,
prompt_adapters=None,
request_logger=None
)
@@ -142,7 +154,7 @@ class OpenAIvLLMEngine(vLLMEngine):
engine_client=self.llm,
model_config=self.model_config,
base_model_paths=self.base_model_paths,
lora_modules=[],
lora_modules=lora_modules,
prompt_adapters=None,
request_logger=None
)
@@ -158,9 +170,6 @@ class OpenAIvLLMEngine(vLLMEngine):
async def _handle_model_request(self):
models = await self.chat_engine.show_available_models()
fixed_model = models.data[0]
fixed_model.id = self.served_model_name
models.data = [fixed_model]
return models.model_dump()
async def _handle_chat_or_completion_request(self, openai_request: JobInput):