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from typing import Any
class LLMRegistry:
_models = {}
@classmethod
def register(cls, name):
def decorator(model_class):
cls._models[name] = model_class
return model_class
return decorator
@classmethod
def get_model(cls, name):
if name not in cls._models:
raise ValueError(f"Model {name} not found in registry")
return cls._models[name]
@LLMRegistry.register("Qwen2-VL")
class Qwen2VL:
def __new__(cls, model_path: str, args: Any) -> Any:
if os.environ.get("use_vllm", "True") == "True":
from models.Qwen2_VL.Qwen2_VL_vllm import Qwen2VL
else:
from models.Qwen2_VL.Qwen2_VL_hf import Qwen2VL
return Qwen2VL(model_path, args)
@LLMRegistry.register("Qwen2.5-VL")
class Qwen2_5_VL:
def __new__(cls, model_path: str, args: Any) -> Any:
if os.environ.get("use_vllm", "True") == "True":
from models.Qwen2_5_VL.Qwen2_5_VL_vllm import Qwen2_5_VL
else:
from models.Qwen2_5_VL.Qwen2_5_VL_hf import Qwen2_5_VL
return Qwen2_5_VL(model_path, args)
@LLMRegistry.register("BiMediX2")
class BiMediX2:
def __new__(cls, model_path: str, args: Any) -> Any:
from models.BiMediX2.BiMediX2_hf import BiMediX2
return BiMediX2(model_path, args)
@LLMRegistry.register("LLava_Med")
class LLavaMed:
def __new__(cls, model_path: str, args: Any) -> Any:
if os.environ.get("use_vllm", "True") == "True":
from models.LLava_Med.LLava_Med_vllm import LLavaMed
else:
from models.LLava_Med.LLava_Med_hf import LLavaMed
return LLavaMed(model_path, args)
@LLMRegistry.register("Huatuo")
class HuatuoGPT:
def __new__(cls, model_path: str, args: Any) -> Any:
if os.environ.get("use_vllm", "True") == "True":
from models.HuatuoGPT.HuatuoGPT_vllm import HuatuoGPT
else:
from models.HuatuoGPT.HuatuoGPT_hf import HuatuoGPT
return HuatuoGPT(model_path, args)
@LLMRegistry.register("InternVL")
class InternVL:
def __new__(cls, model_path: str, args: Any) -> Any:
if os.environ.get("use_vllm", "True") == "True":
from models.InternVL.InternVL_vllm import InternVL
else:
from models.InternVL.InternVL_hf import InternVL
return InternVL(model_path, args)
@LLMRegistry.register("Llama-3.2")
class LlamaVision:
def __new__(cls, model_path: str, args: Any) -> Any:
from models.Llama_3.Llama_3_2_vision_instruct_vllm import LlamaVision
return LlamaVision(model_path, args)
@LLMRegistry.register("LLava")
class Llava:
def __new__(cls, model_path: str, args: Any) -> Any:
if os.environ.get("use_vllm", "True") == "True":
from models.LLava.LLava_vllm import Llava
else:
from models.LLava.LLava_hf import Llava
return Llava(model_path, args)
@LLMRegistry.register("Janus")
class Janus:
def __new__(cls, model_path: str, args: Any) -> Any:
from models.Janus.Janus import Janus
return Janus(model_path, args)
@LLMRegistry.register("HealthGPT")
class HealthGPT:
def __new__(cls, model_path: str, args: Any) -> Any:
if "phi-4" in model_path:
from models.HealthGPT.HealthGPT_phi import HealthGPT
else:
from models.HealthGPT.HealthGPT import HealthGPT
return HealthGPT(model_path, args)
@LLMRegistry.register("BiomedGPT")
class BiomedGPT:
def __new__(cls, model_path: str, args: Any) -> Any:
from models.BiomedGPT.BiomedGPT import BiomedGPT
return BiomedGPT(model_path, args)
@LLMRegistry.register("TestModel")
class TestModel:
def __new__(cls, model_path: str, args: Any) -> Any:
from models.TestModel.TestModel import TestModel
return TestModel(model_path)
@LLMRegistry.register("Vllm_Text")
class VllmText:
def __new__(cls, model_path: str, args: Any) -> Any:
preprocessor_config_path = os.path.join(model_path, "preprocessor_config.json")
if os.path.exists(preprocessor_config_path):
from models.vllm_text.vllm_processor import Vllm_Text
else:
from models.vllm_text.vllm_tokenizer import Vllm_Text
return Vllm_Text(model_path, args)
@LLMRegistry.register("MedGemma")
class MedGemma:
def __new__(cls, model_path: str, args: Any) -> Any:
if os.environ.get("use_vllm", "True") == "True":
from models.MedGemma.MedGemma_vllm import MedGemma
else:
from models.MedGemma.MedGemma_hf import MedGemma
return MedGemma(model_path, args)
@LLMRegistry.register("Med_Flamingo")
class MedFlamingo:
def __new__(cls, model_path: str, args: Any) -> Any:
from models.Med_Flamingo.Med_Flamingo_hf import Med_Flamingo
return Med_Flamingo(model_path, args)
@LLMRegistry.register("GPT")
class GPT:
def __new__(cls, model_path: str, args: Any) -> Any:
from models.GPT.GPT import openai_llm
return openai_llm(model_path, args)
@LLMRegistry.register("MedDr")
class MedDr:
def __new__(cls, model_path: str, args: Any) -> Any:
from models.MedDr.MedDr import MedDr
return MedDr(model_path, args)
def init_llm(args):
try:
model_class = LLMRegistry.get_model(args.model_name)
return model_class(args.model_path, args)
except ValueError as e:
raise ValueError(f"{args.model_name} not supported") from e
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