refactor: 优化参数传递，清理导入样式

astrai/inference/__init__.py

@@ -1,16 +1,15 @@
 from astrai.inference.core import (
-    GeneratorCore,
     EmbeddingEncoderCore,
+    GeneratorCore,
     KVCacheManager,
 )
-
 from astrai.inference.generator import (
-    GenerationRequest,
-    LoopGenerator,
-    StreamGenerator,
     BatchGenerator,
     EmbeddingEncoder,
+    GenerationRequest,
     GeneratorFactory,
+    LoopGenerator,
+    StreamGenerator,
 )
 
 __all__ = [

astrai/inference/core.py

@@ -1,8 +1,9 @@
-import torch
+from typing import Any, Callable, List, Optional, Self, Tuple, Union
 
+import torch
 from torch import Tensor
-from typing import Any, Callable, List, Tuple, Union, Optional, Self
-from astrai.config import ModelParameter, ModelConfig
+
+from astrai.config import ModelConfig, ModelParameter
 
 
 def apply_sampling_strategies(

astrai/inference/generator.py

@@ -1,10 +1,11 @@
-import torch
 from dataclasses import dataclass
-from torch import Tensor
-from typing import List, Tuple, Union, Optional, Generator
-from astrai.inference.core import GeneratorCore, EmbeddingEncoderCore, KVCacheManager
-from astrai.config.param_config import ModelParameter
+from typing import Generator, List, Optional, Tuple, Union
 
+import torch
+from torch import Tensor
+
+from astrai.config.param_config import ModelParameter
+from astrai.inference.core import EmbeddingEncoderCore, GeneratorCore, KVCacheManager
 
 HistoryType = List[Tuple[str, str]]
 

astrai/inference/server.py

@@ -1,13 +1,15 @@
-import torch
-import uvicorn
 import logging
 from pathlib import Path
-from typing import List, Optional, Dict, Any, Tuple
+from typing import Any, Dict, List, Optional, Tuple
+
+import torch
+import uvicorn
 from fastapi import FastAPI, HTTPException
 from fastapi.responses import StreamingResponse
 from pydantic import BaseModel, Field
+
 from astrai.config.param_config import ModelParameter
-from astrai.inference.generator import GeneratorFactory, GenerationRequest
+from astrai.inference.generator import GenerationRequest, GeneratorFactory
 
 logger = logging.getLogger(__name__)