add docstrings, refactor logger

Former-commit-id: c34e489d71f8f539028543ccf8ee92cecedd6276

src/llamafactory/api/app.py

@@ -12,8 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import asyncio
 import os
 from contextlib import asynccontextmanager
+from functools import partial
 from typing import Optional
 
 from typing_extensions import Annotated
@@ -50,15 +52,24 @@ if is_uvicorn_available():
     import uvicorn
 
 
+async def sweeper() -> None:
+    while True:
+        torch_gc()
+        await asyncio.sleep(300)
+
+
 @asynccontextmanager
-async def lifespan(app: "FastAPI"):  # collects GPU memory
+async def lifespan(app: "FastAPI", chat_model: "ChatModel"):  # collects GPU memory
+    if chat_model.engine_type == "huggingface":
+        asyncio.create_task(sweeper())
+
     yield
     torch_gc()
 
 
 def create_app(chat_model: "ChatModel") -> "FastAPI":
     root_path = os.environ.get("FASTAPI_ROOT_PATH", "")
-    app = FastAPI(lifespan=lifespan, root_path=root_path)
+    app = FastAPI(lifespan=partial(lifespan, chat_model=chat_model), root_path=root_path)
     app.add_middleware(
         CORSMiddleware,
         allow_origins=["*"],
@@ -66,7 +77,7 @@ def create_app(chat_model: "ChatModel") -> "FastAPI":
         allow_methods=["*"],
         allow_headers=["*"],
     )
-    api_key = os.environ.get("API_KEY")
+    api_key = os.environ.get("API_KEY", None)
     security = HTTPBearer(auto_error=False)
 
     async def verify_api_key(auth: Annotated[Optional[HTTPAuthorizationCredentials], Depends(security)]):
@@ -80,7 +91,7 @@ def create_app(chat_model: "ChatModel") -> "FastAPI":
         dependencies=[Depends(verify_api_key)],
     )
     async def list_models():
-        model_card = ModelCard(id="gpt-3.5-turbo")
+        model_card = ModelCard(id=os.environ.get("API_MODEL_NAME", "gpt-3.5-turbo"))
         return ModelList(data=[model_card])
 
     @app.post(

src/llamafactory/api/chat.py

@@ -52,9 +52,8 @@ if is_requests_available():
 
 
 if TYPE_CHECKING:
-    from numpy.typing import NDArray
-
     from ..chat import ChatModel
+    from ..data.mm_plugin import ImageInput
     from .protocol import ChatCompletionRequest, ScoreEvaluationRequest
 
 
@@ -70,7 +69,7 @@ ROLE_MAPPING = {
 
 def _process_request(
     request: "ChatCompletionRequest",
-) -> Tuple[List[Dict[str, str]], Optional[str], Optional[str], Optional["NDArray"]]:
+) -> Tuple[List[Dict[str, str]], Optional[str], Optional[str], Optional["ImageInput"]]:
     logger.info("==== request ====\n{}".format(json.dumps(dictify(request), indent=2, ensure_ascii=False)))
 
     if len(request.messages) == 0: