fix api server

Former-commit-id: 08464183b9b034abdbf179d7043705a0754837e5

src/llmtuner/api/app.py

@@ -1,4 +1,6 @@
+import os
 import json
+import asyncio
 from typing import List, Tuple
 from pydantic import BaseModel
 from contextlib import asynccontextmanager
@@ -63,6 +65,8 @@ def create_app(chat_model: "ChatModel") -> "FastAPI":
         allow_headers=["*"],
     )
 
+    semaphore = asyncio.Semaphore(int(os.environ.get("MAX_CONCURRENT", 1)))
+
     @app.get("/v1/models", response_model=ModelList)
     async def list_models():
         model_card = ModelCard(id="gpt-3.5-turbo")
@@ -93,8 +97,13 @@ def create_app(chat_model: "ChatModel") -> "FastAPI":
         else:
             raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Only supports u/a/u/a/u...")
 
+        async with semaphore:
+            loop = asyncio.get_running_loop()
+            return await loop.run_in_executor(None, chat_completion, query, history, system, request)
+
+    def chat_completion(query: str, history: List[Tuple[str, str]], system: str, request: ChatCompletionRequest):
         if request.stream:
-            generate = predict(query, history, system, request)
+            generate = stream_chat_completion(query, history, system, request)
             return EventSourceResponse(generate, media_type="text/event-stream")
 
         responses = chat_model.chat(
@@ -125,7 +134,7 @@ def create_app(chat_model: "ChatModel") -> "FastAPI":
 
         return ChatCompletionResponse(model=request.model, choices=choices, usage=usage)
 
-    async def predict(query: str, history: List[Tuple[str, str]], system: str, request: ChatCompletionRequest):
+    def stream_chat_completion(query: str, history: List[Tuple[str, str]], system: str, request: ChatCompletionRequest):
         choice_data = ChatCompletionResponseStreamChoice(
             index=0,
             delta=DeltaMessage(role=Role.ASSISTANT, content=""),
@@ -169,6 +178,11 @@ def create_app(chat_model: "ChatModel") -> "FastAPI":
         if len(request.messages) == 0:
             raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid request")
 
+        async with semaphore:
+            loop = asyncio.get_running_loop()
+            return await loop.run_in_executor(None, get_score, request)
+
+    def get_score(request: ScoreEvaluationRequest):
         scores = chat_model.get_scores(request.messages, max_length=request.max_length)
         return ScoreEvaluationResponse(model=request.model, scores=scores)
 
@@ -178,4 +192,4 @@ def create_app(chat_model: "ChatModel") -> "FastAPI":
 if __name__ == "__main__":
     chat_model = ChatModel()
     app = create_app(chat_model)
-    uvicorn.run(app, host="0.0.0.0", port=8000, workers=1)
+    uvicorn.run(app, host="0.0.0.0", port=int(os.environ.get("API_PORT", 8000)), workers=1)

src/llmtuner/chat/chat_model.py

@@ -152,7 +152,6 @@ class ChatModel:
             padding=True,
             truncation=True,
             max_length=max_length or getattr(self.model.config, "max_position_embeddings", 1024),
-            pad_to_multiple_of=8,
             return_tensors="pt",
             **kwargs
         ).to(device)