fix openai stream & update chat template

lightllm/server/api_models.py

@@ -24,7 +24,10 @@ class ChatCompletionRequest(BaseModel):
     # Additional parameters supported by LightLLM
     do_sample: Optional[bool] = False
     top_k: Optional[int] = -1
+    repetition_penalty: Optional[float] = 1.0
     ignore_eos: Optional[bool] = False
+    role_settings: Optional[Dict[str, str]] = None
+    character_settings: Optional[List[Dict[str, str]]] = None
 
 
 class UsageInfo(BaseModel):

lightllm/server/api_server.py

@@ -206,6 +206,7 @@ async def chat_completions(request: ChatCompletionRequest, raw_request: Request)
         do_sample=request.do_sample,
         presence_penalty=request.presence_penalty,
         frequency_penalty=request.frequency_penalty,
+        repetition_penalty=request.repetition_penalty,
         temperature=request.temperature,
         top_p=request.top_p,
         top_k=request.top_k,
@@ -283,7 +284,7 @@ async def stream_results() -> AsyncGenerator[bytes, None]:
                 model=request.model,
                 choices=[stream_choice],
             )
-            yield ("data: " + stream_resp.json(ensure_ascii=False) + "\n\n").encode("utf-8")
+            yield ("data: " + json.dumps(stream_resp.dict(), ensure_ascii=False) + "\n\n").encode("utf-8")
 
     background_tasks = BackgroundTasks()
     return StreamingResponse(stream_results(), media_type="text/event-stream", background=background_tasks)

lightllm/server/build_prompt.py

@@ -11,5 +11,10 @@ def init_tokenizer(args):
 async def build_prompt(request) -> str:
     global tokenizer
     messages = request.messages
-    input_str = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+    kwargs = {"conversation": messages}
+    if request.character_settings:
+        kwargs["character_settings"] = request.character_settings
+    if request.role_settings:
+        kwargs["role_setting"] = request.role_settings
+    input_str = tokenizer.apply_chat_template(**kwargs, tokenize=False, add_generation_prompt=True)
     return input_str