diff --git a/src/llmtuner/api/app.py b/src/llmtuner/api/app.py
index 3f06fef1..892bf901 100644
--- a/src/llmtuner/api/app.py
+++ b/src/llmtuner/api/app.py
@@ -141,6 +141,7 @@ def create_app(chat_model: "ChatModel") -> "FastAPI":
             top_p=request.top_p,
             max_new_tokens=request.max_tokens,
             num_return_sequences=request.n,
+            stop=request.stop
         )
 
         prompt_length, response_length = 0, 0
@@ -193,6 +194,7 @@ def create_app(chat_model: "ChatModel") -> "FastAPI":
             temperature=request.temperature,
             top_p=request.top_p,
             max_new_tokens=request.max_tokens,
+            stop=request.stop
         ):
             if len(new_token) == 0:
                 continue
diff --git a/src/llmtuner/api/protocol.py b/src/llmtuner/api/protocol.py
index ece2132b..8f1b7b4c 100644
--- a/src/llmtuner/api/protocol.py
+++ b/src/llmtuner/api/protocol.py
@@ -1,6 +1,6 @@
 import time
 from enum import Enum, unique
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List, Optional, Union
 
 from pydantic import BaseModel, Field
 from typing_extensions import Literal
@@ -78,6 +78,7 @@ class ChatCompletionRequest(BaseModel):
     n: int = 1
     max_tokens: Optional[int] = None
     stream: bool = False
+    stop: Union[Optional[str], List[str]] = None
 
 
 class ChatCompletionResponseChoice(BaseModel):
diff --git a/src/llmtuner/chat/vllm_engine.py b/src/llmtuner/chat/vllm_engine.py
index 0f0dc366..9863d635 100644
--- a/src/llmtuner/chat/vllm_engine.py
+++ b/src/llmtuner/chat/vllm_engine.py
@@ -96,6 +96,7 @@ class VllmEngine(BaseEngine):
         repetition_penalty = input_kwargs.pop("repetition_penalty", None)
         max_length = input_kwargs.pop("max_length", None)
         max_new_tokens = input_kwargs.pop("max_new_tokens", None)
+        stop = input_kwargs.pop("stop", None)
 
         generating_args = self.generating_args.copy()
         generating_args.update(
@@ -105,6 +106,7 @@ class VllmEngine(BaseEngine):
                 top_k=top_k or generating_args["top_k"],
                 num_return_sequences=num_return_sequences or 1,
                 repetition_penalty=repetition_penalty or generating_args["repetition_penalty"],
+                stop=stop or generating_args["stop"]
             )
         )
 
@@ -125,6 +127,7 @@ class VllmEngine(BaseEngine):
             stop_token_ids=[self.tokenizer.eos_token_id] + self.tokenizer.additional_special_tokens_ids,
             max_tokens=generating_args["max_new_tokens"],
             skip_special_tokens=True,
+            stop=generating_args["stop"],
         )
 
         if self.processor is not None and image is not None:
diff --git a/src/llmtuner/hparams/generating_args.py b/src/llmtuner/hparams/generating_args.py
index e792c003..03e760e7 100644
--- a/src/llmtuner/hparams/generating_args.py
+++ b/src/llmtuner/hparams/generating_args.py
@@ -1,5 +1,5 @@
 from dataclasses import asdict, dataclass, field
-from typing import Any, Dict
+from typing import Any, Dict, Union, Optional, List
 
 
 @dataclass
@@ -46,7 +46,10 @@ class GeneratingArguments:
         default=1.0,
         metadata={"help": "Exponential penalty to the length that is used with beam-based generation."},
     )
-
+    stop: Union[Optional[str], List[str]] = field(
+        default=None,
+        metadata={"help": "List of strings or string that stop the generation when they are generated. The returned output will not contain the stop strings."},
+    )
     def to_dict(self) -> Dict[str, Any]:
         args = asdict(self)
         if args.get("max_new_tokens", -1) > 0: