Make stop reason a dict instead of str (#1407)

python/sglang/srt/managers/schedule_batch.py

@@ -56,7 +56,7 @@ class BaseFinishReason:
     def __init__(self, is_error: bool = False):
         self.is_error = is_error
 
-    def __str__(self):
+    def to_json(self):
         raise NotImplementedError("Subclasses must implement this method")
 
 
@@ -65,34 +65,45 @@ class FINISH_MATCHED_TOKEN(BaseFinishReason):
         super().__init__()
         self.matched = matched
 
-    def __str__(self) -> str:
-        return f"FINISH_MATCHED_TOKEN: {self.matched}"
+    def to_json(self):
+        return {
+            "type": "stop",  # to match OpenAI API's return value
+            "matched": self.matched,
+        }
 
 
-class FINISH_LENGTH(BaseFinishReason):
-    def __init__(self, length: int):
+class FINISH_MATCHED_STR(BaseFinishReason):
+    def __init__(self, matched: str):
         super().__init__()
-        self.length = length
+        self.matched = matched
 
-    def __str__(self) -> str:
-        return f"FINISH_LENGTH: {self.length}"
+    def to_json(self):
+        return {
+            "type": "stop",  # to match OpenAI API's return value
+            "matched": self.matched,
+        }
 
 
-class FINISH_MATCHED_STR(BaseFinishReason):
-    def __init__(self, matched: str):
+class FINISH_LENGTH(BaseFinishReason):
+    def __init__(self, length: int):
         super().__init__()
-        self.matched = matched
+        self.length = length
 
-    def __str__(self) -> str:
-        return f"FINISH_MATCHED_STR: {self.matched}"
+    def to_json(self):
+        return {
+            "type": "length",  # to match OpenAI API's return value
+            "length": self.length,
+        }
 
 
 class FINISH_ABORT(BaseFinishReason):
     def __init__(self):
         super().__init__(is_error=True)
 
-    def __str__(self) -> str:
-        return "FINISH_ABORT"
+    def to_json(self):
+        return {
+            "type": "abort",
+        }
 
 
 class Req:

python/sglang/srt/managers/tp_worker.py

@@ -813,7 +813,11 @@ class ModelTpServer:
                         "prompt_tokens": len(req.origin_input_ids),
                         "completion_tokens": len(req.output_ids),
                         "completion_tokens_wo_jump_forward": req.completion_tokens_wo_jump_forward,
-                        "finish_reason": str(req.finished_reason),
+                        "finish_reason": (
+                            req.finished_reason.to_json()
+                            if req.finished_reason is not None
+                            else None
+                        ),
                     }
                     if req.return_logprob:
                         (

python/sglang/srt/openai_api/adapter.py

@@ -95,19 +95,6 @@ file_id_storage: Dict[str, str] = {}
 storage_dir = None
 
 
-def format_finish_reason(finish_reason) -> Optional[str]:
-    if finish_reason.startswith("None"):
-        return None
-    elif finish_reason.startswith("FINISH_MATCHED"):
-        return "stop"
-    elif finish_reason.startswith("FINISH_LENGTH"):
-        return "length"
-    elif finish_reason.startswith("FINISH_ABORT"):
-        return "abort"
-    else:
-        return "unknown"
-
-
 def create_error_response(
     message: str,
     err_type: str = "BadRequestError",
@@ -618,8 +605,10 @@ def v1_generate_response(request, ret, tokenizer_manager, to_file=False):
                 "index": 0,
                 "text": text,
                 "logprobs": logprobs,
-                "finish_reason": format_finish_reason(
-                    ret_item["meta_info"]["finish_reason"]
+                "finish_reason": (
+                    ret_item["meta_info"]["finish_reason"]["type"]
+                    if ret_item["meta_info"]["finish_reason"]
+                    else ""
                 ),
             }
         else:
@@ -627,8 +616,10 @@ def v1_generate_response(request, ret, tokenizer_manager, to_file=False):
                 index=idx,
                 text=text,
                 logprobs=logprobs,
-                finish_reason=format_finish_reason(
-                    ret_item["meta_info"]["finish_reason"]
+                finish_reason=(
+                    ret_item["meta_info"]["finish_reason"]["type"]
+                    if ret_item["meta_info"]["finish_reason"]
+                    else ""
                 ),
             )
 
@@ -762,8 +753,10 @@ async def v1_completions(tokenizer_manager, raw_request: Request):
                         index=index,
                         text=delta,
                         logprobs=logprobs,
-                        finish_reason=format_finish_reason(
-                            content["meta_info"]["finish_reason"]
+                        finish_reason=(
+                            content["meta_info"]["finish_reason"]["type"]
+                            if content["meta_info"]["finish_reason"]
+                            else ""
                         ),
                     )
                     chunk = CompletionStreamResponse(
@@ -999,8 +992,10 @@ def v1_chat_generate_response(request, ret, to_file=False):
                 "index": 0,
                 "message": {"role": "assistant", "content": ret_item["text"]},
                 "logprobs": choice_logprobs,
-                "finish_reason": format_finish_reason(
-                    ret_item["meta_info"]["finish_reason"]
+                "finish_reason": (
+                    ret_item["meta_info"]["finish_reason"]["type"]
+                    if ret_item["meta_info"]["finish_reason"]
+                    else ""
                 ),
             }
         else:
@@ -1008,8 +1003,10 @@ def v1_chat_generate_response(request, ret, to_file=False):
                 index=idx,
                 message=ChatMessage(role="assistant", content=ret_item["text"]),
                 logprobs=choice_logprobs,
-                finish_reason=format_finish_reason(
-                    ret_item["meta_info"]["finish_reason"]
+                finish_reason=(
+                    ret_item["meta_info"]["finish_reason"]["type"]
+                    if ret_item["meta_info"]["finish_reason"]
+                    else ""
                 ),
             )
 
@@ -1134,8 +1131,10 @@ async def v1_chat_completions(tokenizer_manager, raw_request: Request):
                         choice_data = ChatCompletionResponseStreamChoice(
                             index=index,
                             delta=DeltaMessage(role="assistant"),
-                            finish_reason=format_finish_reason(
-                                content["meta_info"]["finish_reason"]
+                            finish_reason=(
+                                content["meta_info"]["finish_reason"]["type"]
+                                if content["meta_info"]["finish_reason"]
+                                else ""
                             ),
                             logprobs=choice_logprobs,
                         )
@@ -1152,8 +1151,10 @@ async def v1_chat_completions(tokenizer_manager, raw_request: Request):
                     choice_data = ChatCompletionResponseStreamChoice(
                         index=index,
                         delta=DeltaMessage(content=delta),
-                        finish_reason=format_finish_reason(
-                            content["meta_info"]["finish_reason"]
+                        finish_reason=(
+                            content["meta_info"]["finish_reason"]["type"]
+                            if content["meta_info"]["finish_reason"]
+                            else ""
                         ),
                         logprobs=choice_logprobs,
                     )