Frontend: better error message handling for FINISH_ABORT in scheduler.py (#2956)

python/sglang/srt/managers/schedule_batch.py

@@ -115,14 +115,18 @@ class FINISH_LENGTH(BaseFinishReason):
 
 
 class FINISH_ABORT(BaseFinishReason):
-    def __init__(self, message="Unknown error"):
+    def __init__(self, message="Unknown error", status_code=None, err_type=None):
         super().__init__(is_error=True)
         self.message = message
+        self.status_code = status_code
+        self.err_type = err_type
 
     def to_json(self):
         return {
             "type": "abort",
             "message": self.message,
+            "status_code": self.status_code,
+            "err_type": self.err_type,
         }
 
 

python/sglang/srt/managers/scheduler.py

@@ -23,6 +23,7 @@ import warnings
 from collections import deque
 from concurrent import futures
 from dataclasses import dataclass
+from http import HTTPStatus
 from types import SimpleNamespace
 from typing import Dict, List, Optional, Tuple, Union
 
@@ -672,15 +673,16 @@ class Scheduler:
             req.extend_image_inputs(image_inputs)
 
             if len(req.origin_input_ids) >= self.max_req_input_len:
-                logger.error(
+                error_msg = (
                     "Multimodal prompt is too long after expanding multimodal tokens. "
-                    f"After expanding {len(req.origin_input_ids_unpadded)=} => {len(req.origin_input_ids)} >= {self.max_req_input_len}. "
+                    f"After expanding {len(req.origin_input_ids_unpadded)=} => {len(req.origin_input_ids)} >= {self.max_req_input_len}."
                 )
+                logger.error(error_msg)
                 req.origin_input_ids = [0]
                 req.image_inputs = None
                 req.sampling_params.max_new_tokens = 0
                 req.finished_reason = FINISH_ABORT(
-                    "Multimodal prompt is too long. Check server logs for details."
+                    error_msg, HTTPStatus.BAD_REQUEST, "BadRequestError"
                 )
                 self.waiting_queue.append(req)
                 return

python/sglang/srt/managers/tokenizer_manager.py

@@ -25,6 +25,7 @@ import threading
 import time
 import uuid
 from datetime import datetime
+from http import HTTPStatus
 from typing import Any, Awaitable, Dict, Generic, List, Optional, Tuple, TypeVar, Union
 
 import fastapi
@@ -384,6 +385,16 @@ class TokenizerManager:
                     msg = f"Finish: obj={dataclass_to_string_truncated(obj)}, out={dataclass_to_string_truncated(out)}"
                     logger.info(msg)
                 del self.rid_to_state[obj.rid]
+
+                # Check if this was an abort/error created by scheduler
+                if isinstance(out["meta_info"].get("finish_reason"), dict):
+                    finish_reason = out["meta_info"]["finish_reason"]
+                    if (
+                        finish_reason.get("type") == "abort"
+                        and finish_reason.get("status_code") == HTTPStatus.BAD_REQUEST
+                    ):
+                        raise ValueError(finish_reason["message"])
+
                 yield out
                 break
 

python/sglang/srt/managers/utils.py

 import logging
+from http import HTTPStatus
 from typing import Optional
 
 from sglang.srt.managers.schedule_batch import FINISH_ABORT, Req
@@ -35,7 +36,9 @@ def validate_input_length(
                 f"Use a shorter input or enable --allow-auto-truncate."
             )
             logger.error(error_msg)
-            req.finished_reason = FINISH_ABORT(error_msg)
+            req.finished_reason = FINISH_ABORT(
+                error_msg, HTTPStatus.BAD_REQUEST, "BadRequestError"
+            )
             return error_msg
 
     return None

test/srt/test_vision_openai_server.py

@@ -392,34 +392,33 @@ class TestQWen2VLServerContextLengthIssue(unittest.TestCase):
     def test_chat_completion(self):
         client = openai.Client(api_key=self.api_key, base_url=self.base_url)
 
-        response = client.chat.completions.create(
-            model="default",
-            messages=[
-                {
-                    "role": "user",
-                    "content": [
-                        {
-                            "type": "image_url",
-                            "image_url": {
-                                "url": "https://github.com/sgl-project/sglang/blob/main/test/lang/example_image.png?raw=true"
+        with self.assertRaises(openai.BadRequestError) as cm:
+            client.chat.completions.create(
+                model="default",
+                messages=[
+                    {
+                        "role": "user",
+                        "content": [
+                            {
+                                "type": "image_url",
+                                "image_url": {
+                                    "url": "https://github.com/sgl-project/sglang/blob/main/test/lang/example_image.png?raw=true"
+                                },
                             },
-                        },
-                        {
-                            "type": "text",
-                            "text": "Give a lengthy description of this picture",
-                        },
-                    ],
-                },
-            ],
-            temperature=0,
-        )
+                            {
+                                "type": "text",
+                                "text": "Give a lengthy description of this picture",
+                            },
+                        ],
+                    },
+                ],
+                temperature=0,
+            )
 
-        assert response.choices[0].finish_reason == "abort"
-        assert response.id
-        assert response.created
-        assert response.usage.prompt_tokens > 0
-        assert response.usage.completion_tokens > 0
-        assert response.usage.total_tokens > 0
+        self.assertIn(
+            "Multimodal prompt is too long after expanding multimodal tokens.",
+            str(cm.exception),
+        )
 
 
 class TestMllamaServer(TestOpenAIVisionServer):