Retry DeepSeek thinking-only turns so review does not 400 on U19.

Empty assistant content is still treated as unset; replay a placeholder and retry once with thinking disabled.

Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
2026-08-28 08:15:07 +02:00
co-authored by Cursor
parent e5e8c42966
commit a9238875dd
2 changed files with 137 additions and 10 deletions
+64 -7
View File
@@ -16,7 +16,7 @@ import json
import logging
from typing import Any
from openai import AsyncOpenAI
from openai import APIStatusError, AsyncOpenAI
from backend.config import settings
from backend.services.llm.base import LLMProvider, LLMSession
@@ -38,6 +38,10 @@ from backend.services.llm.types import (
log = logging.getLogger(__name__)
_VISION_HINT = "vision"
# DeepSeek 400s when an assistant turn has reasoning only: content=null
# and no tool_calls. Empty string is also treated as unset, so replay a
# non-empty placeholder (the official SDK sample would send content=None).
_EMPTY_ASSISTANT_CONTENT = " "
def _is_vision_model(model: str) -> bool:
@@ -97,6 +101,26 @@ def _user_content_parts(blocks: list[ContentBlock], *, vision: bool) -> list[dic
return parts
def _repair_assistant_messages(messages: list[dict]) -> list[dict]:
"""Ensure every assistant turn has content or tool_calls (DeepSeek 400)."""
out: list[dict] = []
changed = False
for m in messages:
if m.get("role") != "assistant":
out.append(m)
continue
tools = m.get("tool_calls") or []
content = m.get("content")
if tools or (isinstance(content, str) and content != ""):
out.append(m)
continue
fixed = dict(m)
fixed["content"] = _EMPTY_ASSISTANT_CONTENT
out.append(fixed)
changed = True
return out if changed else messages
def messages_to_openai(messages: list[Message], *, vision: bool) -> list[dict]:
"""Convert unified messages into DeepSeek/OpenAI chat messages.
@@ -111,9 +135,6 @@ def messages_to_openai(messages: list[Message], *, vision: bool) -> list[dict]:
tool_calls = [b for b in m.content if isinstance(b, ToolCall)]
msg: dict[str, Any] = {"role": "assistant"}
text = "".join(text_parts)
# DeepSeek 400s with "content or tool_calls must be set" when
# thinking-mode returns reasoning only (content=null, no tools).
# Tool turns may keep content=null; text-only turns need "".
if tool_calls:
msg["content"] = text if text else None
msg["tool_calls"] = [
@@ -128,7 +149,7 @@ def messages_to_openai(messages: list[Message], *, vision: bool) -> list[dict]:
for tc in tool_calls
]
else:
msg["content"] = text
msg["content"] = text or _EMPTY_ASSISTANT_CONTENT
reasoning = _reasoning_from_blocks(m.content)
if reasoning:
msg["reasoning_content"] = reasoning
@@ -281,8 +302,44 @@ class DeepSeekSession(LLMSession):
kwargs["tools"] = [_to_openai_tool(t) for t in tools]
kwargs["tool_choice"] = _to_openai_tool_choice(tool_choice)
resp = await self._client.chat.completions.create(**kwargs)
return completion_from_openai(resp)
resp = await self._create(kwargs)
completion = completion_from_openai(resp)
# Thinking-only (no visible text, no tools) cannot be replayed on the
# next turn. Retry once with thinking off so the review loop gets a
# real content/tool_calls message instead of a 400 on the follow-up.
if (
thinking
and not (completion.text or "").strip()
and not completion.tool_calls
):
log.warning(
"DeepSeek thinking-only turn (no content/tool_calls); "
"retrying with thinking disabled"
)
extra_body = {
"thinking": {"type": "disabled"},
}
kwargs = {**kwargs, "extra_body": extra_body}
resp = await self._create(kwargs)
completion = completion_from_openai(resp)
return completion
async def _create(self, kwargs: dict[str, Any]) -> Any:
try:
return await self._client.chat.completions.create(**kwargs)
except APIStatusError as exc:
body = str(exc)
if exc.status_code != 400 or "content or tool_calls" not in body:
raise
repaired = _repair_assistant_messages(list(kwargs["messages"]))
if repaired == kwargs["messages"]:
raise
log.warning(
"DeepSeek 400 (empty assistant content); retrying with "
"placeholder content"
)
kwargs = {**kwargs, "messages": repaired}
return await self._client.chat.completions.create(**kwargs)
async def close(self) -> None:
return None
+73 -3
View File
@@ -72,8 +72,10 @@ def test_messages_to_openai_pdf_becomes_text(sample_pdf: Path):
assert "Extract the pin table" in blob
def test_thinking_only_assistant_sends_empty_content():
"""Thinking with no visible text and no tools must still set content."""
def test_thinking_only_assistant_sends_placeholder_content():
"""Empty string is treated as unset; replay a non-empty placeholder."""
from backend.services.llm.deepseek_provider import _EMPTY_ASSISTANT_CONTENT
out = messages_to_openai(
[Message("assistant", [
TextBlock("", reasoning_content="Need to inspect pin 3 first."),
@@ -81,11 +83,19 @@ def test_thinking_only_assistant_sends_empty_content():
vision=False,
)
assert out[0]["role"] == "assistant"
assert out[0]["content"] == ""
assert out[0]["content"] == _EMPTY_ASSISTANT_CONTENT
assert out[0]["content"]
assert out[0]["reasoning_content"] == "Need to inspect pin 3 first."
assert "tool_calls" not in out[0]
def test_empty_assistant_blocks_still_set_content():
from backend.services.llm.deepseek_provider import _EMPTY_ASSISTANT_CONTENT
out = messages_to_openai([Message("assistant", [])], vision=False)
assert out[0]["content"] == _EMPTY_ASSISTANT_CONTENT
def test_tool_call_assistant_may_have_null_content():
out = messages_to_openai(
[Message("assistant", [
@@ -165,6 +175,66 @@ def test_forced_tool_choice_disables_thinking():
assert captured["tool_choice"]["function"]["name"] == "save_resolved_specs"
def test_thinking_only_retries_with_thinking_disabled():
calls: list[dict] = []
class FakeCompletions:
async def create(self, **kwargs):
calls.append({
"thinking": kwargs["extra_body"]["thinking"]["type"],
})
usage = SimpleNamespace(
prompt_tokens=10, completion_tokens=5,
prompt_cache_hit_tokens=0, prompt_tokens_details=None,
)
if kwargs["extra_body"]["thinking"]["type"] == "enabled":
msg = SimpleNamespace(
content=None,
reasoning_content="pondering the schematic",
tool_calls=None,
)
return SimpleNamespace(
choices=[SimpleNamespace(message=msg, finish_reason="stop")],
usage=usage,
)
fn = SimpleNamespace(name="get_pintable", arguments='{"ref":"U19"}')
tc = SimpleNamespace(id="c1", function=fn)
msg = SimpleNamespace(content=None, reasoning_content=None, tool_calls=[tc])
return SimpleNamespace(
choices=[SimpleNamespace(message=msg, finish_reason="tool_calls")],
usage=usage,
)
class FakeClient:
def __init__(self):
self.chat = SimpleNamespace(completions=FakeCompletions())
from backend.services.llm.deepseek_provider import DeepSeekSession
from backend.services.llm.types import Message, TextBlock, ToolSchema
import asyncio
session = DeepSeekSession(
client=FakeClient(),
model="deepseek-v4-pro",
system="sys",
max_tokens=256,
thinking=True,
reasoning_effort="medium",
)
completion = asyncio.run(session.complete(
messages=[Message("user", [TextBlock("review U19")])],
tools=[ToolSchema(
name="get_pintable", description="x",
input_schema={"type": "object"},
)],
tool_choice="auto",
))
assert len(calls) == 2
assert calls[0]["thinking"] == "enabled"
assert calls[1]["thinking"] == "disabled"
assert completion.tool_calls[0].name == "get_pintable"
def test_tool_schema_and_choice():
schema = ToolSchema(
name="save_pintable",