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Fix spaced DSML variant parsing and reasoning stream filtering.

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Support < | | DSML | | ...> markup from vLLM gateways, filter DSML in reasoning_content during streaming, and fix invoke parse false negatives.

Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
oliver 2026-05-27 16:25:58 +08:00
parent 97d5c1744a
commit 43f6a792eb
3 changed files with 121 additions and 15 deletions
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34
svc/llm/transports/openai_chat_completions.py
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@ -707,13 +707,14 @@ class OpenAIChatModel(ChatModel):
return self._llm_response_from_completion(completion, on_token=on_token)
tool_acc: dict[int, dict[str, Any]] = {}
reasoning_parts: list[str] = []
recover_dsml = _should_recover_dsml_tool_calls(
self.model,
self.base_url,
thinking_mode_enabled=bool(getattr(self, "thinking_mode_enabled", False)),
)
dsml_filter = DeepSeekTextFilter() if recover_dsml else None
content_visible_parts: list[str] = []
reasoning_visible_parts: list[str] = []
def _emit_visible_text(parts: list[str]) -> None:
if not on_token:
@ -723,16 +724,21 @@ class OpenAIChatModel(ChatModel):
on_token(part)
def _consume_stream(stream_obj: Any) -> None:
nonlocal tool_acc, reasoning_parts
nonlocal tool_acc
for chunk in stream_obj:
if not chunk.choices:
continue
delta = chunk.choices[0].delta
rc = getattr(delta, "reasoning_content", None) or ""
if rc:
reasoning_parts.append(rc)
if on_token:
on_token(rc)
if dsml_filter is not None:
parts = dsml_filter.push(rc)
reasoning_visible_parts.extend(parts)
_emit_visible_text(parts)
else:
reasoning_visible_parts.append(rc)
if on_token:
on_token(rc)
if delta.tool_calls:
for tc in delta.tool_calls:
idx = int(tc.index)
@ -753,8 +759,11 @@ class OpenAIChatModel(ChatModel):
slot["thought_signature"] = sig
if delta.content:
if dsml_filter is not None:
_emit_visible_text(dsml_filter.push(delta.content))
parts = dsml_filter.push(delta.content)
content_visible_parts.extend(parts)
_emit_visible_text(parts)
else:
content_visible_parts.append(delta.content)
if on_token:
on_token(delta.content)
@ -764,12 +773,15 @@ class OpenAIChatModel(ChatModel):
raise
if dsml_filter is not None:
_emit_visible_text(dsml_filter.flush())
content = dsml_filter.visible_text
for part in dsml_filter.flush():
content_visible_parts.append(part)
if on_token and part:
on_token(part)
content = "".join(content_visible_parts)
reasoning_text = "".join(reasoning_visible_parts).strip()
else:
content = ""
reasoning_text = "".join(reasoning_parts).strip()
content = "".join(content_visible_parts)
reasoning_text = "".join(reasoning_visible_parts).strip()
tool_calls: list[LLMToolCall] = []
for idx in sorted(tool_acc.keys()):