MrSphay/odysseus
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Support vLLM 0.20.2 / NIM reasoning-parser output end-to-end (surface + agent context + render) (#602)

Browse Source 
* fix(stream): read 'reasoning' SSE field for vLLM 0.20.2 / NIM

vLLM 0.20.2 / NVIDIA NIM emit reasoning-parser output in the `reasoning` delta field; older builds use `reasoning_content`. stream_llm() read only the latter, so reasoning from models like Nemotron-3-Nano (--reasoning-parser) was silently dropped and never rendered. Accept either field.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* fix(agent): keep reasoning_content only on the latest assistant turn

The agent loop echoed each round's reasoning back as `reasoning_content` on every assistant turn, assuming vendors ignore it. Nemotron's chat template re-injects ALL prior reasoning_content as <think> blocks, and the loop is trimmed only once (before it starts) — so reasoning accumulated unbounded across rounds, bloating context and feeding the model its own prior reasoning, which reinforced repetition/looping. Strip reasoning_content from earlier assistant turns so only the most recent round carries it (still satisfies DeepSeek's thinking-mode follow-up requirement).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* fix(agent-ui): wrap each round's reasoning in its own <think> block

The streamed think-tag wrapper gated on whole-message substring checks (accumulated.includes('<think>')), which only ever wrapped ONE reasoning block per message. A multi-round agent response has a reasoning phase per round, so once round 1 closed its <think>...</think>, rounds 2+ reasoning was emitted unwrapped and leaked into the visible answer. Replace the substring checks with a stateful open/close flag that toggles per think/answer cycle, so each round's reasoning gets its own collapsible block. Single-turn chat is unchanged (one open, one close).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test(stream): reasoning/reasoning_content delta surfaces as thinking chunk

Covers @pewdiepie-archdaemon's requested regression: a streamed {reasoning: ...} delta emits a thinking chunk while {content: ...} streams as normal content; plus the older reasoning_content field for backward compat. Mirrors the #591 scenario.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
nsgds
2026-06-02 10:48:17 +08:00
committed by GitHub
parent a857d2016d
commit 5645cce6d0
4 changed files with 124 additions and 7 deletions
Download Patch File Download Diff File Expand all files Collapse all files

14
src/agent_loop.py
View File

@@ -1101,8 +1101,20 @@ def _append_tool_results(
`round_reasoning` (DeepSeek / vLLM reasoning-parser deltas) is echoed
back via `reasoning_content` on the assistant message — DeepSeek's API
rejects follow-up requests in thinking mode that don't include the
prior reasoning. Other vendors ignore the extra field.
prior reasoning.
NOTE: it is NOT universally ignored. Nemotron's chat template re-injects
EVERY prior `reasoning_content` as a <think> block, and this agent loop is
trimmed only once (before the loop), so across rounds the reasoning piles
up unbounded — bloating context and feeding the model its own prior
reasoning, which reinforces repetition/looping. So keep reasoning_content
on the MOST RECENT assistant turn only: enough for DeepSeek continuity,
without the per-round accumulation.
"""
# Strip reasoning_content from earlier assistant turns; only the newest keeps it.
for _m in messages:
if _m.get("role") == "assistant":
_m.pop("reasoning_content", None)
if used_native and native_tool_calls:
assistant_msg = {"role": "assistant"}
# When the model emitted ONLY tool calls (no prose), content must be

4
src/llm_core.py
View File

@@ -1127,8 +1127,8 @@ async def stream_llm(url: str, model: str, messages: List[Dict], temperature: fl
delta = j["choices"][0].get("delta") or {}
if isinstance(delta, dict):
# Text content
# Reasoning tokens (VLLM --reasoning-parser, e.g. Qwen3/DeepSeek-R1)
reasoning = delta.get("reasoning_content") or ""
# Reasoning tokens (VLLM --reasoning-parser, e.g. Qwen3/DeepSeek-R1, Nemotron). vLLM 0.20.2 / NIM emit the field as `reasoning`; older builds use `reasoning_content`. Accept either.
reasoning = delta.get("reasoning_content") or delta.get("reasoning") or ""
if reasoning:
yield f'data: {json.dumps({"delta": reasoning, "thinking": True})}\n\n'
content = delta.get("content") or ""

15
static/js/chat.js
View File

@@ -512,6 +512,10 @@ import createResearchSynapse from './researchSynapse.js';
// Declare accumulated outside try block so it's accessible in catch
let accumulated = '';
// Are we currently inside an unclosed <think> block? Toggled per think/answer
// cycle so a multi-round agent response (one reasoning phase PER round) wraps each
// round's reasoning in its own <think>…</think> instead of leaking rounds 2+ as text.
let _thinkOpen = false;
let holder = null;
let finalMeta = null;
let finalModelName = null;
@@ -1357,12 +1361,15 @@ import createResearchSynapse from './researchSynapse.js';
if (_threadAbove && _threadAbove.classList.contains('agent-thread') && !_threadAbove.classList.contains('has-bottom')) {
_threadAbove.classList.add('has-bottom');
}
// VLLM reasoning tokens: wrap in <think> tags for the thinking UI
// VLLM reasoning tokens: wrap in <think> tags for the thinking UI.
// Stateful open/close (not a whole-message substring check) so each round
// of a multi-round agent response gets its own <think>…</think> — otherwise
// only round 1 is wrapped and rounds 2+ reasoning leaks into the answer.
let _delta = json.delta;
if (json.thinking) {
if (!accumulated.includes('<think>')) _delta = '<think>' + _delta;
} else if (accumulated.includes('<think>') && !accumulated.includes('</think>')) {
_delta = '</think>' + _delta;
if (!_thinkOpen) { _delta = '<think>' + _delta; _thinkOpen = true; }
} else if (_thinkOpen) {
_delta = '</think>' + _delta; _thinkOpen = false;
}
const wasEmpty = !accumulated;
accumulated += _delta;

98
tests/test_llm_core_reasoning.py Normal file
View File

@@ -0,0 +1,98 @@
"""Regression: a streamed `reasoning` delta (vLLM 0.20.2 / NIM / Ollama) must surface
as a thinking chunk, while a `content` delta still streams as normal content. Also
covers the older `reasoning_content` field name for backward compatibility.
"""
import asyncio
import json
from src import llm_core
class _FakeResp:
status_code = 200
def __init__(self, lines):
self._lines = lines
async def aiter_lines(self):
for ln in self._lines:
yield ln
async def aread(self): # only used on non-200; present for safety
return b""
class _FakeStreamCtx:
def __init__(self, lines):
self._lines = lines
async def __aenter__(self):
return _FakeResp(self._lines)
async def __aexit__(self, *exc):
return False
class _FakeClient:
def __init__(self, lines):
self._lines = lines
def stream(self, *args, **kwargs):
return _FakeStreamCtx(self._lines)
def _run_stream(model, lines, monkeypatch):
"""Drive stream_llm against a faked upstream and return parsed SSE payloads."""
monkeypatch.setattr(llm_core, "_get_http_client", lambda: _FakeClient(lines))
async def _go():
out = []
async for chunk in llm_core.stream_llm(
"http://nim-nano:8000/v1/chat/completions",
model,
[{"role": "user", "content": "hi"}],
):
out.append(chunk)
return out
parsed = []
for chunk in asyncio.run(_go()):
for raw in chunk.splitlines():
raw = raw.strip()
if raw.startswith("data:"):
payload = raw[5:].strip()
if payload.startswith("{"):
try:
parsed.append(json.loads(payload))
except json.JSONDecodeError:
pass
return [p for p in parsed if "delta" in p]
def test_reasoning_field_emits_thinking_chunk(monkeypatch):
deltas = _run_stream(
"nvidia/nemotron-3-nano",
[
'data: {"choices":[{"delta":{"reasoning":"weighing options"}}]}',
'data: {"choices":[{"delta":{"content":"Hello"}}]}',
"data: [DONE]",
],
monkeypatch,
)
assert any(d.get("thinking") and "weighing options" in d["delta"] for d in deltas), deltas
assert any((not d.get("thinking")) and d["delta"] == "Hello" for d in deltas), deltas
def test_reasoning_content_field_still_supported(monkeypatch):
# Older builds emit `reasoning_content`; it must still surface as thinking.
deltas = _run_stream(
"some-thinking-model",
[
'data: {"choices":[{"delta":{"reasoning_content":"older field"}}]}',
'data: {"choices":[{"delta":{"content":"Answer"}}]}',
"data: [DONE]",
],
monkeypatch,
)
assert any(d.get("thinking") and "older field" in d["delta"] for d in deltas), deltas
assert any((not d.get("thinking")) and d["delta"] == "Answer" for d in deltas), deltas