fix(agent): 增强 LLM 流式回复兜底
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@@ -1,4 +1,5 @@
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import json
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import logging
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from urllib import error, request
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from django.conf import settings
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@@ -12,6 +13,9 @@ class LLMRequestError(RuntimeError):
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"""Raised when the remote LLM provider call fails."""
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logger = logging.getLogger(__name__)
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def generate_reply(conversation, user_message: str) -> str:
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"""Calls the SiliconFlow OpenAI-compatible chat endpoint and returns assistant text."""
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@@ -130,7 +134,11 @@ def stream_reply(conversation, user_message: str):
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data = line[5:].strip()
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if data == "[DONE]":
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break
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payload = json.loads(data)
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try:
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payload = json.loads(data)
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except json.JSONDecodeError:
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logger.warning("Skipping malformed LLM stream data", extra={"data": data[:200]})
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continue
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delta = (
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payload.get("choices", [{}])[0]
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.get("delta", {})
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@@ -219,26 +219,52 @@ def stream_message(conversation: Conversation, content: str):
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)
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return
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stream_failed = False
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stream_error = ""
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try:
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for chunk in stream_reply(conversation, content):
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assistant_parts.append(chunk)
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yield sse_event("chunk", {"delta": chunk})
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except (LLMConfigurationError, LLMRequestError) as exc:
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fallback = f"模型调用失败:{exc}"
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assistant_parts = [fallback]
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stream_failed = True
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stream_error = str(exc)
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logger.warning(
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"LLM stream failed",
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extra={"conversation_id": conversation.pk, "error": str(exc)},
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)
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yield sse_event("error", {"message": fallback})
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except Exception as exc:
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fallback = f"回复生成中断:{exc}"
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assistant_parts.append("\n\n" + fallback)
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stream_failed = True
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stream_error = str(exc)
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logger.exception(
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"Unexpected stream failure",
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extra={"conversation_id": conversation.pk, "error": str(exc)},
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)
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yield sse_event("error", {"message": fallback})
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if stream_failed:
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try:
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fallback_reply = generate_reply(conversation, content)
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assistant_parts = [fallback_reply]
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logger.info(
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"Non-stream fallback reply succeeded",
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extra={"conversation_id": conversation.pk, "content_length": len(fallback_reply)},
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)
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yield sse_event("replace", {"content": fallback_reply})
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except (LLMConfigurationError, LLMRequestError) as exc:
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fallback = f"模型调用失败:{exc}"
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assistant_parts = [fallback]
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logger.warning(
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"Non-stream fallback reply failed",
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extra={"conversation_id": conversation.pk, "error": str(exc), "stream_error": stream_error},
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)
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yield sse_event("error", {"message": fallback})
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except Exception as exc:
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fallback = f"回复生成中断:{stream_error or exc}"
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assistant_parts.append("\n\n" + fallback)
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logger.exception(
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"Non-stream fallback crashed",
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extra={"conversation_id": conversation.pk, "error": str(exc), "stream_error": stream_error},
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)
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yield sse_event("error", {"message": fallback})
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assistant_message = append_assistant_message(conversation, "".join(assistant_parts).strip())
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41
tests/test_llm_streaming.py
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41
tests/test_llm_streaming.py
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@@ -0,0 +1,41 @@
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import io
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from urllib import request
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import pytest
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from review_agent.llm import stream_reply
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from review_agent.models import Conversation
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pytestmark = pytest.mark.django_db
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class FakeStreamingResponse:
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def __iter__(self):
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return iter(
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[
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b'data: {"choices":[{"delta":{"content":"A"}}]}\n\n',
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b"data: not-json\n\n",
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b'data: {"choices":[{"delta":{"content":"B"}}]}\n\n',
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b"data: [DONE]\n\n",
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]
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)
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def __enter__(self):
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return self
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def __exit__(self, exc_type, exc, traceback):
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return False
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def test_stream_reply_skips_malformed_sse_data(monkeypatch, settings, django_user_model):
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settings.LLM_API_KEY = "key"
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settings.LLM_MODEL = "model"
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settings.LLM_BASE_URL = "https://example.test/v1"
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monkeypatch.setattr(request, "urlopen", lambda req, timeout: FakeStreamingResponse())
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user = django_user_model.objects.create_user(username="owner", password="pass")
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conversation = Conversation.objects.create(user=user, title="会话")
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chunks = list(stream_reply(conversation, "你好"))
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assert chunks == ["A", "B"]
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