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fix: preserve agent debug conversation context

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This commit is contained in:
Nelson
2026-07-17 16:06:43 +08:00
parent cadf44e0b8
commit 537978082a
7 changed files with 92 additions and 15 deletions
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7
ai_knowledge_base_v2/apps/backend/app/schemas/admin.py
View File

@@ -1,6 +1,7 @@
from __future__ import annotations
from datetime import datetime
from typing import Literal
from pydantic import BaseModel, Field
@@ -77,12 +78,18 @@ class PromptSaveRequest(BaseModel):
promptContent: str = Field(min_length=1)
class AgentDebugHistoryMessage(BaseModel):
role: Literal["user", "assistant"]
content: str = Field(min_length=1, max_length=20000)
class AgentDebugRequest(BaseModel):
promptContent: str = Field(min_length=1)
modelId: int = Field(gt=0)
knowledgeIds: list[int] = Field(default_factory=list)
knowledgeVersions: dict[int, int] = Field(default_factory=dict)
question: str = Field(min_length=1, max_length=2000)
history: list[AgentDebugHistoryMessage] = Field(default_factory=list, max_length=100)
temperature: float | None = Field(default=None, ge=0, le=2)
topP: float | None = Field(default=None, ge=0, le=1)
topK: int | None = Field(default=None, ge=1, le=1000)

17
ai_knowledge_base_v2/apps/backend/app/services/agent_debug_service.py
View File

@@ -2,6 +2,7 @@ from __future__ import annotations
import asyncio
from collections.abc import AsyncIterator
from types import SimpleNamespace
from sqlalchemy.orm import Session
@@ -12,31 +13,33 @@ from app.services.admin_service import OperationLogService
from app.services.knowledge_agent_service import KnowledgeAgentService
from app.services.model_stream_service import ModelStreamService
from app.services.reasoning_policy_service import ReasoningPolicyService
from app.services.rag_service import PromptService, RagResult
from app.services.rag_service import RagResult
class AgentDebugService:
@staticmethod
async def build_result(db: Session, payload: AgentDebugRequest) -> RagResult:
history = [
SimpleNamespace(id=index + 1, role=item.role, content=item.content)
for index, item in enumerate(payload.history)
]
rag_result = await KnowledgeAgentService.build_result(
db,
question=payload.question,
history=history,
version_overrides=payload.knowledgeVersions,
preview_knowledge_ids=payload.knowledgeIds,
prompt_override=payload.promptContent,
)
debug_messages = [
{"role": "system", "content": payload.promptContent.strip()},
*(rag_result.messages or []),
]
return RagResult(
question=rag_result.question,
knowledge_scopes=rag_result.knowledge_scopes,
chunks=rag_result.chunks,
prompt=PromptService.render_messages(debug_messages),
prompt=rag_result.prompt,
allow_general_knowledge=rag_result.allow_general_knowledge,
retrieval_log_id=rag_result.retrieval_log_id,
tool_trace=rag_result.tool_trace,
messages=debug_messages,
messages=rag_result.messages,
)
@staticmethod

20
ai_knowledge_base_v2/apps/backend/app/services/knowledge_agent_service.py
View File

@@ -83,6 +83,7 @@ class KnowledgeAgentService:
version_overrides: dict[int, int] | None = None,
preview_knowledge_ids: list[int] | None = None,
context_trace: list[dict] | None = None,
prompt_override: str | None = None,
) -> RagResult:
started = perf_counter()
catalog = cls.get_knowledge_catalog(
@@ -205,6 +206,7 @@ class KnowledgeAgentService:
history,
session_summary,
summary_up_to_message_id,
prompt_override=prompt_override,
)
return RagResult(
question=question,
@@ -309,15 +311,23 @@ class KnowledgeAgentService:
text = question.strip()
if len(text) <= 16:
return True
if re.search(r"(上面|前面|之前|刚才|此前|前一个|原来).{0,8}(问题|内容|回答|练习|流程)", text):
return True
if re.search(r"(再|重新|继续).{0,6}(回答|解释|说明|分析|看看)", text):
return True
return bool(re.search(r"(这个|那个|上述|上面|前面|其中|第二|继续|然后呢|怎么办|怎么做|什么意思|为什么)$", text))
@staticmethod
def _fallback_rewrite(question: str, history) -> str:
previous_user = next(
(message.content.strip() for message in reversed(history) if message.role == "user" and message.content.strip()),
"",
)
return f"关于“{previous_user}”的追问：{question.strip()}" if previous_user else question.strip()
previous_users = [
message.content.strip()
for message in history
if message.role == "user" and message.content.strip()
][-3:]
if not previous_users:
return question.strip()
context = "\n".join(f"历史问题{index + 1}：{content}" for index, content in enumerate(previous_users))
return f"结合以下历史问题回答当前追问：\n{context}\n当前追问：{question.strip()}"
@staticmethod
def get_knowledge_catalog(

3
ai_knowledge_base_v2/apps/backend/app/services/rag_service.py
View File

@@ -118,8 +118,9 @@ class PromptService:
history: list[ChatMessage] | None = None,
session_summary: str | None = None,
summary_up_to_message_id: int | None = None,
prompt_override: str | None = None,
) -> list[dict[str, str]]:
prompt = cls._load_active_prompt(db)
prompt = prompt_override.strip() if prompt_override and prompt_override.strip() else cls._load_active_prompt(db)
# 知识库上下文
context = "\n\n".join(cls._format_chunk(index, chunk) for index, chunk in enumerate(chunks, start=1))

33
ai_knowledge_base_v2/apps/backend/tests/test_agent_runtime_config.py
View File

@@ -1,7 +1,7 @@
import asyncio
from decimal import Decimal
import json
from unittest.mock import patch
from unittest.mock import AsyncMock, patch
import pytest
from sqlalchemy import create_engine
@@ -164,6 +164,37 @@ def test_debug_stream_setting_overrides_model_without_changing_it():
assert AgentDebugService.overrides(payload)["stream_enabled"] == 0
def test_debug_preview_passes_conversation_history_and_replaces_saved_prompt():
rag_result = RagResult(
question="再回答上面的问题",
knowledge_scopes=[],
chunks=[],
prompt="调试提示词渲染结果",
allow_general_knowledge=True,
messages=[{"role": "system", "content": "调试主提示词"}],
)
payload = AgentDebugRequest(
promptContent="调试主提示词",
modelId=1,
question="再回答上面的问题",
history=[
{"role": "user", "content": "最开始的问题"},
{"role": "assistant", "content": "第一次回答"},
],
)
with _database() as db:
build_result = AsyncMock(return_value=rag_result)
with patch("app.services.agent_debug_service.KnowledgeAgentService.build_result", build_result):
result = asyncio.run(AgentDebugService.build_result(db, payload))
kwargs = build_result.await_args.kwargs
assert [item.content for item in kwargs["history"]] == ["最开始的问题", "第一次回答"]
assert kwargs["prompt_override"] == "调试主提示词"
assert result.messages == rag_result.messages
assert result.prompt == "调试提示词渲染结果"
@pytest.mark.parametrize("reasoning_visible", [True, False])
def test_agent_debug_stream_respects_reasoning_visibility(reasoning_visible):
async def chunks():

22
ai_knowledge_base_v2/apps/backend/tests/test_knowledge_agent.py
View File

@@ -269,10 +269,30 @@ def test_contextual_follow_up_is_rewritten_before_agent_decision():
rewrite = next(item for item in result.tool_trace if item["tool"] == "rewrite_contextual_question")
decision = next(item for item in result.tool_trace if item["tool"] == "agent_decision")
assert rewrite["rewrittenQuestion"] == "关于“课程退款条件有哪些？”的追问：那第二种情况呢？"
assert rewrite["rewrittenQuestion"] == (
"结合以下历史问题回答当前追问：\n"
"历史问题1：课程退款条件有哪些？\n"
"当前追问：那第二种情况呢？"
)
assert decision["request"]["question"] == rewrite["rewrittenQuestion"]
def test_long_follow_up_reference_is_detected_and_keeps_multiple_user_questions():
history = [
ChatMessage(id=1, session_id=1, user_id=1, role="user", content="觉式练习和慧氏练习分别是什么，区别是什么？"),
ChatMessage(id=2, session_id=1, user_id=1, role="assistant", content="暂时无法确认。"),
ChatMessage(id=3, session_id=1, user_id=1, role="user", content="阴影人格练习步骤是什么？"),
ChatMessage(id=4, session_id=1, user_id=1, role="assistant", content="先稳定状态，再进行觉察。"),
]
question = "你能根据这个练习的基本方向再来回答一下我上面的问题吗？"
assert KnowledgeAgentService._needs_contextual_rewrite(question) is True
rewritten = KnowledgeAgentService._fallback_rewrite(question, history)
assert "觉式练习和慧氏练习" in rewritten
assert "阴影人格练习步骤" in rewritten
assert question in rewritten
def test_homework_overview_expands_practice_terms_and_section_limit():
terms = KnowledgeAgentService._query_terms("合一的作业是什么？")