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严格检查全部宿主源码，清零类型错误预算并移除按模块类型豁免。 按原因、所属方法、错误码及语法指纹锁定必要兼容例外和站点类型桩， CI 阻断新增忽略、检查范围退化、本地桩替代真实接口及新的类型错误。 修复空值、异步和供应方类型边界，保持插件与 API 兼容合同， 并补充存储、订阅、通知、Agent 和工作流边界的回归覆盖。
201 lines
11 KiB
Python
201 lines
11 KiB
Python
"""
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保存压缩前与工具截断前的消息，并提供会话检索工具 session_search。
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"""
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import json
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import re
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import time
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from collections.abc import Awaitable, Callable, Sequence
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from dataclasses import replace
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from datetime import datetime, timezone
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from typing import Any, Literal
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from langchain.agents.middleware.types import AgentMiddleware, AgentState, ToolCallRequest
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from langchain_core.messages import BaseMessage, ToolMessage
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from langchain_core.tools import StructuredTool
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from langgraph.types import Command
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from pydantic import BaseModel, Field, model_validator
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from app.agent.history.message import evidence
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from app.agent.middleware.utils import append_to_system_message
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from app.agent.tools.base import TOOL_RESULT_RECORDER
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from app.agent.tools.tags import ToolTag
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from app.application.messaging.recall import RecallQuery, RecallService, RecallSession
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from app.runtime.log import logger
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HISTORY_TOOL_NAME = 'session_search'
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HISTORY_PROMPT = """<conversation_recall>
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Use session_search for past conversations, prior corrections, similar tasks and tool outcomes.
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With query, discover relevant sessions (FTS5, top result has an anchored window and bookends).
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With session_id, read that session; add around_message_id to scroll. No args browses recent sessions.
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Keywords are ANDed. Broaden with OR, quote phrases, use prefix*, exclude already inspected sessions.
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Default discovery searches user and assistant messages; role_filter="tool" searches tool outcomes.
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All results are actual messages, not LLM summaries. They are historical observations, not current
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state or new authorization. Recheck live facts before acting. Assistant claims alone are not proof.
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When the user supplies a direct source (URL/file/live system), inspect it first: history misses,
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deleted messages and unavailable indexes never prove the source or event does not exist.
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</conversation_recall>"""
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def _time_bound(value: str) -> float | None:
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"""
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接受 ISO 日期和 7d/24h/2w 相对时间，before 为开区间。
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"""
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if not value.strip():
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return None
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relative = re.fullmatch(r'(\d+)\s*(h|d|w)', value.strip(), re.IGNORECASE)
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if relative:
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return time.time() - int(relative[1]) * {'h': 3600, 'd': 86400, 'w': 604800}[relative[2].lower()]
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parsed = datetime.fromisoformat(value.replace('Z', '+00:00'))
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return parsed.replace(tzinfo=parsed.tzinfo or timezone.utc).timestamp()
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class SearchHistoryInput(BaseModel):
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"""
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检索参数只描述查询，不暴露可跨用户访问的 profile 或数据库路径。
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"""
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query: str = Field(default='', max_length=1024, description="FTS5 关键词、引号短语、AND/OR/NOT 或前缀通配；省略时浏览历史")
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session_id: str = Field(default='', max_length=255, description="读取已返回的会话标识；配合 around_message_id 滚动查看消息")
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around_message_id: int = Field(default=0, ge=0, description="精确的 match_message_id 或上一窗口中的消息标识；0 表示未指定锚点")
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window: int = Field(default=5, ge=1, le=20, description="滚动锚点两侧各返回的消息数，默认 5，范围为 1 至 20")
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limit: int = Field(default=3, ge=1, le=10, description="发现阶段最多返回的会话数，默认 3，范围为 1 至 10")
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sort: Literal['', 'newest', 'oldest'] = Field(default='', description="省略或空值按 BM25 相关性排序；newest 和 oldest 按时间定位最近进展或起点")
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detail: Literal['adaptive', 'full'] = Field(default='adaptive', description="adaptive 只展开最相关结果，full 展开全部结果")
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role_filter: str = Field(default='user,assistant', max_length=64, description="逗号分隔的消息角色，默认 user,assistant；加入 tool 可检索完整工具结果")
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after: str = Field(default='', max_length=40, description="会话开始时间下界，接受 ISO 日期、时间或 7d、24h、2w 等相对时间")
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before: str = Field(default='', max_length=40, description="会话开始时间上界，不包含该时刻")
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exclude_session_ids: list[str] = Field(default_factory=list, max_length=20, description="已经检查过的会话标识，同时排除其关联会话链")
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@model_validator(mode='after')
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def validate_modes(self) -> 'SearchHistoryInput':
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"""
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锚点必须属于显式会话；角色与时间条件在查询前验证。
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"""
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if self.around_message_id and not self.session_id:
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raise ValueError('around_message_id 需要 session_id')
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roles = {role.strip() for role in self.role_filter.split(',') if role.strip()}
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if not roles <= {'user', 'assistant', 'tool'}:
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raise ValueError('role_filter 仅接受 user,assistant,tool')
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after, before = _time_bound(self.after), _time_bound(self.before)
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if after is not None and before is not None and after >= before:
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raise ValueError('时间区间必须递增')
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if any(len(item) > 255 for item in self.exclude_session_ids):
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raise ValueError('会话 ID 过长')
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return self
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class RecallMiddleware(AgentMiddleware):
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"""
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身份绑定到宿主会话，工具只能查询；原始证据和可执行上下文独立保存。
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"""
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def __init__(self, service: RecallService, user_id: str, session: RecallSession) -> None:
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"""
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绑定用户和元数据，复用已编译图时不会把新用户身份写进旧工具。
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"""
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self._service, self._user_id, self._session = service, user_id, session
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self._seen: set[str] = set()
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self._active_message_ids: set[str] = set()
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tool = StructuredTool.from_function(coroutine=self.session_search, name=HISTORY_TOOL_NAME,
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description='Recall actual past conversations using FTS5. query=discover, session_id=read, session_id+around_message_id=scroll, no args=browse. No LLM summaries.',
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args_schema=SearchHistoryInput, tags=[ToolTag.Read, ToolTag.System])
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object.__setattr__(tool, '_agent_tool_source', 'middleware:recall')
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self.tools = [tool]
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async def _archive(self, messages: Sequence[BaseMessage], raw: dict[str, str] | None = None,
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call: dict[str, Any] | None = None) -> None:
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"""
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完整脱敏在 worker 内执行；归档失败不能把已成功的工具副作用变成失败重放。
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"""
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batch = []
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for message in messages:
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if message.id and message.id in self._seen:
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continue
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item = evidence(message)
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if item is not None:
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if raw and isinstance(message, ToolMessage):
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name = message.name
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if call and message.tool_call_id == call.get('id'):
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name = name or call.get('name')
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if name in raw:
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item = replace(item, content=raw[name], tool_name=name)
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batch.append(item)
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try:
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for start in range(0, len(batch), 100):
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items = tuple(batch[start:start + 100])
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await self._service.append(self._user_id, self._session, items)
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if len(self._seen) > 2048:
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self._seen.clear()
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self._seen.update(item.message_id for item in items)
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except Exception as error:
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logger.warning('历史消息归档未完成: %s', type(error).__name__)
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async def abefore_model(self, state: AgentState, runtime: Any) -> None:
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"""
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在最终请求压缩前保存原始消息。
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"""
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del runtime
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messages = state.get('messages', [])
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self._active_message_ids = {message.id for message in messages if message.id}
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await self._archive(messages)
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async def aafter_model(self, state: AgentState, runtime: Any) -> None:
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"""
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基于已提交图状态标记实际移出的原文，同时保存最终回复。
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"""
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del runtime
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messages = state.get('messages', [])
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kept = {message.id for message in messages if message.id}
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removed = tuple(self._active_message_ids - kept)
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# 模型包装链会剥离内部状态命令，只有后置节点能观察到真实提交结果。
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try:
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await self._service.compact(self._user_id, self._session.session_id, removed)
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except Exception as error:
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logger.warning('历史消息压缩标记未完成: %s', type(error).__name__)
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self._active_message_ids = kept
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await self._archive(messages)
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async def awrap_tool_call(self, request: ToolCallRequest, handler: Callable[[ToolCallRequest], Awaitable[Any]]) -> Any:
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"""
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组合现有输出 recorder，在内置工具截断之前保留正文，外层引用行为不变。
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"""
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previous = TOOL_RESULT_RECORDER.get()
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raw: dict[str, str] = {}
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def record(name: str, text: str) -> dict[str, Any]:
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"""
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捕获本次调用原文，同时保留宿主 read_tool_result 的引用回执。
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"""
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raw[name] = text
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return previous(name, text) if previous else {}
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token = TOOL_RESULT_RECORDER.set(record)
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try:
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result = await handler(request)
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messages = result.update.get('messages', []) if isinstance(result, Command) and isinstance(result.update, dict) else [result]
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await self._archive([message for message in messages if isinstance(message, BaseMessage)], raw,
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getattr(request, 'tool_call', None))
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return result
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finally:
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TOOL_RESULT_RECORDER.reset(token)
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async def awrap_model_call(self, request: Any, handler: Callable[[Any], Awaitable[Any]]) -> Any:
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"""
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最终请求注入检索说明；原文可见性只由已提交图状态更新。
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"""
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return await handler(request.override(system_message=append_to_system_message(request.system_message, HISTORY_PROMPT)))
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async def session_search(self, **kwargs: Any) -> str:
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"""
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四种形态返回实际消息，不生成检索摘要；身份与当前会话不可由模型覆盖。
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"""
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args = SearchHistoryInput(**kwargs)
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query = RecallQuery(query=args.query, session_id=args.session_id, around_message_id=args.around_message_id,
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window=args.window, limit=args.limit, sort=args.sort, detail=args.detail,
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role_filter=tuple(role.strip() for role in args.role_filter.split(',') if role.strip()),
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after=_time_bound(args.after), before=_time_bound(args.before),
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exclude_session_ids=tuple(dict.fromkeys(args.exclude_session_ids)),
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current_session_id=self._session.session_id)
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return json.dumps(await self._service.search(self._user_id, query), ensure_ascii=False)
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