feat(agent): агент логов — фильтр, LLM-страж, планировщик grep (#18)

- prefilter: правила из config/agent_rules.yaml (длина, команды, shell,
  секреты и системные файлы, prompt injection) — без LLM
- guard: отдельный вызов, JSON {verdict, reason}; невалидный ответ = attack,
  недоступный LLM — «попробуйте позже», а не атака
- planner: только AgentLogQuery (контейнер из белого списка, ≤ 7 д, шаблон
  ≤ 200 без вложенных квантификаторов, лимит ≤ 500); логи в LLM не идут
- бот: «🤖 Спросить агента» → показывает построенный grep и строки;
  атака — вежливый отказ и 🛡 администраторам; квота 30 в сутки
- журнал agent_requests + log_queries (mode=agent)
- при LLM_PROVIDER=mock агент выключен

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

app/agent/service.py

@@ -0,0 +1,120 @@
+"""The agent pipeline end to end, with the daily quota and the `agent_requests` journal (SPEC L-10…L-17)."""
+
+import logging
+from dataclasses import dataclass
+from datetime import datetime, timedelta
+from enum import StrEnum
+from pathlib import Path
+
+from sqlalchemy import func, select
+
+from app.agent import guard, planner
+from app.agent.log_query import AgentLogQuery
+from app.agent.prefilter import Prefilter, load_rules
+from app.db.models import AgentRequest, Verdict, utcnow
+from app.db.session import SessionMaker
+from app.llm.provider import LLMError, LLMProvider
+
+log = logging.getLogger(__name__)
+
+DAILY_QUOTA = 30  # L-17
+
+
+class Outcome(StrEnum):
+    OK = "ok"
+    ATTACK = "attack"  # prefilter or guard: refuse politely, alert the admins
+    QUOTA = "quota"
+    UNAVAILABLE = "unavailable"  # the LLM is down
+    NOT_UNDERSTOOD = "not_understood"  # the planner's reply failed validation
+
+
+@dataclass(frozen=True)
+class Answer:
+    outcome: Outcome
+    query: AgentLogQuery | None = None
+    reason: str = ""  # for the admins' alert and the journal; never shown to the asker
+    stage: str = ""  # prefilter | guard
+
+
+@dataclass(frozen=True)
+class Prompts:
+    guard: str
+    planner: str
+
+
+def load_prompts(config_dir: Path) -> Prompts:
+    d = config_dir / "prompts"
+    return Prompts(
+        guard=(d / "guard.md").read_text(encoding="utf-8"), planner=(d / "planner.md").read_text(encoding="utf-8")
+    )
+
+
+class Agent:
+    def __init__(
+        self, llm: LLMProvider, sessions: SessionMaker, prefilter: Prefilter, prompts: Prompts, quota: int = DAILY_QUOTA
+    ) -> None:
+        self._llm = llm
+        self._sessions = sessions
+        self._prefilter = prefilter
+        self._prompts = prompts
+        self.quota = quota
+
+    @classmethod
+    def from_config(cls, llm: LLMProvider, sessions: SessionMaker, config_dir: Path) -> "Agent":
+        return cls(llm, sessions, Prefilter(load_rules(config_dir)), load_prompts(config_dir))
+
+    async def used_today(self, user_id: int, now: datetime) -> int:
+        async with self._sessions() as session:
+            count = await session.scalar(
+                select(func.count())
+                .select_from(AgentRequest)
+                .where(AgentRequest.user_id == user_id, AgentRequest.at >= now - timedelta(days=1))
+            )
+        return int(count or 0)
+
+    async def ask(self, user_id: int, prompt: str, containers: list[str], default: str) -> Answer:
+        now = utcnow()
+        prompt = prompt.strip()
+        if await self.used_today(user_id, now) >= self.quota:
+            return Answer(Outcome.QUOTA)
+
+        reason = self._prefilter.check(prompt)
+        if reason is not None:
+            await self._journal(user_id, prompt, Verdict.ATTACK, f"prefilter: {reason}", None, 0)
+            return Answer(Outcome.ATTACK, reason=reason, stage="prefilter")
+
+        tokens = 0
+        try:
+            verdict = await guard.classify(self._llm, self._prompts.guard, prompt)
+            tokens += verdict.tokens
+            if verdict.verdict is not Verdict.SAFE:
+                await self._journal(user_id, prompt, Verdict.ATTACK, f"guard: {verdict.reason}", None, tokens)
+                return Answer(Outcome.ATTACK, reason=verdict.reason, stage="guard")
+            result = await planner.plan(self._llm, self._prompts.planner, prompt, containers, default, now)
+            tokens += result.tokens
+        except LLMError as e:
+            log.warning("agent: llm unavailable: %s", e)
+            await self._journal(user_id, prompt, Verdict.ERROR, f"llm: {str(e)[:200]}", None, tokens)
+            return Answer(Outcome.UNAVAILABLE)
+
+        if result.query is None:
+            await self._journal(user_id, prompt, Verdict.ERROR, f"planner: {result.error}", None, tokens)
+            return Answer(Outcome.NOT_UNDERSTOOD, reason=result.error)
+        await self._journal(user_id, prompt, Verdict.SAFE, None, result.query.model_dump(), tokens)
+        return Answer(Outcome.OK, query=result.query)
+
+    async def _journal(
+        self,
+        user_id: int,
+        prompt: str,
+        verdict: Verdict,
+        reason: str | None,
+        query: dict[str, object] | None,
+        tokens: int,
+    ) -> None:
+        async with self._sessions.begin() as session:
+            session.add(
+                AgentRequest(
+                    user_id=user_id, prompt=prompt, verdict=verdict, reason=reason, log_query=query, tokens=tokens
+                )
+            )