feat(B-RL): Rate-Limiting Konsistenz — zentrale Policies für Auth/AI/Upload/Webhook

B-RL: Rate-Limiting auf zentrale check_rate_limit() umgestellt
- forgejo_error_reporter: In-Memory → zentrale Redis-Rate-Limit
- ai_proactive: eigene Redis-Logik → zentrale check_rate_limit()
- agent_runner: DB-basiertes Limit bleibt (zählt echte Ausführungen)
- RateLimitPolicy Enum (AUTH/AI/UPLOAD/WEBHOOK) + check_rate_limit_policy()
- 8 neue config.py Settings für Policy-Limits
- 12 Routes mit Policies versehen (login, password-reset, AI, uploads, webhooks)

Tests: 20 Tests in test_rate_limit_policies.py — alle grün
- Policies, check_rate_limit, reset, get_client_ip, forgejo, ai_proactive
- Keine Regression: 116 bestehende Tests grün

app/plugins/builtins/ai_assistant/routes.py

@@ -7,7 +7,7 @@ from __future__ import annotations
 import uuid
 
 import aiofiles
-from fastapi import APIRouter, Depends, HTTPException, Query, UploadFile
+from fastapi import APIRouter, Depends, HTTPException, Query, Request, UploadFile
 from fastapi.responses import FileResponse, StreamingResponse
 from sqlalchemy import select
 from sqlalchemy.ext.asyncio import AsyncSession
@@ -556,11 +556,20 @@ async def list_messages(
 async def chat_stream(
     session_id: str,
     data: ChatSendRequest,
+    request: Request,
     current_user: dict = Depends(get_current_user),
     db: AsyncSession = Depends(get_db),
 ):
     tenant_id = uuid.UUID(current_user["tenant_id"])
     user_id = uuid.UUID(current_user["user_id"])
+
+    # Rate limit — AI policy (cost-sensitive LLM call)
+    from app.core.rate_limit import RateLimitPolicy, check_rate_limit_policy
+    await check_rate_limit_policy(
+        f"rate:ai:chat:{tenant_id}:{user_id}",
+        RateLimitPolicy.AI,
+    )
+
     await set_tenant_context(db, tenant_id)
     session = await get_session_by_id(db, uuid.UUID(session_id), user_id, tenant_id)
     if not session: