feat: switch text risk filtering to AI-first with keyword fallback
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@@ -1687,16 +1687,21 @@ class CustomerServiceAgent:
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# 前置风控:客户文本一旦命中政治/敏感询问,直接拒绝,避免“发图我看看”类答非所问
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# 前置风控:客户文本一旦命中政治/敏感询问,直接拒绝,避免“发图我看看”类答非所问
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try:
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try:
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from utils.content_filter import should_block_customer
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from utils.content_filter import should_block_customer_smart
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map_hit = self._is_map_inquiry(message.msg)
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risk_hit, risk_category, _risk_reason = await should_block_customer_smart(message.msg)
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political_hit = self._is_political_inquiry(message.msg)
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map_hit = self._is_map_inquiry(message.msg) or (risk_category == "map")
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if should_block_customer(message.msg) or political_hit or map_hit:
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political_hit = self._is_political_inquiry(message.msg) or (risk_category == "political")
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if risk_hit or political_hit or map_hit:
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# 命中敏感询问时清空待报价队列,避免旧图残留污染后续会话
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# 命中敏感询问时清空待报价队列,避免旧图残留污染后续会话
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state.pending_image_urls.clear()
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state.pending_image_urls.clear()
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state.pending_requirements.clear()
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state.pending_requirements.clear()
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self._sync_pending_quote_state(message.from_id, state)
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self._sync_pending_quote_state(message.from_id, state)
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reject_text = "地图这类不做哈,这边不接地图相关需求。"
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reject_text = "地图这类不做哈,这边不接地图相关需求。"
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if political_hit and not map_hit:
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if risk_category == "sexual":
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reject_text = "这类不做哈,涉黄擦边内容都不接。"
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elif risk_category == "violent":
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reject_text = "这类不做哈,暴力血腥相关都不接。"
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elif political_hit and not map_hit:
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reject_text = "这类不做哈,政治相关图片和人物都不接。"
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reject_text = "这类不做哈,政治相关图片和人物都不接。"
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reply = await self._rewrite_reply_with_ai(
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reply = await self._rewrite_reply_with_ai(
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message=message,
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message=message,
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@@ -1711,6 +1716,7 @@ class CustomerServiceAgent:
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customer_id=message.from_id,
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customer_id=message.from_id,
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map_hit=map_hit,
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map_hit=map_hit,
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political_hit=political_hit,
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political_hit=political_hit,
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risk_category=risk_category,
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reply=reply,
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reply=reply,
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)
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)
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return AgentResponse(reply=reply, should_reply=True, need_transfer=False)
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return AgentResponse(reply=reply, should_reply=True, need_transfer=False)
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@@ -7,6 +7,8 @@
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import os
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import os
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import re
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import re
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import base64
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import base64
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import json
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import asyncio
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from typing import Tuple
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from typing import Tuple
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# 敏感词库(按类别,可扩展)
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# 敏感词库(按类别,可扩展)
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@@ -41,6 +43,8 @@ _SENSITIVE_PATTERNS = {
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}
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}
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_COMPILED: dict = {}
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_COMPILED: dict = {}
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_TEXT_RISK_CACHE: dict = {} # text -> (block, category, reason, ts)
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_TEXT_RISK_CACHE_TTL = 300
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def _get_compiled():
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def _get_compiled():
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@@ -89,6 +93,117 @@ def should_block_customer(text: str) -> bool:
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return len(hit) > 0
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return len(hit) > 0
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def _risk_from_keyword(text: str) -> tuple[bool, str, str]:
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"""关键词风控兜底:返回 (是否拦截, 类别, 原因)。"""
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_, hit = filter_sensitive(text)
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if not hit:
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return False, "none", ""
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cats = set(hit)
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if "地图" in cats:
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return True, "map", "命中地图关键词"
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if "党政" in cats:
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return True, "political", "命中政治关键词"
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if {"黄色", "擦边"} & cats:
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return True, "sexual", "命中涉黄关键词"
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if {"暴力", "血腥"} & cats:
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return True, "violent", "命中暴力关键词"
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return True, "other", "命中敏感关键词"
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def _extract_json(text: str) -> dict:
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t = (text or "").strip()
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if not t:
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return {}
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try:
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return json.loads(t)
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except Exception:
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pass
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m = re.search(r"\{[\s\S]*\}", t)
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if not m:
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return {}
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try:
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return json.loads(m.group(0))
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except Exception:
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return {}
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async def _detect_customer_risk_with_ai(text: str) -> tuple[bool, str, str]:
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"""
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AI 文本风控:返回 (是否拦截, 类别, 原因)。
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类别: map/political/sexual/violent/other/none
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"""
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raw = (text or "").strip()
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if not raw:
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return False, "none", ""
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api_key = os.getenv("OPENAI_API_KEY", "").strip()
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if not api_key:
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return False, "none", ""
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try:
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now = asyncio.get_running_loop().time()
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except Exception:
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now = 0.0
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cached = _TEXT_RISK_CACHE.get(raw)
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if cached and (now - cached[3]) < _TEXT_RISK_CACHE_TTL:
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return cached[0], cached[1], cached[2]
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base_url = os.getenv("OPENAI_BASE_URL", "https://api.openai.com/v1").strip()
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model = os.getenv("TEXT_RISK_MODEL", "").strip() or os.getenv("OPENAI_MODEL", "gpt-4o-mini")
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timeout_s = float(os.getenv("AI_TEXT_RISK_TIMEOUT_SECONDS", "4"))
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prompt = (
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"你是电商客服文本风控分类器。请判断用户文本是否属于禁止接单内容。\n"
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"禁止接单类别:\n"
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"1) map: 地图相关(地图、行政区划图、地形图、卫星地图、导航图等)\n"
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"2) political: 政治/党政/领导人/政治事件\n"
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"3) sexual: 色情/擦边/裸露/性暗示\n"
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"4) violent: 暴力/血腥\n"
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"若不属于以上类别,category=none 且 block=false。\n"
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"只输出 JSON,不要解释。\n"
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"格式:{\"block\":true/false,\"category\":\"map|political|sexual|violent|other|none\",\"reason\":\"简短原因\"}\n"
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f"用户文本:{raw}"
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)
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try:
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from openai import AsyncOpenAI
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client = AsyncOpenAI(api_key=api_key, base_url=base_url, timeout=timeout_s)
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resp = await client.chat.completions.create(
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model=model,
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temperature=0,
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messages=[
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{"role": "system", "content": "你是严格 JSON 输出的风控分类器。"},
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{"role": "user", "content": prompt},
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],
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)
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content = (resp.choices[0].message.content or "").strip()
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data = _extract_json(content)
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block = bool(data.get("block", False))
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category = str(data.get("category", "none") or "none").strip().lower()
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reason = str(data.get("reason", "") or "").strip()
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if category not in {"map", "political", "sexual", "violent", "other", "none"}:
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category = "none"
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block = False
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if category == "none":
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block = False
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_TEXT_RISK_CACHE[raw] = (block, category, reason, now)
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return block, category, reason
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except Exception:
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return False, "none", ""
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async def should_block_customer_smart(text: str) -> tuple[bool, str, str]:
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"""
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客户文本风控总入口:AI 优先,关键词兜底。
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Returns: (block, category, reason)
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"""
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ai_enabled = os.getenv("AI_TEXT_RISK_ENABLED", "true").strip().lower() in {"1", "true", "yes", "on"}
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if ai_enabled:
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block, cat, reason = await _detect_customer_risk_with_ai(text)
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if block:
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return True, cat, reason or "AI 判定敏感"
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return _risk_from_keyword(text)
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_SENSITIVE_IMAGE_PROMPT = """请判断这张图片是否包含以下任何敏感内容:
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_SENSITIVE_IMAGE_PROMPT = """请判断这张图片是否包含以下任何敏感内容:
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- 暴力(打斗、武器、伤害)
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- 暴力(打斗、武器、伤害)
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- 血腥(伤口、血迹、残肢等)
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- 血腥(伤口、血迹、残肢等)
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Block a user