feat: switch text risk filtering to AI-first with keyword fallback

This commit is contained in:
2026-03-01 13:41:25 +08:00
parent 3c92611137
commit 1c266f2887
2 changed files with 126 additions and 5 deletions

View File

@@ -1687,16 +1687,21 @@ class CustomerServiceAgent:
# 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
try:
from utils.content_filter import should_block_customer
map_hit = self._is_map_inquiry(message.msg)
political_hit = self._is_political_inquiry(message.msg)
if should_block_customer(message.msg) or political_hit or map_hit:
from utils.content_filter import should_block_customer_smart
risk_hit, risk_category, _risk_reason = await should_block_customer_smart(message.msg)
map_hit = self._is_map_inquiry(message.msg) or (risk_category == "map")
political_hit = self._is_political_inquiry(message.msg) or (risk_category == "political")
if risk_hit or political_hit or map_hit:
# 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
state.pending_image_urls.clear()
state.pending_requirements.clear()
self._sync_pending_quote_state(message.from_id, state)
reject_text = "地图这类不做哈,这边不接地图相关需求。"
if political_hit and not map_hit:
if risk_category == "sexual":
reject_text = "这类不做哈,涉黄擦边内容都不接。"
elif risk_category == "violent":
reject_text = "这类不做哈,暴力血腥相关都不接。"
elif political_hit and not map_hit:
reject_text = "这类不做哈,政治相关图片和人物都不接。"
reply = await self._rewrite_reply_with_ai(
message=message,
@@ -1711,6 +1716,7 @@ class CustomerServiceAgent:
customer_id=message.from_id,
map_hit=map_hit,
political_hit=political_hit,
risk_category=risk_category,
reply=reply,
)
return AgentResponse(reply=reply, should_reply=True, need_transfer=False)

View File

@@ -7,6 +7,8 @@
import os
import re
import base64
import json
import asyncio
from typing import Tuple
# 敏感词库(按类别,可扩展)
@@ -41,6 +43,8 @@ _SENSITIVE_PATTERNS = {
}
_COMPILED: dict = {}
_TEXT_RISK_CACHE: dict = {} # text -> (block, category, reason, ts)
_TEXT_RISK_CACHE_TTL = 300
def _get_compiled():
@@ -89,6 +93,117 @@ def should_block_customer(text: str) -> bool:
return len(hit) > 0
def _risk_from_keyword(text: str) -> tuple[bool, str, str]:
"""关键词风控兜底:返回 (是否拦截, 类别, 原因)。"""
_, hit = filter_sensitive(text)
if not hit:
return False, "none", ""
cats = set(hit)
if "地图" in cats:
return True, "map", "命中地图关键词"
if "党政" in cats:
return True, "political", "命中政治关键词"
if {"黄色", "擦边"} & cats:
return True, "sexual", "命中涉黄关键词"
if {"暴力", "血腥"} & cats:
return True, "violent", "命中暴力关键词"
return True, "other", "命中敏感关键词"
def _extract_json(text: str) -> dict:
t = (text or "").strip()
if not t:
return {}
try:
return json.loads(t)
except Exception:
pass
m = re.search(r"\{[\s\S]*\}", t)
if not m:
return {}
try:
return json.loads(m.group(0))
except Exception:
return {}
async def _detect_customer_risk_with_ai(text: str) -> tuple[bool, str, str]:
"""
AI 文本风控:返回 (是否拦截, 类别, 原因)。
类别: map/political/sexual/violent/other/none
"""
raw = (text or "").strip()
if not raw:
return False, "none", ""
api_key = os.getenv("OPENAI_API_KEY", "").strip()
if not api_key:
return False, "none", ""
try:
now = asyncio.get_running_loop().time()
except Exception:
now = 0.0
cached = _TEXT_RISK_CACHE.get(raw)
if cached and (now - cached[3]) < _TEXT_RISK_CACHE_TTL:
return cached[0], cached[1], cached[2]
base_url = os.getenv("OPENAI_BASE_URL", "https://api.openai.com/v1").strip()
model = os.getenv("TEXT_RISK_MODEL", "").strip() or os.getenv("OPENAI_MODEL", "gpt-4o-mini")
timeout_s = float(os.getenv("AI_TEXT_RISK_TIMEOUT_SECONDS", "4"))
prompt = (
"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"
"禁止接单类别:\n"
"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"
"2) political: 政治/党政/领导人/政治事件\n"
"3) sexual: 色情/擦边/裸露/性暗示\n"
"4) violent: 暴力/血腥\n"
"若不属于以上类别category=none 且 block=false。\n"
"只输出 JSON不要解释。\n"
"格式:{\"block\":true/false,\"category\":\"map|political|sexual|violent|other|none\",\"reason\":\"简短原因\"}\n"
f"用户文本:{raw}"
)
try:
from openai import AsyncOpenAI
client = AsyncOpenAI(api_key=api_key, base_url=base_url, timeout=timeout_s)
resp = await client.chat.completions.create(
model=model,
temperature=0,
messages=[
{"role": "system", "content": "你是严格 JSON 输出的风控分类器。"},
{"role": "user", "content": prompt},
],
)
content = (resp.choices[0].message.content or "").strip()
data = _extract_json(content)
block = bool(data.get("block", False))
category = str(data.get("category", "none") or "none").strip().lower()
reason = str(data.get("reason", "") or "").strip()
if category not in {"map", "political", "sexual", "violent", "other", "none"}:
category = "none"
block = False
if category == "none":
block = False
_TEXT_RISK_CACHE[raw] = (block, category, reason, now)
return block, category, reason
except Exception:
return False, "none", ""
async def should_block_customer_smart(text: str) -> tuple[bool, str, str]:
"""
客户文本风控总入口AI 优先,关键词兜底。
Returns: (block, category, reason)
"""
ai_enabled = os.getenv("AI_TEXT_RISK_ENABLED", "true").strip().lower() in {"1", "true", "yes", "on"}
if ai_enabled:
block, cat, reason = await _detect_customer_risk_with_ai(text)
if block:
return True, cat, reason or "AI 判定敏感"
return _risk_from_keyword(text)
_SENSITIVE_IMAGE_PROMPT = """请判断这张图片是否包含以下任何敏感内容:
- 暴力(打斗、武器、伤害)
- 血腥(伤口、血迹、残肢等)