chatvx / plugins /keyword /keyword.py
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# encoding:utf-8
import json
import os
import plugins
from bridge.context import ContextType
from bridge.reply import Reply, ReplyType
from common.log import logger
from plugins import *
@plugins.register(
name="Keyword",
desire_priority=900,
hidden=True,
desc="关键词匹配过滤",
version="0.1",
author="fengyege.top",
)
class Keyword(Plugin):
def __init__(self):
super().__init__()
try:
curdir = os.path.dirname(__file__)
config_path = os.path.join(curdir, "config.json")
conf = None
if not os.path.exists(config_path):
logger.debug(f"[keyword]不存在配置文件{config_path}")
conf = {"keyword": {}}
with open(config_path, "w", encoding="utf-8") as f:
json.dump(conf, f, indent=4)
else:
logger.debug(f"[keyword]加载配置文件{config_path}")
with open(config_path, "r", encoding="utf-8") as f:
conf = json.load(f)
# 加载关键词
self.keyword = conf["keyword"]
logger.info("[keyword] {}".format(self.keyword))
self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context
logger.info("[keyword] inited.")
except Exception as e:
logger.warn("[keyword] init failed, ignore or see https://github.com/zhayujie/chatgpt-on-wechat/tree/master/plugins/keyword .")
raise e
def on_handle_context(self, e_context: EventContext):
if e_context["context"].type != ContextType.TEXT:
return
content = e_context["context"].content.strip()
logger.debug("[keyword] on_handle_context. content: %s" % content)
if content in self.keyword:
logger.debug(f"[keyword] 匹配到关键字【{content}】")
reply_text = self.keyword[content]
# 判断匹配内容的类型
if (reply_text.startswith("http://") or reply_text.startswith("https://")) and any(reply_text.endswith(ext) for ext in [".jpg", ".jpeg", ".png", ".gif", ".webp"]):
# 如果是以 http:// 或 https:// 开头,且.jpg/.jpeg/.png/.gif结尾,则认为是图片 URL
reply = Reply()
reply.type = ReplyType.IMAGE_URL
reply.content = reply_text
else:
# 否则认为是普通文本
reply = Reply()
reply.type = ReplyType.TEXT
reply.content = reply_text
e_context["reply"] = reply
e_context.action = EventAction.BREAK_PASS # 事件结束,并跳过处理context的默认逻辑
def get_help_text(self, **kwargs):
help_text = "关键词过滤"
return help_text