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import requests |
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import json |
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import re |
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import plugins |
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from bridge.reply import Reply, ReplyType |
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from bridge.context import ContextType |
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from channel.chat_message import ChatMessage |
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from plugins import * |
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from common.log import logger |
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from common.expired_dict import ExpiredDict |
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import os |
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from docx import Document |
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import markdown |
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import fitz |
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from openpyxl import load_workbook |
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import csv |
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from bs4 import BeautifulSoup |
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from pptx import Presentation |
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from PIL import Image |
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import base64 |
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import html |
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EXTENSION_TO_TYPE = { |
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'pdf': 'pdf', |
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'doc': 'docx', 'docx': 'docx', |
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'md': 'md', |
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'txt': 'txt', |
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'xls': 'excel', 'xlsx': 'excel', |
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'csv': 'csv', |
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'html': 'html', 'htm': 'html', |
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'ppt': 'ppt', 'pptx': 'ppt' |
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} |
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@plugins.register( |
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name="sum4all", |
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desire_priority=2, |
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desc="A plugin for summarizing all things", |
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version="0.7.10", |
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author="fatwang2", |
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) |
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class sum4all(Plugin): |
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def __init__(self): |
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super().__init__() |
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try: |
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curdir = os.path.dirname(__file__) |
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config_path = os.path.join(curdir, "config.json") |
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if os.path.exists(config_path): |
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with open(config_path, "r", encoding="utf-8") as f: |
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self.config = json.load(f) |
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else: |
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# 使用父类的方法来加载配置 |
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self.config = super().load_config() |
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if not self.config: |
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raise Exception("config.json not found") |
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# 设置事件处理函数 |
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self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context |
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self.params_cache = ExpiredDict(300) |
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# 从配置中提取所需的设置 |
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self.keys = self.config.get("keys", {}) |
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self.url_sum = self.config.get("url_sum", {}) |
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self.search_sum = self.config.get("search_sum", {}) |
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self.file_sum = self.config.get("file_sum", {}) |
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self.image_sum = self.config.get("image_sum", {}) |
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self.note = self.config.get("note", {}) |
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self.sum4all_key = self.keys.get("sum4all_key", "") |
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self.search1api_key = self.keys.get("search1api_key", "") |
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self.gemini_key = self.keys.get("gemini_key", "") |
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self.bibigpt_key = self.keys.get("bibigpt_key", "") |
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self.outputLanguage = self.keys.get("outputLanguage", "zh-CN") |
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self.opensum_key = self.keys.get("opensum_key", "") |
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self.open_ai_api_key = self.keys.get("open_ai_api_key", "") |
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self.model = self.keys.get("model", "gpt-3.5-turbo") |
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self.open_ai_api_base = self.keys.get("open_ai_api_base", "https://api.openai.com/v1") |
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self.xunfei_app_id = self.keys.get("xunfei_app_id", "") |
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self.xunfei_api_key = self.keys.get("xunfei_api_key", "") |
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self.xunfei_api_secret = self.keys.get("xunfei_api_secret", "") |
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self.perplexity_key = self.keys.get("perplexity_key", "") |
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self.flomo_key = self.keys.get("flomo_key", "") |
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# 提取sum服务的配置 |
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self.url_sum_enabled = self.url_sum.get("enabled", False) |
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self.url_sum_service = self.url_sum.get("service", "") |
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self.url_sum_group = self.url_sum.get("group", True) |
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self.url_sum_qa_enabled = self.url_sum.get("qa_enabled", True) |
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self.url_sum_qa_prefix = self.url_sum.get("qa_prefix", "问") |
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self.url_sum_prompt = self.url_sum.get("prompt", "") |
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self.search_sum_enabled = self.search_sum.get("enabled", False) |
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self.search_sum_service = self.search_sum.get("service", "") |
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self.search_service = self.search_sum.get("search_service", "duckduckgo") |
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self.search_sum_group = self.search_sum.get("group", True) |
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self.search_sum_search_prefix = self.search_sum.get("search_prefix", "搜") |
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self.search_sum_prompt = self.search_sum.get("prompt", "") |
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self.file_sum_enabled = self.file_sum.get("enabled", False) |
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self.file_sum_service = self.file_sum.get("service", "") |
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self.max_file_size = self.file_sum.get("max_file_size", 15000) |
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self.file_sum_group = self.file_sum.get("group", True) |
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self.file_sum_qa_prefix = self.file_sum.get("qa_prefix", "问") |
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self.file_sum_prompt = self.file_sum.get("prompt", "") |
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self.image_sum_enabled = self.image_sum.get("enabled", False) |
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self.image_sum_service = self.image_sum.get("service", "") |
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self.image_sum_group = self.image_sum.get("group", True) |
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self.image_sum_qa_prefix = self.image_sum.get("qa_prefix", "问") |
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self.image_sum_prompt = self.image_sum.get("prompt", "") |
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self.note_enabled = self.note.get("enabled", False) |
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self.note_service = self.note.get("service", "") |
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self.note_prefix = self.note.get("prefix", "记") |
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# 初始化成功日志 |
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logger.info("[sum4all] inited.") |
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except Exception as e: |
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# 初始化失败日志 |
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logger.warn(f"sum4all init failed: {e}") |
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def on_handle_context(self, e_context: EventContext): |
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context = e_context["context"] |
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if context.type not in [ContextType.TEXT, ContextType.SHARING,ContextType.FILE,ContextType.IMAGE]: |
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return |
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msg: ChatMessage = e_context["context"]["msg"] |
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user_id = msg.from_user_id |
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content = context.content |
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isgroup = e_context["context"].get("isgroup", False) |
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url_match = re.match('https?://(?:[-\w.]|(?:%[\da-fA-F]{2}))+', content) |
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unsupported_urls = re.search(r'.*finder\.video\.qq\.com.*|.*support\.weixin\.qq\.com/update.*|.*support\.weixin\.qq\.com/security.*|.*mp\.weixin\.qq\.com/mp/waerrpage.*', content) |
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# 检查输入是否以"搜索前缀词" 开头 |
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if content.startswith(self.search_sum_search_prefix) and self.search_sum_enabled: |
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# 如果消息来自一个群聊，并且你不希望在群聊中启用搜索功能，直接返回 |
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if isgroup and not self.search_sum_group: |
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return |
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# Call new function to handle search operation |
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self.call_service(content, e_context, "search") |
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return |
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if user_id in self.params_cache and ('last_file_content' in self.params_cache[user_id] or 'last_image_base64' in self.params_cache[user_id] or 'last_url' in self.params_cache[user_id]): |
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# 如果存在最近一次处理的文件路径，触发文件理解函数 |
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if 'last_file_content' in self.params_cache[user_id] and content.startswith(self.file_sum_qa_prefix): |
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logger.info('Content starts with the file_sum_qa_prefix.') |
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# 去除关键词和紧随其后的空格 |
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new_content = content[len(self.file_sum_qa_prefix):] |
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self.params_cache[user_id]['prompt'] = new_content |
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logger.info('params_cache for user has been successfully updated.') |
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self.handle_file(self.params_cache[user_id]['last_file_content'], e_context) |
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# 如果存在最近一次处理的图片路径，触发图片理解函数 |
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elif 'last_image_base64' in self.params_cache[user_id] and content.startswith(self.image_sum_qa_prefix): |
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logger.info('Content starts with the image_sum_qa_prefix.') |
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# 去除关键词和紧随其后的空格 |
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new_content = content[len(self.image_sum_qa_prefix):] |
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self.params_cache[user_id]['prompt'] = new_content |
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logger.info('params_cache for user has been successfully updated.') |
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self.handle_image(self.params_cache[user_id]['last_image_base64'], e_context) |
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# 如果存在最近一次处理的URL，触发URL理解函数 |
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elif 'last_url' in self.params_cache[user_id] and content.startswith(self.url_sum_qa_prefix): |
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logger.info('Content starts with the url_sum_qa_prefix.') |
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# 去除关键词和紧随其后的空格 |
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new_content = content[len(self.url_sum_qa_prefix):] |
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self.params_cache[user_id]['prompt'] = new_content |
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logger.info('params_cache for user has been successfully updated.') |
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self.call_service(self.params_cache[user_id]['last_url'], e_context ,"sum") |
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elif 'last_url' in self.params_cache[user_id] and content.startswith(self.note_prefix) and self.note_enabled and not isgroup: |
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logger.info('Content starts with the note_prefix.') |
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new_content = content[len(self.note_prefix):] |
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self.params_cache[user_id]['note'] = new_content |
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logger.info('params_cache for user has been successfully updated.') |
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self.call_service(self.params_cache[user_id]['last_url'], e_context, "note") |
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if context.type == ContextType.FILE: |
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if isgroup and not self.file_sum_group: |
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# 群聊中忽略处理文件 |
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logger.info("群聊消息，文件处理功能已禁用") |
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return |
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logger.info("on_handle_context: 处理上下文开始") |
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context.get("msg").prepare() |
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file_path = context.content |
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logger.info(f"on_handle_context: 获取到文件路径 {file_path}") |
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# 检查是否应该进行文件总结 |
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if self.file_sum_enabled: |
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# 更新params_cache中的last_file_content |
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self.params_cache[user_id] = {} |
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file_content = self.extract_content(file_path) |
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if file_content is None: |
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logger.info("文件内容无法提取，跳过处理") |
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else: |
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self.params_cache[user_id]['last_file_content'] = file_content |
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logger.info('Updated last_file_content in params_cache for user.') |
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self.handle_file(file_content, e_context) |
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else: |
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logger.info("文件总结功能已禁用，不对文件内容进行处理") |
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# 删除文件 |
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os.remove(file_path) |
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logger.info(f"文件 {file_path} 已删除") |
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elif context.type == ContextType.IMAGE: |
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if isgroup and not self.image_sum_group: |
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# 群聊中忽略处理图片 |
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logger.info("群聊消息，图片处理功能已禁用") |
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return |
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logger.info("on_handle_context: 开始处理图片") |
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context.get("msg").prepare() |
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image_path = context.content |
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logger.info(f"on_handle_context: 获取到图片路径 {image_path}") |
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# 检查是否应该进行图片总结 |
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if self.image_sum_enabled: |
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# 将图片路径转换为Base64编码的字符串 |
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base64_image = self.encode_image_to_base64(image_path) |
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# 更新params_cache中的last_image_path |
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self.params_cache[user_id] = {} |
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self.params_cache[user_id]['last_image_base64'] = base64_image |
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logger.info('Updated last_image_base64 in params_cache for user.') |
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self.handle_image(base64_image, e_context) |
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else: |
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logger.info("图片总结功能已禁用，不对图片内容进行处理") |
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# 删除文件 |
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os.remove(image_path) |
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logger.info(f"文件 {image_path} 已删除") |
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elif context.type == ContextType.SHARING and self.url_sum_enabled: #匹配卡片分享 |
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content = html.unescape(content) |
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if unsupported_urls: #匹配不支持总结的卡片 |
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if isgroup: ##群聊中忽略 |
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return |
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else: ##私聊回复不支持 |
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logger.info("[sum4all] Unsupported URL : %s", content) |
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reply = Reply(type=ReplyType.TEXT, content="不支持总结小程序和视频号") |
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e_context["reply"] = reply |
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e_context.action = EventAction.BREAK_PASS |
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else: #匹配支持总结的卡片 |
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if isgroup: #处理群聊总结 |
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if self.url_sum_group: #group_sharing = True进行总结，False则忽略。 |
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logger.info("[sum4all] Summary URL : %s", content) |
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# 更新params_cache中的last_url |
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self.params_cache[user_id] = {} |
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self.params_cache[user_id]['last_url'] = content |
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logger.info('Updated last_url in params_cache for user.') |
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self.call_service(content, e_context, "sum") |
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return |
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else: |
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return |
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else: #处理私聊总结 |
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logger.info("[sum4all] Summary URL : %s", content) |
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# 更新params_cache中的last_url |
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self.params_cache[user_id] = {} |
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self.params_cache[user_id]['last_url'] = content |
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logger.info('Updated last_url in params_cache for user.') |
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self.call_service(content, e_context, "sum") |
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return |
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elif url_match and self.url_sum_enabled: #匹配URL链接 |
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if unsupported_urls: #匹配不支持总结的网址 |
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logger.info("[sum4all] Unsupported URL : %s", content) |
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reply = Reply(type=ReplyType.TEXT, content="不支持总结小程序和视频号") |
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e_context["reply"] = reply |
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e_context.action = EventAction.BREAK_PASS |
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else: |
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logger.info("[sum4all] Summary URL : %s", content) |
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# 更新params_cache中的last_url |
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self.params_cache[user_id] = {} |
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self.params_cache[user_id]['last_url'] = content |
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logger.info('Updated last_url in params_cache for user.') |
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self.call_service(content, e_context, "sum") |
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return |
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def call_service(self, content, e_context, service_type): |
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if service_type == "search": |
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if self.search_sum_service == "openai" or self.search_sum_service == "sum4all" or self.search_sum_service == "gemini": |
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self.handle_search(content, e_context) |
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elif self.search_sum_service == "perplexity": |
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self.handle_perplexity(content, e_context) |
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elif service_type == "sum": |
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if self.url_sum_service == "bibigpt": |
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self.handle_bibigpt(content, e_context) |
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elif self.url_sum_service == "openai" or self.url_sum_service == "sum4all" or self.url_sum_service == "gemini": |
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self.handle_url(content, e_context) |
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elif self.url_sum_service == "opensum": |
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self.handle_opensum(content, e_context) |
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elif service_type == "note": |
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if self.note_service == "flomo": |
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self.handle_note(content, e_context) |
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def handle_note(self,link,e_context): |
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msg: ChatMessage = e_context["context"]["msg"] |
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user_id = msg.from_user_id |
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title = self.params_cache[user_id].get('title', '') |
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content = self.params_cache[user_id].get('content', '') |
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note = self.params_cache[user_id].get('note', '') |
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# 将这些内容按照一定的格式整合到一起 |
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note_content = f"#sum4all\n{title}\n📒笔记：{note}\n{content}\n{link}" |
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payload = {"content": note_content} |
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# 将这个字典转换为JSON格式 |
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payload_json = json.dumps(payload) |
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# 创建一个POST请求 |
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url = self.flomo_key |
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headers = {'Content-Type': 'application/json'} |
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# 发送这个POST请求 |
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response = requests.post(url, headers=headers, data=payload_json) |
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reply = Reply() |
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reply.type = ReplyType.TEXT |
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if response.status_code == 200 and response.json()['code'] == 0: |
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reply.content = f"已发送到{self.note_service}" |
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else: |
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reply.content = "发送失败，错误码：" + str(response.status_code) |
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e_context["reply"] = reply |
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e_context.action = EventAction.BREAK_PASS |
|
|
|
def short_url(self, long_url): |
|
|
|
url = "https://short.fatwang2.com" |
|
|
|
payload = { |
|
|
|
"url": long_url |
|
|
|
} |
|
|
|
headers = {'Content-Type': "application/json"} |
|
|
|
response = requests.request("POST", url, json=payload, headers=headers) |
|
|
|
if response.status_code == 200: |
|
|
|
res_data = response.json() |
|
|
|
# 直接从返回的 JSON 中获取短链接 |
|
|
|
short_url = res_data.get('shorturl', None) |
|
|
|
|
|
|
|
if short_url: |
|
|
|
return short_url |
|
|
|
return None |
|
|
|
def handle_url(self, content, e_context): |
|
|
|
logger.info('Handling Sum4All request...') |
|
|
|
# 根据sum_service的值选择API密钥和基础URL |
|
|
|
if self.url_sum_service == "openai": |
|
|
|
api_key = self.open_ai_api_key |
|
|
|
api_base = self.open_ai_api_base |
|
|
|
model = self.model |
|
|
|
elif self.url_sum_service == "sum4all": |
|
|
|
api_key = self.sum4all_key |
|
|
|
api_base = "https://pro.sum4all.site/v1" |
|
|
|
model = "sum4all" |
|
|
|
elif self.url_sum_service == "gemini": |
|
|
|
api_key = self.gemini_key |
|
|
|
model = "gemini" |
|
|
|
api_base = "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-latest:generateContent" |
|
|
|
else: |
|
|
|
logger.error(f"未知的sum_service配置: {self.url_sum_service}") |
|
|
|
return |
|
|
|
|
|
|
|
msg: ChatMessage = e_context["context"]["msg"] |
|
|
|
user_id = msg.from_user_id |
|
|
|
user_params = self.params_cache.get(user_id, {}) |
|
|
|
isgroup = e_context["context"].get("isgroup", False) |
|
|
|
prompt = user_params.get('prompt', self.url_sum_prompt) |
|
|
|
headers = { |
|
|
|
'Content-Type': 'application/json', |
|
|
|
'Authorization': f'Bearer {api_key}' |
|
|
|
} |
|
|
|
payload = json.dumps({ |
|
|
|
"link": content, |
|
|
|
"prompt": prompt, |
|
|
|
"model": model, |
|
|
|
"base": api_base |
|
|
|
}) |
|
|
|
additional_content = "" # 在 try 块之前初始化 additional_content |
|
|
|
|
|
|
|
try: |
|
|
|
logger.info('Sending request to LLM...') |
|
|
|
api_url = "https://ai.sum4all.site" |
|
|
|
response = requests.post(api_url, headers=headers, data=payload) |
|
|
|
response.raise_for_status() |
|
|
|
logger.info('Received response from LLM.') |
|
|
|
response_data = response.json() # 解析响应的 JSON 数据 |
|
|
|
if response_data.get("success"): |
|
|
|
content = response_data["content"].replace("\\n", "\n") # 替换 \\n 为 \n |
|
|
|
self.params_cache[user_id]['content'] = content |
|
|
|
|
|
|
|
# 新增加的部分，用于解析 meta 数据 |
|
|
|
meta = response_data.get("meta", {}) # 如果没有 meta 数据，则默认为空字典 |
|
|
|
title = meta.get("og:title", "") # 获取 og:title，如果没有则默认为空字符串 |
|
|
|
self.params_cache[user_id]['title'] = title |
|
|
|
# 只有当 title 非空时，才加入到回复中 |
|
|
|
if title: |
|
|
|
additional_content += f"{title}\n\n" |
|
|
|
reply_content = additional_content + content # 将内容加入回复 |
|
|
|
|
|
|
|
else: |
|
|
|
reply_content = "Content not found or error in response" |
|
|
|
|
|
|
|
except requests.exceptions.RequestException as e: |
|
|
|
# 处理可能出现的错误 |
|
|
|
logger.error(f"Error calling new combined api: {e}") |
|
|
|
reply_content = f"An error occurred" |
|
|
|
|
|
|
|
reply = Reply() |
|
|
|
reply.type = ReplyType.TEXT |
|
|
|
if not self.url_sum_qa_enabled: |
|
|
|
reply.content = remove_markdown(reply_content) |
|
|
|
elif isgroup or not self.note_enabled: |
|
|
|
# reply.content = f"{remove_markdown(reply_content)}\n\n💬5min内输入{self.url_sum_qa_prefix}+问题，可继续追问" |
|
|
|
reply.content = f"{remove_markdown(reply_content)}" |
|
|
|
elif self.note_enabled: |
|
|
|
reply.content = f"{remove_markdown(reply_content)}\n\n💬5min内输入{self.url_sum_qa_prefix}+问题，可继续追问。\n\n📒输入{self.note_prefix}+笔记，可发送当前总结&笔记到{self.note_service}" |
|
|
|
e_context["reply"] = reply |
|
|
|
e_context.action = EventAction.BREAK_PASS |
|
|
|
def handle_bibigpt(self, content, e_context): |
|
|
|
headers = { |
|
|
|
'Content-Type': 'application/json' |
|
|
|
} |
|
|
|
payload_params = { |
|
|
|
"url": content, |
|
|
|
"includeDetail": False, |
|
|
|
"promptConfig": { |
|
|
|
"outputLanguage": self.outputLanguage |
|
|
|
} |
|
|
|
} |
|
|
|
|
|
|
|
payload = json.dumps(payload_params) |
|
|
|
try: |
|
|
|
api_url = f"https://bibigpt.co/api/open/{self.bibigpt_key}" |
|
|
|
response = requests.request("POST",api_url, headers=headers, data=payload) |
|
|
|
response.raise_for_status() |
|
|
|
data = json.loads(response.text) |
|
|
|
summary_original = data.get('summary', 'Summary not available') |
|
|
|
html_url = data.get('htmlUrl', 'HTML URL not available') |
|
|
|
# 获取短链接 |
|
|
|
short_url = self.short_url(html_url) |
|
|
|
|
|
|
|
# 如果获取短链接失败，使用 html_url |
|
|
|
if short_url is None: |
|
|
|
short_url = html_url if html_url != 'HTML URL not available' else 'URL not available' |
|
|
|
|
|
|
|
# 移除 "##摘要"、"## 亮点" 和 "-" |
|
|
|
summary = summary_original.split("详细版（支持对话追问）")[0].replace("## 摘要\n", "📌总结：").replace("## 亮点\n", "").replace("- ", "") |
|
|
|
except requests.exceptions.RequestException as e: |
|
|
|
reply = f"An error occurred" |
|
|
|
|
|
|
|
reply = Reply() |
|
|
|
reply.type = ReplyType.TEXT |
|
|
|
reply.content = f"{summary}\n\n详细链接：{short_url}" |
|
|
|
|
|
|
|
e_context["reply"] = reply |
|
|
|
e_context.action = EventAction.BREAK_PASS |
|
|
|
def handle_opensum(self, content, e_context): |
|
|
|
headers = { |
|
|
|
'Content-Type': 'application/json', |
|
|
|
'Authorization': f'Bearer {self.opensum_key}' |
|
|
|
} |
|
|
|
payload = json.dumps({"link": content}) |
|
|
|
try: |
|
|
|
api_url = "https://read.thinkwx.com/api/v1/article/summary" |
|
|
|
response = requests.request("POST",api_url, headers=headers, data=payload) |
|
|
|
response.raise_for_status() |
|
|
|
data = json.loads(response.text) |
|
|
|
summary_data = data.get('data', {}) # 获取data字段 |
|
|
|
summary_original = summary_data.get('summary', 'Summary not available') |
|
|
|
# 使用正则表达式提取URL |
|
|
|
url_pattern = r'https:\/\/[^\s]+' |
|
|
|
match = re.search(url_pattern, summary_original) |
|
|
|
html_url = match.group(0) if match else 'HTML URL not available' |
|
|
|
# 获取短链接 |
|
|
|
short_url = self.short_url(html_url) if match else html_url |
|
|
|
# 用于移除摘要中的URL及其后的所有内容 |
|
|
|
url_pattern_remove = r'https:\/\/[^\s]+[\s\S]*' |
|
|
|
summary = re.sub(url_pattern_remove, '', summary_original).strip() |
|
|
|
|
|
|
|
except requests.exceptions.RequestException as e: |
|
|
|
summary = f"An error occurred" |
|
|
|
short_url = 'URL not available' |
|
|
|
|
|
|
|
reply = Reply() |
|
|
|
reply.type = ReplyType.TEXT |
|
|
|
reply.content = f"{summary}\n\n详细链接：{short_url}" |
|
|
|
|
|
|
|
e_context["reply"] = reply |
|
|
|
e_context.action = EventAction.BREAK_PASS |
|
|
|
def handle_search(self, content, e_context): |
|
|
|
# 根据sum_service的值选择API密钥和基础URL |
|
|
|
if self.search_sum_service == "openai": |
|
|
|
api_key = self.open_ai_api_key |
|
|
|
api_base = self.open_ai_api_base |
|
|
|
model = self.model |
|
|
|
elif self.search_sum_service == "sum4all": |
|
|
|
api_key = self.sum4all_key |
|
|
|
api_base = "https://pro.sum4all.site/v1" |
|
|
|
model = "sum4all" |
|
|
|
elif self.search_sum_service == "gemini": |
|
|
|
api_key = self.gemini_key |
|
|
|
model = "gemini" |
|
|
|
api_base = "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-latest:generateContent" |
|
|
|
|
|
|
|
else: |
|
|
|
logger.error(f"未知的search_service配置: {self.search_sum_service}") |
|
|
|
return |
|
|
|
headers = { |
|
|
|
'Content-Type': 'application/json', |
|
|
|
'Authorization': f'Bearer {api_key}' |
|
|
|
} |
|
|
|
content = content[len(self.search_sum_search_prefix):] |
|
|
|
payload = json.dumps({ |
|
|
|
"ur": content, |
|
|
|
"prompt": self.search_sum_prompt, |
|
|
|
"model": model, |
|
|
|
"base": api_base, |
|
|
|
"search1api_key": self.search1api_key, |
|
|
|
"search_service": self.search_service |
|
|
|
}) |
|
|
|
try: |
|
|
|
api_url = "https://ai.sum4all.site" |
|
|
|
response = requests.post(api_url, headers=headers, data=payload) |
|
|
|
response.raise_for_status() |
|
|
|
response_data = response.json() # 解析响应的 JSON 数据 |
|
|
|
if response_data.get("success"): |
|
|
|
content = response_data["content"].replace("\\n", "\n") # 替换 \\n 为 \n |
|
|
|
reply_content = content # 将内容加入回复 |
|
|
|
|
|
|
|
# 解析 meta 数据 |
|
|
|
meta = response_data.get("meta", {}) # 如果没有 meta 数据，则默认为空字典 |
|
|
|
title = meta.get("og:title", "") # 获取 og:title，如果没有则默认为空字符串 |
|
|
|
og_url = meta.get("og:url", "") # 获取 og:url，如果没有则默认为空字符串 |
|
|
|
# 打印 title 和 og_url 以调试 |
|
|
|
print("Title:", title) |
|
|
|
print("Original URL:", og_url) |
|
|
|
# 只有当 title 和 url 非空时，才加入到回复中 |
|
|
|
if title: |
|
|
|
reply_content += f"\n\n参考文章：{title}" |
|
|
|
if og_url: |
|
|
|
short_url = self.short_url(og_url) # 获取短链接 |
|
|
|
reply_content += f"\n\n参考链接：{short_url}" |
|
|
|
|
|
|
|
else: |
|
|
|
content = "Content not found or error in response" |
|
|
|
|
|
|
|
except requests.exceptions.RequestException as e: |
|
|
|
# 处理可能出现的错误 |
|
|
|
logger.error(f"Error calling new combined api: {e}") |
|
|
|
reply_content = f"An error occurred" |
|
|
|
|
|
|
|
reply = Reply() |
|
|
|
reply.type = ReplyType.TEXT |
|
|
|
reply.content = f"{remove_markdown(reply_content)}" |
|
|
|
e_context["reply"] = reply |
|
|
|
e_context.action = EventAction.BREAK_PASS |
|
|
|
def handle_perplexity(self, content, e_context): |
|
|
|
|
|
|
|
headers = { |
|
|
|
'Content-Type': 'application/json', |
|
|
|
'Authorization': f'Bearer {self.perplexity_key}' |
|
|
|
} |
|
|
|
data = { |
|
|
|
"model": "sonar-small-online", |
|
|
|
"messages": [ |
|
|
|
{"role": "system", "content": self.search_sum_prompt}, |
|
|
|
{"role": "user", "content": content} |
|
|
|
] |
|
|
|
} |
|
|
|
try: |
|
|
|
api_url = "https://api.perplexity.ai/chat/completions" |
|
|
|
response = requests.post(api_url, headers=headers, json=data) |
|
|
|
response.raise_for_status() |
|
|
|
# 处理响应数据 |
|
|
|
response_data = response.json() |
|
|
|
# 这里可以根据你的需要处理响应数据 |
|
|
|
# 解析 JSON 并获取 content |
|
|
|
if "choices" in response_data and len(response_data["choices"]) > 0: |
|
|
|
first_choice = response_data["choices"][0] |
|
|
|
if "message" in first_choice and "content" in first_choice["message"]: |
|
|
|
content = first_choice["message"]["content"] |
|
|
|
else: |
|
|
|
print("Content not found in the response") |
|
|
|
else: |
|
|
|
print("No choices available in the response") |
|
|
|
except requests.exceptions.RequestException as e: |
|
|
|
# 处理可能出现的错误 |
|
|
|
logger.error(f"Error calling perplexity: {e}") |
|
|
|
reply = Reply() |
|
|
|
reply.type = ReplyType.TEXT |
|
|
|
reply.content = f"{remove_markdown(content)}" |
|
|
|
e_context["reply"] = reply |
|
|
|
e_context.action = EventAction.BREAK_PASS |
|
|
|
def get_help_text(self, verbose=False, **kwargs): |
|
|
|
help_text = "Help you summarize all things\n" |
|
|
|
if not verbose: |
|
|
|
return help_text |
|
|
|
help_text += "1.Share me the link and I will summarize it for you\n" |
|
|
|
help_text += f"2.{self.search_sum_search_prefix}+query,I will search online for you\n" |
|
|
|
return help_text |
|
|
|
def handle_file(self, content, e_context): |
|
|
|
logger.info("handle_file: 向LLM发送内容总结请求") |
|
|
|
# 根据sum_service的值选择API密钥和基础URL |
|
|
|
if self.file_sum_service == "openai": |
|
|
|
api_key = self.open_ai_api_key |
|
|
|
api_base = self.open_ai_api_base |
|
|
|
model = self.model |
|
|
|
elif self.file_sum_service == "sum4all": |
|
|
|
api_key = self.sum4all_key |
|
|
|
api_base = "https://pro.sum4all.site/v1" |
|
|
|
model = "sum4all" |
|
|
|
elif self.file_sum_service == "gemini": |
|
|
|
api_key = self.gemini_key |
|
|
|
model = "gemini" |
|
|
|
api_base = "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-latest:generateContent" |
|
|
|
else: |
|
|
|
logger.error(f"未知的sum_service配置: {self.file_sum_service}") |
|
|
|
return |
|
|
|
msg: ChatMessage = e_context["context"]["msg"] |
|
|
|
user_id = msg.from_user_id |
|
|
|
user_params = self.params_cache.get(user_id, {}) |
|
|
|
prompt = user_params.get('prompt', self.file_sum_prompt) |
|
|
|
if model == "gemini": |
|
|
|
headers = { |
|
|
|
'Content-Type': 'application/json', |
|
|
|
'x-goog-api-key': api_key |
|
|
|
} |
|
|
|
data = { |
|
|
|
"contents": [ |
|
|
|
{"role": "user", "parts": [{"text": prompt}]}, |
|
|
|
{"role": "model", "parts": [{"text": "okay"}]}, |
|
|
|
{"role": "user", "parts": [{"text": content}]} |
|
|
|
], |
|
|
|
"generationConfig": { |
|
|
|
"maxOutputTokens": 800 |
|
|
|
} |
|
|
|
} |
|
|
|
api_url = api_base |
|
|
|
else: |
|
|
|
headers = { |
|
|
|
'Content-Type': 'application/json', |
|
|
|
'Authorization': f'Bearer {api_key}' |
|
|
|
} |
|
|
|
data = { |
|
|
|
"model": model, |
|
|
|
"messages": [ |
|
|
|
{"role": "system", "content": prompt}, |
|
|
|
{"role": "user", "content": content} |
|
|
|
] |
|
|
|
} |
|
|
|
api_url = f"{api_base}/chat/completions" |
|
|
|
try: |
|
|
|
response = requests.post(api_url, headers=headers, data=json.dumps(data)) |
|
|
|
response.raise_for_status() |
|
|
|
response_data = response.json() |
|
|
|
|
|
|
|
# 解析 JSON 并获取 content |
|
|
|
if model == "gemini": |
|
|
|
if "candidates" in response_data and len(response_data["candidates"]) > 0: |
|
|
|
first_candidate = response_data["candidates"][0] |
|
|
|
if "content" in first_candidate: |
|
|
|
if "parts" in first_candidate["content"] and len(first_candidate["content"]["parts"]) > 0: |
|
|
|
response_content = first_candidate["content"]["parts"][0]["text"].strip() # 获取响应内容 |
|
|
|
logger.info(f"Gemini API response content: {response_content}") # 记录响应内容 |
|
|
|
reply_content = response_content.replace("\\n", "\n") # 替换 \\n 为 \n |
|
|
|
else: |
|
|
|
logger.error("Parts not found in the Gemini API response content") |
|
|
|
reply_content = "Parts not found in the Gemini API response content" |
|
|
|
else: |
|
|
|
logger.error("Content not found in the Gemini API response candidate") |
|
|
|
reply_content = "Content not found in the Gemini API response candidate" |
|
|
|
else: |
|
|
|
logger.error("No candidates available in the Gemini API response") |
|
|
|
reply_content = "No candidates available in the Gemini API response" |
|
|
|
else: |
|
|
|
if "choices" in response_data and len(response_data["choices"]) > 0: |
|
|
|
first_choice = response_data["choices"][0] |
|
|
|
if "message" in first_choice and "content" in first_choice["message"]: |
|
|
|
response_content = first_choice["message"]["content"].strip() # 获取响应内容 |
|
|
|
logger.info(f"LLM API response content") # 记录响应内容 |
|
|
|
reply_content = response_content.replace("\\n", "\n") # 替换 \\n 为 \n |
|
|
|
else: |
|
|
|
logger.error("Content not found in the response") |
|
|
|
reply_content = "Content not found in the LLM API response" |
|
|
|
else: |
|
|
|
logger.error("No choices available in the response") |
|
|
|
reply_content = "No choices available in the LLM API response" |
|
|
|
|
|
|
|
except requests.exceptions.RequestException as e: |
|
|
|
logger.error(f"Error calling LLM API: {e}") |
|
|
|
reply_content = f"An error occurred while calling LLM API" |
|
|
|
|
|
|
|
reply = Reply() |
|
|
|
reply.type = ReplyType.TEXT |
|
|
|
# reply.content = f"{remove_markdown(reply_content)}\n\n💬5min内输入{self.file_sum_qa_prefix}+问题，可继续追问" |
|
|
|
reply.content = f"{remove_markdown(reply_content)}" |
|
|
|
e_context["reply"] = reply |
|
|
|
e_context.action = EventAction.BREAK_PASS |
|
|
|
def read_pdf(self, file_path): |
|
|
|
logger.info(f"开始读取PDF文件：{file_path}") |
|
|
|
doc = fitz.open(file_path) |
|
|
|
content = ' '.join([page.get_text() for page in doc]) |
|
|
|
logger.info(f"PDF文件读取完成：{file_path}") |
|
|
|
|
|
|
|
return content |
|
|
|
def read_word(self, file_path): |
|
|
|
doc = Document(file_path) |
|
|
|
return ' '.join([p.text for p in doc.paragraphs]) |
|
|
|
def read_markdown(self, file_path): |
|
|
|
with open(file_path, 'r', encoding='utf-8') as file: |
|
|
|
md_content = file.read() |
|
|
|
return markdown.markdown(md_content) |
|
|
|
def read_excel(self, file_path): |
|
|
|
workbook = load_workbook(file_path) |
|
|
|
content = '' |
|
|
|
for sheet in workbook: |
|
|
|
for row in sheet.iter_rows(): |
|
|
|
content += ' '.join([str(cell.value) for cell in row]) |
|
|
|
content += '\n' |
|
|
|
return content |
|
|
|
def read_txt(self, file_path): |
|
|
|
logger.debug(f"开始读取TXT文件: {file_path}") |
|
|
|
try: |
|
|
|
with open(file_path, 'r', encoding='utf-8') as file: |
|
|
|
content = file.read() |
|
|
|
logger.debug(f"TXT文件读取完成: {file_path}") |
|
|
|
logger.debug("TXT文件内容的前50个字符：") |
|
|
|
logger.debug(content[:50]) # 打印文件内容的前50个字符 |
|
|
|
return content |
|
|
|
except Exception as e: |
|
|
|
logger.error(f"读取TXT文件时出错: {file_path}，错误信息: {str(e)}") |
|
|
|
return "" |
|
|
|
def read_csv(self, file_path): |
|
|
|
content = '' |
|
|
|
with open(file_path, 'r', encoding='utf-8') as csvfile: |
|
|
|
reader = csv.reader(csvfile) |
|
|
|
for row in reader: |
|
|
|
content += ' '.join(row) + '\n' |
|
|
|
return content |
|
|
|
def read_html(self, file_path): |
|
|
|
with open(file_path, 'r', encoding='utf-8') as file: |
|
|
|
soup = BeautifulSoup(file, 'html.parser') |
|
|
|
return soup.get_text() |
|
|
|
def read_ppt(self, file_path): |
|
|
|
presentation = Presentation(file_path) |
|
|
|
content = '' |
|
|
|
for slide in presentation.slides: |
|
|
|
for shape in slide.shapes: |
|
|
|
if hasattr(shape, "text"): |
|
|
|
content += shape.text + '\n' |
|
|
|
return content |
|
|
|
def extract_content(self, file_path): |
|
|
|
logger.info(f"extract_content: 提取文件内容，文件路径: {file_path}") |
|
|
|
file_size = os.path.getsize(file_path) // 1000 # 将文件大小转换为KB |
|
|
|
if file_size > int(self.max_file_size): |
|
|
|
logger.warning(f"文件大小超过限制({self.max_file_size}KB),不进行处理。文件大小: {file_size}KB") |
|
|
|
return None |
|
|
|
file_extension = os.path.splitext(file_path)[1][1:].lower() |
|
|
|
logger.info(f"extract_content: 文件类型为 {file_extension}") |
|
|
|
|
|
|
|
file_type = EXTENSION_TO_TYPE.get(file_extension) |
|
|
|
|
|
|
|
if not file_type: |
|
|
|
logger.error(f"不支持的文件扩展名: {file_extension}") |
|
|
|
return None |
|
|
|
|
|
|
|
read_func = { |
|
|
|
'pdf': self.read_pdf, |
|
|
|
'docx': self.read_word, |
|
|
|
'md': self.read_markdown, |
|
|
|
'txt': self.read_txt, |
|
|
|
'excel': self.read_excel, |
|
|
|
'csv': self.read_csv, |
|
|
|
'html': self.read_html, |
|
|
|
'ppt': self.read_ppt |
|
|
|
}.get(file_type) |
|
|
|
|
|
|
|
if not read_func: |
|
|
|
logger.error(f"不支持的文件类型: {file_type}") |
|
|
|
return None |
|
|
|
logger.info("extract_content: 文件内容提取完成") |
|
|
|
return read_func(file_path) |
|
|
|
def encode_image_to_base64(self, image_path): |
|
|
|
logger.info(f"开始处理图片: {image_path}") |
|
|
|
try: |
|
|
|
with Image.open(image_path) as img: |
|
|
|
logger.info(f"成功打开图片. 原始大小: {img.size}") |
|
|
|
if img.width > 1024: |
|
|
|
new_size = (1024, int(img.height*1024/img.width)) |
|
|
|
img = img.resize(new_size) |
|
|
|
img.save(image_path) # 保存调整大小后的图片 |
|
|
|
logger.info(f"调整图片大小至: {new_size}") |
|
|
|
|
|
|
|
with open(image_path, "rb") as image_file: |
|
|
|
img_byte_arr = image_file.read() |
|
|
|
logger.info(f"读取图片完成. 大小: {len(img_byte_arr)} 字节") |
|
|
|
|
|
|
|
encoded = base64.b64encode(img_byte_arr).decode('ascii') |
|
|
|
logger.info(f"Base64编码完成. 编码后长度: {len(encoded)}") |
|
|
|
return encoded |
|
|
|
except Exception as e: |
|
|
|
logger.error(f"图片编码过程中发生错误: {str(e)}", exc_info=True) |
|
|
|
raise |
|
|
|
# Function to handle OpenAI image processing |
|
|
|
def handle_image(self, base64_image, e_context): |
|
|
|
logger.info("handle_image: 解析图像处理API的响应") |
|
|
|
msg: ChatMessage = e_context["context"]["msg"] |
|
|
|
user_id = msg.from_user_id |
|
|
|
user_params = self.params_cache.get(user_id, {}) |
|
|
|
prompt = user_params.get('prompt', self.image_sum_prompt) |
|
|
|
|
|
|
|
if self.image_sum_service == "openai": |
|
|
|
api_key = self.open_ai_api_key |
|
|
|
api_base = f"{self.open_ai_api_base}/chat/completions" |
|
|
|
model = "gpt-4o-mini" |
|
|
|
elif self.image_sum_service == "xunfei": |
|
|
|
api_key = self.xunfei_api_key |
|
|
|
api_base = "https://spark.sum4all.site/v1/chat/completions" |
|
|
|
model = "spark-chat-vision" |
|
|
|
elif self.image_sum_service == "sum4all": |
|
|
|
api_key = self.sum4all_key |
|
|
|
api_base = "https://pro.sum4all.site/v1/chat/completions" |
|
|
|
model = "sum4all-vision" |
|
|
|
elif self.image_sum_service == "gemini": |
|
|
|
api_key = self.gemini_key |
|
|
|
api_base = "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-latest:generateContent" |
|
|
|
payload = { |
|
|
|
"contents": [ |
|
|
|
{ |
|
|
|
"parts": [ |
|
|
|
{"text": prompt}, |
|
|
|
{ |
|
|
|
"inline_data": { |
|
|
|
"mime_type":"image/png", |
|
|
|
"data": base64_image |
|
|
|
} |
|
|
|
} |
|
|
|
] |
|
|
|
} |
|
|
|
] |
|
|
|
} |
|
|
|
headers = { |
|
|
|
"Content-Type": "application/json", |
|
|
|
"x-goog-api-key": api_key |
|
|
|
} |
|
|
|
logger.info(f"准备发送请求. Payload大小: {len(json.dumps(payload))} 字节") |
|
|
|
|
|
|
|
else: |
|
|
|
logger.error(f"未知的image_sum_service配置: {self.image_sum_service}") |
|
|
|
return |
|
|
|
|
|
|
|
if self.image_sum_service != "gemini": |
|
|
|
payload = { |
|
|
|
"model": model, |
|
|
|
"messages": [ |
|
|
|
{ |
|
|
|
"role": "user", |
|
|
|
"content": [ |
|
|
|
{ |
|
|
|
"type": "text", |
|
|
|
"text": prompt |
|
|
|
}, |
|
|
|
{ |
|
|
|
"type": "image_url", |
|
|
|
"image_url": { |
|
|
|
"url": f"data:image/jpeg;base64,{base64_image}" |
|
|
|
} |
|
|
|
} |
|
|
|
] |
|
|
|
} |
|
|
|
], |
|
|
|
"max_tokens": 3000 |
|
|
|
} |
|
|
|
headers = { |
|
|
|
"Content-Type": "application/json", |
|
|
|
"Authorization": f"Bearer {api_key}" |
|
|
|
} |
|
|
|
|
|
|
|
try: |
|
|
|
response = requests.post(api_base, headers=headers, json=payload) |
|
|
|
logger.info(f"API请求已发送. 状态码: {response.status_code}") |
|
|
|
response.raise_for_status() |
|
|
|
logger.info("API响应状态码正常，开始解析JSON") |
|
|
|
response_json = response.json() |
|
|
|
logger.info("JSON解析完成") |
|
|
|
|
|
|
|
if self.image_sum_service == "gemini": |
|
|
|
reply_content = response_json.get('candidates', [{}])[0].get('content', {}).get('parts', [{}])[0].get('text', 'No text found in the response') |
|
|
|
logger.info(f"成功解析Gemini响应. 回复内容长度: {len(reply_content)}") |
|
|
|
else: |
|
|
|
if "choices" in response_json and len(response_json["choices"]) > 0: |
|
|
|
first_choice = response_json["choices"][0] |
|
|
|
if "message" in first_choice and "content" in first_choice["message"]: |
|
|
|
response_content = first_choice["message"]["content"].strip() |
|
|
|
logger.info("LLM API response content") |
|
|
|
reply_content = response_content |
|
|
|
else: |
|
|
|
logger.error("Content not found in the response") |
|
|
|
reply_content = "Content not found in the LLM API response" |
|
|
|
else: |
|
|
|
logger.error("No choices available in the response") |
|
|
|
reply_content = "No choices available in the LLM API response" |
|
|
|
except Exception as e: |
|
|
|
logger.error(f"Error processing LLM API response: {e}") |
|
|
|
reply_content = f"An error occurred while processing LLM API response" |
|
|
|
|
|
|
|
reply = Reply() |
|
|
|
reply.type = ReplyType.TEXT |
|
|
|
# reply.content = f"{remove_markdown(reply_content)}\n\n💬5min内输入{self.image_sum_qa_prefix}+问题，可继续追问" |
|
|
|
reply.content = f"{remove_markdown(reply_content)}" |
|
|
|
e_context["reply"] = reply |
|
|
|
e_context.action = EventAction.BREAK_PASS |
|
|
|
|
|
|
|
def remove_markdown(text): |
|
|
|
# 替换Markdown的粗体标记 |
|
|
|
text = text.replace("**", "") |
|
|
|
# 替换Markdown的标题标记 |
|
|
|
text = text.replace("### ", "").replace("## ", "").replace("# ", "") |
|
|
|
return text |
