镜像自地址
https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-06 06:26:47 +00:00
8042750d41
* stage academic conversation * stage document conversation * fix buggy gradio version * file dynamic load * merge more academic plugins * accelerate nltk * feat: 为predict函数添加文件和URL读取功能 - 添加URL检测和网页内容提取功能，支持自动提取网页文本 - 添加文件路径识别和文件内容读取功能，支持private_upload路径格式 - 集成WebTextExtractor处理网页内容提取 - 集成TextContentLoader处理本地文件读取 - 支持文件路径与问题组合的智能处理 * back * block unstable --------- Co-authored-by: XiaoBoAI <liuboyin2019@ia.ac.cn>
75 行
2.9 KiB
Python
75 行
2.9 KiB
Python
import re
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import os
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def start_with_url(inputs:str):
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"""
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检查输入是否以 http:// 或 https:// 开头，且为有效的网址
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"""
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if not ("http://" in inputs or "https://" in inputs):
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return False
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try:
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text = text.strip(',.!?，。！？ \t\n\r')
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words = text.split()
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if len(words) != 1:
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return False
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from urllib.parse import urlparse
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result = urlparse(text)
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return all([result.scheme, result.netloc])
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except:
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return False
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def load_web_content(inputs:str, chatbot_with_cookie, history:list):
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from crazy_functions.doc_fns.read_fns.web_reader import WebTextExtractor, WebExtractorConfig
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from toolbox import update_ui
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extractor = WebTextExtractor(WebExtractorConfig())
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try:
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# 添加正在处理的提示信息
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chatbot_with_cookie.append([None, "正在提取网页内容，请稍作等待..."])
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yield from update_ui(chatbot=chatbot_with_cookie, history=history)
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web_content = extractor.extract_text(inputs)
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# 移除提示信息
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chatbot_with_cookie.pop()
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# 显示提取的内容
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chatbot_with_cookie.append([None, f"网页{inputs}的文本内容如下：" + web_content])
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history.extend([f"网页{inputs}的文本内容如下：" + web_content])
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yield from update_ui(chatbot=chatbot_with_cookie, history=history)
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except Exception as e:
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# 如果出错，移除提示信息（如果存在）
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if len(chatbot_with_cookie) > 0 and chatbot_with_cookie[-1][-1] == "正在提取网页内容，请稍作等待...":
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chatbot_with_cookie.pop()
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chatbot_with_cookie.append([inputs, f"网页内容提取失败: {str(e)}"])
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yield from update_ui(chatbot=chatbot_with_cookie, history=history)
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def extract_file_path(text):
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# 匹配以 private_upload 开头，包含时间戳格式的路径
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pattern = r'(private_upload/[^\s]+?/\d{4}-\d{2}-\d{2}-\d{2}-\d{2}-\d{2})'
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match = re.search(pattern, text)
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if match and os.path.exists(match.group(1)):
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return match.group(1)
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return None
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def contain_uploaded_files(inputs: str):
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file_path_match = extract_file_path(inputs)
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if file_path_match:
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return True
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return False
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def load_uploaded_files(inputs, method, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, stream, additional_fn):
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# load file
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from crazy_functions.doc_fns.text_content_loader import TextContentLoader
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file_path = extract_file_path(inputs)
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loader = TextContentLoader(chatbot_with_cookie, history)
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yield from loader.execute(file_path)
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# get question
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original_question = inputs.replace(file_path, '').strip()
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if not original_question:
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original_question = f"请简单分析上述文件内容"
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else:
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original_question = f"基于上述文件内容，{original_question}"
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return original_question
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