Master 4.0 (#2210)

* 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>

crazy_functions/review_fns/prompts/crossref_prompts.py

@@ -0,0 +1,55 @@
+# Crossref query optimization prompt
+CROSSREF_QUERY_PROMPT = """Analyze and optimize the query for Crossref search.
+
+Query: {query}
+
+Task: Transform the natural language query into an optimized Crossref search query.
+Always generate English search terms regardless of the input language.
+
+IMPORTANT: Ignore any requirements about journal ranking (CAS, JCR, IF index), 
+or output format requirements. Focus only on the core research topic for the search query.
+
+Available search fields and filters:
+1. Basic fields:
+   - title: Search in title
+   - abstract: Search in abstract
+   - author: Search for author names
+   - container-title: Search in journal/conference name
+   - publisher: Search by publisher name
+   - type: Filter by work type (journal-article, book-chapter, etc.)
+   - year: Filter by publication year
+
+2. Boolean operators:
+   - AND: Both terms must appear
+   - OR: Either term can appear
+   - NOT: Exclude terms
+   - "": Exact phrase match
+
+3. Special filters:
+   - is-referenced-by-count: Filter by citation count
+   - from-pub-date: Filter by publication date
+   - has-abstract: Filter papers with abstracts
+
+Examples:
+
+1. Query: "Machine learning in healthcare after 2020"
+<query>title:"machine learning" AND title:healthcare AND from-pub-date:2020</query>
+
+2. Query: "Papers by Geoffrey Hinton about deep learning"
+<query>author:"Hinton, Geoffrey" AND (title:"deep learning" OR abstract:"deep learning")</query>
+
+3. Query: "Most cited papers about transformers in Nature"
+<query>title:transformer AND container-title:Nature AND is-referenced-by-count:[100 TO *]</query>
+
+4. Query: "Recent BERT applications in medical domain"
+<query>title:BERT AND abstract:medical AND from-pub-date:2020 AND type:journal-article</query>
+
+Please analyze the query and respond ONLY with XML tags:
+<query>Provide the optimized Crossref search query using appropriate fields and operators</query>"""
+
+# System prompt
+CROSSREF_QUERY_SYSTEM_PROMPT = """You are an expert at crafting Crossref search queries.
+Your task is to optimize natural language queries for Crossref's API.
+Focus on creating precise queries that will return relevant results.
+Always generate English search terms regardless of the input language.
+Consider using field-specific search terms and appropriate filters to improve search accuracy."""