What is Shandu
Shandu is an open-source AI research automation tool that combines LangChain and LangGraph technologies to automatically conduct multi-level information mining and analysis and generate structured research reports. Shandu's core features include recursive exploration, multi-engine search, intelligent web crawling, and report generation. Users can input a research topic through simple command-line operations and set depth and breadth parameters to quickly generate Markdown-format research reports with citations. It supports search engines such as Google and DuckDuckGo and can handle dynamically rendered web content, making it suitable for a variety of scenarios such as academic research, market intelligence, and technology exploration.
Shandu's main features
- Automated research: Users only need to input a research topic, and Shandu will automatically perform multi-level information mining and generate a detailed structured report.
- Recursive exploration: Through multiple rounds of iterative searching, it gradually digs deeper into hidden information to ensure the depth and breadth of the research.
- Multi-engine search: It supports mainstream search engines such as Google and DuckDuckGo, combined with web crawling technology, to obtain more comprehensive information.
- Intelligent web crawling: It can handle dynamically rendered web pages, extract key content, and avoid interference from irrelevant information.
- Report generation: It organizes research results into Markdown-format reports, including citations and links, making it easy for users to read and share.
- Flexible parameter settings: Users can adjust the depth of the research (recursion levels) and breadth (number of search results per level) according to their needs, adapting to different research scenarios.
- Fast AI search: It provides a quick Q&A function, suitable for instant answers to simple questions.
Shandu's technical principles
- LangChain technology: LangChain is a framework for building language model applications. By combining language models with external data sources (such as search engines, documents, etc.), it enables efficient retrieval and analysis of information.
- LangGraph technology: LangGraph may be used to build knowledge graphs, storing and analyzing data through graph structures to help Shandu find associations and logical relationships in complex information.
Shandu's project address
- Github repository：https://github.com/jolovicdev/shandu
Shandu's application scenarios
- Academic research: Shandu can help researchers quickly collect and organize large amounts of literature and materials, generate structured research reports, and improve research efficiency.
- Market analysis: Through multi-engine search and recursive exploration, Shandu can dig into industry trends, competitor information, and more, providing data support for market analysis.
- Technology exploration: For emerging technologies or complex technical issues, Shandu can quickly generate research reports in related fields, helping users quickly understand the technical background and development.
- Content creation: Shandu can provide background information and creative inspiration for content creators, assisting in the generation of high-quality content through fast searching and organizing of materials.
- Education and learning: In the field of education, Shandu can provide students and teachers with rapid knowledge organization and learning material arrangement, helping them quickly master new knowledge.