ck-unifr/pdf_parsing
PDF解析（文字，章节，表格，图片，参考），基于大模型(ChatGLM2-6B, RWKV)+langchain+streamlit的PDF问答，摘要，信息抽取
This tool helps researchers and analysts quickly make sense of large PDF documents. It takes a PDF document as input and breaks it down into its core components: text (including titles and sections), images, tables, and references. The output is structured data—text, image files, CSVs, and structured reference information—making it easier to analyze, summarize, and extract key insights. Anyone who regularly processes research papers, reports, or other complex PDF documents can benefit from this.
211 stars. No commits in the last 6 months.
Use this if you need to systematically extract, structure, and understand the content within PDF documents, especially for tasks like summarizing, answering questions, or extracting detailed reference information.
Not ideal if you primarily need to extract content from highly complex or irregularly formatted tables and charts, as these areas are still undergoing active development and improvement.
Stars
211
Forks
33
Language
Python
License
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Category
Last pushed
Oct 17, 2023
Commits (30d)
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