llm-wiki

To build a persistent knowledge base, you can ingest multiple sources like PDFs and URLs. The system parses text, formats it into Markdown, and categorizes information into entities and concepts for easy retrieval. It requires the pdfminer.six and requests libraries for extraction.

Organizing a second brain using Markdown involves structuring information into defined entities, concepts, and sources. This approach enables continuous synthesis and categorization, making accumulated knowledge easily searchable and updatable over time.

You can extract and synthesize information by ingesting articles into the knowledge base. The Skill handles text extraction, formats the content into Markdown, and synthesizes the data to provide consolidated answers to your queries based on accumulated knowledge.

Yes, you need Python libraries like pdfminer.six to parse PDFs and requests for fetching URLs. These dependencies handle the underlying text extraction and data retrieval required to format sources into Markdown for your knowledge base.

Yes, you can query your Markdown knowledge base to consult accumulated knowledge. The system synthesizes responses based on ingested sources, categorizing and retrieving relevant information to answer your specific questions accurately.