$ loading_
Search local PDF and EPUB files conceptually with RAG-enhanced understanding.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "concept-rag" yet — see the docs or source repo.
Run a conceptual search across my local PDF and EPUB files for “sustainable supply chain,” identify related concepts and key documents, and summarize the main points from each source.
A list of related concepts, matched documents, and concise summaries to quickly understand the topic landscape.
Using my local document library, search for the concept of “privacy protection in federated learning,” cluster relevant papers by theme, and explain the differences and representative works in each group.
The output includes themed literature groups, concept relationships, and notes on representative papers.
Search my EPUB study materials for concepts related to “opportunity cost” and “marginal effect,” find the most relevant chapters, and explain their relationship in simple terms.
It provides the most relevant chapters, concept links, and easy-to-understand explanations of the key ideas.
Convert PDFs to Markdown and query them with AI, sources, and confidence scores.
Ingest PDFs, run semantic search, and answer questions with source citations.
Search and question PDF documents with Pinecone and local AI models.
Extract PDFs into Markdown, RAG chunks, and cited tables.
Search local knowledge packs and retrieve chunks for stronger AI answers.
Semantically search Confluence pages and return chunks, citations, and bundled results.