Personal Knowledge Base (RAG)

Overview

Build your personal research library by simply sharing links with your agent. It fetches content, extracts key information, generates embeddings, and makes everything searchable. Ask questions in natural language and get answers synthesized from your entire knowledge base with source citations.

Benefits

• Effortless knowledge capture—just share links
• Semantic search finds relevant content by meaning, not keywords
• AI-generated summaries and insights across sources
• Perfect for research, learning, and competitive intelligence

Requirements

• Web scraping capability for content extraction
• Vector database (Pinecone, Weaviate, or local)
• Messaging app for link sharing (Slack, Telegram, SMS)

Technical Details

Fetches and parses URLs, generates embeddings using OpenAI or local models, stores in vector database. Hybrid search combines semantic (vector) and keyword (BM25) retrieval. RAG pipeline generates answers with source attribution. Supports PDF, Twitter threads, YouTube transcripts, and web articles.