openkb

📢 Recent Updates

• Google Open Knowledge Format (OKF): Wiki pages follow the Google OKF specification for knowledge sharing.
• Entity Pages: People, orgs, places, and products as dedicated wiki pages, auto-extracted and kept in sync.

---

📑 What is OpenKB

OpenKB (Open Knowledge Base) is an open-source system (in CLI) that compiles raw documents into a structured, interlinked wiki-style knowledge base using LLMs, powered by PageIndex's vectorless, reasoning-based retrieval for long documents.

The idea is based on a concept described by Andrej Karpathy: LLMs generate summaries, concept pages, and cross-references, all maintained automatically. Knowledge compounds over time instead of being re-derived on every query.

Why not traditional RAG?

Traditional RAG rediscovers knowledge from scratch on every query. Nothing accumulates. OpenKB compiles knowledge once into a persistent wiki, then keeps it current. Cross-references already exist, contradictions are flagged, and synthesis reflects everything consumed.

OpenKB has two layers: a wiki foundation that compiles and maintains your knowledge, and generators (query / chat / Skill Factory) that turn it into useful output. See Usage for the full command list.

Features

• Broad format support: PDF, Word, Markdown, PowerPoint, HTML, Excel, CSV, text, URLs, and more.
• Scales to long documents: Long and complex documents are handled via PageIndex tree indexing, enabling accurate, vectorless, context-aware retrieval.
• Native multi-modality: Retrieves and understands figures, tables, and images, not just text.
• Compiled wiki: The LLM compiles your documents into summaries, concept pages, entity pages, and cross-links, all kept in sync.
• Query & chat: One-off questions or multi-turn conversations over your wiki, with persisted sessions to resume.
• Skill Factory: Distills redistributable agent skills from your wiki.
• OKF-ready: Wiki pages follow the Google OKF specification for knowledge sharing.
• Obsidian-compatible: The wiki is plain .md files with cross-links. Opens in Obsidian for graph view.

🚀 Getting Started

Install

pip install openkb

Other install options:

• Latest from GitHub:

  pip install git+https://github.com/VectifyAI/OpenKB.git
  

• Install from source (editable, for development):

  git clone https://github.com/VectifyAI/OpenKB.git
  cd OpenKB
  pip install -e .
  

Quick Start

# 1. Create a directory for your knowledge base
mkdir my-kb && cd my-kb

# 2. Initialize the knowledge base
openkb init

# 3. Add documents
openkb add paper.pdf
openkb add ~/papers/                            # Add a whole directory
openkb add https://arxiv.org/pdf/2509.11420     # Or fetch from a URL

# 4. Ask a question
openkb query "What are the main findings?"

# 5. Or chat interactively
openkb chat

# (Optional) Turn the wiki into other outputs
openkb skill new my-expert "Reason like an expert on <your-topic>"   # a portable agent skill
openkb visualize                                                     # an interactive knowledge graph
openkb deck new my-deck "An intro deck on <your-topic>"              # slides — a single-file HTML deck

Set up your LLM

OpenKB supports multiple LLM providers (OpenAI, Claude, Gemini, etc.) via LiteLLM (pinned to a safe version).

Set your model during openkb init or in .openkb/config.yaml using the provider/model LiteLLM format (e.g. anthropic/claude-sonnet-4-6). OpenAI models can omit the prefix (e.g. gpt-5.4).

Create a .env file with your LLM API key:

LLM_API_KEY=your_llm_api_key

🧩 How OpenKB Works

Architecture