Overview
PandaWiki, developed by Chaitin, is an open-source knowledge base system that leverages large models to help teams quickly build intelligent centers for documentation, FAQs, and blogs. It supports multi-source ingestion from web pages, RSS, and files, and provides high-quality QA and semantic search via vector retrieval and RAG pipelines.
Key features
- Multi-source ingestion and format compatibility: bulk import and parse Markdown, HTML, Word, PDF and other common document formats.
- Model-driven retrieval: vector indexing with context stitching for retrieval-augmented generation and semantic search.
- Embeddable and extensible: frontend plugins and SDKs make it easy to integrate the knowledge base into websites or chatbots.
Use cases
- Organize product documentation, FAQs and blog content into an intelligent knowledge base to improve self-service.
- Build internal knowledge discovery and QA systems to reduce repetitive communication overhead.
- Provide intelligent assistance for customer support, training and documentation through search and QA.
Technical notes
- Implementation uses TypeScript and Go components, designed for containerized deployment and CI integration.
- Supports vector indexes, configurable RAG pipelines and easy integration with external models and vector databases.