kb-ingest

Automating raw document ingestion into structured wiki pages requires orchestrating a multi-agent pipeline to extract concepts, analyze claims, and apply edits to pending items. This process generates detailed reports on processed sources, created pages, and flagged contradictions.

The best way to process pending items in a knowledge base is using a multi-agent pipeline that extracts concepts and analyzes claims. This automated approach applies edits directly to structured wiki pages while tracking processed sources and flagging any content contradictions.

A multi-agent pipeline handles knowledge base updates by sequentially extracting concepts, analyzing claims, and applying edits to raw materials. It converts unstructured documents into structured wiki pages and generates a final report detailing sources and identified issues.

You need access to raw knowledge base materials and the ability to read and write to wiki pages. The ingestion pipeline processes pending raw items, updates existing structured pages, or creates new ones while producing a detailed summary of all modifications.

When automated ingestion encounters contradictions in raw knowledge base materials, the pipeline flags these issues in a final detailed report. This report summarizes the number of processed sources, updated pages, and specific content conflicts requiring manual review.

You can use kb-ingest to generate detailed reports on processed knowledge base sources. After orchestrating the extraction and analysis of pending items, it produces a final summary detailing the number of pages created, updated, and any flagged contradictions.