# Libingest

> libingest - Document ingestion pipeline. IngestPipeline orchestrates configurable transformation steps. IngestStep defines individual processors like pdf-to-images, images-to-html, extract-context, annotate-html. Converts PDF, PowerPoint, images to Schema.org annotated HTML. Use for document processing, knowledge extraction, and content transformation.

- Skill: `majiayu000/libingest` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add majiayu000/libingest`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/libingest/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Web & Frontend
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/majiayu000/libingest

---


# libingest Skill

## When to Use

- Converting PDF documents to structured HTML
- Processing PowerPoint presentations for indexing
- Extracting semantic content from images via OCR
- Building document ingestion pipelines

## Key Concepts

**IngestPipeline**: Orchestrates a sequence of transformation steps defined in
config/ingest.yml.

**IngestStep**: Individual processing step (pdf-to-images, images-to-html,
extract-context, annotate-html, normalize-html).

## Usage Patterns

### Pattern 1: Run ingestion via CLI

```bash
# Drop files in data/ingest/in/
cp document.pdf data/ingest/in/

# Run pipeline
make ingest
```

### Pattern 2: Programmatic ingestion

```javascript
import { IngestPipeline } from "@copilot-ld/libingest";

const pipeline = new IngestPipeline(config, storage, llmClient);
const result = await pipeline.process("document.pdf");
// result.output points to final HTML
```

## Integration

Configured via config/ingest.yml. Uses libllm for vision processing. Output
stored in data/ingest/pipeline/.