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@github-actions github-actions released this 13 May 21:49
v7.0.0
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v7.0.0: 🚀 Dual-Purpose Office Parser & Generator with Native RAG Suite

We are thrilled to announce the release of officeParser v7.0.0, a milestone version that redefines document processing for the AI era.

Since 2019, officeParser has been a trusted utility for simple text extraction. Today, we are evolving into a comprehensive document knowledge engine designed specifically for the next generation of AI-first infrastructure.

🌟 Key Pillars of the v7.0.0 Revolution

1. The Generation Revolution: OfficeGenerator

officeParser is now a dual-purpose engine. Beyond parsing, you can now generate high-fidelity outputs from the unified Office AST.

  • Universal Serialization: Transform any document into Markdown, HTML, CSV, RTF, or Layout-Aware Text.
  • The StyleMapper Engine: A new semantic translation layer that preserves formatting (bold, italic, colors, tables) across all output formats using a robust DSL.

2. The OfficeConverter & Fluent .to() API

v7.0.0 introduces OfficeConverter, our new flagship API for one-step document transformations.

  • Streamlined convert: A single method to go from any source file to any target format with automatic configuration sync.
  • Fluent AST Interface: The AST now features an asynchronous .to() method, allowing you to chain transformations effortlessly: await ast.to('markdown'), await ast.to('html'), or await ast.to('chunks').

3. Native AI/RAG Infrastructure

We’ve built the "Knowledge Bridge" required to turn messy, unstructured office files into high-precision data for your AI agents.

  • Native RAG Chunking Suite: No more external dependencies. Split documents using fixed-size (recursive), structural (hierarchy-aware), or semantic strategies.
  • Metadata-Aware: Every chunk retains its structural context, ensuring your Vector DB retrieval is more accurate than ever.

4. Unified Document Intelligence

  • New Parser Extensions: We now natively ingest CSV, HTML, and Markdown, treating them as first-class citizens in our unified Office AST.
  • Redesigned AST: Support for complex table structures (vertical/horizontal merging), nested lists, and format-specific metadata.

5. Engineering Excellence & Performance

  • Extreme Speedups: We eliminated $O(n^2)$ bottlenecks in RTF parsing and achieved up to 23x speedups in OpenOffice (ODP) processing.
  • Memory Efficiency: Re-engineered Excel parsing with matchAll iteration, preventing execution stalls on massive spreadsheets.
  • DOCX Fidelity: Full support for w:vMerge and w:gridSpan, ensuring table structures are preserved exactly as they appear in Word.

🛠 Getting Started

npm install officeparser

The new API makes complex transformations trivial:

const { parseOffice, convert } = require('officeparser');
// Option 1: One-step conversion (High-level)
// Convert any file to Markdown, HTML, CSV, etc. in one line.
const { value } = await convert('proposal.docx', 'md');
console.log(value); // The generated Markdown string
// Option 2: Parse once, convert many (Fluent API)
// Ideal for multi-format export or RAG chunking.
const ast = await parseOffice('data.xlsx');
const { value: html } = await ast.to('html');
const { value: chunks } = await ast.to('chunks');

🔗 Full Changelog: View v7.0.0 Details
🔗 Documentation & Visualizer: officeparser.harshankur.com

❤️ Supporting the Future of Document Infrastructure

Since 2019, officeParser has been maintained by a single person as a voluntary project, growing from a simple utility to a critical piece of infrastructure with over 10 million downloads and 300,000+ weekly installations.

As we pivot towards the "Super-Tool" era, I am seeking professional sustainability to fund the next phase of the roadmap:

  • Core Sustainability: Maintaining 100% test coverage and dependency health for my global user base.
  • Multi-Runtime Excellence: Official support and drivers for Bun, Deno, and Edge (Cloudflare Workers, Vercel).
  • Enterprise Connectivity: High-performance connectors for LangChain, LlamaIndex, and Haystack, alongside intelligent chart-to-JSON extraction.

If officeParser powers your production workflows or AI pipelines, please consider supporting its development:

👉 GitHub Sponsors
👉 Buy Me A Coffee

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