# wisupai/e2m

E2M converts various file types (doc, docx, epub, html, htm, url, pdf, ppt, pptx, mp3, m4a) into Markdown. It’s easy to install, with dedicated parsers and converters, supporting custom configs. E2M offers an all-in-one, flexible, and open-source solution.

Repository: https://github.com/wisupai/e2m
Canonical: https://ross.abutalabs.com/products/e2m
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Topics: doc2x, llm, markdown, text-cleaning, e2m, pdf-to-markdown
Last push: 2024-09-08T08:18:11+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 54
- inputs: {"age_days": 759, "days_push": 724, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1294, forks 74 (observed 2026-08-28T04:04:16.307307+00:00)

## What it is
E2M is a Python library that parses and converts many file types (doc, docx, epub, html, url, pdf, ppt, pptx, mp3, m4a) into Markdown using a parser-converter architecture. It aims to produce high-quality text data for RAG pipelines and model training or fine-tuning.

## Use cases
- convert pdf to markdown
- convert docx and pptx files to markdown for llm training
- prepare clean text data for rag pipelines
- extract text from epub and html into markdown
- transcribe mp3 audio files to markdown text
- batch convert documents for fine-tuning datasets

## When to choose
- you need a single Python library that handles many document formats as input
- you want configurable parsers and converters for markdown output
- you are building RAG or fine-tuning data pipelines from mixed file sources

## When to avoid
- you only need one specific format and a lighter single-purpose converter
- you need a polished GUI application rather than a library
- you require battle-tested enterprise-grade document conversion at scale

## Facets
- artifact type: library
- maturity: active
- function: parser, pdf, ocr, speech-recognition, llm-inference, rag
- domain: pdf, files, large-language-models, developer-tools
- platform: python, cli, cross-platform
- tags: markdown-conversion, document-parsing, file-converter, data-preparation, fine-tuning-data, natural-language-processing, retrieval-augmented-generation

## Member repositories
- wisupai/e2m (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:16.307307+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:54:06.941315+00:00, confidence not recorded.
  - readme: https://github.com/wisupai/e2m (fetched 2026-08-28T04:04:16.307307+00:00, sha ac050e249d10)
- Data as of 2026-08-30T08:39:29.467469+00:00.