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emcf/thepipe

Get clean data from tricky documents, powered by vision-language models ⚡ observed · 2026-10-13

github.com/emcf/thepipe · homepage · Python · MIT (permissive) observed · 2026-10-13

Health v2 · maintenance only

80/100

  • Activity 97
  • Release rhythm 65
  • Longevity 67
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 943
  • days_rel: 23
  • days_push: 23
  • n_releases_24m: 1

Full methodology

Adoption not part of the score

1529 stars · 99 forks observed · 2026-10-13

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

thepipe is a Python package and API that extracts clean markdown, multimodal media, and structured data from tricky documents like PDFs, Word docs, webpages, videos, and audio, using vision-language models under the hood. It integrates out-of-the-box with LLMs, vector databases, and RAG frameworks, and can be self-hosted or used via a hosted cloud API.

Use cases

  • extract clean markdown from complex pdfs
  • parse tables and figures from word documents for llms
  • scrape webpages into structured data for rag pipelines
  • chunk documents for vector databases like chromadb
  • convert pdfs to or csv with vision-language models
  • transcribe and extract data from audio and video files
  • build an ai document etl pipeline for ingestion

When to choose

  • you need high-quality extraction from messy or complex document layouts
  • you want multimodal extraction including images, tables, video, and audio
  • you need output ready for LLMs, vector databases, or RAG frameworks
  • you want a self-hosted, on-prem or air-gapped document pipeline

When to avoid

  • you only need simple plain-text extraction from well-structured documents without AI overhead
  • you cannot use external VLM APIs and lack GPU hardware for local models
  • you need a lightweight CPU-only parser with no optional heavy dependencies

Facets

library · maturity active

web-scraping ocr pdf etl rag nlp machine-learning parser data-generation large-language-models pdf artificial-intelligence developer-tools files python cross-platform self-hosted vision-language-models document-extraction multimodal markdown-conversion structured-data-extraction chunking vector-database-integration document-parsing retrieval-augmented-generation natural-language-processing data-engineering web-server

2 sources

Member repositories

RepositoryRoleHealth v2
emcf/thepipemain80

For agents

markdown · JSON · MCP: product_card(name="emcf/thepipe")

Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem