emcf/thepipe

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1524 stars · 99 forks observed · 2026-08-28

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

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