unstructured-ingest
Local ETL data pipeline to get data RAG ready
What it is and what it does
Unstructured Ingest is a Python package that runs as a local ETL pipeline designed to take raw, unstructured documents and prepare them for use in AI systems, particularly retrieval-augmented generation (RAG) applications. It handles the work of ingesting documents and transforming them into clean, structured formats that downstream AI models can consume.
The package depends on a lean set of runtime libraries: pydantic for data validation, click for CLI support, tqdm for progress indication, opentelemetry-sdk for observability, ijson for JSON streaming, certifi for SSL certificates, and python-dateutil for date handling. It supports Python 3.11, 3.12, and 3.13, and is currently in Beta status with active maintenance.
Use it for:
- Ingest a folder of documents and transform them into text chunks for a vector database.
- Build a preprocessing step in a RAG pipeline that normalizes documents from multiple sources.
- Extract structured content from unstructured documents before feeding them to a language model.
- Automate local document processing workflows without relying on external APIs.
- Prepare datasets by cleaning and standardizing raw document collections.
Worth the install?
AI-flagged interpretation of the facts on this page — verify before relying
Unstructured Ingest is a local ETL pipeline that prepares unstructured data for retrieval-augmented generation (RAG) and other AI workflows by ingesting and transforming raw documents into structured, ready-to-use formats.
Yes, if you need to prepare unstructured documents for AI/RAG workflows locally. The package is actively maintained, has low install friction, carries a permissive Apache-2.0 license, and depends on stable, lightweight libraries. No known vulnerabilities as of 2026-08-14. The main uncertainty is whether its supported document formats and transformation capabilities match your specific use case.
Install
unstructured-ingest on PyPI
pip
pip install unstructured-ingestuv
uv add unstructured-ingestpoetry
poetry add unstructured-ingestInstalling unstructured-ingest
Before you install
Low install friction with a pure-Python wheel distribution. Active maintenance with a release on 2026-08-14. Runtime dependencies are all well-established libraries, suggesting a stable, dependency-light setup.
License in practice
Apache-2.0 is a permissive open-source license. You can use, modify, and distribute this package freely in commercial and private projects, provided you include a copy of the license and state significant changes.
Quickstart
pip install unstructured-ingest
from unstructured_ingest import ...
# See documentation for specific ingestion and transformation workflows
Requires Python 3.11 or later (supports 3.11, 3.12, 3.13)
Verify before relying
- What document formats (PDF, Word, HTML, etc.) does the ingestion pipeline actually support?
- Does the package require external services or APIs, or does it run entirely locally?
- What is the typical performance or throughput for document ingestion and transformation?
Package facts
| License | Apache-2.0 (permissive) |
| Python support | supports the current Python release (<3.14,>=3.11) |
| Install friction | low — pure-Python wheel |
| Runtime dependencies | 7 — certifi, click, ijson, opentelemetry-sdk, pydantic, python-dateutil, tqdm |
| Maintenance | actively maintained — 0 days since the last release |
| First released | |
| Downloads | 620,054/month — #5,727 on PyPI (30-day window, as of 2026-08-14) |
| Known vulnerabilities | none known (OSV.dev, checked 2026-08-14) |
Evidence: unstructured_ingest-1.9.3-py3-none-any.whl
Tags
More Artificial Intelligence packages
LiteLLM provides a unified Python interface to…
permissive · top 100 on PyPI
huggingface-hubClient library and CLI tool for downloading,…
permissive · top 100 on PyPI
langchainLangChain provides a framework for building…
permissive · top 1,000 on PyPI
hf-xethf-xet provides chunk-based deduplication and…
permissive · top 1,000 on PyPI
tokenizersTokenizers converts raw text into token…
permissive · top 1,000 on PyPI
transformersTransformers provides a unified framework for…
permissive · top 1,000 on PyPI
ingestringestr is a command-line tool that copies data…
permissive · top 15,000 on PyPI
openmetadata-ingestionOpenMetadata Ingestion is a framework for…
unclear · top 15,000 on PyPI
unstructuredIngests and pre-processes unstructured…
permissive · top 5,000 on PyPI
langchain-unstructuredIntegrates LangChain with Unstructured to…
permissive · top 15,000 on PyPI
graphragGraphRAG extracts structured knowledge graphs…
permissive · top 15,000 on PyPI
nv-ingest-clientPython client library for submitting and…
permissive · top 15,000 on PyPI
unstructured-clientHTTP client SDK for the Unstructured Platform…
permissive · top 5,000 on PyPI
embedchainEmbedchain is a framework for building…
permissive · top 15,000 on PyPI
azure-ai-contentunderstandingExtracts structured content from documents,…
unclear · top 5,000 on PyPI
humiolibPython SDK that wraps Humio's web API to enable…
permissive · top 15,000 on PyPI