Practical overview
When it fits
Use Ragctl when the task is document ingestion and chunk preparation before retrieval in a RAG system, especially when you want a terminal-based workflow for individual files or batches.
Who it is for
- Developers preparing document collections for a RAG application.
- Teams that need command-line batch processing and configurable document chunking.
- Builders who want to evaluate chunking strategies before using prepared data downstream.
Documented uses
- Extract text from supported office files, PDFs, web documents and images.
- Apply OCR to scanned documents and create chunks using semantic, sentence or token-based strategies.
- Batch-process a directory and export chunks as JSON, JSONL or CSV.
- Send chunks to Qdrant or compare chunking strategies using documented evaluation metrics.
Requirements & limits
The README documents installation through PyPI with pip or from source with an editable pip install. The repository lists an MIT license and describes the project as beta.
- The README specifies Python 3.10 or later.
- Supported formats listed include PDF, DOCX, ODT, TXT, HTML, Markdown, JPEG and PNG.
- Chunking choices include semantic, sentence and token strategies, with configurable token limits and overlap.
- Exports include JSON, JSONL and CSV; direct Qdrant ingestion is also documented.
- The README describes automatic retry, run history, and batch error-handling modes.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Install Ragctl from PyPI
Install the CLI and check that its version command is available.
Before you start
- Python 3.10 or later, as specified in the README.
- A terminal with pip available.
Steps
Run the command below.
pip install ragctlRun
ragctl --versionto check the installed command.
Expected outcome
Ragctl is installed from PyPI and the README’s version check can be run.
Guide limitations
- This guide covers installation and the version check only; it does not process a document.
- The repository describes the project as beta.
Chunk a document and export the result
Create an output file of chunks from a supported document.
Before you start
- Ragctl installed in a Python 3.10-or-later environment.
- A source file in a documented format, such as PDF, DOCX, TXT, HTML, Markdown, JPEG or PNG.
Steps
Choose a source document, for example
report.pdf.Run
ragctl chunk report.pdf -o report_chunks.json.For scanned documents, use the documented OCR option, such as
ragctl chunk scanned.pdf --advanced-ocr -o chunks.json.
Expected outcome
The command is configured to save chunk output as JSON; the OCR example applies OCR processing to a scanned PDF.
Guide limitations
- The README documents JSON, JSONL and CSV exports, but this recipe uses the shown JSON example.
- The OCR command does not document a separate OCR installation procedure.
Compare options for Retrieval-augmented applications
These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.
| Project | Documented purpose | Platform | Access and requirements |
|---|---|---|---|
| Ragctl | Extract text from supported office files, PDFs, web documents and images. | CLI | The README documents installation through PyPI with pip or from source with an editable pip install. The repository lists an MIT license and describes the project as beta. |
| Langsearch | Crawl website or local data for a knowledge base. | CLI, Self-hosted, Server | |
| Hybrid Search Rag | Combine document retrieval and language-model generation in a configurable workflow. |
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 16 October 2026
- Original website title
- datallmhub/ragctl · Official homepage title · retained in its source language