easy-dataset
A powerful tool for creating datasets for LLM fine-tuning, RAG, and evaluation
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Decision brief
Easy-dataset is a JavaScript-based tool designed to simplify the creation and management of datasets for LLM fine-tuning, RAG systems, and evaluations.
Good fit when
- - You prefer using JavaScript, as Easy-Dataset leverages this language for its setup.
- - Your workflows include both local deployment options and Docker containerization, ensuring flexibility in setup environments.
Avoid when
- - When you require a multi-language support beyond JavaScript, as Easy-Dataset is specifically built with JavaScript in mind.
- - In cases where you do not want to use automatic initialization of databases or prefer manual setup configurations.
Observed Jul 11, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Slowing (108d since push)
- As of 2d
- Provenance
- Not a fork · Personal account
- As of 2d
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
npm install easy-datasetHow it fits your stack(7)
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
easy-dataset is a JavaScript-based tool designed to facilitate the creation of datasets used in various stages of AI model development such as fine-tuning large language models (LLM), Retrieval-Augmented Generation (RAG) systems, and evaluation processes. It provides both local setup and Docker image options for quick deployment.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Aug 18, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Aug 18, 2026
- CLI
- CLI entrypoint
Source: package.json:bin|scripts · Aug 18, 2026
- MCP server
- No MCP server detected
Source: repo_scan · Aug 18, 2026
- Languages
- javascript
Source: github.language+package.json · Aug 18, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Tags
README
Install with NPM
- Clone the repository:
git clone https://github.com/ConardLi/easy-dataset.git
cd easy-dataset
- Install dependencies:
npm install
- Start the development server:
npm run build
npm run start
- Open your browser and visit
http://localhost:1717
Using the Official Docker Image
- Clone the repository:
git clone https://github.com/ConardLi/easy-dataset.git
cd easy-dataset
- Modify the
docker-compose.ymlfile:
services:
easy-dataset:
image: ghcr.io/conardli/easy-dataset
container_name: easy-dataset
ports:
- '1717:1717'
volumes:
- ./local-db:/app/local-db
- ./prisma:/app/prisma
restart: unless-stopped
Note: It is recommended to use the
local-dbandprismafolders in the current code repository directory as mount paths to maintain consistency with the database paths when starting via NPM.
Note: The database file will be automatically initialized on first startup, no need to manually run
npm run db:push.
- Start with docker-compose:
docker-compose up -d
- Open a browser and visit
http://localhost:1717
License
This project is licensed under the AGPL 3.0 License - see the LICENSE file for details.
For agents
This page has a .md twin and JSON over the API.