{"data":{"slug":"conardli-easy-dataset","name":"easy-dataset","tagline":"A powerful tool for creating datasets for LLM fine-tuning, RAG, and evaluation","github_url":"https://github.com/ConardLi/easy-dataset","owner":"ConardLi","repo":"easy-dataset","owner_avatar_url":"https://avatars.githubusercontent.com/u/30708545?v=4","primary_language":"JavaScript","stars":14792,"forks":1523,"topics":["dataset","fine-tuning","javascript","llm","rag"],"archived":false,"github_pushed_at":"2026-05-01T15:03:32+00:00","maintenance_label":"Slowing","stars_delta_30d":125,"url":"https://www.graphcanon.com/tools/conardli-easy-dataset","markdown_url":"https://www.graphcanon.com/tools/conardli-easy-dataset.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/conardli-easy-dataset","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=conardli-easy-dataset","description":"A powerful tool for creating datasets for LLM fine-tuning 、RAG and Eval","homepage_url":"https://docs.easy-dataset.com","license":"Other","open_issues":125,"watchers":66,"ai_summary":"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.","readme_excerpt":"### Install with NPM\n\n1. Clone the repository:\n\n```bash\n   git clone https://github.com/ConardLi/easy-dataset.git\n   cd easy-dataset\n```\n\n2. Install dependencies:\n\n```bash\n   npm install\n```\n\n3. Start the development server:\n\n```bash\n   npm run build\n\n   npm run start\n```\n\n4. Open your browser and visit `http://localhost:1717`\n\n---\n\n### Using the Official Docker Image\n\n1. Clone the repository:\n\n```bash\ngit clone https://github.com/ConardLi/easy-dataset.git\ncd easy-dataset\n```\n\n2. Modify the `docker-compose.yml` file:\n\n```yml\nservices:\n  easy-dataset:\n    image: ghcr.io/conardli/easy-dataset\n    container_name: easy-dataset\n    ports:\n      - '1717:1717'\n    volumes:\n      - ./local-db:/app/local-db\n      - ./prisma:/app/prisma\n    restart: unless-stopped\n```\n\n> **Note:** It is recommended to use the `local-db` and `prisma` folders in the current code repository directory as mount paths to maintain consistency with the database paths when starting via NPM.\n\n> **Note:** The database file will be automatically initialized on first startup, no need to manually run `npm run db:push`.\n\n3. Start with docker-compose:\n\n```bash\ndocker-compose up -d\n```\n\n4. Open a browser and visit `http://localhost:1717`\n\n---\n\n## License\n\nThis project is licensed under the AGPL 3.0 License - see the [LICENSE](LICENSE) file for details.","github_created_at":"2025-03-04T16:14:14+00:00","created_at":"2026-07-07T17:36:53.914293+00:00","updated_at":"2026-08-18T06:02:19.065178+00:00","categories":[{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"dataset","name":"dataset"},{"slug":"fine-tuning","name":"fine-tuning"},{"slug":"javascript","name":"javascript"},{"slug":"llm","name":"llm"},{"slug":"rag","name":"rag"}],"trust":{"provenance":{"is_fork":false,"github_id":942756187,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-18T06:02:17.996Z","maintenance":{"label":"Slowing","score":36,"methodology":"github_public_v1","releases_90d":0,"days_since_push":108,"last_release_at":"2026-04-09T13:08:33Z","stars_delta_30d":125,"open_issues_delta_30d":1},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:08:22.705Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"mcp":{"source":"repo_scan","observed_at":"2026-08-18T06:02:18.455Z","server_manifest":false},"scan":{"source":"repo_scan","observed_at":"2026-08-18T06:02:18.455Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-08-18T06:02:18.455Z","managed_saas":false},"has_cli":{"value":true,"source":"package.json:bin|scripts","observed_at":"2026-08-18T06:02:18.455Z"},"languages":{"value":["javascript"],"source":"github.language+package.json","observed_at":"2026-08-18T06:02:18.455Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-08-18T06:02:18.455Z"},"license_spdx":{"value":"Other","source":"github.license","observed_at":"2026-08-18T06:02:18.455Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["- 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.","- You need a tool that automatically initializes the database on first startup without manual intervention."],"when_not_to_use":["- 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.","- If your deployment environment strictly avoids Docker images and prefers alternatives for application containerization."],"source":"enrich:decision_facts","observed_at":"2026-07-11T15:08:18.836Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Easy-dataset is a JavaScript-based tool designed to simplify the creation and management of datasets for LLM fine-tuning, RAG systems, and evaluations."}]}}