VectorAdmin is a universal GUI and tool suite for managing vector databases, targeting developers and users who need to interact with and understand their vectorized data. It simplifies tasks like viewing, updating, deleting, copying, and migrating embeddings across different vector databases, aiming to provide a traditional database management experience for vector data.

How It Works

The project is a full-stack monorepo comprising a Flask-based document-processor for parsing and embedding, a Node.js/Express backend for database management, a ViteJS/React frontend for user interaction, and InngestJS workers for background tasks. This architecture allows for a comprehensive, multi-user interface that can be self-hosted via Docker, offering a unified experience for managing diverse vector databases.

Quick Start & Requirements

• Install/Run: Recommended via Docker: docker run mintplex/vector-admin
• Prerequisites: Node.js, Yarn, Python 3.9+, OpenAI API key, and access to Pinecone.io or a running ChromaDB instance.
• Setup: Docker setup is described as "minutes." Development setup involves multiple yarn and python commands.
• Docs: Docs

Highlighted Details

• Multi-user instance support and oversight.
• Atomic view, update, and delete of individual text chunks.
• Copy entire documents or namespaces without re-embedding.
• Upload and embed new documents directly.
• Migrate entire vector databases between types or instances.

Maintenance & Community

The project is no longer actively maintained by Mintplex Labs, with focus shifted to AnythingLLM. While the repo remains available and functional for many providers, breaking changes from provider updates are possible. New issues and PRs may be reviewed.

Licensing & Compatibility

The README does not explicitly state a license. Compatibility for commercial use or closed-source linking is not specified.

Limitations & Caveats

The project is not actively maintained, meaning potential breaking changes from external provider updates are unaddressed. Features marked "still in progress" (e.g., permission management, cloud deployment readiness, automated regression testing, full API/LangChain integration) may not be fully implemented or stable.