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LanceDB Node.js Vector Search

by vurtnec

Data/DatabasesLanceDBNode.jsVector SearchOllamaEmbeddingsSimilarity Search

A Node.js implementation for vector search using LanceDB and Ollama's embedding model. It demonstrates how to connect to LanceDB, create custom embedding functions, and perform vector similarity searches.

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What is LanceDB Node.js Vector Search?

This project is a Node.js implementation for performing vector similarity searches using LanceDB as the vector database and Ollama to generate embeddings for text data.

How to use LanceDB Node.js Vector Search?

  1. Clone the repository. 2. Install dependencies using pnpm install. 3. Ensure Ollama is running locally with the nomic-embed-text model. 4. Configure the LanceDB path and Ollama API endpoint if necessary. 5. Run the vector search test script using pnpm test-vector-search or node test-vector-search.js. To integrate with Claude Desktop as an MCP service, add the provided configuration to your MCP configuration JSON, adjusting the paths to your installation.

Key features of LanceDB Node.js Vector Search

  • Connects to LanceDB database

  • Creates custom embedding functions using Ollama

  • Performs vector similarity search

  • Processes and displays search results

  • Includes a custom OllamaEmbeddingFunction

Use cases of LanceDB Node.js Vector Search

  • Semantic search

  • Question answering systems

  • Document retrieval

  • Recommendation systems

FAQ from LanceDB Node.js Vector Search

What is LanceDB?

LanceDB is a serverless vector database for AI applications.

What is Ollama used for?

Ollama is used to generate text embeddings, which are numerical representations of text used for similarity search.

What are the prerequisites for running this project?

Node.js (v14 or later), Ollama running locally with the nomic-embed-text model, and a LanceDB storage location with read/write permissions.

How do I install the dependencies?

Run pnpm install in the project directory.

How do I run the vector search example?

Run pnpm test-vector-search or node test-vector-search.js.