LanceDB integration

What the LanceDB package does

Store and search embeddings in LanceDB - the embedded vector database. Works against a local directory, S3/GCS/Azure object storage or LanceDB Cloud. Vector, full-text and hybrid search, SQL filters, upserts, indexing, plus a Toolkit that hands the whole database to an AI agent.

Namespace

Robomotion.LanceDB

Latest version

0.1.0

Written in

Python

Categories

DatabaseArtificial Intelligence

LanceDB nodes (16)

These are the node IDs an agentic flow or an RPA bot uses, exactly as they appear in the Flow Designer and in flow code. The Toolkit node hands an agent several of the package operations at once.

Platforms

The LanceDB package runs on Windows, macOS and Linux robots. Any Robomotion robot on these operating systems can run a flow that uses it.

How to install the LanceDB package

1. Open Packages in the Robomotion Flow Designer.
2. Search for LanceDB or Robomotion.LanceDB, then click Install on its card.
3. The LanceDB nodes appear in the node palette for everyone in the workspace, because installation is per workspace.

From a terminal, the Robomotion CLI installs the same package:

robomotion install Robomotion.LanceDB

Templates that use LanceDB

One ready-made template uses LanceDB nodes in their flows. Open one to start from a working flow.

• RAG with DeepSeek

  Retrieval-augmented generation over your own documents, with the retrieval handed to the agent instead of done for it. Documents are read, chunked, embedded and stored in LanceDB - an embedded vector database that is just a directory on disk. A DeepSeek Agent then answers questions through a search_knowledge tool built from ordinary flow nodes, writing its own queries and searching as many times as a question needs, with the source document named against every fact.

Related integrations

Packages that share a category or keywords with LanceDB. It is filed under Database and Artificial Intelligence.

• QdrantConnect to Qdrant vector database for similarity search, embeddings storage, and vector operations
• Knowledge BaseQuery Robomotion Knowledge Bases from flows. Hybrid (vector + keyword) retrieval over locally cached sqlite-vec indexes, an optional Rerank node (Cohere / Voyage AI / Jina), plus a Knowledge Toolkit for Hermes agents. The same binary doubles as the ingestion worker used by robomotion-agent.
• PineconeProvides a simple interface to access the Pinecone API, Pinecone's vector database is fully-managed, developer-friendly, and easily scalable.
• Document ProcessorParse and process documents for RAG applications. Supports PDF, DOCX, PPTX, TXT, HTML, Markdown and more. Extract text, chunk content for embeddings.
• PerplexityConnect to Perplexity AI for AI-powered search and chat completions with real-time web data
• TavilyAI-powered web search, content extraction, crawling, and site mapping with Tavily API