Documentation Index
Fetch the complete documentation index at: https://docs.lancedb.com/llms.txt
Use this file to discover all available pages before exploring further.
genkitx-lancedb
Genkit is an open-source framework for building end-to-end AI and RAG pipelines with a clean, TypeScript-first
developer experience. The genkitx-lancedb plugin lets you use LanceDB as a high-performance vector store
inside your Genkit flows, so you can index, search, and retrieve data efficiently as part of your AI
applications.
Installation
pnpm install genkitx-lancedb
Usage
Adding LanceDB plugin to your genkit instance.
You can run this app with the following command:
genkit start -- tsx --watch src/index.ts
Testing retrieval on a sample table
Let’s see the raw retrieval results
On running this query, you’ll get 5 results fetched from the lancedb table, where each result looks something like this:
Creating a custom RAG flow
Now that we’ve seen how you can use LanceDB in a Genkit pipeline, let’s refine the flow and create a RAG. A RAG flow will consist of an index and a retriever with its outputs postprocessed and fed into an LLM for final response
Creating custom indexer flows
You can also create custom indexer flows, utilizing more options and features provided by LanceDB.
In your console, you can see the logs
Creating custom retriever flows
You can also create custom retriever flows, utilizing more options and features provided by LanceDB.
Now using our retrieval flow, we can ask a question about the ingested PDF
