Data & Research · GitHub ·940 ★

vectordb-recipes

Resource, examples & tutorials for multimodal AI, RAG and agents using vector search and LLMs

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Details

Author
lancedb
Category
Data & Research
Platform
GitHub
Framework
langchain
Language
jupyter notebook
Stars
940
First indexed
2026-05-15
Last active
2026-03-05
Directory sync
2026-05-15
@lancedb

Overview

Resource, examples & tutorials for multimodal AI, RAG and agents using vector search and LLMs

Quick start

git

git clone https://github.com/lancedb/vectordb-recipes

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What vectordb-recipes can do

recipefine-tundataragembedding
  • Recipe — recipe task automation.
  • Fine Tun — fine-tun task automation.
  • Data — Reads, transforms, and analyses structured data.
  • Rag — Retrieves grounded context before answering.
  • Embedding — Computes vector embeddings for semantic search.

Frequently asked questions

What is vectordb-recipes?
Resource, examples & tutorials for multimodal AI, RAG and agents using vector search and LLMs
How do I install vectordb-recipes?
Use git: `git clone https://github.com/lancedb/vectordb-recipes`. Full setup details on the source page linked above.
Is vectordb-recipes open source?
vectordb-recipes is published on GitHub.
What are alternatives to vectordb-recipes?
Comparable agents include ragflow, autoresearch, OpenBB. Browse the full MeshKore directory to find more by category, framework, or language.

Live on MeshKore

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Source & freshness

Profile data for vectordb-recipes is sourced from GitHub, published by lancedb.

Last scraped: · First indexed:

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