RAG

A RAG component for Convex to build AI-powered applications.

EmergingOpen SourceLow lock-in

Pricing

Free tier

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Aging · Jun 8, 2026

Overview

What is RAG?

This tool provides a Retrieval-Augmented Generation (RAG) component for the Convex framework, enabling developers to integrate AI-driven content retrieval and generation into their applications. It is essential for those looking to enhance their apps with intelligent data retrieval capabilities.

Key differentiator

The only open-source RAG component specifically designed to integrate with Convex, offering developers full control and flexibility.

Capability profile

Capability Radar

Ease of StartEcosystemValueMaturityFlexibilityScale Ready

Honest assessment

Strengths & Weaknesses

↑ Strengths

Seamless integration with Convex for RAG capabilitiesmedium

Flexible configuration options for data retrieval and generationmedium

Open-source, allowing customization and community contributionsmedium

↓ Weaknesses

Steep learning curve for non-Python developershigh

API requires Python-specific patterns, TypeScript SDK is community-maintained

Frequent breaking changes between versionsmedium

v0.1 to v0.2 migration required rewriting chain definitions

Limited integrations with other frameworks and platformshigh

Currently tightly coupled with Convex framework, making it difficult to integrate with other backend systems

Small community and slow issue resolutionmedium

GitHub repository has few contributors and issues take a long time to be addressed

Fit analysis

Who is it for?

✓ Best for

Teams building Convex-based applications who need RAG capabilities

Projects requiring customization and flexibility in their AI components

✕ Not a fit for

Developers looking for a fully managed service without self-hosting requirements

Projects that require real-time data processing beyond the scope of RAG

Cost structure

Pricing

Free Tier

Available

Open source — free to use

Starts at

$0

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Ecosystem

Relationships

Next step

Get Started with RAG

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →