by Rio Fujita 1 (0 reviews)

RiTriever

Name: RiTriever
Author: Rio Fujita

Adds RAG-style vector retrieval to WordPress search using native database vector indexes and configurable embeddings.

RiTriever ranks #50,294 among WordPress.org plugins with 1+ active installations, a 1/5 rating from 0 reviews, and was last updated Jul 3, 2026. Data from WordPress.org, refreshed twice daily — see methodology.

Tested up to WP 7 (Current: 7.1.2)

v0.2.3 Current Version v0.2.3

Updated 2 months ago Last Update on 03 Jul, 2026

Refreshed 7 hours ago Last Refreshed on

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Rank

#50,294

— No change

Active Installs

— No change

KW Avg Position

78.5

0.7 worse

Downloads

214

+2 today

Support Resolved

— No change

Rating

20%

Review 1 out of 5

1 (0 reviews)

Next Milestone 10

Total Progress 30%

0+ 10+

49,594

Ranks to Climb

Growth Needed

8,000,000

Active Installs

Pro

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Rank Changes

Current #50,294

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Active Installs Growth

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Active Installs 0,000,000+

Growth +0.0%

Peak 0,000,000

Downloads Growth

Downloads

Growth

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Reviews & Ratings

1.0

0 reviews

Overall 20%

0 (0%)

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Plugin Details

Version: 0.2.3
Last Updated: Jul 03, 2026
Requires WP: 6.6+
Tested Up To: 7
PHP Version: 8.1 or higher
Author: Rio Fujita

Support & Rating

Rating: ★ ☆ ☆ ☆ ☆ 1
Reviews: 0
Support Threads: 0
Resolved: 0%

Keywords

embeddings rag search semantic search vector search

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Frequently Asked Questions

Common questions about RiTriever

OpenAI and Azure OpenAI are supported as external hosted embedding providers.

Yes. Ollama, LM Studio, Infinity, TEI, and Custom HTTP endpoints are available for local or self-hosted embeddings.

Only when an external embedding provider is configured. See the External services section for details.

Yes. MariaDB 11.7 or later is the primary supported target for native vector columns and indexes.

The vector table must be rebuilt. Run initialization again after changing target language, provider, model, dimensions, or vector distance settings.

RiTriever

Next Milestone 10

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