Vector Retrieval and RAG · Public

korvus

Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.

Vector databaseRAGEmbeddingsSemantic searchData boundaries

Best fitDevelopers connecting knowledge bases, documents, or app data to semantic retrieval or RAG workflows.

Check whether this project matches your task before installing it.

What it can doVector database setup checks, embedding model boundaries, collection management, query acceptance, and deletion guidance

Review the portable capability path.

Before continuingVerify in a sandbox

Do not treat a preview pack as a proven local install.

GitHub snapshot1.5k stars

50 forks · 3 contributors

Doramagic.ai Last verification date: 2026-07-02 Verification method: source evidence, semantic profile, public page gate, and static build acceptance.

Official first step Read manual preview Source repository

Publication status · 2026-07-02

What is korvus?

korvus is a vector database, retrieval, or RAG storage component for AI applications.
Best fit: Developers connecting knowledge bases, documents, or app data to semantic retrieval or RAG workflows.
Not for: Not for one-off model API calls or environments that cannot isolate indexed data, credentials, and persistence paths.
Capability added to an AI workflow: Vector database setup checks, embedding model boundaries, collection management, query acceptance, and deletion guidance
First safe verification step: Verify create, query, delete, and rollback with a small public text sample before using real data.
Verification state: source, Quick Start, and sandbox install checks are recorded as passed.
Top risk: May increase setup, validation, or first-run risk for the user.
Evidence base: https://github.com/postgresml/korvus, https://github.com/postgresml/korvus#readme, Human Manual, Pitfall Log

Quick decision

Use this section to decide whether the project is worth a deeper read.

Best forDevelopers connecting knowledge bases, documents, or app data to semantic retrieval or RAG workflows.

Match the project to your task before installing it.

CapabilityVector database setup checks, embedding model boundaries, collection management, query acceptance, and deletion guidance

Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.

Repositorypostgresml/korvus

1.5k stars · 50 forks

What it can do

Translate the upstream project into concrete capabilities the user can judge before installing.

Overview and Getting Started

Related topics: System Architecture and Core Components, Multi-Language SDK Bindings and Examples

Source: https://github.com/postgresml/korvus / Human Manual

System Architecture and Core Components

Related topics: Overview and Getting Started, RAG Operations, Configuration, and Common Failure Modes

Source: https://github.com/postgresml/korvus / Human Manual

Multi-Language SDK Bindings and Examples

Related topics: Overview and Getting Started, System Architecture and Core Components

Source: https://github.com/postgresml/korvus / Human Manual

RAG Operations, Configuration, and Common Failure Modes

Related topics: System Architecture and Core Components, Multi-Language SDK Bindings and Examples

Source: https://github.com/postgresml/korvus / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

Sources: https://github.com/postgresml/korvus, Human Manual, Project Pack evidence, and downstream validation signals.

Community Discussion Evidence

Project-level external discussion stays visible on the detail page, not only inside the manual.

Stars1.5k stars

Forks50 forks

Contributors3 contributors

Licenseunknown

Community Discussion Evidence

12 source-linked items

Review these external discussions before using korvus with real data or production workflows. They are review inputs, not standalone proof that the project is production-ready.

01
Hi! My Korvus Cloud pipeline is stuck with a worker error (os error 11)
github / github_issue
02
6 rows with limit 6 and 0 rows with limit 5
github / github_issue
03
Multimodal RAG
github / github_issue
04
Exception: error returned from database: function pgml.transform(task =>
github / github_issue
05
Adding query support for edge runtimes
github / github_issue
06
FEAT add base url to model config
github / github_issue
07
Add TypeScript
github / github_issue
08
High gpu consumption
github / github_issue
09
Add documentation
github / github_issue
10
How to use Llama.cpp/OpenAI server endpoint?
github / github_issue
11
content must be a string
github / github_issue
12
Add PHP
github / github_issue

How to start

Only source-backed commands are shown here. Verify them in an isolated environment first.

Try the prompt first

Test the workflow without installing the upstream project.

preview

Read the Human Manual

Understand inputs, outputs, limits, and failure modes.

manual

Take context to your AI host

Use the compiled assets in your preferred AI environment.

context

Run sandbox verification

Confirm install commands and rollback before using a primary environment.

verify

pip install korvus

Official start command · https://github.com/postgresml/korvus#readme · verified: yes

Human Manual

The English page must expose the real manual, not a short placeholder.

8+ sections · Human Manual

korvus Manual

Korvus is a search SDK that unifies the entire RAG pipeline in a single database query. Built on top of Postgres with bindings for Python, JavaScript, Rust and C.

Open the full manual

https://github.com/postgresml/korvus Project Manual
Table of Contents
Overview and Getting Started
Related Pages
Project Purpose and Scope
High-Level Architecture
Language Bindings via rust-bridge
Getting Started and Example Workflows

Overview and Getting Started

Related topics: System Architecture and Core Components, Multi-Language SDK Bindings and Examples

Source: https://github.com/postgresml/korvus / Human Manual

System Architecture and Core Components

Related topics: Overview and Getting Started, RAG Operations, Configuration, and Common Failure Modes

Source: https://github.com/postgresml/korvus / Human Manual

Multi-Language SDK Bindings and Examples

Related topics: Overview and Getting Started, System Architecture and Core Components

Source: https://github.com/postgresml/korvus / Human Manual

RAG Operations, Configuration, and Common Failure Modes

Related topics: System Architecture and Core Components, Multi-Language SDK Bindings and Examples

Source: https://github.com/postgresml/korvus / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

AI Context Pack and portable assets

After deciding to continue, take the project context into your own AI host.

Complete pack plus user-owned assets

These files are planning and verification assets for Claude Code, Codex, Gemini, Cursor, ChatGPT, and other AI hosts.

Download complete pack Read Human Manual

BundleComplete Project Pack AssetAI Context Pack AssetBoundary & Risk Card AssetHuman Manual AssetPitfall Log AssetPrompt Preview AssetQuick Start EvidenceREPO_INSPECTION.json

Preflight checks

Treat this page as a planning asset, not proof that your local environment is ready.

The manual is generated from source-linked project files and Doramagic validation signals.
Community evidence warnings stay visible instead of being converted into marketing claims.
This English page is indexable because the locale quality gate passed and explicit English index approval is enabled.
Use the upstream repository as the final authority for installation commands, license, and version-specific behavior.

Pitfall Log and verification risks

Doramagic surfaces high-risk items before users treat a candidate capability as verified.

high

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

high

Security or permission risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Capability evidence risk requires verification

May increase setup, validation, or first-run risk for the user.