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korvus

postgresml/korvus

Unified RAG pipeline in a single database query

GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026

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1.5k stars50 forksLast push Jan 31, 2025 Rust MIT

Decision brief

Korvus is an SDK leveraging the Retrieval-Augmented Generation (RAG) pipeline within Postgres database operations, supporting multiple programming languages.

Good fit when

  • You require seamless integration of AI capabilities into data retrieval actions performed on a Postgres database.
  • Need to implement RAG functionality in your project but desire simplicity and efficiency by leveraging a single-query approach.

Avoid when

  • You seek a solution that operates beyond the Postgres ecosystem, as Korvus specifically integrates with this type of database.
  • If your project necessitates highly specialized RAG implementations without leveraging existing databases for retrieval tasks.
Requirements:
Compatible programming languages include Rust, Python, JavaScript, and C.

Observed Jul 12, 2026 · Source: enrich:decision_facts

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Maintenance and security

Full trust report
Maintenance
Dormant (597d since push)
As of Sep 20, 2026
Provenance
Not a fork · Organization account
As of Sep 20, 2026
Security (OSV)
No lockfile
As of Jul 11, 2026

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

cargo add korvus
crates.io

Similar tools

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

Korvus is an SDK for search over Postgres that integrates the Retrieval-Augmented Generation (RAG) pipeline. It supports multiple programming languages and focuses on embedding AI capabilities within data retrieval operations.

Capability facts

Languages
rust

Source: github.language · Sep 20, 2026

Categories

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Sep 20, 2026)

```python from korvus import Collection, Pipeline
Source link

Tags

README

🏁 Quick Start 1. Install Korvus: 2. Set the env variable: 3. Initialize a Collection and Pipeline: 4. Insert documents: 5. Perform RAG

For agents

This page has a .md twin and JSON over the API.

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