https://github.com/syahidfrd/rago

Go app integrating OpenAI chat & embeddings with PostgreSQL vector storage
https://github.com/syahidfrd/rago

golang llm openai pgvector rag

Last synced: 21 days ago
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Go app integrating OpenAI chat & embeddings with PostgreSQL vector storage

• Host: GitHub
• URL: https://github.com/syahidfrd/rago
• Owner: syahidfrd
• Created: 2024-10-28T10:47:05.000Z (23 days ago)
• Default Branch: main
• Last Pushed: 2024-10-29T01:24:13.000Z (22 days ago)
• Last Synced: 2024-10-29T02:24:42.452Z (22 days ago)
• Topics: golang, llm, openai, pgvector, rag
• Language: Go
• Homepage: https://syahidfrd.com/blog/konsep-rag-llm-dan-contoh-implementasinya
• Size: 2.93 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# OpenAI Chat Completion and Embedding with PostgreSQL

This repository demonstrates how to use OpenAI's chat completion and text embedding capabilities in conjunction with a PostgreSQL database to store embeddings and perform similarity searches.

For further details, refer to my blog post: [Konsep RAG pada LLM dan Contoh Implementasinya](https://syahidfrd.com/blog/konsep-rag-llm-dan-contoh-implementasinya)

## Overview

This application allows you to:

1. Generate text embeddings from OpenAI's `text-embedding-3-small` model.

2. Store and retrieve these embeddings from PostgreSQL using the `pgvector` extension.

3. Perform similarity search on the stored embeddings to find relevant context for chat completion.

## Requirements

- Golang

- PostgreSQL with `pgvector` extension installed

- OpenAI API Key