pgai simplifies the process of building search, and Retrieval Augmented Generation(RAG) AI applications with PostgreSQL.

pgai brings embedding and generation AI models closer to the database. With pgai, you can now do the following directly from within PostgreSQL in a SQL query:

• Create embeddings for your data.
• Retrieve LLM chat completions from models like OpenAI GPT4o and Llama 3.
• Generate responses for models such as Ollama.
• Reason over your data and facilitate use cases like classification, summarization, and data enrichment on your existing relational data in PostgreSQL.

Here's how to get started with pgai:

• Everyone: Use pgai in your PostgreSQL database.
  1. Install pgai.
  2. Use pgai to integrate AI from your provider:
     • Ollama - configure pgai with Ollama, then use the model to embed, chat complete and generate.
     • OpenAI - configure pgai with OpenAI, then use the model to tokenize, embed, chat complete and moderate. This page also includes advanced examples.
• Extension contributor: Contribute to pgai and improve the project.
  • Develop and test changes to the pgai extension.
  • See the Issues tab for a list of feature ideas to contribute.

Learn more about pgai: To learn more about the pgai extension and why we built it, read this blog post pgai: Giving PostgreSQL Developers AI Engineering Superpowers.

Installation

The fastest ways to run PostgreSQL with the pgai extension are to:

1. Create your database environment. Either:

   • Use a pre-built Docker container.
   • Install from source.
   • Use a Timescale Cloud service.

2. Enable the pgai extension.

3. Use pgai.

Use a pre-built Docker container

Run the TimescaleDB Docker image.

Install from source

You can install pgai from source in an existing PostgreSQL server. You will need Python3 and pip installed system-wide. You will also need to install the plpython3 and pgvector extensions. After installing these prerequisites, run:

make install

Use a Timescale Cloud service

Create a new Timescale Service.

If you want to use an existing service, pgai is added as an available extension on the first maintenance window after the pgai release date.

Enable the pgai extension in your database

1. Connect to your database with a postgres client like psql v16 or PopSQL.

   psql -d "postgres://<username>:<password>@<host>:<port>/<database-name>"

2. Create the pgai extension:

   CREATE EXTENSION IF NOT EXISTS ai CASCADE;

   The CASCADE automatically installs pgvector and plpython3u extensions.

Use pgai

Now, use pgai to integrate AI from Ollama and OpenAI. Learn how to moderate and embed content directly in the database using triggers and background jobs.

Get involved

pgai is still at an early stage. Now is a great time to help shape the direction of this project; we are currently deciding priorities. Have a look at the list of features we're thinking of working on. Feel free to comment, expand the list, or hop on the Discussions forum.

To get started, take a look at how to contribute and how to set up a dev/test environment.

About Timescale

Timescale is a PostgreSQL database company. To learn more visit the timescale.com.

Timescale Cloud is a high-performance, developer focused, cloud platform that provides PostgreSQL services for the most demanding AI, time-series, analytics, and event workloads. Timescale Cloud is ideal for production applications and provides high availability, streaming backups, upgrades over time, roles and permissions, and great security.