---
title: "pgai"
url: "/docs/projects/pgai"
canonical_url: "https://docs.litellm.ai/docs/projects/pgai"
type: "docs"
last_updated: "2026-10-09"
summary: "pgai is a suite of tools to develop RAG, semantic search, and other AI applications more easily with PostgreSQL."
related:
  - "/docs/projects/llm_cord"
  - "/docs/projects/GPTLocalhost"
---
# pgai

> Index of all LiteLLM docs: https://docs.litellm.ai/llms.txt


[pgai](https://github.com/timescale/pgai) is a suite of tools to develop RAG, semantic search, and other AI applications more easily with PostgreSQL.

If you don't know what pgai is yet check out the [README](https://github.com/timescale/pgai)!

If you're already familiar with pgai, you can find litellm specific docs here:
- Litellm for [model calling](https://github.com/timescale/pgai/blob/main/docs/model_calling/litellm.md) in pgai
- Use the [litellm provider](https://github.com/timescale/pgai/blob/main/docs/vectorizer/api-reference.md#aiembedding_litellm) to automatically create embeddings for your data via the pgai vectorizer.

## Related pages

- [llmcord.py](https://docs.litellm.ai/docs/projects/llm_cord.md)
- [GPTLocalhost](https://docs.litellm.ai/docs/projects/GPTLocalhost.md)