Files
supabase/apps/docs/content/guides/ai/python-clients.mdx
3dffdefd6e fix(docs) Resolve 196 mdx lint warnings for just, quickly, actually, PostgreSQL (#47358)
Closes DOCS-1057
Contributes to DOCS-1052

## I have read the
[CONTRIBUTING.md](https://github.com/supabase/supabase/blob/master/CONTRIBUTING.md)
file.

YES

## Problem

We have hundreds of MDX lint warnings in our docs going against style
best practices.

## Solution

Remove and replace in context the following:

- PostgreSQL. There was only one. There was concern about exceptions,
but I found none.
- Just
- Quickly
- Actually

### What changed

Edits follow the [Google developer documentation style
guide](https://developers.google.com/style): concise, direct, active
voice. The flagged words were removed when the sentence still read well,
or replaced when meaning needed to be preserved.

### Common patterns

| Flagged word | Approach | Example |
|---|---|---|
| **just** (filler) | Removed | "you just installed" → "you installed" |
| **just** (limiting) | **only** | "just one row" → "only one row" |
| **just like** | **like** / **the same as** | "function just like
regular users" → "function like regular users" |
| **not just** | **not only** | "not just errors" → "not only errors" |
| **quickly** (performance) | **efficiently** or removed | "find rows
quickly" → "find rows efficiently" |
| **quickly** (time) | **soon** / **rapidly** / removed | "expires too
quickly" → "expires too soon" |
| **actually** (filler) | Removed | "actually execute" → "execute"; "is
actually the most common" → "is the most common" |

## Tophatting

1. See the diff.
2. See that content continues to make sense in context.
3. Locally, `cd apps/docs` and run `pnpm run lint:mdx`.
4. Search for "just," "actually," "quickly", and "PostgreSQL" and see
there are 0 warnings.




<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

* **Documentation**
* Updated wording across quickstarts, guides, and troubleshooting
articles for grammar, clarity, and consistent step-by-step phrasing.
* Clarified key concepts including Row Level Security policy evaluation
across Supabase products, deferred foreign key constraint behavior, and
when `EXPLAIN ANALYZE` executes queries (and related side effects).
* Refined several troubleshooting instructions and added guidance to cap
log payload size to reduce billed Logs Ingest volume.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Nik Richers <nrichers@gmail.com>
Co-authored-by: Chris Chinchilla <chris.ward@supabase.io>
2026-06-29 09:40:25 -07:00

21 lines
1.1 KiB
Plaintext

---
id: 'ai-python-clients'
title: 'Choosing a Client'
description: 'Learn how to manage vectors using Python'
sidebar_label: 'Choosing a Client'
---
As described in [Structured & Unstructured Embeddings](/docs/guides/ai/structured-unstructured), AI workloads come in many forms.
For data science or ephemeral workloads, the [Supabase Vecs](https://supabase.github.io/vecs/) client gets you started. You need a connection string and vecs handles setting up your database to store and query vectors with associated metadata.
<Admonition type="tip">
Click [**Connect**](/dashboard/project/_/?showConnect=true) at the top of any project page to get your connection string.
Copy the URI from the **Shared pooler** option.
</Admonition>
For production python applications with version controlled migrations, we recommend adding first class vector support to your toolchain by [registering the vector type with your ORM](https://github.com/pgvector/pgvector-python). pgvector provides bindings for the most commonly used SQL drivers/libraries including Django, SQLAlchemy, SQLModel, psycopg, asyncpg and Peewee.