[mihow]

Summary

Antenna is about to start storing feature vectors (what each detection looks like, as a list of numbers) so that tracking, retraining and similarity search can compare detections. PostgreSQL needs the pgvector extension for that. This PR does only that one step: it installs pgvector in the local and CI database images and adds a migration that switches the extension on, or stops the deploy with a clear message when the database server does not have it.

It is split out of #1462 so the database change can be reviewed and deployed on its own, before any table uses it. Nothing in the application reads or writes vectors yet.

List of Changes

#	Change (what it does for operators and developers)	How (implementation)
1	A deploy to a database server without pgvector, or with a version older than 0.8, stops with one message that says what to install, instead of a Postgres error about a missing control file	ml/0030_enable_pgvector reads pg_available_extensions before running any SQL
2	The extension is switched on in each database	CREATE EXTENSION IF NOT EXISTS vector; the reverse leaves the extension in place, because it may be shared with other databases and dropping it is often restricted on hosted servers
3	An extension created earlier below 0.8 is upgraded; a current one is left alone, so the migration also runs where an administrator created the extension	ALTER EXTENSION vector UPDATE only when pg_extension.extversion is below 0.8, because that statement needs ownership of the extension even when there is nothing to update
4	Local and CI databases have pgvector without extra steps	compose/local/postgres/Dockerfile installs postgresql-16-pgvector from the PostgreSQL apt repository (0.8.x today); not pinned, since the migration enforces the minimum
5	The Python client for vector columns is available for #1462	pgvector==0.5.1 (the current release of pgvector-python) in requirements/base.txt
6	The checks are tested without a database	ami/ml/test_pgvector_migration.py: missing package, old package, current package, and upgrade only below the minimum

Before deploying

Local development

After pulling, rebuild the database and Django images once, then start the stack as usual:

docker compose build postgres django   # celeryworker, celerybeat and flower share the django build
docker compose up -d

The PostgreSQL major version does not change (still postgres:16), so existing data volumes keep working and no dump or reset is needed. The local start script runs migrate, and the local database user is a superuser, so the migration creates the extension by itself. Worktree and CI stacks build their own images and need the same rebuild. A stack started without rebuilding stops at ml.0030 with the "not installed" message below; rebuilding and starting again fixes it.

Servers (demo, staging and production)

Each database server needs two things before this migration runs:

1. The pgvector package, version 0.8 or later, for the server's PostgreSQL version. On Debian or Ubuntu this is postgresql-16-pgvector from the PostgreSQL apt repository; on a hosted database it is the provider's pgvector option. This needs root on the database host.

2. Permission to create the extension. pgvector is not a "trusted" extension (its control file does not set trusted = true), so CREATE EXTENSION needs a superuser. To check the application's role, run SELECT rolsuper FROM pg_roles WHERE rolname = current_user; as that role. If it is not a superuser, an administrator runs this once as the postgres superuser in the application database before deploying:

   CREATE EXTENSION IF NOT EXISTS vector;

   The migration then finds the extension, skips creating it, and only checks its version.

What happens if a step is missed:

• Package missing: migrate stops at ml.0030 with "The pgvector extension is not installed on this PostgreSQL server..." before running any SQL. Install the package and run migrate again.
• Role cannot create the extension: Postgres refuses CREATE EXTENSION with a permission error. Have an administrator create it as above, then run migrate again.
• An older pgvector (below 0.8) created earlier by another role: the migration stops and asks an administrator to run ALTER EXTENSION vector UPDATE;. If the application role owns the extension, the migration upgrades it itself.

The production start script does not run migrate, so a stopped migration does not keep the web server from starting, and this PR adds no table that uses vectors. Later ml migrations, including the vector table in #1462, wait behind ml.0030 until it succeeds.

Why the Python client is 0.5 and the extension 0.8

This was asked on #1462 (#1462 (comment)). They are two different projects with their own version numbers. requirements/base.txt pins pgvector-python, the Django field library, whose current release is 0.5.1; it has provided the HalfVectorField that #1462 uses since 0.3.0. The server extension is the one that needs 0.8: halfvec columns need 0.7, and 0.8 adds the iterative index scans a future nearest-neighbour index would rely on. The migration enforces that floor on the server.

Plan for the split

1. This PR (Enable the pgvector database extension for storing feature vectors #1517): enable pgvector (base main, no dependencies).
2. Show post-processing results in the occurrence algorithm filter, and keep the occurrence result queries side by side #1518: one list of model output tables, used by the algorithm and job filters (base main, no dependencies).
3. Store feature vectors for Detections, introduce BaseEmbedding model and general patterns for vectors #1462 keeps the vector table, the writer, and the UI and admin pieces, and builds on both.

How to Test

1. docker compose build postgres && docker compose up -d postgres, then docker compose run --rm django python manage.py migrate ml. ml.0030_enable_pgvector applies silently.
2. docker compose run --rm django python manage.py test ami.ml.test_pgvector_migration.
3. Optional: on a Postgres image without the package, migrate ml 0030 stops with the "not installed" message.

Checklist

• Migration included and makemigrations --check reports no changes.
• Full backend suite passes locally.

🤖 Generated with Claude Code

https://claude.ai/code/session_0121zMVjnPsqeDFSBXRCPvMy

Summary by CodeRabbit

• Infrastructure
  • Local PostgreSQL setups now include pgvector support, and the Python environment includes the pgvector package.
  • Database setup requires pgvector 0.8 or later. Older installed extensions are upgraded when the database role has permission; otherwise, setup stops with guidance for resolving the issue.
  • Existing extensions that meet the minimum version are left unchanged.

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📝 Walkthrough

The change adds pgvector packages to the local PostgreSQL image and Python requirements. A new migration checks for a server pgvector version of at least 0.8, creates the extension if needed, and updates older installed versions.

Changes: pgvector migration support

Layer / File(s)	Summary
Provision and validate pgvector ami/ml/migrations/0030_enable_pgvector.py, compose/local/postgres/Dockerfile, requirements/base.txt	The migration checks that the server has pgvector version 0.8 or later. The PostgreSQL image installs the pgvector package, and the base requirements add the pinned Python package.
Create and update the extension ami/ml/migrations/0030_enable_pgvector.py, ami/ml/test_pgvector_migration.py	The migration creates the extension if absent and updates it only when its installed version is below 0.8. Tests cover missing and older server packages, accepted versions, and conditional extension updates.

Priority: ⬇️ Low

Estimated code review effort: 2 (Simple) | ~10 minutes

Change: Feature

Merge Risk: ⚪ Minimal · up to 54141

The migration checks server support, creates the extension, and then updates older installations. The reviewed path presents no identified merge-blocking risk.

Pre-merge checks: 4 · 1

Failed checks: 1 warning

Check name	Status	Explanation	Resolution
Docstring Coverage		Docstring coverage is 28.57% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 7 functions across 2 files.	Write docstrings for the functions missing them to satisfy the coverage threshold.

Passed checks: 4 passed

Check name	Status	Explanation
Linked Issues check		Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check		Check skipped because no linked issues were found for this pull request.
Description check		The description clearly explains the purpose, implementation, deployment requirements, risks, and test steps. It includes the main change list and checklist results. It does not use a separate Related…
Title check		The title clearly and concisely describes the main change: enabling the pgvector database extension for feature vectors.

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Actionable comments posted: 1

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• 🪄 Fix comments: Fix CodeRabbit comments on this PR

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Inline comments:
Review comments at @ami/ml/migrations/0030_enable_pgvector.py:
- Around line 53-54: Before `cursor.execute` runs `ALTER EXTENSION vector
UPDATE`, detect whether the migration role owns the existing extension; if it
does not and the installed version is below `MINIMUM_VERSION`, stop with a clear
instruction for an administrator to upgrade the extension before deployment.

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