Running Immich with AI-Powered Image Search on Raspberry Pi 5 + AXera NPU

[yuyun2000]

TL;DR: Got Immich running with CLIP-based semantic search on a Raspberry Pi 5 using the AXera AX8850 NPU. Chinese language search works surprisingly well thanks to the ViT-L-14-336-CN model. Setup took about 30 minutes once I figured out the ML server configuration.

What is Immich?

Immich is an open-source, self-hosted photo and video management platform. Think Google Photos, but you control the data. It supports automatic backup, intelligent search, and cross-device access.

Why This Setup?

I wanted to test AI-accelerated image search on edge hardware. The AXera AX8850 NPU on our M5Stack development board provides hardware acceleration for the CLIP models, making semantic search actually usable on a Pi.

Hardware Setup

• Raspberry Pi 5
• M5Stack AX8850 AI Module (provides NPU acceleration)
• Standard Pi power supply and storage

Step-by-Step Deployment

1. Download the Pre-built Package

Grab the optimized Immich build from HuggingFace:

git clone https://huggingface.co/AXERA-TECH/immich

Note: You'll need git lfs installed. If you don't have it, install it first.

What you get:

m5stack@raspberrypi:~/rsp/immich $ ls -lh
total 421M
drwxrwxr-x 2 m5stack m5stack 4.0K Oct 10 09:12 asset
-rw-rw-r-- 1 m5stack m5stack 421M Oct 10 09:20 ax-immich-server-aarch64.tar.gz
-rw-rw-r-- 1 m5stack m5stack    0 Oct 10 09:12 config.json
-rw-rw-r-- 1 m5stack m5stack 7.6K Oct 10 09:12 docker-deploy.zip
-rw-rw-r-- 1 m5stack m5stack 104K Oct 10 09:12 immich_ml-1.129.0-py3-none-any.whl
-rw-rw-r-- 1 m5stack m5stack 9.4K Oct 10 09:12 README.md
-rw-rw-r-- 1 m5stack m5stack  177 Oct 10 09:12 requirements.txt

2. Load the Docker Image

cd immich
docker load -i ax-immich-server-aarch64.tar.gz

If Docker isn't installed, you'll need to set that up first.

3. Configure the Environment

unzip docker-deploy.zip
cp example.env .env

4. Start the Core Services

docker compose -f docker-compose.yml -f docker-compose.override.yml up -d

Success looks like this:

[+] Running 3/3
 ✔ Container immich_postgres  Started                                      1.0s 
 ✔ Container immich_redis     Started                                      0.9s 
 ✔ Container immich_server    Started                                      0.9s 

5. Set Up the ML Service (The Interesting Part)

The ML service handles the AI-powered image search. It runs separately to leverage the NPU.

Create and activate a virtual environment:

python -m venv mich
source mich/bin/activate

Install dependencies:

pip install https://github.com/AXERA-TECH/pyaxengine/releases/download/0.1.3.rc2/axengine-0.1.3-py3-none-any.whl
pip install -r requirements.txt
pip install immich_ml-1.129.0-py3-none-any.whl

Launch the ML server:

python -m immich_ml

You should see:

[10/10/25 09:50:12] INFO     Listening at: http://[::]:3003 (8698)              
[INFO] Available providers:  ['AXCLRTExecutionProvider']
[10/10/25 09:50:16] INFO     Application startup complete.  

The AXCLRTExecutionProvider confirms the NPU is being used.

Web Interface Configuration

Initial Setup

1. Navigate to http://<your-pi-ip>:3003 (e.g., 192.168.20.27:3003)
2. First visit requires admin account creation - credentials are stored locally

<img src="https://m5stack.oss-cn-shenzhen.aliyuncs.com/resource/linux/ax8850_card/images/immich1.png" width="95%" />

Configure the ML Server

This is critical - the web interface needs to know where your ML service is running.

1. Go to Settings → Machine Learning
2. Set the URL to your Pi's IP and port 3003: http://192.168.20.27:3003
3. Choose your CLIP model based on language:
   • Chinese search: ViT-L-14-336-CN__axera
   • English search: ViT-L-14-336__axera

<img src="https://m5stack.oss-cn-shenzhen.aliyuncs.com/resource/linux/ax8850_card/images/immich4.png" width="95%" />

First-Time Index

Important: You need to manually trigger the initial indexing.

1. Go to Administration → Jobs
2. Find "SMART SEARCH"
3. Click "Run Job" to process your uploaded images

<img src="https://m5stack.oss-cn-shenzhen.aliyuncs.com/resource/linux/ax8850_card/images/immich6.png" width="95%" />

Testing Image Search

Upload some photos, wait for indexing to complete, then try semantic searches:

<img src="https://m5stack.oss-cn-shenzhen.aliyuncs.com/resource/linux/ax8850_card/images/immich7.png" width="95%" />

The search works conceptually - you can search for "sunset" or "dogs playing" and it'll find relevant images even if those exact words aren't in the filename.

Technical Notes

• The NPU acceleration makes CLIP inference fast enough for interactive search
• Chinese language support is genuinely good with the CN model
• The ML server runs independently, so you can restart it without affecting the main Immich service
• Docker handles PostgreSQL and Redis automatically

Why M5Stack in This Stack?

The AX8850 NPU module provides the hardware acceleration that makes this practical on a Pi. Without it, running CLIP inference would be too slow for interactive use. We're working on more edge AI applications that leverage this acceleration - this Immich setup is a good real-world test case.

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Questions about the setup or the NPU integration? Happy to dig into specifics.