Easy Setup - CPU Docker
- You will need about 10gb of RAM Free
- You will need about 15gb of space free on C drive for
Docker compose
We are going to run LocalAI
with docker compose
for this set up.
Lets setup our folders for LocalAI
mkdir "LocalAI"
cd LocalAI
mkdir "models"
mkdir "images"
mkdir -p "LocalAI"
cd LocalAI
mkdir -p "models"
mkdir -p "images"
At this point we want to set up our .env
file, here is a copy for you to use if you wish, Make sure this is in the LocalAI
folder.
## Set number of threads.
## Note: prefer the number of physical cores. Overbooking the CPU degrades performance notably.
THREADS=2
## Specify a different bind address (defaults to ":8080")
# ADDRESS=127.0.0.1:8080
## Define galleries.
## models will to install will be visible in `/models/available`
GALLERIES=[{"name":"model-gallery", "url":"github:go-skynet/model-gallery/index.yaml"}, {"url": "github:go-skynet/model-gallery/huggingface.yaml","name":"huggingface"}]
## Default path for models
MODELS_PATH=/models
## Enable debug mode
# DEBUG=true
## Disables COMPEL (Lets Stable Diffuser work, uncomment if you plan on using it)
# COMPEL=0
## Enable/Disable single backend (useful if only one GPU is available)
# SINGLE_ACTIVE_BACKEND=true
## Specify a build type. Available: cublas, openblas, clblas.
BUILD_TYPE=cublas
## Uncomment and set to true to enable rebuilding from source
# REBUILD=true
## Enable go tags, available: stablediffusion, tts
## stablediffusion: image generation with stablediffusion
## tts: enables text-to-speech with go-piper
## (requires REBUILD=true)
#
#GO_TAGS=tts
## Path where to store generated images
# IMAGE_PATH=/tmp
## Specify a default upload limit in MB (whisper)
# UPLOAD_LIMIT
# HUGGINGFACEHUB_API_TOKEN=Token here
Now that we have the .env
set lets set up our docker-compose
file.
It will use a container from quay.io.
Also note this docker-compose
file is for CPU
only.
version: '3.6'
services:
api:
image: quay.io/go-skynet/local-ai:v2.0.0
tty: true # enable colorized logs
restart: always # should this be on-failure ?
ports:
- 8080:8080
env_file:
- .env
volumes:
- ./models:/models
- ./images/:/tmp/generated/images/
command: ["/usr/bin/local-ai" ]
Make sure to save that in the root of the LocalAI
folder. Then lets spin up the Docker run this in a CMD
or BASH
docker compose up -d --pull always
Now we are going to let that set up, once it is done, lets check to make sure our huggingface / localai galleries are working (wait until you see this screen to do this)
You should see:
┌───────────────────────────────────────────────────┐
│ Fiber v2.42.0 │
│ http://127.0.0.1:8080 │
│ (bound on host 0.0.0.0 and port 8080) │
│ │
│ Handlers ............. 1 Processes ........... 1 │
│ Prefork ....... Disabled PID ................. 1 │
└───────────────────────────────────────────────────┘
curl http://localhost:8080/models/available
Output will look like this:
Now that we got that setup, lets go setup a model