Ollama LLM Engine Docker Setup
This JSON object contains information about setting up the Ollama LLM engine in a Docker container. The process involves creating a Docker Compose file, running the Docker container, and accessing the application. The smallest model that can be loaded into Ollama is the 7B model, which requires approximately 8 GB of RAM.
use realtime search to find out what LLM engine i can run in a docker container and instructions for doing so
To run an LLM engine in a Docker container, you can use Ollama. Here are the steps to set up Ollama in a Docker container:
Prerequisites
- Ensure you have Docker installed on your system.
- For Linux, install the NVIDIA Container Toolkit.
- For Windows 10/11, install the latest NVIDIA driver and use the WSL2 backend.
Create a Docker Compose File
Create a compose.yaml file with the following content:
services:
server:
build: .
ports:
- 8000:8000
env_file:
- .env
depends_on:
database:
condition: service_healthy
database:
image: neo4j:5.11
ports:
- 7474:7474
- 7687:7687
environment:
- NEO4J_AUTH=${NEO4J_USERNAME}/${NEO4J_PASSWORD}
healthcheck:
test: ["CMD-SHELL", "wget --no-verbose --tries=1 --spider localhost:7474 || exit 1"]
interval: 5s
timeout: 3s
retries: 5
ollama:
build: .
ports:
- 7860:7860
env_file:
- .env
depends_on:
server:
condition: service_started
Run the Docker Container
Run the Docker container using the following command:
docker compose up --build
Access the Application
Open a browser and navigate to http://localhost:8000 to access the application.
For more detailed instructions and additional setup options, refer to the Docker documentation on using containers for generative AI development.
rtsearch: what is the smallest model that can be loaded into ollama (in terms of memory reqs)
The smallest model that can be loaded into Ollama is the 7B model, which requires approximately 8 GB of RAM to run.