Awesome

ramalama

The Ramalama project's goal is to make working with AI boring through the use of OCI containers.

On first run Ramalama inspects your system for GPU support, falling back to CPU support if no GPUs are present. It then uses container engines like Podman to pull the appropriate OCI image with all of the software necessary to run an AI Model for your systems setup. This eliminates the need for the user to configure the system for AI themselves. After the initialization, Ramalama will run the AI Models within a container based on the OCI image.

Install

Install Ramalama by running this one-liner (on macOS run without sudo):

Linux:

curl -fsSL https://raw.githubusercontent.com/containers/ramalama/s/install.py | sudo python3

macOS:

curl -fsSL https://raw.githubusercontent.com/containers/ramalama/s/install.py | python3

Hardware Support

Hardware	Enabled
CPU	:white_check_mark:
Apple Silicon GPU (macOS)	:white_check_mark:
Apple Silicon GPU (podman-machine)	:x:
Nvidia GPU (cuda)	:x:
AMD GPU (rocm)	:x:

COMMANDS

Command	Description
ramalama-containers(1)	List all ramalama containers.
ramalama-list(1)	List all AI models in local storage.
ramalama-login(1)	Login to remote model registry.
ramalama-logout(1)	Logout from remote model registry.
ramalama-pull(1)	Pull AI Models into local storage.
ramalama-push(1)	Push AI Model (OCI-only at present)
ramalama-rm(1)	Remove specified AI Model from local storage.
ramalama-run(1)	Run specified AI Model as a chatbot.
ramalama-serve(1)	Serve specified AI Model as an API server.
ramalama-stop(1)	Stop ramalaman container running an AI Model.
ramalama-version(1)	Display the ramalama version.

Usage

Running Models

You can run a chatbot on a model using the run command. By default, it pulls from the ollama registry.

Note: Ramalama will inspect your machine for native GPU support and then will use a container engine like Podman to pull an OCI container image with the appropriate code and libraries to run the AI Model. This can take a long time to setup, but only on the first run.

$ ramalama run instructlab/merlinite-7b-lab
Copying blob 5448ec8c0696 [--------------------------------------] 0.0b / 63.6MiB (skipped: 0.0b = 0.00%)
Copying blob cbd7e392a514 [--------------------------------------] 0.0b / 65.3MiB (skipped: 0.0b = 0.00%)
Copying blob 5d6c72bcd967 done  208.5MiB / 208.5MiB (skipped: 0.0b = 0.00%)
Copying blob 9ccfa45da380 [--------------------------------------] 0.0b / 7.6MiB (skipped: 0.0b = 0.00%)
Copying blob 4472627772b1 [--------------------------------------] 0.0b / 120.0b (skipped: 0.0b = 0.00%)
>

After the initial container image has been downloaded, you can interact with different models, using the container image.

$ ramalama run granite-code
> Write a hello world application in python

print("Hello World")

In a different terminal window see the running podman container.

$ podman ps
CONTAINER ID  IMAGE                             COMMAND               CREATED        STATUS        PORTS       NAMES
91df4a39a360  quay.io/ramalama/ramalama:latest  /home/dwalsh/rama...  4 minutes ago  Up 4 minutes              gifted_volhard

Listing Models

You can list all models pulled into local storage.

$ ramalama list
NAME                                                                MODIFIED     SIZE
ollama://tiny-llm:latest                                            16 hours ago 5.5M
huggingface://afrideva/Tiny-Vicuna-1B-GGUF/tiny-vicuna-1b.q2_k.gguf 14 hours ago 460M
ollama://granite-code:3b                                            5 days ago   1.9G
ollama://granite-code:latest                                        1 day ago    1.9G
ollama://moondream:latest                                           6 days ago   791M

Pulling Models

You can pull a model using the pull command. By default, it pulls from the ollama registry.

$ ramalama pull granite-code
###################################################                       32.5%

Serving Models

You can serve a chatbot on a model using the serve command. By default, it pulls from the ollama registry.

$ ramalama serve llama3

Diagram

+---------------------------+
|                           |
| ramalama run granite-code |
|                           |
+-------+-------------------+
        |
        |
        |                                          +------------------+
        |                                          | Pull model layer |
        +----------------------------------------->| granite-code     |
                                                   +------------------+
                                                   | Repo options:    |
                                                   +-+-------+------+-+
                                                     |       |      |
                                                     v       v      v
                                             +---------+ +------+ +----------+
                                             | Hugging | | quay | | Ollama   |
                                             | Face    | |      | | Registry |
                                             +-------+-+ +---+--+ +-+--------+
                                                     |       |      |
                                                     v       v      v
                                                   +------------------+
                                                   | Start with       |
                                                   | llama.cpp and    |
                                                   | granite-code     |
                                                   | model            |
                                                   +------------------+

In development

Regard this alpha, everything is under development, so expect breaking changes, luckily it's easy to reset everything and re-install:

rm -rf /var/lib/ramalama # only required if running as root user
rm -rf $HOME/.local/share/ramalama

and install again.

Credit where credit is due

This project wouldn't be possible without the help of other projects like:

llama.cpp whisper.cpp vllm podman omlmd huggingface

so if you like this tool, give some of these repos a :star:, and hey, give us a :star: too while you are at it.

Contributors

Open to contributors