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docs/source/getting_started/distributions/self_hosted_distro/ollama.md
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# Ollama Distribution
The `llamastack/distribution-ollama` distribution consists of the following provider configurations.
| API | Provider(s) |
|-----|-------------|
| agents | `inline::meta-reference` |
| inference | `remote::ollama` |
| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
| safety | `inline::llama-guard` |
| telemetry | `inline::meta-reference` |
You should use this distribution if you have a regular desktop machine without very powerful GPUs. Of course, if you have powerful GPUs, you can still continue using this distribution since Ollama supports GPU acceleration.### Environment Variables
The following environment variables can be configured:
- `LLAMASTACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `OLLAMA_URL`: URL of the Ollama server (default: `http://127.0.0.1:11434`)
- `INFERENCE_MODEL`: Inference model loaded into the Ollama server (default: `meta-llama/Llama-3.2-3B-Instruct`)
- `SAFETY_MODEL`: Safety model loaded into the Ollama server (default: `meta-llama/Llama-Guard-3-1B`)
## Setting up Ollama server
Please check the [Ollama Documentation](https://github.com/ollama/ollama) on how to install and run Ollama. After installing Ollama, you need to run `ollama serve` to start the server.
In order to load models, you can run:
```bash
export INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct"
# ollama names this model differently, and we must use the ollama name when loading the model
export OLLAMA_INFERENCE_MODEL="llama3.2:3b-instruct-fp16"
ollama run $OLLAMA_INFERENCE_MODEL --keepalive 60m
```
If you are using Llama Stack Safety / Shield APIs, you will also need to pull and run the safety model.
```bash
export SAFETY_MODEL="meta-llama/Llama-Guard-3-1B"
# ollama names this model differently, and we must use the ollama name when loading the model
export OLLAMA_SAFETY_MODEL="llama-guard3:1b"
ollama run $OLLAMA_SAFETY_MODEL --keepalive 60m
```
## Running Llama Stack
Now you are ready to run Llama Stack with Ollama as the inference provider. You can do this via Conda (build code) or Docker which has a pre-built image.
### Via Docker
This method allows you to get started quickly without having to build the distribution code.
```bash
export LLAMA_STACK_PORT=5001
docker run \
-it \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ~/.llama:/root/.llama \
-v ./run.yaml:/root/my-run.yaml \
llamastack/distribution-ollama \
--yaml-config /root/my-run.yaml \
--port $LLAMA_STACK_PORT \
--env INFERENCE_MODEL=$INFERENCE_MODEL \
--env OLLAMA_URL=http://host.docker.internal:11434
```
If you are using Llama Stack Safety / Shield APIs, use:
```bash
docker run \
-it \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ~/.llama:/root/.llama \
-v ./run-with-safety.yaml:/root/my-run.yaml \
llamastack/distribution-ollama \
--yaml-config /root/my-run.yaml \
--port $LLAMA_STACK_PORT \
--env INFERENCE_MODEL=$INFERENCE_MODEL \
--env SAFETY_MODEL=$SAFETY_MODEL \
--env OLLAMA_URL=http://host.docker.internal:11434
```
### Via Conda
Make sure you have done `pip install llama-stack` and have the Llama Stack CLI available.
```bash
export LLAMA_STACK_PORT=5001
llama stack build --template ollama --image-type conda
llama stack run ./run.yaml \
--port $LLAMA_STACK_PORT \
--env INFERENCE_MODEL=$INFERENCE_MODEL \
--env OLLAMA_URL=http://localhost:11434
```
If you are using Llama Stack Safety / Shield APIs, use:
```bash
llama stack run ./run-with-safety.yaml \
--port $LLAMA_STACK_PORT \
--env INFERENCE_MODEL=$INFERENCE_MODEL \
--env SAFETY_MODEL=$SAFETY_MODEL \
--env OLLAMA_URL=http://localhost:11434
```
### (Optional) Update Model Serving Configuration
> [!NOTE]
> Please check the [OLLAMA_SUPPORTED_MODELS](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers.remote/inference/ollama/ollama.py) for the supported Ollama models.
To serve a new model with `ollama`
```bash
ollama run <model_name>
```
To make sure that the model is being served correctly, run `ollama ps` to get a list of models being served by ollama.
```
$ ollama ps
NAME ID SIZE PROCESSOR UNTIL
llama3.1:8b-instruct-fp16 4aacac419454 17 GB 100% GPU 4 minutes from now
```
To verify that the model served by ollama is correctly connected to Llama Stack server
```bash
$ llama-stack-client models list
+----------------------+----------------------+---------------+-----------------------------------------------+
| identifier | llama_model | provider_id | metadata |
+======================+======================+===============+===============================================+
| Llama3.1-8B-Instruct | Llama3.1-8B-Instruct | ollama0 | {'ollama_model': 'llama3.1:8b-instruct-fp16'} |
+----------------------+----------------------+---------------+-----------------------------------------------+
```