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Distributions updates (slight updates to ollama, add inline-vllm and remote-vllm) (#408)

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* remote vllm distro

* add inline-vllm details, fix things

* Write some docs
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Ashwin Bharambe 2024-11-08 18:09:39 -08:00 • committed by GitHub
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66
docs/source/getting_started/distributions/self_hosted_distro/ollama.md
View file

@ -2,25 +2,35 @@
The `llamastack/distribution-ollama` distribution consists of the following provider configurations.
| **API** | **Inference** | **Agents** | **Memory** | **Safety** | **Telemetry** |
|----------------- |---------------- |---------------- |---------------------------------- |---------------- |---------------- |
| **Provider(s)** | remote::ollama | meta-reference | remote::pgvector, remote::chroma | remote::ollama | meta-reference |
| **API** | **Inference** | **Agents** | **Memory** | **Safety** | **Telemetry** |
|----------------- |---------------- |---------------- |------------------------------------ |---------------- |---------------- |
| **Provider(s)** | remote::ollama | meta-reference | remote::pgvector, remote::chromadb | meta-reference | meta-reference |
### Docker: Start a Distribution (Single Node GPU)
## Using Docker Compose
You can use `docker compose` to start a Ollama server and connect with Llama Stack server in a single command.
### Docker: Start the Distribution (Single Node regular Desktop machine)
> [!NOTE]
> This will start an ollama server with CPU only, please see [Ollama Documentations](https://github.com/ollama/ollama) for serving models on CPU only.
```bash
$ cd distributions/ollama; docker compose up
```
### Docker: Start a Distribution (Single Node with nvidia GPUs)
> [!NOTE]
> This assumes you have access to GPU to start a Ollama server with access to your GPU.
```
$ cd distributions/ollama/gpu
$ ls
compose.yaml run.yaml
$ docker compose up
```bash
$ cd distributions/ollama-gpu; docker compose up
```
You will see outputs similar to following ---
```
```bash
[ollama] | [GIN] 2024/10/18 - 21:19:41 | 200 | 226.841µs | ::1 | GET "/api/ps"
[ollama] | [GIN] 2024/10/18 - 21:19:42 | 200 | 60.908µs | ::1 | GET "/api/ps"
INFO: Started server process [1]
@ -34,36 +44,24 @@ INFO: Uvicorn running on http://[::]:5000 (Press CTRL+C to quit)
```
To kill the server
```
```bash
docker compose down
```
### Docker: Start the Distribution (Single Node CPU)
## Starting Ollama and Llama Stack separately
> [!NOTE]
> This will start an ollama server with CPU only, please see [Ollama Documentations](https://github.com/ollama/ollama) for serving models on CPU only.
If you wish to separately spin up a Ollama server, and connect with Llama Stack, you should use the following commands.
```
$ cd distributions/ollama/cpu
$ ls
compose.yaml run.yaml
$ docker compose up
```
### Conda: ollama run + llama stack run
If you wish to separately spin up a Ollama server, and connect with Llama Stack, you may use the following commands.
#### Start Ollama server.
- Please check the [Ollama Documentations](https://github.com/ollama/ollama) for more details.
#### Start Ollama server
- Please check the [Ollama Documentation](https://github.com/ollama/ollama) for more details.
**Via Docker**
```
```bash
docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama
```
**Via CLI**
```
```bash
ollama run <model_id>
```
@ -71,7 +69,7 @@ ollama run <model_id>
**Via Conda**
```
```bash
llama stack build --template ollama --image-type conda
llama stack run ./gpu/run.yaml
```
@ -82,7 +80,7 @@ docker run --network host -it -p 5000:5000 -v ~/.llama:/root/.llama -v ./gpu/run
```
Make sure in your `run.yaml` file, your inference provider is pointing to the correct Ollama endpoint. E.g.
```
```yaml
inference:
- provider_id: ollama0
provider_type: remote::ollama
@ -96,7 +94,7 @@ inference:
You can use ollama for managing model downloads.
```
```bash
ollama pull llama3.1:8b-instruct-fp16
ollama pull llama3.1:70b-instruct-fp16
```
@ -106,7 +104,7 @@ ollama pull llama3.1:70b-instruct-fp16
To serve a new model with `ollama`
```
```bash
ollama run <model_name>
```
@ -119,7 +117,7 @@ llama3.1:8b-instruct-fp16 4aacac419454 17 GB 100% GPU 4 minutes fro
```
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 |