remote vllm distro

distributions/ollama-gpu/build.yaml

@@ -0,0 +1 @@
+../../llama_stack/templates/ollama/build.yaml

distributions/remote-vllm/build.yaml

@@ -0,0 +1 @@
+../../llama_stack/templates/ollama/build.yaml

distributions/remote-vllm/cpu/compose.yaml

@@ -0,0 +1,30 @@
+services:
+  ollama:
+    image: ollama/ollama:latest
+    network_mode: "host"
+    volumes:
+      - ollama:/root/.ollama # this solution synchronizes with the docker volume and loads the model rocket fast
+    ports:
+      - "11434:11434"
+    command: []
+  llamastack:
+    depends_on:
+    - ollama
+    image: llamastack/distribution-ollama
+    network_mode: "host"
+    volumes:
+      - ~/.llama:/root/.llama
+      # Link to ollama run.yaml file
+      - ./run.yaml:/root/my-run.yaml
+    ports:
+      - "5000:5000"
+    # Hack: wait for ollama server to start before starting docker
+    entrypoint: bash -c "sleep 60; python -m llama_stack.distribution.server.server --yaml_config /root/my-run.yaml"
+    deploy:
+      restart_policy:
+        condition: on-failure
+        delay: 3s
+        max_attempts: 5
+        window: 60s
+volumes:
+  ollama:

distributions/remote-vllm/cpu/run.yaml

@@ -0,0 +1,46 @@
+version: '2'
+built_at: '2024-10-08T17:40:45.325529'
+image_name: local
+docker_image: null
+conda_env: local
+apis:
+- shields
+- agents
+- models
+- memory
+- memory_banks
+- inference
+- safety
+providers:
+  inference:
+  - provider_id: ollama0
+    provider_type: remote::ollama
+    config:
+      url: http://127.0.0.1:14343
+  safety:
+  - provider_id: meta0
+    provider_type: meta-reference
+    config:
+      llama_guard_shield:
+        model: Llama-Guard-3-1B
+        excluded_categories: []
+        disable_input_check: false
+        disable_output_check: false
+      prompt_guard_shield:
+        model: Prompt-Guard-86M
+  memory:
+  - provider_id: meta0
+    provider_type: meta-reference
+    config: {}
+  agents:
+  - provider_id: meta0
+    provider_type: meta-reference
+    config:
+      persistence_store:
+        namespace: null
+        type: sqlite
+        db_path: ~/.llama/runtime/kvstore.db
+  telemetry:
+  - provider_id: meta0
+    provider_type: meta-reference
+    config: {}

distributions/remote-vllm/gpu/compose.yaml

@@ -0,0 +1,48 @@
+services:
+  ollama:
+    image: ollama/ollama:latest
+    network_mode: "host"
+    volumes:
+      - ollama:/root/.ollama # this solution synchronizes with the docker volume and loads the model rocket fast
+    ports:
+      - "11434:11434"
+    devices:
+      - nvidia.com/gpu=all
+    environment:
+      - CUDA_VISIBLE_DEVICES=0
+    command: []
+    deploy:
+      resources:
+        reservations:
+          devices:
+          - driver: nvidia
+            # that's the closest analogue to --gpus; provide
+            # an integer amount of devices or 'all'
+            count: 1
+            # Devices are reserved using a list of capabilities, making
+            # capabilities the only required field. A device MUST
+            # satisfy all the requested capabilities for a successful
+            # reservation.
+            capabilities: [gpu]
+    runtime: nvidia
+  llamastack:
+    depends_on:
+    - ollama
+    image: llamastack/distribution-ollama
+    network_mode: "host"
+    volumes:
+      - ~/.llama:/root/.llama
+      # Link to ollama run.yaml file
+      - ./run.yaml:/root/llamastack-run-ollama.yaml
+    ports:
+      - "5000:5000"
+    # Hack: wait for ollama server to start before starting docker
+    entrypoint: bash -c "sleep 60; python -m llama_stack.distribution.server.server --yaml_config /root/llamastack-run-ollama.yaml"
+    deploy:
+      restart_policy:
+        condition: on-failure
+        delay: 3s
+        max_attempts: 5
+        window: 60s
+volumes:
+  ollama:

distributions/remote-vllm/gpu/run.yaml

@@ -0,0 +1,46 @@
+version: '2'
+built_at: '2024-10-08T17:40:45.325529'
+image_name: local
+docker_image: null
+conda_env: local
+apis:
+- shields
+- agents
+- models
+- memory
+- memory_banks
+- inference
+- safety
+providers:
+  inference:
+  - provider_id: ollama0
+    provider_type: remote::ollama
+    config:
+      url: http://127.0.0.1:14343
+  safety:
+  - provider_id: meta0
+    provider_type: meta-reference
+    config:
+      llama_guard_shield:
+        model: Llama-Guard-3-1B
+        excluded_categories: []
+        disable_input_check: false
+        disable_output_check: false
+      prompt_guard_shield:
+        model: Prompt-Guard-86M
+  memory:
+  - provider_id: meta0
+    provider_type: meta-reference
+    config: {}
+  agents:
+  - provider_id: meta0
+    provider_type: meta-reference
+    config:
+      persistence_store:
+        namespace: null
+        type: sqlite
+        db_path: ~/.llama/runtime/kvstore.db
+  telemetry:
+  - provider_id: meta0
+    provider_type: meta-reference
+    config: {}

docs/source/getting_started/distributions/self_hosted_distro/ollama.md

@@ -7,16 +7,22 @@ The `llamastack/distribution-ollama` distribution consists of the following prov
 | **Provider(s)** 	| remote::ollama 	| meta-reference 	| remote::pgvector, remote::chroma 	| remote::ollama 	| meta-reference 	|
 
 
-### Docker: Start a Distribution (Single Node GPU)
+### 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.
+
+```
+$ 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
+$ cd distributions/ollama-gpu; docker compose up
 ```
 
 You will see outputs similar to following ---
@@ -38,18 +44,6 @@ To kill the server
 docker compose down
 ```
 
-### Docker: Start the Distribution (Single Node CPU)
-
-> [!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.
-
-```
-$ 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.

docs/source/getting_started/index.md

@@ -144,7 +144,11 @@ docker compose down
 
 :::{tab-item} ollama
 ```
-$ cd llama-stack/distributions/ollama/cpu && docker compose up
+$ cd llama-stack/distributions/ollama && docker compose up
+
+# OR
+
+$ cd llama-stack/distributions/ollama-gpu && docker compose up
 ```
 
 You will see outputs similar to following ---