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16
docs/source/distributions/self_hosted_distro/bedrock.md
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@ -1,6 +1,3 @@
---
orphan: true
---
# Bedrock Distribution
```{toctree}
@ -15,10 +12,14 @@ The `llamastack/distribution-bedrock` distribution consists of the following pro
| API | Provider(s) |
|-----|-------------|
| agents | `inline::meta-reference` |
| datasetio | `remote::huggingface`, `inline::localfs` |
| eval | `inline::meta-reference` |
| inference | `remote::bedrock` |
| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
| safety | `remote::bedrock` |
| scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
| telemetry | `inline::meta-reference` |
| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
@ -26,8 +27,15 @@ The `llamastack/distribution-bedrock` distribution consists of the following pro
The following environment variables can be configured:
- `LLAMASTACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `LLAMA_STACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
### Models
The following models are available by default:
- `meta-llama/Llama-3.1-8B-Instruct (meta.llama3-1-8b-instruct-v1:0)`
- `meta-llama/Llama-3.1-70B-Instruct (meta.llama3-1-70b-instruct-v1:0)`
- `meta-llama/Llama-3.1-405B-Instruct-FP8 (meta.llama3-1-405b-instruct-v1:0)`
### Prerequisite: API Keys

15
docs/source/distributions/self_hosted_distro/cerebras.md
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@ -1,5 +1,15 @@
---
orphan: true
---
# Cerebras Distribution
```{toctree}
:maxdepth: 2
:hidden:
self
```
The `llamastack/distribution-cerebras` distribution consists of the following provider configurations.
| API | Provider(s) |
@ -9,13 +19,14 @@ The `llamastack/distribution-cerebras` distribution consists of the following pr
| memory | `inline::meta-reference` |
| safety | `inline::llama-guard` |
| telemetry | `inline::meta-reference` |
| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
### Environment Variables
The following environment variables can be configured:
- `LLAMASTACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `LLAMA_STACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `CEREBRAS_API_KEY`: Cerebras API Key (default: ``)
### Models
@ -23,7 +34,7 @@ The following environment variables can be configured:
The following models are available by default:
- `meta-llama/Llama-3.1-8B-Instruct (llama3.1-8b)`
- `meta-llama/Llama-3.1-70B-Instruct (llama3.1-70b)`
- `meta-llama/Llama-3.3-70B-Instruct (llama-3.3-70b)`
### Prerequisite: API Keys

25
docs/source/distributions/self_hosted_distro/fireworks.md
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@ -15,32 +15,37 @@ The `llamastack/distribution-fireworks` distribution consists of the following p
| API | Provider(s) |
|-----|-------------|
| agents | `inline::meta-reference` |
| datasetio | `remote::huggingface`, `inline::localfs` |
| eval | `inline::meta-reference` |
| inference | `remote::fireworks` |
| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
| safety | `inline::llama-guard` |
| scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
| telemetry | `inline::meta-reference` |
| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
### Environment Variables
The following environment variables can be configured:
- `LLAMASTACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `LLAMA_STACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `FIREWORKS_API_KEY`: Fireworks.AI API Key (default: ``)
### Models
The following models are available by default:
- `meta-llama/Llama-3.1-8B-Instruct (fireworks/llama-v3p1-8b-instruct)`
- `meta-llama/Llama-3.1-70B-Instruct (fireworks/llama-v3p1-70b-instruct)`
- `meta-llama/Llama-3.1-405B-Instruct-FP8 (fireworks/llama-v3p1-405b-instruct)`
- `meta-llama/Llama-3.2-1B-Instruct (fireworks/llama-v3p2-1b-instruct)`
- `meta-llama/Llama-3.2-3B-Instruct (fireworks/llama-v3p2-3b-instruct)`
- `meta-llama/Llama-3.2-11B-Vision-Instruct (fireworks/llama-v3p2-11b-vision-instruct)`
- `meta-llama/Llama-3.2-90B-Vision-Instruct (fireworks/llama-v3p2-90b-vision-instruct)`
- `meta-llama/Llama-Guard-3-8B (fireworks/llama-guard-3-8b)`
- `meta-llama/Llama-Guard-3-11B-Vision (fireworks/llama-guard-3-11b-vision)`
- `meta-llama/Llama-3.1-8B-Instruct (accounts/fireworks/models/llama-v3p1-8b-instruct)`
- `meta-llama/Llama-3.1-70B-Instruct (accounts/fireworks/models/llama-v3p1-70b-instruct)`
- `meta-llama/Llama-3.1-405B-Instruct-FP8 (accounts/fireworks/models/llama-v3p1-405b-instruct)`
- `meta-llama/Llama-3.2-1B-Instruct (accounts/fireworks/models/llama-v3p2-1b-instruct)`
- `meta-llama/Llama-3.2-3B-Instruct (accounts/fireworks/models/llama-v3p2-3b-instruct)`
- `meta-llama/Llama-3.2-11B-Vision-Instruct (accounts/fireworks/models/llama-v3p2-11b-vision-instruct)`
- `meta-llama/Llama-3.2-90B-Vision-Instruct (accounts/fireworks/models/llama-v3p2-90b-vision-instruct)`
- `meta-llama/Llama-3.3-70B-Instruct (accounts/fireworks/models/llama-v3p3-70b-instruct)`
- `meta-llama/Llama-Guard-3-8B (accounts/fireworks/models/llama-guard-3-8b)`
- `meta-llama/Llama-Guard-3-11B-Vision (accounts/fireworks/models/llama-guard-3-11b-vision)`
### Prerequisite: API Keys

8
docs/source/distributions/self_hosted_distro/meta-reference-gpu.md
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@ -15,10 +15,14 @@ The `llamastack/distribution-meta-reference-gpu` distribution consists of the fo
| API | Provider(s) |
|-----|-------------|
| agents | `inline::meta-reference` |
| datasetio | `remote::huggingface`, `inline::localfs` |
| eval | `inline::meta-reference` |
| inference | `inline::meta-reference` |
| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
| safety | `inline::llama-guard` |
| scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
| telemetry | `inline::meta-reference` |
| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
Note that you need access to nvidia GPUs to run this distribution. This distribution is not compatible with CPU-only machines or machines with AMD GPUs.
@ -27,7 +31,7 @@ Note that you need access to nvidia GPUs to run this distribution. This distribu
The following environment variables can be configured:
- `LLAMASTACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `LLAMA_STACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `INFERENCE_MODEL`: Inference model loaded into the Meta Reference server (default: `meta-llama/Llama-3.2-3B-Instruct`)
- `INFERENCE_CHECKPOINT_DIR`: Directory containing the Meta Reference model checkpoint (default: `null`)
- `SAFETY_MODEL`: Name of the safety (Llama-Guard) model to use (default: `meta-llama/Llama-Guard-3-1B`)
@ -57,6 +61,7 @@ LLAMA_STACK_PORT=5001
docker run \
-it \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ~/.llama:/root/.llama \
llamastack/distribution-meta-reference-gpu \
--port $LLAMA_STACK_PORT \
--env INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct
@ -68,6 +73,7 @@ If you are using Llama Stack Safety / Shield APIs, use:
docker run \
-it \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ~/.llama:/root/.llama \
llamastack/distribution-meta-reference-gpu \
--port $LLAMA_STACK_PORT \
--env INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \

8
docs/source/distributions/self_hosted_distro/meta-reference-quantized-gpu.md
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@ -15,10 +15,14 @@ The `llamastack/distribution-meta-reference-quantized-gpu` distribution consists
| API | Provider(s) |
|-----|-------------|
| agents | `inline::meta-reference` |
| datasetio | `remote::huggingface`, `inline::localfs` |
| eval | `inline::meta-reference` |
| inference | `inline::meta-reference-quantized` |
| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
| safety | `inline::llama-guard` |
| scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
| telemetry | `inline::meta-reference` |
| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
The only difference vs. the `meta-reference-gpu` distribution is that it has support for more efficient inference -- with fp8, int4 quantization, etc.
@ -29,7 +33,7 @@ Note that you need access to nvidia GPUs to run this distribution. This distribu
The following environment variables can be configured:
- `LLAMASTACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `LLAMA_STACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `INFERENCE_MODEL`: Inference model loaded into the Meta Reference server (default: `meta-llama/Llama-3.2-3B-Instruct`)
- `INFERENCE_CHECKPOINT_DIR`: Directory containing the Meta Reference model checkpoint (default: `null`)
@ -57,6 +61,7 @@ LLAMA_STACK_PORT=5001
docker run \
-it \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ~/.llama:/root/.llama \
llamastack/distribution-meta-reference-quantized-gpu \
--port $LLAMA_STACK_PORT \
--env INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct
@ -68,6 +73,7 @@ If you are using Llama Stack Safety / Shield APIs, use:
docker run \
-it \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ~/.llama:/root/.llama \
llamastack/distribution-meta-reference-quantized-gpu \
--port $LLAMA_STACK_PORT \
--env INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \

8
docs/source/distributions/self_hosted_distro/ollama.md
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@ -15,17 +15,21 @@ The `llamastack/distribution-ollama` distribution consists of the following prov
| API | Provider(s) |
|-----|-------------|
| agents | `inline::meta-reference` |
| datasetio | `remote::huggingface`, `inline::localfs` |
| eval | `inline::meta-reference` |
| inference | `remote::ollama` |
| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
| safety | `inline::llama-guard` |
| scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
| telemetry | `inline::meta-reference` |
| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
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`)
- `LLAMA_STACK_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`)
@ -119,7 +123,7 @@ llama stack run ./run-with-safety.yaml \
### (Optional) Update Model Serving Configuration
```{note}
Please check the [model_aliases](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers/remote/inference/ollama/ollama.py#L45) variable for supported Ollama models.
Please check the [model_aliases](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers/remote/inference/ollama/ollama.py#L45) for the supported Ollama models.
```
To serve a new model with `ollama`

5
docs/source/distributions/self_hosted_distro/remote-vllm.md
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@ -18,6 +18,7 @@ The `llamastack/distribution-remote-vllm` distribution consists of the following
| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
| safety | `inline::llama-guard` |
| telemetry | `inline::meta-reference` |
| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
You can use this distribution if you have GPUs and want to run an independent vLLM server container for running inference.
@ -26,9 +27,9 @@ You can use this distribution if you have GPUs and want to run an independent vL
The following environment variables can be configured:
- `LLAMASTACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `LLAMA_STACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `INFERENCE_MODEL`: Inference model loaded into the vLLM server (default: `meta-llama/Llama-3.2-3B-Instruct`)
- `VLLM_URL`: URL of the vLLM server with the main inference model (default: `http://host.docker.internal:5100}/v1`)
- `VLLM_URL`: URL of the vLLM server with the main inference model (default: `http://host.docker.internal:5100/v1`)
- `MAX_TOKENS`: Maximum number of tokens for generation (default: `4096`)
- `SAFETY_VLLM_URL`: URL of the vLLM server with the safety model (default: `http://host.docker.internal:5101/v1`)
- `SAFETY_MODEL`: Name of the safety (Llama-Guard) model to use (default: `meta-llama/Llama-Guard-3-1B`)

6
docs/source/distributions/self_hosted_distro/tgi.md
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@ -16,10 +16,14 @@ The `llamastack/distribution-tgi` distribution consists of the following provide
| API | Provider(s) |
|-----|-------------|
| agents | `inline::meta-reference` |
| datasetio | `remote::huggingface`, `inline::localfs` |
| eval | `inline::meta-reference` |
| inference | `remote::tgi` |
| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
| safety | `inline::llama-guard` |
| scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
| telemetry | `inline::meta-reference` |
| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
You can use this distribution if you have GPUs and want to run an independent TGI server container for running inference.
@ -28,7 +32,7 @@ You can use this distribution if you have GPUs and want to run an independent TG
The following environment variables can be configured:
- `LLAMASTACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `LLAMA_STACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `INFERENCE_MODEL`: Inference model loaded into the TGI server (default: `meta-llama/Llama-3.2-3B-Instruct`)
- `TGI_URL`: URL of the TGI server with the main inference model (default: `http://127.0.0.1:8080}/v1`)
- `TGI_SAFETY_URL`: URL of the TGI server with the safety model (default: `http://127.0.0.1:8081/v1`)

7
docs/source/distributions/self_hosted_distro/together.md
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@ -15,17 +15,21 @@ The `llamastack/distribution-together` distribution consists of the following pr
| API | Provider(s) |
|-----|-------------|
| agents | `inline::meta-reference` |
| datasetio | `remote::huggingface`, `inline::localfs` |
| eval | `inline::meta-reference` |
| inference | `remote::together` |
| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
| safety | `inline::llama-guard` |
| scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
| telemetry | `inline::meta-reference` |
| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
### Environment Variables
The following environment variables can be configured:
- `LLAMASTACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `LLAMA_STACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `TOGETHER_API_KEY`: Together.AI API Key (default: ``)
### Models
@ -38,6 +42,7 @@ The following models are available by default:
- `meta-llama/Llama-3.2-3B-Instruct`
- `meta-llama/Llama-3.2-11B-Vision-Instruct`
- `meta-llama/Llama-3.2-90B-Vision-Instruct`
- `meta-llama/Llama-3.3-70B-Instruct`
- `meta-llama/Llama-Guard-3-8B`
- `meta-llama/Llama-Guard-3-11B-Vision`