mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-06-28 02:53:30 +00:00
c810a4184d
* move docs -> source * Add files via upload * mv image * Add files via upload * colocate iOS setup doc * delete image * Add files via upload * fix * delete image * Add files via upload * Update developer_cookbook.md * toctree * wip subfolder * docs update * subfolder * updates * name * updates * index * updates * refactor structure * depth * docs * content * docs * getting started * distributions * fireworks * fireworks * update * theme * theme * theme * pdj theme * pytorch theme * css * theme * agents example * format * index * headers * copy button * test tabs * test tabs * fix * tabs * tab * tabs * sphinx_design * quick start commands * size * width * css * css * download models * asthetic fix * tab format * update * css * width * css * docs * tab based * tab * tabs * docs * style * image * css * color * typo * update docs * missing links * list templates * links * links update * troubleshooting * fix * distributions * docs * fix table * kill llamastack-local-gpu/cpu * Update index.md * Update index.md * mv ios_setup.md * Update ios_setup.md * Add remote_or_local.gif * Update ios_setup.md * release notes * typos * Add ios_setup to index * nav bar * hide torctree * ios image * links update * rename * rename * docs * rename * links * distributions * distributions * distributions * distributions * remove release * remote --------- Co-authored-by: dltn <6599399+dltn@users.noreply.github.com> Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
357 lines
28 KiB
Markdown
357 lines
28 KiB
Markdown
# Developer Guide: Assemble a Llama Stack Distribution
|
|
|
|
> NOTE: This doc may be out-of-date.
|
|
|
|
This guide will walk you through the steps to get started with building a Llama Stack distributiom from scratch with your choice of API providers. Please see the [Getting Started Guide](./getting_started.md) if you just want the basic steps to start a Llama Stack distribution.
|
|
|
|
## Step 1. Build
|
|
In the following steps, imagine we'll be working with a `Meta-Llama3.1-8B-Instruct` model. We will name our build `8b-instruct` to help us remember the config. We will start build our distribution (in the form of a Conda environment, or Docker image). In this step, we will specify:
|
|
- `name`: the name for our distribution (e.g. `8b-instruct`)
|
|
- `image_type`: our build image type (`conda | docker`)
|
|
- `distribution_spec`: our distribution specs for specifying API providers
|
|
- `description`: a short description of the configurations for the distribution
|
|
- `providers`: specifies the underlying implementation for serving each API endpoint
|
|
- `image_type`: `conda` | `docker` to specify whether to build the distribution in the form of Docker image or Conda environment.
|
|
|
|
|
|
At the end of build command, we will generate `<name>-build.yaml` file storing the build configurations.
|
|
|
|
After this step is complete, a file named `<name>-build.yaml` will be generated and saved at the output file path specified at the end of the command.
|
|
|
|
#### Building from scratch
|
|
- For a new user, we could start off with running `llama stack build` which will allow you to a interactively enter wizard where you will be prompted to enter build configurations.
|
|
```
|
|
llama stack build
|
|
```
|
|
|
|
Running the command above will allow you to fill in the configuration to build your Llama Stack distribution, you will see the following outputs.
|
|
|
|
```
|
|
> Enter an unique name for identifying your Llama Stack build distribution (e.g. my-local-stack): 8b-instruct
|
|
> Enter the image type you want your distribution to be built with (docker or conda): conda
|
|
|
|
Llama Stack is composed of several APIs working together. Let's configure the providers (implementations) you want to use for these APIs.
|
|
> Enter the API provider for the inference API: (default=meta-reference): meta-reference
|
|
> Enter the API provider for the safety API: (default=meta-reference): meta-reference
|
|
> Enter the API provider for the agents API: (default=meta-reference): meta-reference
|
|
> Enter the API provider for the memory API: (default=meta-reference): meta-reference
|
|
> Enter the API provider for the telemetry API: (default=meta-reference): meta-reference
|
|
|
|
> (Optional) Enter a short description for your Llama Stack distribution:
|
|
|
|
Build spec configuration saved at ~/.conda/envs/llamastack-my-local-llama-stack/8b-instruct-build.yaml
|
|
```
|
|
|
|
**Ollama (optional)**
|
|
|
|
If you plan to use Ollama for inference, you'll need to install the server [via these instructions](https://ollama.com/download).
|
|
|
|
|
|
#### Building from templates
|
|
- To build from alternative API providers, we provide distribution templates for users to get started building a distribution backed by different providers.
|
|
|
|
The following command will allow you to see the available templates and their corresponding providers.
|
|
```
|
|
llama stack build --list-templates
|
|
```
|
|
|
|
```
|
|
+------------------------------+--------------------------------------------+----------------------------------------------------------------------------------+
|
|
| Template Name | Providers | Description |
|
|
+------------------------------+--------------------------------------------+----------------------------------------------------------------------------------+
|
|
| bedrock | { | Use Amazon Bedrock APIs. |
|
|
| | "inference": "remote::bedrock", | |
|
|
| | "memory": "meta-reference", | |
|
|
| | "safety": "meta-reference", | |
|
|
| | "agents": "meta-reference", | |
|
|
| | "telemetry": "meta-reference" | |
|
|
| | } | |
|
|
+------------------------------+--------------------------------------------+----------------------------------------------------------------------------------+
|
|
| databricks | { | Use Databricks for running LLM inference |
|
|
| | "inference": "remote::databricks", | |
|
|
| | "memory": "meta-reference", | |
|
|
| | "safety": "meta-reference", | |
|
|
| | "agents": "meta-reference", | |
|
|
| | "telemetry": "meta-reference" | |
|
|
| | } | |
|
|
+------------------------------+--------------------------------------------+----------------------------------------------------------------------------------+
|
|
| fireworks | { | Use Fireworks.ai for running LLM inference |
|
|
| | "inference": "remote::fireworks", | |
|
|
| | "memory": [ | |
|
|
| | "meta-reference", | |
|
|
| | "remote::weaviate", | |
|
|
| | "remote::chromadb", | |
|
|
| | "remote::pgvector" | |
|
|
| | ], | |
|
|
| | "safety": "meta-reference", | |
|
|
| | "agents": "meta-reference", | |
|
|
| | "telemetry": "meta-reference" | |
|
|
| | } | |
|
|
+------------------------------+--------------------------------------------+----------------------------------------------------------------------------------+
|
|
| hf-endpoint | { | Like local, but use Hugging Face Inference Endpoints for running LLM inference. |
|
|
| | "inference": "remote::hf::endpoint", | See https://hf.co/docs/api-endpoints. |
|
|
| | "memory": "meta-reference", | |
|
|
| | "safety": "meta-reference", | |
|
|
| | "agents": "meta-reference", | |
|
|
| | "telemetry": "meta-reference" | |
|
|
| | } | |
|
|
+------------------------------+--------------------------------------------+----------------------------------------------------------------------------------+
|
|
| hf-serverless | { | Like local, but use Hugging Face Inference API (serverless) for running LLM |
|
|
| | "inference": "remote::hf::serverless", | inference. |
|
|
| | "memory": "meta-reference", | See https://hf.co/docs/api-inference. |
|
|
| | "safety": "meta-reference", | |
|
|
| | "agents": "meta-reference", | |
|
|
| | "telemetry": "meta-reference" | |
|
|
| | } | |
|
|
+------------------------------+--------------------------------------------+----------------------------------------------------------------------------------+
|
|
| meta-reference-gpu | { | Use code from `llama_stack` itself to serve all llama stack APIs |
|
|
| | "inference": "meta-reference", | |
|
|
| | "memory": [ | |
|
|
| | "meta-reference", | |
|
|
| | "remote::chromadb", | |
|
|
| | "remote::pgvector" | |
|
|
| | ], | |
|
|
| | "safety": "meta-reference", | |
|
|
| | "agents": "meta-reference", | |
|
|
| | "telemetry": "meta-reference" | |
|
|
| | } | |
|
|
+------------------------------+--------------------------------------------+----------------------------------------------------------------------------------+
|
|
| meta-reference-quantized-gpu | { | Use code from `llama_stack` itself to serve all llama stack APIs |
|
|
| | "inference": "meta-reference-quantized", | |
|
|
| | "memory": [ | |
|
|
| | "meta-reference", | |
|
|
| | "remote::chromadb", | |
|
|
| | "remote::pgvector" | |
|
|
| | ], | |
|
|
| | "safety": "meta-reference", | |
|
|
| | "agents": "meta-reference", | |
|
|
| | "telemetry": "meta-reference" | |
|
|
| | } | |
|
|
+------------------------------+--------------------------------------------+----------------------------------------------------------------------------------+
|
|
| ollama | { | Use ollama for running LLM inference |
|
|
| | "inference": "remote::ollama", | |
|
|
| | "memory": [ | |
|
|
| | "meta-reference", | |
|
|
| | "remote::chromadb", | |
|
|
| | "remote::pgvector" | |
|
|
| | ], | |
|
|
| | "safety": "meta-reference", | |
|
|
| | "agents": "meta-reference", | |
|
|
| | "telemetry": "meta-reference" | |
|
|
| | } | |
|
|
+------------------------------+--------------------------------------------+----------------------------------------------------------------------------------+
|
|
| tgi | { | Use TGI for running LLM inference |
|
|
| | "inference": "remote::tgi", | |
|
|
| | "memory": [ | |
|
|
| | "meta-reference", | |
|
|
| | "remote::chromadb", | |
|
|
| | "remote::pgvector" | |
|
|
| | ], | |
|
|
| | "safety": "meta-reference", | |
|
|
| | "agents": "meta-reference", | |
|
|
| | "telemetry": "meta-reference" | |
|
|
| | } | |
|
|
+------------------------------+--------------------------------------------+----------------------------------------------------------------------------------+
|
|
| together | { | Use Together.ai for running LLM inference |
|
|
| | "inference": "remote::together", | |
|
|
| | "memory": [ | |
|
|
| | "meta-reference", | |
|
|
| | "remote::weaviate" | |
|
|
| | ], | |
|
|
| | "safety": "remote::together", | |
|
|
| | "agents": "meta-reference", | |
|
|
| | "telemetry": "meta-reference" | |
|
|
| | } | |
|
|
+------------------------------+--------------------------------------------+----------------------------------------------------------------------------------+
|
|
| vllm | { | Like local, but use vLLM for running LLM inference |
|
|
| | "inference": "vllm", | |
|
|
| | "memory": "meta-reference", | |
|
|
| | "safety": "meta-reference", | |
|
|
| | "agents": "meta-reference", | |
|
|
| | "telemetry": "meta-reference" | |
|
|
| | } | |
|
|
+------------------------------+--------------------------------------------+----------------------------------------------------------------------------------+
|
|
```
|
|
|
|
You may then pick a template to build your distribution with providers fitted to your liking.
|
|
|
|
```
|
|
llama stack build --template tgi
|
|
```
|
|
|
|
```
|
|
$ llama stack build --template tgi
|
|
...
|
|
...
|
|
Build spec configuration saved at ~/.conda/envs/llamastack-tgi/tgi-build.yaml
|
|
You may now run `llama stack configure tgi` or `llama stack configure ~/.conda/envs/llamastack-tgi/tgi-build.yaml`
|
|
```
|
|
|
|
#### Building from config file
|
|
- In addition to templates, you may customize the build to your liking through editing config files and build from config files with the following command.
|
|
|
|
- The config file will be of contents like the ones in `llama_stack/distributions/templates/`.
|
|
|
|
```
|
|
$ cat llama_stack/templates/ollama/build.yaml
|
|
|
|
name: ollama
|
|
distribution_spec:
|
|
description: Like local, but use ollama for running LLM inference
|
|
providers:
|
|
inference: remote::ollama
|
|
memory: meta-reference
|
|
safety: meta-reference
|
|
agents: meta-reference
|
|
telemetry: meta-reference
|
|
image_type: conda
|
|
```
|
|
|
|
```
|
|
llama stack build --config llama_stack/templates/ollama/build.yaml
|
|
```
|
|
|
|
#### How to build distribution with Docker image
|
|
|
|
> [!TIP]
|
|
> Podman is supported as an alternative to Docker. Set `DOCKER_BINARY` to `podman` in your environment to use Podman.
|
|
|
|
To build a docker image, you may start off from a template and use the `--image-type docker` flag to specify `docker` as the build image type.
|
|
|
|
```
|
|
llama stack build --template local --image-type docker
|
|
```
|
|
|
|
Alternatively, you may use a config file and set `image_type` to `docker` in our `<name>-build.yaml` file, and run `llama stack build <name>-build.yaml`. The `<name>-build.yaml` will be of contents like:
|
|
|
|
```
|
|
name: local-docker-example
|
|
distribution_spec:
|
|
description: Use code from `llama_stack` itself to serve all llama stack APIs
|
|
docker_image: null
|
|
providers:
|
|
inference: meta-reference
|
|
memory: meta-reference-faiss
|
|
safety: meta-reference
|
|
agentic_system: meta-reference
|
|
telemetry: console
|
|
image_type: docker
|
|
```
|
|
|
|
The following command allows you to build a Docker image with the name `<name>`
|
|
```
|
|
llama stack build --config <name>-build.yaml
|
|
|
|
Dockerfile created successfully in /tmp/tmp.I0ifS2c46A/DockerfileFROM python:3.10-slim
|
|
WORKDIR /app
|
|
...
|
|
...
|
|
You can run it with: podman run -p 8000:8000 llamastack-docker-local
|
|
Build spec configuration saved at ~/.llama/distributions/docker/docker-local-build.yaml
|
|
```
|
|
|
|
|
|
## Step 2. Configure
|
|
After our distribution is built (either in form of docker or conda environment), we will run the following command to
|
|
```
|
|
llama stack configure [ <docker-image-name> | <path/to/name.build.yaml>]
|
|
```
|
|
- For `conda` environments: <path/to/name.build.yaml> would be the generated build spec saved from Step 1.
|
|
- For `docker` images downloaded from Dockerhub, you could also use <docker-image-name> as the argument.
|
|
- Run `docker images` to check list of available images on your machine.
|
|
|
|
```
|
|
$ llama stack configure tgi
|
|
|
|
Configuring API: inference (meta-reference)
|
|
Enter value for model (existing: Meta-Llama3.1-8B-Instruct) (required):
|
|
Enter value for quantization (optional):
|
|
Enter value for torch_seed (optional):
|
|
Enter value for max_seq_len (existing: 4096) (required):
|
|
Enter value for max_batch_size (existing: 1) (required):
|
|
|
|
Configuring API: memory (meta-reference-faiss)
|
|
|
|
Configuring API: safety (meta-reference)
|
|
Do you want to configure llama_guard_shield? (y/n): y
|
|
Entering sub-configuration for llama_guard_shield:
|
|
Enter value for model (default: Llama-Guard-3-1B) (required):
|
|
Enter value for excluded_categories (default: []) (required):
|
|
Enter value for disable_input_check (default: False) (required):
|
|
Enter value for disable_output_check (default: False) (required):
|
|
Do you want to configure prompt_guard_shield? (y/n): y
|
|
Entering sub-configuration for prompt_guard_shield:
|
|
Enter value for model (default: Prompt-Guard-86M) (required):
|
|
|
|
Configuring API: agentic_system (meta-reference)
|
|
Enter value for brave_search_api_key (optional):
|
|
Enter value for bing_search_api_key (optional):
|
|
Enter value for wolfram_api_key (optional):
|
|
|
|
Configuring API: telemetry (console)
|
|
|
|
YAML configuration has been written to ~/.llama/builds/conda/tgi-run.yaml
|
|
```
|
|
|
|
After this step is successful, you should be able to find a run configuration spec in `~/.llama/builds/conda/tgi-run.yaml` with the following contents. You may edit this file to change the settings.
|
|
|
|
As you can see, we did basic configuration above and configured:
|
|
- inference to run on model `Meta-Llama3.1-8B-Instruct` (obtained from `llama model list`)
|
|
- Llama Guard safety shield with model `Llama-Guard-3-1B`
|
|
- Prompt Guard safety shield with model `Prompt-Guard-86M`
|
|
|
|
For how these configurations are stored as yaml, checkout the file printed at the end of the configuration.
|
|
|
|
Note that all configurations as well as models are stored in `~/.llama`
|
|
|
|
|
|
## Step 3. Run
|
|
Now, let's start the Llama Stack Distribution Server. You will need the YAML configuration file which was written out at the end by the `llama stack configure` step.
|
|
|
|
```
|
|
llama stack run 8b-instruct
|
|
```
|
|
|
|
You should see the Llama Stack server start and print the APIs that it is supporting
|
|
|
|
```
|
|
$ llama stack run 8b-instruct
|
|
|
|
> initializing model parallel with size 1
|
|
> initializing ddp with size 1
|
|
> initializing pipeline with size 1
|
|
Loaded in 19.28 seconds
|
|
NCCL version 2.20.5+cuda12.4
|
|
Finished model load YES READY
|
|
Serving POST /inference/batch_chat_completion
|
|
Serving POST /inference/batch_completion
|
|
Serving POST /inference/chat_completion
|
|
Serving POST /inference/completion
|
|
Serving POST /safety/run_shield
|
|
Serving POST /agentic_system/memory_bank/attach
|
|
Serving POST /agentic_system/create
|
|
Serving POST /agentic_system/session/create
|
|
Serving POST /agentic_system/turn/create
|
|
Serving POST /agentic_system/delete
|
|
Serving POST /agentic_system/session/delete
|
|
Serving POST /agentic_system/memory_bank/detach
|
|
Serving POST /agentic_system/session/get
|
|
Serving POST /agentic_system/step/get
|
|
Serving POST /agentic_system/turn/get
|
|
Listening on :::5000
|
|
INFO: Started server process [453333]
|
|
INFO: Waiting for application startup.
|
|
INFO: Application startup complete.
|
|
INFO: Uvicorn running on http://[::]:5000 (Press CTRL+C to quit)
|
|
```
|
|
|
|
> [!NOTE]
|
|
> Configuration is in `~/.llama/builds/local/conda/tgi-run.yaml`. Feel free to increase `max_seq_len`.
|
|
|
|
> [!IMPORTANT]
|
|
> The "local" distribution inference server currently only supports CUDA. It will not work on Apple Silicon machines.
|
|
|
|
> [!TIP]
|
|
> You might need to use the flag `--disable-ipv6` to Disable IPv6 support
|
|
|
|
This server is running a Llama model locally.
|