# Build your own Distribution This guide will walk you through the steps to get started with building a Llama Stack distribution from scratch with your choice of API providers. ### Llama Stack Build In order to build your own distribution, we recommend you clone the `llama-stack` repository. ``` git clone git@github.com:meta-llama/llama-stack.git cd llama-stack pip install -e . ``` Use the CLI to build your distribution. The main points to consider are: 1. **Image Type** - Do you want a Conda / venv environment or a Container (eg. Docker) 2. **Template** - Do you want to use a template to build your distribution? or start from scratch ? 3. **Config** - Do you want to use a pre-existing config file to build your distribution? ``` llama stack build -h usage: llama stack build [-h] [--config CONFIG] [--template TEMPLATE] [--list-templates] [--image-type {conda,container,venv}] [--image-name IMAGE_NAME] [--print-deps-only] Build a Llama stack container options: -h, --help show this help message and exit --config CONFIG Path to a config file to use for the build. You can find example configs in llama_stack/distribution/**/build.yaml. If this argument is not provided, you will be prompted to enter information interactively --template TEMPLATE Name of the example template config to use for build. You may use `llama stack build --list-templates` to check out the available templates --list-templates Show the available templates for building a Llama Stack distribution --image-type {conda,container,venv} Image Type to use for the build. This can be either conda or container or venv. If not specified, will use the image type from the template config. --image-name IMAGE_NAME [for image-type=conda] Name of the conda environment to use for the build. If not specified, currently active Conda environment will be used. If no Conda environment is active, you must specify a name. --print-deps-only Print the dependencies for the stack only, without building the stack ``` After this step is complete, a file named `-build.yaml` and template file `-run.yaml` will be generated and saved at the output file path specified at the end of the command. ::::{tab-set} :::{tab-item} Building from a template 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 | Description | +------------------------------+-----------------------------------------------------------------------------+ | hf-serverless | Use (an external) Hugging Face Inference Endpoint for running LLM inference | +------------------------------+-----------------------------------------------------------------------------+ | together | Use Together.AI for running LLM inference | +------------------------------+-----------------------------------------------------------------------------+ | vllm-gpu | Use a built-in vLLM engine for running LLM inference | +------------------------------+-----------------------------------------------------------------------------+ | experimental-post-training | Experimental template for post training | +------------------------------+-----------------------------------------------------------------------------+ | remote-vllm | Use (an external) vLLM server for running LLM inference | +------------------------------+-----------------------------------------------------------------------------+ | fireworks | Use Fireworks.AI for running LLM inference | +------------------------------+-----------------------------------------------------------------------------+ | tgi | Use (an external) TGI server for running LLM inference | +------------------------------+-----------------------------------------------------------------------------+ | bedrock | Use AWS Bedrock for running LLM inference and safety | +------------------------------+-----------------------------------------------------------------------------+ | meta-reference-gpu | Use Meta Reference for running LLM inference | +------------------------------+-----------------------------------------------------------------------------+ | nvidia | Use NVIDIA NIM for running LLM inference | +------------------------------+-----------------------------------------------------------------------------+ | meta-reference-quantized-gpu | Use Meta Reference with fp8, int4 quantization for running LLM inference | +------------------------------+-----------------------------------------------------------------------------+ | cerebras | Use Cerebras for running LLM inference | +------------------------------+-----------------------------------------------------------------------------+ | ollama | Use (an external) Ollama server for running LLM inference | +------------------------------+-----------------------------------------------------------------------------+ | hf-endpoint | Use (an external) Hugging Face Inference Endpoint for running LLM inference | +------------------------------+-----------------------------------------------------------------------------+ ``` You may then pick a template to build your distribution with providers fitted to your liking. For example, to build a distribution with TGI as the inference provider, you can run: ``` $ llama stack build --template tgi ... You can now edit ~/.llama/distributions/llamastack-tgi/tgi-run.yaml and run `llama stack run ~/.llama/distributions/llamastack-tgi/tgi-run.yaml` ``` ::: :::{tab-item} Building from Scratch If the provided templates do not fit your use case, you 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. It would be best to start with a template and understand the structure of the config file and the various concepts ( APIS, providers, resources, etc.) before starting from scratch. ``` llama stack build > Enter a name for your Llama Stack (e.g. my-local-stack): my-stack > Enter the image type you want your Llama Stack to be built as (container or conda): conda Llama Stack is composed of several APIs working together. Let's select the provider types (implementations) you want to use for these APIs. Tip: use to see options for the providers. > Enter provider for API inference: inline::meta-reference > Enter provider for API safety: inline::llama-guard > Enter provider for API agents: inline::meta-reference > Enter provider for API memory: inline::faiss > Enter provider for API datasetio: inline::meta-reference > Enter provider for API scoring: inline::meta-reference > Enter provider for API eval: inline::meta-reference > Enter provider for API telemetry: inline::meta-reference > (Optional) Enter a short description for your Llama Stack: You can now edit ~/.llama/distributions/llamastack-my-local-stack/my-local-stack-run.yaml and run `llama stack run ~/.llama/distributions/llamastack-my-local-stack/my-local-stack-run.yaml` ``` ::: :::{tab-item} Building from a pre-existing build 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/templates/*build.yaml`. ``` $ 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: inline::faiss safety: inline::llama-guard agents: inline::meta-reference telemetry: inline::meta-reference image_type: conda ``` ``` llama stack build --config llama_stack/templates/ollama/build.yaml ``` ::: :::{tab-item} Building Container > [!TIP] > Podman is supported as an alternative to Docker. Set `CONTAINER_BINARY` to `podman` in your environment to use Podman. To build a container image, you may start off from a template and use the `--image-type container` flag to specify `container` as the build image type. ``` llama stack build --template ollama --image-type container ``` ``` $ llama stack build --template ollama --image-type container ... Containerfile created successfully in /tmp/tmp.viA3a3Rdsg/ContainerfileFROM python:3.10-slim ... You can now edit ~/meta-llama/llama-stack/tmp/configs/ollama-run.yaml and run `llama stack run ~/meta-llama/llama-stack/tmp/configs/ollama-run.yaml` ``` After this step is successful, you should be able to find the built container image and test it with `llama stack run `. ::: :::: ### Running your Stack server 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 build` step. ``` llama stack run -h usage: llama stack run [-h] [--port PORT] [--image-name IMAGE_NAME] [--disable-ipv6] [--env KEY=VALUE] [--tls-keyfile TLS_KEYFILE] [--tls-certfile TLS_CERTFILE] [--image-type {conda,container,venv}] config start the server for a Llama Stack Distribution. You should have already built (or downloaded) and configured the distribution. positional arguments: config Path to config file to use for the run options: -h, --help show this help message and exit --port PORT Port to run the server on. Defaults to 8321 --image-name IMAGE_NAME Name of the image to run. Defaults to the current conda environment --disable-ipv6 Disable IPv6 support --env KEY=VALUE Environment variables to pass to the server in KEY=VALUE format. Can be specified multiple times. --tls-keyfile TLS_KEYFILE Path to TLS key file for HTTPS --tls-certfile TLS_CERTFILE Path to TLS certificate file for HTTPS --image-type {conda,container,venv} Image Type used during the build. This can be either conda or container or venv. ``` ``` # Start using template name llama stack run tgi # Start using config file llama stack run ~/.llama/distributions/llamastack-my-local-stack/my-local-stack-run.yaml # Start using a venv llama stack run --image-type venv ~/.llama/distributions/llamastack-my-local-stack/my-local-stack-run.yaml # Start using a conda environment llama stack run --image-type conda ~/.llama/distributions/llamastack-my-local-stack/my-local-stack-run.yaml ``` ``` $ llama stack run ~/.llama/distributions/llamastack-my-local-stack/my-local-stack-run.yaml Serving API inspect GET /health GET /providers/list GET /routes/list Serving API inference POST /inference/chat_completion POST /inference/completion POST /inference/embeddings ... Serving API agents POST /agents/create POST /agents/session/create POST /agents/turn/create POST /agents/delete POST /agents/session/delete POST /agents/session/get POST /agents/step/get POST /agents/turn/get Listening on ['::', '0.0.0.0']:8321 INFO: Started server process [2935911] INFO: Waiting for application startup. INFO: Application startup complete. INFO: Uvicorn running on http://['::', '0.0.0.0']:8321 (Press CTRL+C to quit) INFO: 2401:db00:35c:2d2b:face:0:c9:0:54678 - "GET /models/list HTTP/1.1" 200 OK ``` ### Troubleshooting If you encounter any issues, ask questions in our discord or search through our [GitHub Issues](https://github.com/meta-llama/llama-stack/issues), or file an new issue.