From e2a5a2e10d64cae4eb46ec8b1045640bb7b8fd5f Mon Sep 17 00:00:00 2001
From: raghotham <rsm@meta.com>
Date: Tue, 22 Oct 2024 10:15:58 +0530
Subject: [PATCH] first version of readthedocs (#278)

---
 .gitignore                        |   1 +
 .readthedocs.yaml                 |   8 +-
 docs/Makefile                     |  20 ++
 docs/_static/llama-stack-logo.png | Bin 0 -> 71620 bytes
 docs/_static/llama-stack.png      | Bin 0 -> 72643 bytes
 docs/make.bat                     |  35 +++
 docs/requirements.txt             |   3 +
 docs/source/cli_reference.md      | 485 ++++++++++++++++++++++++++++++
 docs/source/conf.py               |  53 ++++
 docs/source/getting_started.md    | 430 ++++++++++++++++++++++++++
 docs/source/index.md              |  40 +++
 11 files changed, 1071 insertions(+), 4 deletions(-)
 create mode 100644 docs/Makefile
 create mode 100644 docs/_static/llama-stack-logo.png
 create mode 100644 docs/_static/llama-stack.png
 create mode 100644 docs/make.bat
 create mode 100644 docs/requirements.txt
 create mode 100644 docs/source/cli_reference.md
 create mode 100644 docs/source/conf.py
 create mode 100644 docs/source/getting_started.md
 create mode 100644 docs/source/index.md

diff --git a/.gitignore b/.gitignore
index d0a5f0056..f6ef5d9ca 100644
--- a/.gitignore
+++ b/.gitignore
@@ -14,3 +14,4 @@ Package.resolved
 *.pte
 *.ipynb_checkpoints*
 .idea
+_build
diff --git a/.readthedocs.yaml b/.readthedocs.yaml
index f89fc906d..f114dbf9b 100644
--- a/.readthedocs.yaml
+++ b/.readthedocs.yaml
@@ -17,7 +17,7 @@ build:
 
 # Build documentation in the "docs/" directory with Sphinx
 sphinx:
-  configuration: docs/conf.py
+  configuration: docs/source/conf.py
 
 # Optionally build your docs in additional formats such as PDF and ePub
 # formats:
@@ -27,6 +27,6 @@ sphinx:
 # Optional but recommended, declare the Python requirements required
 # to build your documentation
 # See https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html
-# python:
-#    install:
-#    - requirements: docs/requirements.txt
+python:
+   install:
+   - requirements: docs/requirements.txt
diff --git a/docs/Makefile b/docs/Makefile
new file mode 100644
index 000000000..92dd33a1a
--- /dev/null
+++ b/docs/Makefile
@@ -0,0 +1,20 @@
+# Minimal makefile for Sphinx documentation
+#
+
+# You can set these variables from the command line, and also
+# from the environment for the first two.
+SPHINXOPTS    ?=
+SPHINXBUILD   ?= sphinx-build
+SOURCEDIR     = source
+BUILDDIR      = _build
+
+# Put it first so that "make" without argument is like "make help".
+help:
+	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+
+.PHONY: help Makefile
+
+# Catch-all target: route all unknown targets to Sphinx using the new
+# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
+%: Makefile
+	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
diff --git a/docs/_static/llama-stack-logo.png b/docs/_static/llama-stack-logo.png
new file mode 100644
index 0000000000000000000000000000000000000000..1899a0fc7f4a814f358e54ed3539fc29c681216b
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diff --git a/docs/make.bat b/docs/make.bat
new file mode 100644
index 000000000..32bb24529
--- /dev/null
+++ b/docs/make.bat
@@ -0,0 +1,35 @@
+@ECHO OFF
+
+pushd %~dp0
+
+REM Command file for Sphinx documentation
+
+if "%SPHINXBUILD%" == "" (
+	set SPHINXBUILD=sphinx-build
+)
+set SOURCEDIR=.
+set BUILDDIR=_build
+
+%SPHINXBUILD% >NUL 2>NUL
+if errorlevel 9009 (
+	echo.
+	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
+	echo.installed, then set the SPHINXBUILD environment variable to point
+	echo.to the full path of the 'sphinx-build' executable. Alternatively you
+	echo.may add the Sphinx directory to PATH.
+	echo.
+	echo.If you don't have Sphinx installed, grab it from
+	echo.https://www.sphinx-doc.org/
+	exit /b 1
+)
+
+if "%1" == "" goto help
+
+%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+goto end
+
+:help
+%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+
+:end
+popd
diff --git a/docs/requirements.txt b/docs/requirements.txt
new file mode 100644
index 000000000..f1f94c681
--- /dev/null
+++ b/docs/requirements.txt
@@ -0,0 +1,3 @@
+sphinx
+myst-parser
+linkify
diff --git a/docs/source/cli_reference.md b/docs/source/cli_reference.md
new file mode 100644
index 000000000..a5ea03673
--- /dev/null
+++ b/docs/source/cli_reference.md
@@ -0,0 +1,485 @@
+# Llama CLI Reference
+
+The `llama` CLI tool helps you setup and use the Llama Stack & agentic systems. It should be available on your path after installing the `llama-stack` package.
+
+## Subcommands
+1. `download`: `llama` cli tools supports downloading the model from Meta or Hugging Face.
+2. `model`: Lists available models and their properties.
+3. `stack`: Allows you to build and run a Llama Stack server. You can read more about this in Step 3 below.
+
+## Sample Usage
+
+```
+llama --help
+```
+<pre style="font-family: monospace;">
+usage: llama [-h] {download,model,stack} ...
+
+Welcome to the Llama CLI
+
+options:
+  -h, --help            show this help message and exit
+
+subcommands:
+  {download,model,stack}
+</pre>
+
+## Step 1. Get the models
+
+You first need to have models downloaded locally.
+
+To download any model you need the **Model Descriptor**.
+This can be obtained by running the command
+```
+llama model list
+```
+
+You should see a table like this:
+
+<pre style="font-family: monospace;">
++----------------------------------+------------------------------------------+----------------+
+| Model Descriptor                 | Hugging Face Repo                        | Context Length |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.1-8B                      | meta-llama/Llama-3.1-8B                  | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.1-70B                     | meta-llama/Llama-3.1-70B                 | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.1-405B:bf16-mp8           | meta-llama/Llama-3.1-405B                | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.1-405B                    | meta-llama/Llama-3.1-405B-FP8            | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.1-405B:bf16-mp16          | meta-llama/Llama-3.1-405B                | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.1-8B-Instruct             | meta-llama/Llama-3.1-8B-Instruct         | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.1-70B-Instruct            | meta-llama/Llama-3.1-70B-Instruct        | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.1-405B-Instruct:bf16-mp8  | meta-llama/Llama-3.1-405B-Instruct       | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.1-405B-Instruct           | meta-llama/Llama-3.1-405B-Instruct-FP8   | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.1-405B-Instruct:bf16-mp16 | meta-llama/Llama-3.1-405B-Instruct       | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.2-1B                      | meta-llama/Llama-3.2-1B                  | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.2-3B                      | meta-llama/Llama-3.2-3B                  | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.2-11B-Vision              | meta-llama/Llama-3.2-11B-Vision          | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.2-90B-Vision              | meta-llama/Llama-3.2-90B-Vision          | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.2-1B-Instruct             | meta-llama/Llama-3.2-1B-Instruct         | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.2-3B-Instruct             | meta-llama/Llama-3.2-3B-Instruct         | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.2-11B-Vision-Instruct     | meta-llama/Llama-3.2-11B-Vision-Instruct | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama3.2-90B-Vision-Instruct     | meta-llama/Llama-3.2-90B-Vision-Instruct | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama-Guard-3-11B-Vision         | meta-llama/Llama-Guard-3-11B-Vision      | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama-Guard-3-1B:int4-mp1        | meta-llama/Llama-Guard-3-1B-INT4         | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama-Guard-3-1B                 | meta-llama/Llama-Guard-3-1B              | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama-Guard-3-8B                 | meta-llama/Llama-Guard-3-8B              | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama-Guard-3-8B:int8-mp1        | meta-llama/Llama-Guard-3-8B-INT8         | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Prompt-Guard-86M                 | meta-llama/Prompt-Guard-86M              | 128K           |
++----------------------------------+------------------------------------------+----------------+
+| Llama-Guard-2-8B                 | meta-llama/Llama-Guard-2-8B              | 4K             |
++----------------------------------+------------------------------------------+----------------+
+</pre>
+
+To download models, you can use the llama download command.
+
+### Downloading from [Meta](https://llama.meta.com/llama-downloads/)
+
+Here is an example download command to get the 3B-Instruct/11B-Vision-Instruct model. You will need META_URL which can be obtained from [here](https://llama.meta.com/docs/getting_the_models/meta/)
+
+Download the required checkpoints using the following commands:
+```bash
+# download the 8B model, this can be run on a single GPU
+llama download --source meta --model-id Llama3.2-3B-Instruct --meta-url META_URL
+
+# you can also get the 70B model, this will require 8 GPUs however
+llama download --source meta --model-id Llama3.2-11B-Vision-Instruct --meta-url META_URL
+
+# llama-agents have safety enabled by default. For this, you will need
+# safety models -- Llama-Guard and Prompt-Guard
+llama download --source meta --model-id Prompt-Guard-86M --meta-url META_URL
+llama download --source meta --model-id Llama-Guard-3-1B --meta-url META_URL
+```
+
+### Downloading from [Hugging Face](https://huggingface.co/meta-llama)
+
+Essentially, the same commands above work, just replace `--source meta` with `--source huggingface`.
+
+```bash
+llama download --source huggingface --model-id  Llama3.1-8B-Instruct --hf-token <HF_TOKEN>
+
+llama download --source huggingface --model-id Llama3.1-70B-Instruct --hf-token <HF_TOKEN>
+
+llama download --source huggingface --model-id Llama-Guard-3-1B --ignore-patterns *original*
+llama download --source huggingface --model-id Prompt-Guard-86M --ignore-patterns *original*
+```
+
+**Important:** Set your environment variable `HF_TOKEN` or pass in `--hf-token` to the command to validate your access. You can find your token at [https://huggingface.co/settings/tokens](https://huggingface.co/settings/tokens).
+
+> **Tip:** Default for `llama download` is to run with `--ignore-patterns *.safetensors` since we use the `.pth` files in the `original` folder. For Llama Guard and Prompt Guard, however, we need safetensors. Hence, please run with `--ignore-patterns original` so that safetensors are downloaded and `.pth` files are ignored.
+
+### Downloading via Ollama
+
+If you're already using ollama, we also have a supported Llama Stack distribution `local-ollama` and you can continue to use ollama for managing model downloads.
+
+```
+ollama pull llama3.1:8b-instruct-fp16
+ollama pull llama3.1:70b-instruct-fp16
+```
+
+> [!NOTE]
+> Only the above two models are currently supported by Ollama.
+
+
+## Step 2: Understand the models
+The `llama model` command helps you explore the model’s interface.
+
+### 2.1 Subcommands
+1. `download`: Download the model from different sources. (meta, huggingface)
+2. `list`: Lists all the models available for download with hardware requirements to deploy the models.
+3. `prompt-format`: Show llama model message formats.
+4. `describe`: Describes all the properties of the model.
+
+### 2.2 Sample Usage
+
+`llama model <subcommand> <options>`
+
+```
+llama model --help
+```
+<pre style="font-family: monospace;">
+usage: llama model [-h] {download,list,prompt-format,describe} ...
+
+Work with llama models
+
+options:
+  -h, --help            show this help message and exit
+
+model_subcommands:
+  {download,list,prompt-format,describe}
+</pre>
+
+You can use the describe command to know more about a model:
+```
+llama model describe -m Llama3.2-3B-Instruct
+```
+### 2.3 Describe
+
+<pre style="font-family: monospace;">
++-----------------------------+----------------------------------+
+| Model                       | Llama3.2-3B-Instruct             |
++-----------------------------+----------------------------------+
+| Hugging Face ID             | meta-llama/Llama-3.2-3B-Instruct |
++-----------------------------+----------------------------------+
+| Description                 | Llama 3.2 3b instruct model      |
++-----------------------------+----------------------------------+
+| Context Length              | 128K tokens                      |
++-----------------------------+----------------------------------+
+| Weights format              | bf16                             |
++-----------------------------+----------------------------------+
+| Model params.json           | {                                |
+|                             |     "dim": 3072,                 |
+|                             |     "n_layers": 28,              |
+|                             |     "n_heads": 24,               |
+|                             |     "n_kv_heads": 8,             |
+|                             |     "vocab_size": 128256,        |
+|                             |     "ffn_dim_multiplier": 1.0,   |
+|                             |     "multiple_of": 256,          |
+|                             |     "norm_eps": 1e-05,           |
+|                             |     "rope_theta": 500000.0,      |
+|                             |     "use_scaled_rope": true      |
+|                             | }                                |
++-----------------------------+----------------------------------+
+| Recommended sampling params | {                                |
+|                             |     "strategy": "top_p",         |
+|                             |     "temperature": 1.0,          |
+|                             |     "top_p": 0.9,                |
+|                             |     "top_k": 0                   |
+|                             | }                                |
++-----------------------------+----------------------------------+
+</pre>
+### 2.4 Prompt Format
+You can even run `llama model prompt-format` see all of the templates and their tokens:
+
+```
+llama model prompt-format -m Llama3.2-3B-Instruct
+```
+![alt text](https://github.com/meta-llama/llama-stack/docs/resources/prompt-format.png)
+
+
+
+You will be shown a Markdown formatted description of the model interface and how prompts / messages are formatted for various scenarios.
+
+**NOTE**: Outputs in terminal are color printed to show special tokens.
+
+
+## Step 3: Building, and Configuring Llama Stack Distributions
+
+- Please see our [Getting Started](getting_started.md) guide for more details on how to build and start a Llama Stack distribution.
+
+### Step 3.1 Build
+In the following steps, imagine we'll be working with a `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): my-local-llama-stack
+> 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/my-local-llama-stack-build.yaml
+```
+
+#### 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
+```
+
+![alt text](https://github.com/meta-llama/llama-stack/docs/resources/list-templates.png)
+
+You may then pick a template to build your distribution with providers fitted to your liking.
+
+```
+llama stack build --template local-tgi --name my-tgi-stack
+```
+
+```
+$ llama stack build --template local-tgi --name my-tgi-stack
+...
+...
+Build spec configuration saved at ~/.conda/envs/llamastack-my-tgi-stack/my-tgi-stack-build.yaml
+You may now run `llama stack configure my-tgi-stack` or `llama stack configure ~/.conda/envs/llamastack-my-tgi-stack/my-tgi-stack-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/distribution/templates/local-ollama-build.yaml
+
+name: local-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/distribution/templates/local-ollama-build.yaml
+```
+
+#### How to build distribution with Docker image
+
+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 --name docker-0
+```
+
+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 3.2 Configure
+After our distribution is built (either in form of docker or conda environment), we will run the following command to
+```
+llama stack configure [ <name> | <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 ~/.llama/distributions/conda/8b-instruct-build.yaml
+
+Configuring API: inference (meta-reference)
+Enter value for model (existing: 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/8b-instruct-run.yaml
+```
+
+After this step is successful, you should be able to find a run configuration spec in `~/.llama/builds/conda/8b-instruct-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 `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 3.3 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 ~/.llama/builds/conda/8b-instruct-run.yaml
+```
+
+You should see the Llama Stack server start and print the APIs that it is supporting
+
+```
+$ llama stack run ~/.llama/builds/local/conda/8b-instruct.yaml
+
+> 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/8b-instruct-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.
+
+### Step 3.4 Test with Client
+Once the server is setup, we can test it with a client to see the example outputs.
+```
+cd /path/to/llama-stack
+conda activate <env>  # any environment containing the llama-stack pip package will work
+
+python -m llama_stack.apis.inference.client localhost 5000
+```
+
+This will run the chat completion client and query the distribution’s /inference/chat_completion API.
+
+Here is an example output:
+```
+User>hello world, write me a 2 sentence poem about the moon
+Assistant> Here's a 2-sentence poem about the moon:
+
+The moon glows softly in the midnight sky,
+A beacon of wonder, as it passes by.
+```
+
+Similarly you can test safety (if you configured llama-guard and/or prompt-guard shields) by:
+
+```
+python -m llama_stack.apis.safety.client localhost 5000
+```
+
+You can find more example scripts with client SDKs to talk with the Llama Stack server in our [llama-stack-apps](https://github.com/meta-llama/llama-stack-apps/tree/main/examples) repo.
diff --git a/docs/source/conf.py b/docs/source/conf.py
new file mode 100644
index 000000000..8f1d4b6ef
--- /dev/null
+++ b/docs/source/conf.py
@@ -0,0 +1,53 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+# Configuration file for the Sphinx documentation builder.
+#
+# For the full list of built-in configuration values, see the documentation:
+# https://www.sphinx-doc.org/en/master/usage/configuration.html
+
+# -- Project information -----------------------------------------------------
+# https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information
+
+project = "llama-stack"
+copyright = "2024, Meta"
+author = "Meta"
+
+# -- General configuration ---------------------------------------------------
+# https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration
+
+extensions = ["myst_parser"]
+
+templates_path = ["_templates"]
+exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"]
+
+myst_enable_extensions = [
+    "amsmath",
+    "attrs_inline",
+    "colon_fence",
+    "deflist",
+    "dollarmath",
+    "fieldlist",
+    "html_admonition",
+    "html_image",
+    # "linkify",
+    "replacements",
+    "smartquotes",
+    "strikethrough",
+    "substitution",
+    "tasklist",
+]
+
+# -- Options for HTML output -------------------------------------------------
+# https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output
+
+html_theme = "alabaster"
+html_theme_options = {
+    "canonical_url": "https://github.com/meta-llama/llama-stack",
+}
+
+html_static_path = ["../_static"]
+html_logo = "../_static/llama-stack-logo.png"
diff --git a/docs/source/getting_started.md b/docs/source/getting_started.md
new file mode 100644
index 000000000..61f8f46c6
--- /dev/null
+++ b/docs/source/getting_started.md
@@ -0,0 +1,430 @@
+# Getting Started
+
+This guide will walk you though the steps to get started on end-to-end flow for LlamaStack. This guide mainly focuses on getting started with building a LlamaStack distribution, and starting up a LlamaStack server. Please see our [documentations](https://github.com/meta-llama/llama-stack/README.md) on what you can do with Llama Stack, and [llama-stack-apps](https://github.com/meta-llama/llama-stack-apps/tree/main) on examples apps built with Llama Stack.
+
+## Installation
+The `llama` CLI tool helps you setup and use the Llama toolchain & agentic systems. It should be available on your path after installing the `llama-stack` package.
+
+You can install this repository as a [package](https://pypi.org/project/llama-stack/) with `pip install llama-stack`
+
+If you want to install from source:
+
+```bash
+mkdir -p ~/local
+cd ~/local
+git clone git@github.com:meta-llama/llama-stack.git
+
+conda create -n stack python=3.10
+conda activate stack
+
+cd llama-stack
+$CONDA_PREFIX/bin/pip install -e .
+```
+
+For what you can do with the Llama CLI, please refer to [CLI Reference](./cli_reference.md).
+
+## Quick Starting Llama Stack Server
+
+### Starting up server via docker
+
+We provide 2 pre-built Docker image of Llama Stack distribution, which can be found in the following links.
+- [llamastack-local-gpu](https://hub.docker.com/repository/docker/llamastack/llamastack-local-gpu/general)
+  - This is a packaged version with our local meta-reference implementations, where you will be running inference locally with downloaded Llama model checkpoints.
+- [llamastack-local-cpu](https://hub.docker.com/repository/docker/llamastack/llamastack-local-cpu/general)
+   - This is a lite version with remote inference where you can hook up to your favourite remote inference framework (e.g. ollama, fireworks, together, tgi) for running inference without GPU.
+
+> [!NOTE]
+> For GPU inference, you need to set these environment variables for specifying local directory containing your model checkpoints, and enable GPU inference to start running docker container.
+```
+export LLAMA_CHECKPOINT_DIR=~/.llama
+```
+
+> [!NOTE]
+> `~/.llama` should be the path containing downloaded weights of Llama models.
+
+
+To download and start running a pre-built docker container, you may use the following commands:
+
+```
+docker run -it -p 5000:5000 -v ~/.llama:/root/.llama --gpus=all llamastack/llamastack-local-gpu
+```
+
+> [!TIP]
+> Pro Tip: We may use `docker compose up` for starting up a distribution with remote providers (e.g. TGI) using [llamastack-local-cpu](https://hub.docker.com/repository/docker/llamastack/llamastack-local-cpu/general). You can checkout [these scripts](https://github.com/meta-llama/llama-stack/llama_stack/distribution/docker/README.md) to help you get started.
+
+### Build->Configure->Run Llama Stack server via conda
+You may also build a LlamaStack distribution from scratch, configure it, and start running the distribution. This is useful for developing on LlamaStack.
+
+**`llama stack build`**
+- You'll be prompted to enter build information interactively.
+```
+llama stack build
+
+> Enter an unique name for identifying your Llama Stack build distribution (e.g. my-local-stack): my-local-stack
+> 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-stack/my-local-stack-build.yaml
+You can now run `llama stack configure my-local-stack`
+```
+
+**`llama stack configure`**
+- Run `llama stack configure <name>` with the name you have previously defined in `build` step.
+```
+llama stack configure <name>
+```
+- You will be prompted to enter configurations for your Llama Stack
+
+```
+$ llama stack configure my-local-stack
+
+Could not find my-local-stack. Trying conda build name instead...
+Configuring API `inference`...
+=== Configuring provider `meta-reference` for API inference...
+Enter value for model (default: Llama3.1-8B-Instruct) (required):
+Do you want to configure quantization? (y/n): n
+Enter value for torch_seed (optional):
+Enter value for max_seq_len (default: 4096) (required):
+Enter value for max_batch_size (default: 1) (required):
+
+Configuring API `safety`...
+=== Configuring provider `meta-reference` for API safety...
+Do you want to configure llama_guard_shield? (y/n): n
+Do you want to configure prompt_guard_shield? (y/n): n
+
+Configuring API `agents`...
+=== Configuring provider `meta-reference` for API agents...
+Enter `type` for persistence_store (options: redis, sqlite, postgres) (default: sqlite):
+
+Configuring SqliteKVStoreConfig:
+Enter value for namespace (optional):
+Enter value for db_path (default: /home/xiyan/.llama/runtime/kvstore.db) (required):
+
+Configuring API `memory`...
+=== Configuring provider `meta-reference` for API memory...
+> Please enter the supported memory bank type your provider has for memory: vector
+
+Configuring API `telemetry`...
+=== Configuring provider `meta-reference` for API telemetry...
+
+> YAML configuration has been written to ~/.llama/builds/conda/my-local-stack-run.yaml.
+You can now run `llama stack run my-local-stack --port PORT`
+```
+
+**`llama stack run`**
+- Run `llama stack run <name>` with the name you have previously defined.
+```
+llama stack run my-local-stack
+
+...
+> initializing model parallel with size 1
+> initializing ddp with size 1
+> initializing pipeline with size 1
+...
+Finished model load YES READY
+Serving POST /inference/chat_completion
+Serving POST /inference/completion
+Serving POST /inference/embeddings
+Serving POST /memory_banks/create
+Serving DELETE /memory_bank/documents/delete
+Serving DELETE /memory_banks/drop
+Serving GET /memory_bank/documents/get
+Serving GET /memory_banks/get
+Serving POST /memory_bank/insert
+Serving GET /memory_banks/list
+Serving POST /memory_bank/query
+Serving POST /memory_bank/update
+Serving POST /safety/run_shield
+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/session/get
+Serving POST /agentic_system/step/get
+Serving POST /agentic_system/turn/get
+Serving GET /telemetry/get_trace
+Serving POST /telemetry/log_event
+Listening on :::5000
+INFO:     Started server process [587053]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+INFO:     Uvicorn running on http://[::]:5000 (Press CTRL+C to quit)
+```
+
+### End-to-end flow of building, configuring, running, and testing a 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
+```
+
+![alt text](https://github.com/meta-llama/llama-stack/docs/resources/list-templates.png)
+
+You may then pick a template to build your distribution with providers fitted to your liking.
+
+```
+llama stack build --template local-tgi --name my-tgi-stack
+```
+
+```
+$ llama stack build --template local-tgi --name my-tgi-stack
+...
+...
+Build spec configuration saved at ~/.conda/envs/llamastack-my-tgi-stack/my-tgi-stack-build.yaml
+You may now run `llama stack configure my-tgi-stack` or `llama stack configure ~/.conda/envs/llamastack-my-tgi-stack/my-tgi-stack-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/distribution/templates/local-ollama-build.yaml
+
+name: local-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/distribution/templates/local-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 --name docker-0
+```
+
+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 [ <name> | <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 8b-instruct
+
+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/8b-instruct-run.yaml
+```
+
+After this step is successful, you should be able to find a run configuration spec in `~/.llama/builds/conda/8b-instruct-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/8b-instruct-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.
+
+### Step 4. Test with Client
+Once the server is setup, we can test it with a client to see the example outputs.
+```
+cd /path/to/llama-stack
+conda activate <env>  # any environment containing the llama-stack pip package will work
+
+python -m llama_stack.apis.inference.client localhost 5000
+```
+
+This will run the chat completion client and query the distribution’s /inference/chat_completion API.
+
+Here is an example output:
+```
+User>hello world, write me a 2 sentence poem about the moon
+Assistant> Here's a 2-sentence poem about the moon:
+
+The moon glows softly in the midnight sky,
+A beacon of wonder, as it passes by.
+```
+
+Similarly you can test safety (if you configured llama-guard and/or prompt-guard shields) by:
+
+```
+python -m llama_stack.apis.safety.client localhost 5000
+```
+
+
+Check out our client SDKs for connecting to Llama Stack server in your preferred language, you can choose from [python](https://github.com/meta-llama/llama-stack-client-python), [node](https://github.com/meta-llama/llama-stack-client-node), [swift](https://github.com/meta-llama/llama-stack-client-swift), and [kotlin](https://github.com/meta-llama/llama-stack-client-kotlin) programming languages to quickly build your applications.
+
+You can find more example scripts with client SDKs to talk with the Llama Stack server in our [llama-stack-apps](https://github.com/meta-llama/llama-stack-apps/tree/main/examples) repo.
diff --git a/docs/source/index.md b/docs/source/index.md
new file mode 100644
index 000000000..7d95eaf40
--- /dev/null
+++ b/docs/source/index.md
@@ -0,0 +1,40 @@
+# llama-stack documentation
+
+Llama Stack defines and standardizes the building blocks needed to bring generative AI applications to market. It empowers developers building agentic applications by giving them options to operate in various environments (on-prem, cloud, single-node, on-device) while relying on a standard API interface and the same DevEx that is certified by Meta.
+
+The Llama Stack defines and standardizes the building blocks needed to bring generative AI applications to market. These blocks span the entire development lifecycle: from model training and fine-tuning, through product evaluation, to building and running AI agents in production. Beyond definition, we are building providers for the Llama Stack APIs. These were developing open-source versions and partnering with providers, ensuring developers can assemble AI solutions using consistent, interlocking pieces across platforms. The ultimate goal is to accelerate innovation in the AI space.
+
+The Stack APIs are rapidly improving, but still very much work in progress and we invite feedback as well as direct contributions.
+
+![Llama Stack](../_static/llama-stack.png)
+
+## APIs
+
+The Llama Stack consists of the following set of APIs:
+
+- Inference
+- Safety
+- Memory
+- Agentic System
+- Evaluation
+- Post Training
+- Synthetic Data Generation
+- Reward Scoring
+Each of the APIs themselves is a collection of REST endpoints.
+
+## API Providers
+
+A Provider is what makes the API real -- they provide the actual implementation backing the API.
+
+As an example, for Inference, we could have the implementation be backed by open source libraries like [ torch | vLLM | TensorRT ] as possible options.
+
+A provider can also be just a pointer to a remote REST service -- for example, cloud providers or dedicated inference providers could serve these APIs.
+
+## Distribution
+
+A Distribution is where APIs and Providers are assembled together to provide a consistent whole to the end application developer. You can mix-and-match providers -- some could be backed by local code and some could be remote. As a hobbyist, you can serve a small model locally, but can choose a cloud provider for a large model. Regardless, the higher level APIs your app needs to work with don't need to change at all. You can even imagine moving across the server / mobile-device boundary as well always using the same uniform set of APIs for developing Generative AI applications.
+
+```{toctree}
+cli_reference.md
+getting_started.md
+```