Upgrade README a bit

README.md

@@ -1,48 +1,79 @@
-<img src="https://github.com/user-attachments/assets/33d9576d-95ea-468d-95e2-8fa233205a50" width="480" title="Llama Stack" alt="Llama Stack"/>
-
 # Llama Stack
 
 [![PyPI version](https://img.shields.io/pypi/v/llama_stack.svg)](https://pypi.org/project/llama_stack/)
 [![PyPI - Downloads](https://img.shields.io/pypi/dm/llama-stack)](https://pypi.org/project/llama-stack/)
 [![Discord](https://img.shields.io/discord/1257833999603335178)](https://discord.gg/llama-stack)
 
-[**Quick Start**](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html) | [**Documentation**](https://llama-stack.readthedocs.io/en/latest/index.html) | [**Zero2Hero Guide**](https://github.com/meta-llama/llama-stack/tree/main/docs/zero_to_hero_guide)
+[**Quick Start**](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html) | [**Documentation**](https://llama-stack.readthedocs.io/en/latest/index.html) | [**Zero-to-Hero Guide**](https://github.com/meta-llama/llama-stack/tree/main/docs/zero_to_hero_guide)
 
-This repository contains the Llama Stack API specifications as well as API Providers and Llama Stack Distributions.
+Llama Stack defines and standardizes the set of core building blocks needed to bring generative AI applications to market. These building blocks are presented in the form of interoperable APIs with a broad set of Service Providers providing their implementations.
 
-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.
+<div style="text-align: center;">
+  <img
+    src="https://github.com/user-attachments/assets/33d9576d-95ea-468d-95e2-8fa233205a50"
+    width="480"
+    title="Llama Stack"
+    alt="Llama Stack"
+  />
+</div>
 
-The Stack APIs are rapidly improving, but still very much work in progress and we invite feedback as well as direct contributions.
+Our goal is to provide pre-packaged implementations which can be operated in a variety of deployment environments: developers start iterating with Desktops or their mobile devices and can seamlessly transition to on-prem or public cloud deployments. At every point in this transition, the same set of APIs and the same developer experience is available.
+
+> ⚠️ **Note**
+> The Stack APIs are rapidly improving, but still very much work in progress and we invite feedback as well as direct contributions.
 
 
 ## APIs
 
-The Llama Stack consists of the following set of APIs:
+We have working implementations of the following APIs today:
-
 - Inference
 - Safety
 - Memory
-- Agentic System
+- Agents
-- Evaluation
+- Eval
+- Telemetry
+
+Alongside these APIs, we also related APIs for operating with associated resources (see [Concepts](https://llama-stack.readthedocs.io/en/latest/concepts/index.html#resources)):
+
+- Models
+- Shields
+- Memory Banks
+- EvalTasks
+- Datasets
+- Scoring Functions
+
+We are also working on the following APIs which will be released soon:
+
 - Post Training
 - Synthetic Data Generation
 - Reward Scoring
 
 Each of the APIs themselves is a collection of REST endpoints.
 
+## Philosophy
 
-## API Providers
+### Service-oriented design
 
-A Provider is what makes the API real -- they provide the actual implementation backing the API.
+Unlike other frameworks, Llama Stack is built with a service-oriented, REST API-first approach. Such a design not only allows for seamless transitions from a local to remote deployments, but also forces the design to be more declarative. We believe this restriction can result in a much simpler, robust developer experience. This will necessarily trade-off against expressivity however if we get the APIs right, it can lead to a very powerful platform.
 
-As an example, for Inference, we could have the implementation be backed by open source libraries like `[ torch | vLLM | TensorRT ]` as possible options.
+### Composability
 
-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.
+We expect the set of APIs we design to be composable. An Agent abstractly depends on { Inference, Memory, Safety } APIs but does not care about the actual implementation details. Safety itself may require model inference and hence can depend on the Inference API.
 
+### Turnkey one-stop solutions
 
-## Llama Stack Distribution
+We expect to provide turnkey solutions for popular deployment scenarios. It should be easy to deploy a Llama Stack server on AWS or on a private data center. Either of these should allow a developer to get started with powerful agentic apps, model evaluations or fine-tuning services in a matter of minutes. They should all result in the same uniform observability and developer experience.
+
+### Focus on Llama models
+
+As a Meta initiated project, we have started by explicitly focusing on Meta's Llama series of models. Supporting the broad set of open models is no easy task and we want to start with models we understand best.
+
+### Supporting the Ecosystem
+
+There is a vibrant ecosystem of Providers which provide efficient inference or scalable vector stores or powerful observability solutions. We want to make sure it is easy for developers to pick and choose the best implementations for their use cases. We also want to make sure it is easy for new Providers to onboard and participate in the ecosystem.
+
+Additionally, we have designed every element of the Stack such that APIs as well as Resources (like Models) can be federated.
 
-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.
 
 ## Supported Llama Stack Implementations
 ### API Providers
@@ -93,9 +124,9 @@ You have two ways to install this repository:
     $CONDA_PREFIX/bin/pip install -e .
    ```
 
-## Documentations
+## Documentation
 
-Please checkout our [Documentations](https://llama-stack.readthedocs.io/en/latest/index.html) page for more details.
+Please checkout our [Documentation](https://llama-stack.readthedocs.io/en/latest/index.html) page for more details.
 
 * [CLI reference](https://llama-stack.readthedocs.io/en/latest/cli_reference/index.html)
     * Guide using `llama` CLI to work with Llama models (download, study prompts), and building/starting a Llama Stack distribution.
@@ -103,11 +134,11 @@ Please checkout our [Documentations](https://llama-stack.readthedocs.io/en/lates
     * Quick guide to start a Llama Stack server.
     * [Jupyter notebook](./docs/getting_started.ipynb) to walk-through how to use simple text and vision inference llama_stack_client APIs
     * The complete Llama Stack lesson [Colab notebook](https://colab.research.google.com/drive/1dtVmxotBsI4cGZQNsJRYPrLiDeT0Wnwt) of the new [Llama 3.2 course on Deeplearning.ai](https://learn.deeplearning.ai/courses/introducing-multimodal-llama-3-2/lesson/8/llama-stack).
-    * The [Zero2Hero Guide](https://github.com/meta-llama/llama-stack/tree/main/docs/zero_to_hero_guide) that guide you through all the key components of llama stack with code samples.
+    * A [Zero-to-Hero Guide](https://github.com/meta-llama/llama-stack/tree/main/docs/zero_to_hero_guide) that guide you through all the key components of llama stack with code samples.
 * [Contributing](CONTRIBUTING.md)
     * [Adding a new API Provider](https://llama-stack.readthedocs.io/en/latest/api_providers/new_api_provider.html) to walk-through how to add a new API provider.
 
-## Llama Stack Client SDK
+## Llama Stack Client SDKs
 
 |  **Language** |  **Client SDK** | **Package** |
 | :----: | :----: | :----: |