update getting started

docs/getting_started.md

@@ -88,7 +88,6 @@ In the following steps, imagine we'll be working with a `Meta-Llama3.1-8B-Instru
 - `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
-  - `distribution_type`: an unique name to identify our distribution. The available distributions can be found in [llama_toolchain/configs/distributions/distribution_registry](llama_toolchain/configs/distributions/distribution_registry/) folder in the form of YAML files. You can run `llama stack list-distributions` to see the available distributions.
   - `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.
@@ -96,32 +95,13 @@ In the following steps, imagine we'll be working with a `Meta-Llama3.1-8B-Instru
 #### Build a local distribution with conda
 The following command and specifications allows you to get started with building.
 ```
-llama stack build
+llama stack build <path/to/config>
 ```
-
+- You will be required to pass in a file path to the build.config file (e.g. `./llama_toolchain/configs/distributions/conda/local-conda-example-build.yaml`). We provide some example build config files for configuring different types of distributions in the `./llama_toolchain/configs/distributions/` folder.
-You will be prompted to enter config specifications.
-```
-$ llama stack build
-
-Enter value for name (required): 8b-instruct
-
-Entering sub-configuration for distribution_spec:
-Enter value for distribution_type (default: local) (required):
-Enter value for description (default: Use code from `llama_toolchain` itself to serve all llama stack APIs) (required):
-Enter value for docker_image (optional):
-Enter value for providers (default: {'inference': 'meta-reference', 'memory': 'meta-reference-faiss', 'safety': 'meta-reference', 'agentic_system': 'meta-reference', 'telemetry': 'console'}) (required):
-Enter value for image_type (default: conda) (required):
-
-Conda environment 'llamastack-8b-instruct' exists. Checking Python version...
-
-Build spec configuration saved at ~/.llama/distributions/conda/8b-instruct-build.yaml
-```
-
-After this step is complete, a file named `8b-instruct-build.yaml` will be generated and saved at `~/.llama/distributions/conda/8b-instruct-build.yaml`.
 
 The file will be of the contents
 ```
-$ cat ~/.llama/distributions/conda/8b-instruct-build.yaml
+$ cat ./llama_toolchain/configs/distributions/conda/local-conda-example-build.yaml
 
 name: 8b-instruct
 distribution_spec:
@@ -137,11 +117,17 @@ distribution_spec:
 image_type: conda
 ```
 
-You may edit the `8b-instruct-build.yaml` file and re-run the `llama stack build` command to re-build and update the distribution.
+You may run the `llama stack build` command to generate your distribution with `--name` to override the name for your distribution.
 ```
-llama stack build --config ~/.llama/distributions/conda/8b-instruct-build.yaml
+$ llama stack build ~/.llama/distributions/conda/8b-instruct-build.yaml --name 8b-instruct
+...
+...
+Build spec configuration saved at ~/.llama/distributions/conda/8b-instruct-build.yaml
 ```
 
+After this step is complete, a file named `8b-instruct-build.yaml` will be generated and saved at `~/.llama/distributions/conda/8b-instruct-build.yaml`.
+
+
 #### How to build distribution with different API providers using configs
 To specify a different API provider, we can change the `distribution_spec` in our `<name>-build.yaml` config. For example, the following build spec allows you to build a distribution using TGI as the inference API provider.
 
@@ -150,7 +136,6 @@ $ cat ./llama_toolchain/configs/distributions/conda/local-tgi-conda-example-buil
 
 name: local-tgi-conda-example
 distribution_spec:
-  distribution_type: local-plus-tgi-inference
   description: Use TGI (local or with Hugging Face Inference Endpoints for running LLM inference. When using HF Inference Endpoints, you must provide the name of the endpoint).
   docker_image: null
   providers:
@@ -177,7 +162,6 @@ $ cat ./llama_toolchain/configs/distributions/docker/local-docker-example-build.
 
 name: local-docker-example
 distribution_spec:
-  distribution_type: local
   description: Use code from `llama_toolchain` itself to serve all llama stack APIs
   docker_image: null
   providers: