Llama_Stack_Building_AI_Applications.ipynb -> getting_started.ipynb (#854)

Llama_Stack_Building_AI_Applications.ipynb -> getting_started.ipynb

.github/workflows/publish-to-test-pypi.yml

@@ -238,7 +238,7 @@ jobs:
       run: |
         pip install pytest nbval
         llama stack build --template together --image-type venv
-        pytest -v -s --nbval-lax ./docs/notebooks/Llama_Stack_Building_AI_Applications.ipynb
+        pytest -v -s --nbval-lax ./docs/getting_started.ipynb
         pytest -v -s --nbval-lax ./docs/notebooks/Llama_Stack_Benchmark_Evals.ipynb
 
     # TODO: add trigger for integration test workflow & docker builds

README.md

@@ -4,7 +4,7 @@
 [![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) | [**Colab Notebook**](./docs/notebooks/Llama_Stack_Building_AI_Applications.ipynb)
+[**Quick Start**](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html) | [**Documentation**](https://llama-stack.readthedocs.io/en/latest/index.html) | [**Colab Notebook**](./docs/getting_started.ipynb)
 
 Llama Stack defines and standardizes the core building blocks that simplify AI application development. It codified best practices across the Llama ecosystem. More specifically, it provides
 
@@ -97,7 +97,7 @@ Please checkout our [Documentation](https://llama-stack.readthedocs.io/en/latest
     * Guide using `llama` CLI to work with Llama models (download, study prompts), and building/starting a Llama Stack distribution.
 * [Getting Started](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html)
     * Quick guide to start a Llama Stack server.
-    * [Jupyter notebook](./docs/notebooks/Llama_Stack_Building_AI_Applications.ipynb) to walk-through how to use simple text and vision inference llama_stack_client APIs
+    * [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).
     * 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)

docs/source/building_applications/telemetry.md

@@ -77,4 +77,4 @@ Once the Jaeger instance is running, you can visualize traces by navigating to h
 
 ## Querying Traces Stored in SQLIte
 
-The `sqlite` sink allows you to query traces without an external system. Here are some example queries. Refer to the notebook at [Llama Stack Building AI Applications](https://github.com/meta-llama/llama-stack/blob/main/docs/notebooks/Llama_Stack_Building_AI_Applications.ipynb) for more examples on how to query traces and spaces.
+The `sqlite` sink allows you to query traces without an external system. Here are some example queries. Refer to the notebook at [Llama Stack Building AI Applications](https://github.com/meta-llama/llama-stack/blob/main/docs/getting_started.ipynb) for more examples on how to query traces and spaces.

docs/source/building_applications/tools.md

@@ -7,7 +7,7 @@ Tools are treated as any other resource in llama stack like models. You can regi
 
 When instatiating an agent, you can provide it a list of tool groups that it has access to. Agent gets the corresponding tool definitions for the specified tool groups and passes them along to the model.
 
-Refer to the [Building AI Applications](https://github.com/meta-llama/llama-stack/blob/main/docs/notebooks/Llama_Stack_Building_AI_Applications.ipynb) notebook for more examples on how to use tools.
+Refer to the [Building AI Applications](https://github.com/meta-llama/llama-stack/blob/main/docs/getting_started.ipynb) notebook for more examples on how to use tools.
 
 ## Types of Tool Group providers