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llama-stack/docs/source/building_applications/index.md
Francisco Arceo d495922949
docs: Updated documentation and Sphinx configuration (#1845) 
# What does this PR do?

The goal of this PR is to make the pages easier to navigate by surfacing
the child pages on the navbar, updating some of the copy, moving some of
the files around.

Some changes:
1. Clarifying Titles
2. Restructuring "Distributions" more formally in its own page to be
consistent with Providers and adding some clarity to the child pages to
surface them and make them easier to navigate
3. Updated sphinx config to not collapse navigation by default
4. Updated copyright year to be calculated dynamically 
5. Moved `docs/source/distributions/index.md` ->
`docs/source/distributions/starting_llama_stack_server.md`

Another for https://github.com/meta-llama/llama-stack/issues/1815

## Test Plan
Tested locally and pages build (screen shots for example).

## Documentation
###  Before:
![Screenshot 2025-03-31 at 1 09
21 PM](https://github.com/user-attachments/assets/98e34f76-f0d9-4055-8e2c-441b1e7d8f6a)

### After:
![Screenshot 2025-03-31 at 1 08
52 PM](https://github.com/user-attachments/assets/dfb6b8ad-3a1d-46b6-8f54-0c553664093f)

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
2025-03-31 13:08:05 -07:00

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Building AI Applications (Examples)

Llama Stack provides all the building blocks needed to create sophisticated AI applications.

The best way to get started is to look at this notebook which walks through the various APIs (from basic inference, to RAG agents) and how to use them.

Notebook: Building AI Applications

Here are some key topics that will help you build effective agents:

  • Agent: Understand the components and design patterns of the Llama Stack agent framework.
  • Agent Execution Loop: Understand how agents process information, make decisions, and execute actions in a continuous loop.
  • RAG (Retrieval-Augmented Generation): Learn how to enhance your agents with external knowledge through retrieval mechanisms.
  • Tools: Extend your agents' capabilities by integrating with external tools and APIs.
  • Evals: Evaluate your agents' effectiveness and identify areas for improvement.
  • Telemetry: Monitor and analyze your agents' performance and behavior.
  • Safety: Implement guardrails and safety measures to ensure responsible AI behavior.
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agent
agent_execution_loop
rag
tools
telemetry
evals
advanced_agent_patterns
safety