mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-06-28 02:53:30 +00:00
52977e56a8
Summary: - [new] Agent concepts (session, turn) - [new] how to write custom tools - [new] non-streaming API and how to get outputs - [update] remaining `memory` -> `rag` rename - [new] note importance of `instructions` Test Plan: read
31 lines
1.3 KiB
Markdown
31 lines
1.3 KiB
Markdown
# Building AI Applications
|
|
|
|
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](https://github.com/meta-llama/llama-stack/blob/main/docs/getting_started.ipynb)
|
|
|
|
Here are some key topics that will help you build effective agents:
|
|
|
|
- **[Agent](agent)**: Understand the components and design patterns of the Llama Stack agent framework.
|
|
- **[Agent Execution Loop](agent_execution_loop)**: Understand how agents process information, make decisions, and execute actions in a continuous loop.
|
|
- **[RAG (Retrieval-Augmented Generation)](rag)**: Learn how to enhance your agents with external knowledge through retrieval mechanisms.
|
|
- **[Tools](tools)**: Extend your agents' capabilities by integrating with external tools and APIs.
|
|
- **[Evals](evals)**: Evaluate your agents' effectiveness and identify areas for improvement.
|
|
- **[Telemetry](telemetry)**: Monitor and analyze your agents' performance and behavior.
|
|
- **[Safety](safety)**: Implement guardrails and safety measures to ensure responsible AI behavior.
|
|
|
|
```{toctree}
|
|
:hidden:
|
|
:maxdepth: 1
|
|
|
|
agent
|
|
agent_execution_loop
|
|
rag
|
|
tools
|
|
telemetry
|
|
evals
|
|
advanced_agent_patterns
|
|
safety
|
|
```
|