> For the complete documentation index, see [llms.txt](https://opencampus.gitbook.io/opencampus-machine-learning-program/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://opencampus.gitbook.io/opencampus-machine-learning-program/courses/archive/deep-dive-into-llms/week-5-agents.md).

# Week 5 - RAG and Agents

{% embed url="<https://drive.google.com/file/d/18VsrKSqNFaWeWsL24ULFrNnwpghpdwJZ/view?usp=sharing>" %}

### This week you will...

* Learn about Retrieval augmented generation
* Agents

### Learning Resources

* Watch OpenAIs Tips and Tricks on RAG and Finetuning

{% embed url="<https://www.youtube.com/watch?v=ahnGLM-RC1Y>" %}

* Get to know Openai Function calling

{% embed url="<https://www.youtube.com/watch?v=7oZKIwz2wk8>" %}

{% embed url="<https://www.youtube.com/watch?v=dgV4WFisK5Y>" %}

## Until next week you should...

* [x] further investigate your dataset characteristics as described [here](https://github.com/opencampus-sh/ml-project-template/blob/main/1_DatasetCharacteristics/INSTRUCTIONS.md).
* [x] be prepared for a presentation of your dataset characteristics.
* [x] do [this short course](https://www.deeplearning.ai/short-courses/evaluating-debugging-generative-ai/) by Deeplearning.AI and Weights & Biases on how to use the Weights & Biases framework to track and evaluate your model results.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://opencampus.gitbook.io/opencampus-machine-learning-program/courses/archive/deep-dive-into-llms/week-5-agents.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
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Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
