Translated English(en) into Brazilian Portuguese (pt_br) #609

maurorisonho · 2025-10-23T00:05:09Z

Translated all main modules (unit 0 to unit 4) and bonus modules (bonus-unit 1 to bonus-unit 3), as well as the communication section, into Portuguese-Brazilian Portuguese.
Adjusted quizzes, conclusions, hands-on tutorials, certificates, and GAIA guides to natural language in Portuguese-Brazilian Portuguese, maintaining the structure and links.
Standardized notices, feedback invitations, and final messages; confirmed that there are no remaining English sections.

- Translated all main modules (unit 0 to unit 4) and bonus modules (bonus-unit 1 to bonus-unit 3), as well as the communication section, into Portuguese-Brazilian Portuguese. - Adjusted quizzes, conclusions, hands-on tutorials, certificates, and GAIA guides to natural language in Portuguese-Brazilian Portuguese, maintaining the structure and links. - Standardized notices, feedback invitations, and final messages; confirmed that there are no remaining English sections.

Copilot

Pull Request Overview

This PR completes the Portuguese-Brazilian (pt_br) translation for the AI Agents course, covering all main units (0-4) and bonus modules. The translation maintains technical accuracy while adapting content to natural Brazilian Portuguese, preserving all links, code examples, and structural elements.

Key changes:

Full translation of Units 0-4 content into Brazilian Portuguese
Adaptation of quizzes, hands-on tutorials, and certificate instructions
Translation of GAIA benchmark documentation and workflow guides

Reviewed Changes

Copilot reviewed 77 out of 78 changed files in this pull request and generated 17 comments.

Show a summary per file

File	Description
units/pt_br/unit4/*.mdx	Unit 4 files translated: introduction, GAIA benchmark explanation, hands-on guide, certificate instructions, and conclusion
units/pt_br/unit3/agentic-rag/*.mdx	Unit 3 Agentic RAG case study translated: introduction, tools, retriever, agent implementation, and conclusion
units/pt_br/unit2/smolagents/*.mdx	Unit 2 smolagents module translated: introduction, agents, tools, quizzes, and conclusion
units/pt_br/unit2/llama-index/*.mdx	Unit 2 LlamaIndex module translated: components, agents, workflows, tools, and quizzes
units/pt_br/unit2/langgraph/*.mdx	Unit 2 LangGraph module translated: introduction, building blocks, first graph, document analysis, and conclusion
units/pt_br/unit1/*.mdx	Unit 1 fundamentals translated: agent definitions, LLMs, tools, actions, observations, thoughts, and tutorials
units/pt_br/unit0/discord101.mdx	Unit 0 Discord guide translated with community channel information

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Copilot · 2025-10-23T00:07:36Z

units/pt_br/unit3/agentic-rag/introduction.mdx

+> [!TIP]
+> This is a 'real-world' use case for Agentic RAG, that you could use in your own projects or workplaces. If you want to get more out of this project, why not try it out on your own use case and share in Discord?


Lines 8-9 and 15-16 contain English text that should be translated to Portuguese. The TIP section and the phrase 'Now, it's time to get our hands dirty with an actual use case. Let's set the stage!' are not translated.

Copilot · 2025-10-23T00:07:37Z

units/pt_br/unit3/agentic-rag/introduction.mdx

+
+Comecemos definindo os requisitos rígidos da gala.
+
+## The Gala Requirements


The heading 'The Gala Requirements' on line 27 is in English and should be translated to Portuguese.

Suggested change

## The Gala Requirements

## Requisitos da Gala

Copilot · 2025-10-23T00:07:37Z

units/pt_br/unit3/agentic-rag/agentic-rag.mdx

+Nesta unidade, veremos como usar Agentic RAG para ajudar Alfred a preparar a grande gala.
+
+> [!TIP]
+> We know we've already discussed Retrieval Augmented Generation (RAG) and agentic RAG in the previous unit, so feel free to skip ahead if you're already familiar with the concepts.


Lines 6-7 contain English text in a TIP block that should be translated to Portuguese.

Suggested change

> We know we've already discussed Retrieval Augmented Generation (RAG) and agentic RAG in the previous unit, so feel free to skip ahead if you're already familiar with the concepts.

> Sabemos que já discutimos a Geração Aumentada por Recuperação (RAG) e o Agentic RAG na unidade anterior, então sinta-se à vontade para pular esta seção se já estiver familiarizado com os conceitos.

Copilot · 2025-10-23T00:07:37Z

units/pt_br/unit3/agentic-rag/agentic-rag.mdx

+1. We've asked Alfred to help plan a gala
+2. Alfred needs to find the latest news and weather information
+3. Alfred needs to structure and search the guest information
+
+Just as Alfred needs to search through your household information to be helpful, any agent needs a way to find and understand relevant data.
+**Agentic RAG is a powerful way to use agents to answer questions about your data.** We can pass various tools to Alfred to help him answer questions.
+However, instead of answering the question on top of documents automatically, Alfred can decide to use any other tool or flow to answer the question.


Lines 16-22 contain English text that should be translated to Portuguese.

Suggested change

1. We've asked Alfred to help plan a gala

2. Alfred needs to find the latest news and weather information

3. Alfred needs to structure and search the guest information

Just as Alfred needs to search through your household information to be helpful, any agent needs a way to find and understand relevant data.

**Agentic RAG is a powerful way to use agents to answer questions about your data.** We can pass various tools to Alfred to help him answer questions.

However, instead of answering the question on top of documents automatically, Alfred can decide to use any other tool or flow to answer the question.

1. Pedimos para Alfred ajudar a planejar uma gala

2. Alfred precisa encontrar as últimas notícias e informações sobre o clima

3. Alfred precisa estruturar e buscar as informações dos convidados

Assim como Alfred precisa buscar informações da sua casa para ser útil, qualquer agente precisa de uma forma de encontrar e entender dados relevantes.

**Agentic RAG é uma maneira poderosa de usar agentes para responder perguntas sobre seus dados.** Podemos fornecer várias ferramentas para Alfred ajudá-lo a responder perguntas.

No entanto, em vez de responder automaticamente com base nos documentos, Alfred pode decidir usar qualquer outra ferramenta ou fluxo para responder à pergunta.

Copilot · 2025-10-23T00:07:38Z

units/pt_br/unit2/llama-index/workflows.mdx

+> You can follow the code in <a href="https://huggingface.co/agents-course/notebooks/blob/main/unit2/llama-index/workflows.ipynb" target="_blank">this notebook</a> that you can run using Google Colab.
+
+### Construção básica
+
+<details>
+<summary>Install the Workflow package</summary>
+As introduced in the <a href="./llama-hub">section on the LlamaHub</a>, we can install the Workflow package with the following command:
+
+```python
+pip install llama-index-utils-workflow
+```
+</details>
+
+We can create a single-step workflow by defining a class that inherits from `Workflow` and decorating your functions with `@step`.
+We will also need to add `StartEvent` and `StopEvent`, which are special events that are used to indicate the start and end of the workflow.


Lines 25-26 and 31-40 contain English text that should be translated to Portuguese.

Suggested change

> You can follow the code in <a href="https://huggingface.co/agents-course/notebooks/blob/main/unit2/llama-index/workflows.ipynb" target="_blank">this notebook</a> that you can run using Google Colab.

### Construção básica

<details>

<summary>Install the Workflow package</summary>

As introduced in the <a href="./llama-hub">section on the LlamaHub</a>, we can install the Workflow package with the following command:

```python

pip install llama-index-utils-workflow

```

</details>

We can create a single-step workflow by defining a class that inherits from `Workflow` and decorating your functions with `@step`.

We will also need to add `StartEvent` and `StopEvent`, which are special events that are used to indicate the start and end of the workflow.

> Você pode acompanhar o código neste <a href="https://huggingface.co/agents-course/notebooks/blob/main/unit2/llama-index/workflows.ipynb" target="_blank">notebook</a> que pode ser executado no Google Colab.

### Construção básica

<details>

<summary>Instale o pacote Workflow</summary>

Como apresentado na <a href="./llama-hub">seção sobre o LlamaHub</a>, podemos instalar o pacote Workflow com o seguinte comando:

```python

pip install llama-index-utils-workflow

Podemos criar um workflow de etapa única definindo uma classe que herda de Workflow e decorando suas funções com @step.
Também precisaremos adicionar StartEvent e StopEvent, que são eventos especiais usados para indicar o início e o fim do workflow.

Copilot · 2025-10-23T00:07:40Z

units/pt_br/unit2/langgraph/first_graph.mdx

+1. Read incoming emails
+2. Classify them as spam or legitimate
+3. Draft a preliminary response for legitimate emails
+4. Send information to Mr. Wayne when legitimate (printing only)
+
+This example demonstrates how to structure a workflow with LangGraph that involves LLM-based decision-making. While this can't be considered an Agent as no tool is involved, this section focuses more on learning the LangGraph framework than Agents.
+
+> [!TIP]
+> You can follow the code in <a href="https://huggingface.co/agents-course/notebooks/blob/main/unit2/langgraph/mail_sorting.ipynb" target="_blank">this notebook</a> that you can run using Google Colab.


Lines 4-13 contain English text that should be translated to Portuguese.

Suggested change

1. Read incoming emails

2. Classify them as spam or legitimate

3. Draft a preliminary response for legitimate emails

4. Send information to Mr. Wayne when legitimate (printing only)

This example demonstrates how to structure a workflow with LangGraph that involves LLM-based decision-making. While this can't be considered an Agent as no tool is involved, this section focuses more on learning the LangGraph framework than Agents.

> [!TIP]

> You can follow the code in <a href="https://huggingface.co/agents-course/notebooks/blob/main/unit2/langgraph/mail_sorting.ipynb" target="_blank">this notebook</a> that you can run using Google Colab.

1. Ler e-mails recebidos

2. Classificá-los como spam ou legítimos

3. Redigir uma resposta preliminar para e-mails legítimos

4. Enviar informações ao Sr. Wayne quando legítimo (apenas imprimir)

Este exemplo demonstra como estruturar um fluxo de trabalho com LangGraph que envolve tomada de decisão baseada em LLM. Embora isso não possa ser considerado um Agente, já que nenhuma ferramenta está envolvida, esta seção foca mais em aprender o framework LangGraph do que em Agentes.

> [!DICA]

> Você pode acompanhar o código neste <a href="https://huggingface.co/agents-course/notebooks/blob/main/unit2/langgraph/mail_sorting.ipynb" target="_blank">notebook</a> que pode ser executado no Google Colab.

Copilot · 2025-10-23T00:07:40Z

units/pt_br/unit2/langgraph/introduction.mdx

+## Module Overview
+
+Nesta unidade, você vai descobrir:
+
+### 1️⃣ [What is LangGraph, and when to use it?](./when_to_use_langgraph)
+### 2️⃣ [Building Blocks of LangGraph](./building_blocks)
+### 3️⃣ [Alfred, the mail sorting butler](./first_graph)
+### 4️⃣ [Alfred, the document Analyst agent](./document_analysis_agent)


The heading 'Module Overview' on line 9 and section titles on lines 13-17 are in English and should be translated to Portuguese.

Suggested change

## Module Overview

Nesta unidade, você vai descobrir:

### 1️⃣ [What is LangGraph, and when to use it?](./when_to_use_langgraph)

### 2️⃣ [Building Blocks of LangGraph](./building_blocks)

### 3️⃣ [Alfred, the mail sorting butler](./first_graph)

### 4️⃣ [Alfred, the document Analyst agent](./document_analysis_agent)

## Visão Geral do Módulo

Nesta unidade, você vai descobrir:

### 1️⃣ [O que é LangGraph e quando usá-lo?](./when_to_use_langgraph)

### 2️⃣ [Blocos de Construção do LangGraph](./building_blocks)

### 3️⃣ [Alfred, o mordomo organizador de correspondências](./first_graph)

### 4️⃣ [Alfred, o agente Analista de Documentos](./document_analysis_agent)

Copilot · 2025-10-23T00:07:41Z

units/pt_br/unit2/langgraph/introduction.mdx

+
+Vamos lá!
+
+## Resources


The heading 'Resources' on line 28 is in English and should be translated to Portuguese.

Suggested change

## Resources

## Recursos

Copilot · 2025-10-23T00:07:41Z

units/pt_br/unit2/smolagents/final_quiz.mdx

+# Exam Time!
+
+Well done on working through the material on `smolagents`! You've already achieved a lot. Now, it's time to put your knowledge to the test with a quiz. 🧠
+
+## Instructions
+
+- The quiz consists of code questions.
+- You will be given instructions to complete the code snippets.
+- Read the instructions carefully and complete the code snippets accordingly.
+- For each question, you will be given the result and some feedback.
+
+🧘 **This quiz is ungraded and uncertified**. It's about you understanding the `smolagents` library and knowing whether you should spend more time on the written material. In the coming units you'll put this knowledge to the test in use cases and projects.
+
+Let's get started! 


Lines 1-24 contain English text that should be translated to Portuguese, including headings and instructions.

Suggested change

# Exam Time!

Well done on working through the material on `smolagents`! You've already achieved a lot. Now, it's time to put your knowledge to the test with a quiz. 🧠

## Instructions

- The quiz consists of code questions.

- You will be given instructions to complete the code snippets.

- Read the instructions carefully and complete the code snippets accordingly.

- For each question, you will be given the result and some feedback.

🧘 **This quiz is ungraded and uncertified**. It's about you understanding the `smolagents` library and knowing whether you should spend more time on the written material. In the coming units you'll put this knowledge to the test in use cases and projects.

Let's get started!

# Hora do Exame!

Parabéns por ter concluído o material sobre `smolagents`! Você já conquistou muito. Agora, é hora de colocar seu conhecimento à prova com um quiz. 🧠

## Instruções

- O quiz consiste em perguntas de código.

- Você receberá instruções para completar os trechos de código.

- Leia as instruções com atenção e complete os trechos de código conforme solicitado.

- Para cada pergunta, você verá o resultado e receberá um feedback.

🧘 **Este quiz não é avaliado nem certificado**. Ele serve para você entender a biblioteca `smolagents` e saber se deve dedicar mais tempo ao material escrito. Nas próximas unidades, você colocará esse conhecimento em prática em casos de uso e projetos.

Vamos começar!

Copilot · 2025-10-23T00:07:41Z

units/pt_br/unit1/actions.mdx

+
+Depois disso, estaremos **finalmente prontos para construir nosso primeiro agente!**
+
+After this, we will **finally be ready to build our first Agent!**


Line 120 is a duplicate of line 118 and contains English text. This line should be removed or translated to Portuguese.

Suggested change

After this, we will **finally be ready to build our first Agent!**

Copilot AI review requested due to automatic review settings October 23, 2025 00:05

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Translated English(en) into Brazilian Portuguese (pt_br) #609

Translated English(en) into Brazilian Portuguese (pt_br) #609

maurorisonho commented Oct 23, 2025

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		> [!TIP]
		> This is a 'real-world' use case for Agentic RAG, that you could use in your own projects or workplaces. If you want to get more out of this project, why not try it out on your own use case and share in Discord?


		Comecemos definindo os requisitos rígidos da gala.

		## The Gala Requirements

	> We know we've already discussed Retrieval Augmented Generation (RAG) and agentic RAG in the previous unit, so feel free to skip ahead if you're already familiar with the concepts.
	> Sabemos que já discutimos a Geração Aumentada por Recuperação (RAG) e o Agentic RAG na unidade anterior, então sinta-se à vontade para pular esta seção se já estiver familiarizado com os conceitos.


		Depois disso, estaremos finalmente prontos para construir nosso primeiro agente!

		After this, we will finally be ready to build our first Agent!

Uh oh!

Translated English(en) into Brazilian Portuguese (pt_br) #609

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Translated English(en) into Brazilian Portuguese (pt_br) #609

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