# ToolBrain Tutorials

Welcome to the ToolBrain tutorials! This guide will walk you through the core concepts and practical examples to help you master the library.

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## Part 1: Getting Started

This section covers the basics to get you up and running with ToolBrain.

1.  **What is ToolBrain?**
    -   Understand the core problems ToolBrain solves and its fundamental concepts.
    -  [[Jupyter Notebook]](./00_what_is_toolbrain.ipynb)

2.  **Setting Up Your Environment**
    -   A step-by-step guide to installing ToolBrain and its dependencies.
    -   [[Jupyter Notebook]](./01_setting_up_your_environment.ipynb)

3.  **Your First Training Run**
    -   A complete walkthrough of your first training script using GRPO.
    -   [[Jupyter Notebook]](./02_your_first_training_run.ipynb)

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## Part 2: Core Concepts in Depth

Dive deeper into the key components that make ToolBrain work.

1.  **Understanding Traces**
    -   Learn about the `Trace` and `Turn` objects, the backbone of trace-based learning.
    -   [[Jupyter Notebook]](./03_understanding_traces.ipynb)

2.  **Crafting Custom Reward Functions**
    -   Explore built-in reward functions and learn how to create your own.
    -   [[Jupyter Notebook]](./04_crafting_custom_reward_functions.ipynb)

3.  **DPO vs. GRPO vs. Supervised - Choosing Your Algorithm**
    -   Understand the differences between the available learning algorithms and when to use each.
    -   [[Jupyter Notebook]](./05_dpo_vs_grpo_vs_supervised.ipynb)

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## Part 3: More Examples

Explore practical, real-world applications of ToolBrain.

1.  **Email Search Agent**
    -   Build a complex agent that can search a database to answer questions.
    -   [[Jupyter Notebook]](./06_email_search_agent.ipynb)

2.  **Hyperparameter Optimization (HPO) Training**
    -   Use ToolBrain in a novel way to perform HPO on a machine learning model.
    -   [[Jupyter Notebook]](./07_hpo_training.ipynb)

3.  **Knowledge Distillation**
    -   Learn how to train a small, efficient model by distilling knowledge from a larger teacher model.
    -   [[Jupyter Notebook]](./08_knowledge_distillation.ipynb)

4.  **Tool Retrieval**
    -   Manage large sets of tools efficiently by dynamically selecting the most relevant ones for a given task.
    -   [[Jupyter Notebook]](./09_tool_retrieval.ipynb)

5.  **Automatic Task Generation (Zero-Learn)**
    -   Bootstrap your training process by automatically generating a dataset from a high-level description.
    -   [[Jupyter Notebook]](./10_zero_learn_for_automatic_task_generation.ipynb)

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## Part 4: Efficient Training

Learn how to train larger models faster and with less memory.

-   **Techniques for Efficiency (FP16, LoRA, BitsAndBytes, Unsloth)**
    -   A guide to using LoRA, 4-bit quantization, and Unsloth to optimize your training runs.
    -   [[Jupyter Notebook]](./part_04_efficient_learning.ipynb)

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## Part 5: Development and Contribution

Get involved with the ToolBrain community.

-   **Extending and Contributing to ToolBrain**
    -   Learn how to write a custom adapter for a new agent framework and how to contribute to the project.
    -   [[Jupyter Notebook]](./part_05_development_and_contribution.ipynb)