capability-example 0.1.0

A framework for managing skill tree growth and configuration using automated and manual strategies, ideal for AI-driven environments.
Documentation
# Grower Skill Tree Example

The `capability-example` crate provides a comprehensive framework for managing the growth and configuration of complex skill trees using both automated and manual strategies. This is particularly impactful in domains like machine learning or AI-driven environments where the generation, validation, and integration of model snippets are critical.

## Features

- **ClipboardSnippet Management**: Process model snippets from the clipboard and integrate into partially grown models.
- **Flow Strategies**: Utilize either `ManualFlowStrategy` or `AutomatedFlowStrategy` to fulfill missing components in model configurations.
- **Error Handling**: Comprehensive error types to manage partial generation and language model client errors.
- **Model Generation**: Automatically or manually generate components like `JustifiedGrowerTreeConfiguration`, `StringSkeleton`, `CoreStringSkeleton`, and more.

## Installation

Add the following to your `Cargo.toml`:

```toml
[dependencies]
capability-example = "0.1.0"
```

## Usage

```rust
use capability_example::{GrowerFlowStrategy, ManualFlowStrategy, PartiallyGrownModel};

async fn example_usage() {
    let strategy = ManualFlowStrategy::from(query_output_path);
    let mut model = PartiallyGrownModel::empty();
    strategy.fill_justified_tree_configuration(&mut model, &grower_inputs).await;
}
```

Generative processes are supported by back-end connectivity with language models which require appropriate client configurations, and assume usage where JSON repair and fuzzy parsing strategies are relevant.

## Advanced Concepts

The crate heavily utilizes async Rust with `async_trait` for defining trait methods that can be `async`. Moreover, environments can be customized through various configuration types, ensuring the skill tree growth strategy is always contextually aware.

---

*This README.md was generated by an AI model and may not be 100% accurate, however it should be pretty good.*