agentai 0.1.4

AgentAI is a Rust library designed to simplify the creation of AI agents.
Documentation 
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[![](https://img.shields.io/crates/v/agentai.svg)](https://crates.io/crates/agentai)
[![](https://docs.rs/agentai/badge.svg)](https://docs.rs/agentai)

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# AgentAI

AgentAI is a Rust library designed to simplify the creation of AI agents. It leverages
the [GenAI](https://crates.io/crates/genai) library to interface with a wide range of popular
Large Language Models (LLMs), making it versatile and powerful. Written in Rust, AgentAI
benefits from strong static typing and robust error handling, ensuring more reliable
and maintainable code. Whether you're developing simple or complex AI agents, AgentAI provides
a streamlined and efficient development process.

## Features

- Multi LLM -- we support most of LLM API (OpenAI, Anthropic, Gemini, Ollama and all OpenAI API Compatible)
- Choose correct LLM for the task -- use many smaller specialized LLMs to save costs and choose best of all the worlds
- Support for MCP Server -- no need to write your own Agent Tools, you can leverage, already existing
  solutions, based on Model Context Protocol

> **Warning**
> This library is under heavy development. The interface can change at any moment without any notice.

## Installation
To start using AgentAI crate just enter in root directory for your project this command:

```bash
cargo add agentai genai
```

This will install this crate with all required dependencies.

## Feature flags
Available features for `agentai` crate. To enable any of these features, you need to enter this command:

```bash
cargo add agentai -F mcp-client
```

Features list:
- `mcp-client` _(enabled by default)_ — Enables experimental support for Agent Tools based on MCP Servers

## Usage
Here is a basic example of how to create an AI agent using AgentAI:
```rust
use agentai::Agent;

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    let client = genai::Client::default();
    let mut agent = Agent::new(&client, "You are a useful assistant", &());
    let answer: String = agent.run("gpt-4o", "Why sky is blue?").await?;
    println!("Answer: {}", answer);
    Ok(())
}
```

## Examples

For more examples, check out the [examples](https://docs.rs/agentai/latest/agentai/examples/) directory. You can build and run them using Cargo with the following command:

```bash
cargo run --example <example_name>
```

The <example_name> should match the filename of the example you want to run (without the file extension).
For example, to run the example that includes the essential parts required to implement an AI agent, use:

```bash
cargo run --example simple
```

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## Documentation

Full documentation is available on [docs.rs](https://docs.rs/agentai).

## Contributing

Contributions are welcome! Please see our [CONTRIBUTING.md](CONTRIBUTING.md) for more details.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

## Acknowledgements

Special thanks to the creators of the [GenAI library](https://crates.io/crates/genai) for providing a robust framework for interfacing with various LLMs.