# Gemini AI Rust Wrapper
Welcome to the **Rust Gemini AI**! This crate provides a Rust interface to interact with the **Gemini AI API**, which powers advanced natural language processing (NLP) and multimodal capabilities.
![License](https://img.shields.io/badge/license-MIT-blue.svg)
![Gemini AI Logo](https://img.shields.io/crates/v/gemini-ai)
## New Feature Added
- **Added Function Calling Feature**
- **MaxTokenLimit Based Response**
- **Instruction Based Response**
## Previous New Feature Added
- **MaxTokenLimit Based Response**
- **Instruction Based Response**
## Features
- **Instruction Processing**: Based on instruction customize the response in the way you like.
- **Natural Language Processing**: Access powerful language models like Gemini 1.5 Pro for advanced text analysis, summarization, and generation.
- **Multimodal Capabilities**: Interact with Gemini models that can handle not only text but also images, audio, and video inputs.
- **Easy Integration**: A straightforward API wrapper for easy integration into your Rust projects.
## Installation
To add this crate to your project, include it in your `Cargo.toml`:
```toml
[dependencies]
gemini-ai = "0.1.14"
```
```toml
let builder = GeminiContentGenBuilder::new()
.env("GEMINI_API_KEY")
.model(gemini_ai::Models::GEMINI_1_5_PRO_002)
.kind(gemini_ai::Kind::Image("statics/OIP.jpeg"))
.instruction(
"you are great image analyzer and tell the image design accuratly and how it can be made great",
)
.text("image")
.max_token(gemini_ai::TokenLen::Default)
.build()
.output();
let string = decode_gemini(&builder); // optional to decode the output if it sends the reponse else error
```
```toml
let feature1 = Properties::new(
"get_current_place_detail",
"current palce details",
Some(gemini_ai::pulse::format::Paramters {
r#type: String::from("object"),
properties: gemini_ai::pulse::format::SubProperties {
name: String::from("events"),
r#type: String::from("string"),
description: String::from("Render all the events located in current location"),
},
}),
Some(&["events"]),
);
let feature = feature(&[&feature1]);
```
```toml
let pluse = GeminiPulse::new()
.env("GEMINI_API_KEY")
.model(gemini_ai::Models::GEMINI_1_5_PRO)
.train(&feature)
.instruction("your are great in telling events in the current place")
.tell("banglore at 24 november 2024")
.build()
.output();
```