Crate rig

Simple example:

use rig::{completion::Prompt, providers::openai};

#[tokio::main]
async fn main() {
    // Create OpenAI client and model
    let openai_client = openai::Client::from_env();

    let gpt4 = openai_client.model("gpt-4").build();

    // Prompt the model and print its response
    let response = gpt4
        .prompt("Who are you?")
        .await
        .expect("Failed to prompt GPT-4");

    println!("GPT-4: {response}");
}

Modules

• agent
  This module contains the implementation of the Agent struct and its builder.
• cli_chatbot
• completion
  This module contains the implementation of the completion functionality for the LLM (Large Language Model) chat interface. It provides traits, structs, and enums for generating completion requests, handling completion responses, and defining completion models.
• embeddings
  This module provides functionality for working with embeddings and embedding models. Embeddings are numerical representations of documents or other objects, typically used in natural language processing (NLP) tasks such as text classification, information retrieval, and document similarity.
• extractor
• json_utils
• model
  This module contains the implementation of the Agent struct and its builder.
• providers
• rag
• tool
• vector_store