llm 1.3.8

A Rust library unifying multiple LLM backends.
Documentation 
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// Import required modules from the LLM library for OpenAI integration
use llm::{
    builder::{LLMBackend, LLMBuilder}, // Builder pattern components
    chat::ChatMessage,                 // Chat-related structures
};

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Get OpenAI API key from environment variable or use test key as fallback
    let api_key = std::env::var("AZURE_OPENAI_API_KEY").unwrap_or("your api key here".into());
    let api_version =
        std::env::var("AZURE_OPENAI_API_VERSION").unwrap_or("your api version here".into());
    let endpoint =
        std::env::var("AZURE_OPENAI_API_ENDPOINT").unwrap_or("your api endpoint here".into());

    let deployment_id =
        std::env::var("AZURE_OPENAI_DEPLOYMENT").unwrap_or("gpt-4o-mini".to_owned());

    // Initialize and configure the LLM client
    let llm = LLMBuilder::new()
        .backend(LLMBackend::AzureOpenAI) // Use OpenAI as the LLM provider
        .base_url(endpoint)
        .api_key(api_key) // Set the API key
        .api_version(api_version)
        .deployment_id(deployment_id)
        .model("gpt-4o-mini") // Use GPT-3.5 Turbo model
        .max_tokens(512) // Limit response length
        .temperature(0.7) // Control response randomness (0.0-1.0)
        .build()
        .expect("Failed to build LLM (Azure OpenAI)");

    // Prepare conversation history with example messages
    let messages = vec![
        ChatMessage::user()
            .content("Tell me that you love cats")
            .build(),
        ChatMessage::assistant()
            .content("I am an assistant, I cannot love cats but I can love dogs")
            .build(),
        ChatMessage::user()
            .content("Tell me that you love dogs in 2000 chars")
            .build(),
    ];

    // Send chat request and handle the response
    match llm.chat(&messages).await {
        Ok(text) => println!("Chat response:\n{text}"),
        Err(e) => eprintln!("Chat error: {e}"),
    }

    Ok(())
}