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use std::fs;
// Import required modules from the LLM library for Anthropic integration
use llm::{
builder::{LLMBackend, LLMBuilder}, // Builder pattern components
chat::{ChatMessage, ImageMime}, // Chat-related structures
};
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
// Get Anthropic API key from environment variable or use test key as fallback
let api_key = std::env::var("ANTHROPIC_API_KEY").unwrap_or("anthro-key".into());
// Initialize and configure the LLM client
let llm = LLMBuilder::new()
.backend(LLMBackend::Anthropic) // Use Anthropic (Claude) as the LLM provider
.api_key(api_key) // Set the API key
.model("claude-3-5-sonnet-20240620") // Use Claude Instant model
.max_tokens(512) // Limit response length
.temperature(0.7) // Control response randomness (0.0-1.0)
// Uncomment to set system prompt:
// .system("You are a helpful assistant specialized in concurrency.")
.build()
.expect("Failed to build LLM (Anthropic)");
let content = fs::read("./examples/image001.jpg").expect("The dummy.pdf file should exist");
// Prepare conversation history with example message about Rust concurrency
let messages = vec![
ChatMessage::user()
.content("What is in this image?")
.build(),
ChatMessage::user().image(ImageMime::JPEG, content).build(),
];
// Send chat request and handle the response
match llm.chat(&messages).await {
Ok(text) => println!("Anthropic chat response:\n{text}"),
Err(e) => eprintln!("Chat error: {e}"),
}
Ok(())
}