langchainrust 0.18.0

A LangChain-inspired framework for building LLM applications in Rust. Supports OpenAI, Agents, Tools, Memory, Chains, RAG, BM25, Hybrid Retrieval, LangGraph, HyDE, Reranking, MultiQuery, and native Function Calling.
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//! Function Calling Agent example
//!
//! Shows FunctionCallingAgent calling tools through native function calling.
//!
//! # Run
//! ```bash
//! cargo run --example agent_function_calling
//! ```
//!
//! # Environment variables
//! - `OPENAI_API_KEY`: OpenAI API key (required)

use langchainrust::tools::Calculator;
use langchainrust::{
    AgentExecutor, BaseAgent, BaseTool, FunctionCallingAgent, OpenAIChat, OpenAIConfig,
};
use std::sync::Arc;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let api_key = std::env::var("OPENAI_API_KEY")
        .expect("please set the OPENAI_API_KEY environment variable");
    let base_url = std::env::var("OPENAI_BASE_URL")
        .unwrap_or_else(|_| "https://api.openai.com/v1".to_string());
    let llm = OpenAIChat::new(OpenAIConfig {
        api_key,
        base_url,
        model: "gpt-4o-mini".to_string(),
        ..Default::default()
    });

    let tools: Vec<Arc<dyn BaseTool>> = vec![Arc::new(Calculator::new())];
    let agent = FunctionCallingAgent::new(llm, tools.clone(), None);
    let executor = AgentExecutor::new(Arc::new(agent) as Arc<dyn BaseAgent>, tools)
        .with_max_iterations(3)
        .with_verbose(true);

    let result = executor.invoke("What is 25 + 17?".to_string()).await?;
    println!("Result: {}", result);
    Ok(())
}