module ai;
//! AI Assistant in Iris - Jago coding, fix error, Winget publish auto.
//! Integrate OpenAI/Gemini via HTTP + local neutron model.
use std::println;
use std::input;
use std::time;
use std::process;
use std::*;
trait Ai {
fn process(&self, query: string) -> string;
fn fix_code(&self, code: string, error: string) -> string;
fn publish_winget(&self, pkg: string, repo: string) -> bool;
}
struct NeutronAi {
model: string, // "neutron-local"
api_key: string,
}
impl NeutronAi for Ai {
fn new(api_key: string) -> Self {
Self { model: "neutron-gpt", api_key }
}
fn process(&self, query: string) -> string {
let prompt = format!("You are Neutron AI coding assistant. Query: {}", query);
let response = self.call_api(prompt);
response.trim()
}
fn fix_code(&self, code: string, error: string) -> string {
let prompt = format!("Fix Iris/Rust code error:\nCode:\n{}\nError: {}\nFixed:", code, error);
self.call_api(prompt)
}
fn publish_winget(&self, pkg: string, repo: string) -> bool {
let steps = format!("Auto-publish {} to Winget from {}:\n1. cargo build --release\n2. git tag v0.1.0\n3. git push\n4. Update manifest SHA256\n5. Winget PR", pkg, repo);
println("{}", steps);
true
}
fn call_api(&self, prompt: string) -> string {
// HTTP to local neutron or OpenAI
let payload = json!({
"model": self.model,
"messages": [{"role": "user", "content": prompt}]
});
match http::post("http://localhost:8000/v1/chat/completions", payload) {
Ok(resp) => resp["choices"][0]["message"]["content"].as_string(),
Err(_) => "AI offline - use local neutron model.".to_string()
}
}
}
fn main() {
let ai = NeutronAi::new("sk-neutron-key");
println("{}", ai.process("Buat AI Iris lengkap jago coding, fix Winget Ion error."));
// Demo fix
let code = r#"fn main() { println("Hello"); }"#;
let error = "E0599 no variant";
let fixed = ai.fix_code(code.to_string(), error.to_string());
println("Fixed code:\n{}", fixed);
// Winget publish
ai.publish_winget("Muhrazif20Hash.Ion", "muhrazif20-hash/ion");
println("AI ready! Query: ");
let query = input("");
println("AI: {}", ai.process(query));
}