botserver/src/basic/keywords/llm_keyword.rs

use crate::shared::models::UserSession;
use crate::shared::state::AppState;
use log::{error};
use rhai::{Dynamic, Engine};
use uuid::Uuid;
use std::sync::Arc;
use std::time::Duration;
pub fn llm_keyword(state: Arc<AppState>, _user: UserSession, engine: &mut Engine) {
 let state_clone = Arc::clone(&state);
 engine
 .register_custom_syntax(&["LLM", "$expr$"], false, move |context, inputs| {
 let text = context.eval_expression_tree(&inputs[0])?.to_string();
 let state_for_thread = Arc::clone(&state_clone);
 let prompt = build_llm_prompt(&text);
 let (tx, rx) = std::sync::mpsc::channel();
 std::thread::spawn(move || {
 let rt = tokio::runtime::Builder::new_multi_thread().worker_threads(2).enable_all().build();
 let send_err = if let Ok(rt) = rt {
 let result = rt.block_on(async move {
 execute_llm_generation(state_for_thread, prompt).await
 });
 tx.send(result).err()
 } else {
 tx.send(Err("failed to build tokio runtime".into())).err()
 };
 if send_err.is_some() {
 error!("Failed to send LLM thread result");
 }
 });
 match rx.recv_timeout(Duration::from_secs(500)) {
 Ok(Ok(result)) => Ok(Dynamic::from(result)),
 Ok(Err(e)) => Err(Box::new(rhai::EvalAltResult::ErrorRuntime(e.to_string().into(), rhai::Position::NONE))),
 Err(std::sync::mpsc::RecvTimeoutError::Timeout) => {
 Err(Box::new(rhai::EvalAltResult::ErrorRuntime("LLM generation timed out".into(), rhai::Position::NONE)))
 }
 Err(e) => Err(Box::new(rhai::EvalAltResult::ErrorRuntime(format!("LLM thread failed: {e}").into(), rhai::Position::NONE))),
 }
 })
 .unwrap();
}
fn build_llm_prompt(user_text: &str) -> String {
 user_text.trim().to_string()
}
pub async fn execute_llm_generation(state: Arc<AppState>, prompt: String) -> Result<String, Box<dyn std::error::Error + Send + Sync>> {
 let config_manager = crate::config::ConfigManager::new(state.conn.clone());
 let model = config_manager.get_config(&Uuid::nil(), "llm-model", None).unwrap_or_default();
 let handler = crate::llm_models::get_handler(&model);
 let raw_response = state.llm_provider.generate(&prompt, &serde_json::Value::Null, &model).await?;
 let processed = handler.process_content(&raw_response);
 Ok(processed)
}