173 lines
5.9 KiB
Rust
173 lines
5.9 KiB
Rust
//! AiPlugin — AI 语音对话插件 (M2.1)
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//!
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//! 设备本地跑 ASR (whisper.cpp) → LLM (llama.cpp) → TTS (piper) 管线,
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//! 提供语音/文字对话回合能力。声音一律返回客户端播放,设备不出声。
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//!
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//! # 架构
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//! ```text
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//! HTTP /api/chat → ChatPipeline.run() → ASR → LLM → TTS → ChatResponse
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//! (Arc<Mutex> 共享, HTTP 在 spawn_blocking 调用)
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//! ```
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//!
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//! AiPlugin 本身是薄层:持有 ChatPipeline Arc 供 HTTP 层取用,
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//! 并处理消息系统触发的联动(如 talk/idle 状态切换)。
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//!
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//! # 硬件约束 (Spike 2026-07-03 张明远实测)
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//! - 测试机全志 A733: 2×A78@2.0G + 6×A55@1.8G, 4G 内存
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//! - LLM 推理必须 t=2 锁大核 (全核反而崩且挤死视频)
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//! - 严禁默认上下文长度 (4096/8192 会吃 1-3.3GB)
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//! - 推荐默认 Qwen2.5-0.5B Q4_K_M (16.4 t/s, RSS 985M)
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pub mod backend;
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pub mod chat;
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pub mod model_manager;
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pub use chat::{ChatPipeline, SessionContext};
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use crate::core::message::Message;
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use crate::core::plugin::*;
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use anyhow::Result;
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use std::path::PathBuf;
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use std::sync::{Arc, Mutex};
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/// AiPlugin — AI 对话插件(薄层)
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///
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/// 持有 ChatPipeline 的共享句柄,供 HTTP 层取用。
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/// 自身处理消息系统触发的联动(talk/idle 状态切换等)。
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pub struct AiPlugin {
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ctx: Option<PluginContext>,
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/// 对话管线(HTTP 层通过 Arc clone 直接调用)
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pipeline: Arc<ChatPipeline>,
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/// 工具目录
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tools_dir: PathBuf,
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}
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impl AiPlugin {
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/// 创建默认本地后端实例
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pub fn new_default(
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model_store: PathBuf,
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tools_dir: PathBuf,
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whisper_lib_dir: Option<PathBuf>,
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piper_lib_dir: Option<PathBuf>,
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piper_config: Option<PathBuf>,
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espeak_data_dir: Option<PathBuf>,
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tmp_dir: PathBuf,
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context_window: usize,
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) -> Self {
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let mut backend_builder = backend::LocalCliBackend::new(tools_dir.clone());
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if let Some(lib_dir) = whisper_lib_dir {
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backend_builder = backend_builder.with_whisper_lib_dir(lib_dir);
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}
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// piper 三个依赖必须同时设置
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if let (Some(lib_dir), Some(config), Some(espeak_data)) = (piper_lib_dir, piper_config, espeak_data_dir) {
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backend_builder = backend_builder.with_piper_deps(lib_dir, config, espeak_data);
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}
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let backend = Box::new(backend_builder);
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let models = model_manager::ModelManager::new(model_store);
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let pipeline = ChatPipeline::new(backend, models, tmp_dir, context_window);
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Self {
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ctx: None,
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pipeline,
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tools_dir,
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}
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}
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/// 获取对话管线共享句柄(main.rs 注册时传给 HttpPlugin)
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pub fn pipeline(&self) -> Arc<ChatPipeline> {
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Arc::clone(&self.pipeline)
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}
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/// 获取模型管理器共享句柄(main.rs 注册时传给 HttpPlugin)
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pub fn models(&self) -> Arc<Mutex<model_manager::ModelManager>> {
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Arc::clone(&self.pipeline.models)
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}
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}
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impl Plugin for AiPlugin {
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fn id(&self) -> &str {
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"ai"
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}
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fn info(&self) -> PluginInfo {
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PluginInfo {
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name: "AiPlugin".to_string(),
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version: "0.1.0".to_string(),
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description: "AI 语音对话 (ASR/LLM/TTS 本地推理)".to_string(),
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platform: Platform::LinuxArm64,
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}
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}
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fn capabilities(&self) -> Vec<String> {
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vec!["chat".to_string(), "model_management".to_string()]
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}
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fn init(&mut self, ctx: PluginContext) -> Result<()> {
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self.ctx = Some(ctx);
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Ok(())
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}
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fn start(&mut self) -> Result<()> {
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// 确保临时目录存在
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if let Some(tmp) = self.pipeline.tmp_dir.parent() {
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std::fs::create_dir_all(tmp).ok();
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}
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std::fs::create_dir_all(&self.pipeline.tmp_dir).ok();
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// 预加载默认模型清单
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let mut models = self.pipeline.models.lock().unwrap();
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if let Err(e) = models.ensure_default_models() {
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eprintln!("[AiPlugin] 警告: 模型初始化失败: {e}");
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}
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drop(models);
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println!(
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"[AiPlugin] 启动 (tools={}, tmp={})",
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self.tools_dir.display(),
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self.pipeline.tmp_dir.display()
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);
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Ok(())
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}
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fn handle_message(&mut self, msg: Message) -> Result<()> {
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match msg {
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Message::ChatRequest(req) => {
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// 通过消息系统发起的对话(非 HTTP 路径),同步执行并广播结果
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let resp = self.pipeline.run(&req);
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if let Some(ctx) = &self.ctx {
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let _ = ctx.tx.send(crate::core::message::Envelope {
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from: self.id().to_string(),
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to: crate::core::message::Destination::Broadcast,
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message: Message::ChatResponse(resp),
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});
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}
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}
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Message::Shutdown => {
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self.stop()?;
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}
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Message::StateChanged { old_state, new_state } => {
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// 画面联动:进入/离开 talk 状态时记录日志(实际联动由 video 插件处理状态机)
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if new_state == "talk" || old_state == "talk" {
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println!("[AiPlugin] 画面状态: {old_state} → {new_state}");
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}
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}
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_ => {}
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}
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Ok(())
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}
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fn stop(&mut self) -> Result<()> {
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// 清理临时文件
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if self.pipeline.tmp_dir.exists() {
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if let Ok(entries) = std::fs::read_dir(&self.pipeline.tmp_dir) {
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for entry in entries.flatten() {
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let path = entry.path();
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if path.extension().and_then(|s| s.to_str()) == Some("wav") {
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let _ = std::fs::remove_file(&path);
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}
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}
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}
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}
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Ok(())
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}
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}
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