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package main
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import (
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"context"
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"encoding/json"
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"fmt"
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"log"
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"net/http"
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"os"
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"os/signal"
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"syscall"
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"time"
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"github.com/yourname/cyrene-ai/ai-core/internal/context"
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"github.com/yourname/cyrene-ai/ai-core/internal/llm"
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"github.com/yourname/cyrene-ai/ai-core/internal/memory"
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"github.com/yourname/cyrene-ai/ai-core/internal/model"
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"github.com/yourname/cyrene-ai/ai-core/internal/orchestrator"
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"github.com/yourname/cyrene-ai/ai-core/internal/persona"
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)
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func main() {
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log.SetFlags(log.LstdFlags | log.Lshortfile)
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log.Println("🧠 AI-Core 服务启动中...")
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// 加载配置
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cfg := loadConfig()
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// 初始化人格加载器
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personaDir := cfg.PersonaDir
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if personaDir == "" {
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personaDir = "./internal/persona"
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}
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personaLoader, err := persona.NewLoader(personaDir)
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if err != nil {
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log.Fatalf("加载人格配置失败: %v", err)
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}
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log.Printf("已加载 %d 个人格: %v", len(personaLoader.List()), personaLoader.List())
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// 初始化LLM适配器
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llmProvider := llm.NewOpenAIProvider(llm.OpenAIConfig{
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BaseURL: cfg.LLMBaseURL,
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APIKey: cfg.LLMAPIKey,
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Model: cfg.LLMModel,
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FallbackModel: cfg.LLMFallbackModel,
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Timeout: 120 * time.Second,
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})
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llmAdapter := llm.NewAdapter(llmProvider)
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log.Printf("LLM适配器已就绪: 模型=%s", llmAdapter.ModelName())
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// 初始化记忆系统
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var memStore *memory.Store
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var memRetriever *memory.Retriever
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var memExtractor *memory.Extractor
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if cfg.DatabaseURL != "" {
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memStore, err = memory.NewStore(cfg.DatabaseURL)
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if err != nil {
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log.Printf("⚠ 记忆存储初始化失败 (将跳过记忆功能): %v", err)
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} else {
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defer memStore.Close()
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log.Println("记忆存储已就绪")
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memRetriever = memory.NewRetriever(memStore, nil)
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// 记忆提取器使用LLM
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memExtractor = memory.NewExtractor(memStore, func(ctx context.Context, messages []model.LLMMessage) (*model.LLMResponse, error) {
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return llmAdapter.Chat(ctx, messages)
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})
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log.Println("记忆提取器已就绪")
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}
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}
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// 初始化上下文构建器
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ctxBuilder := &context.Builder{}
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// 手动注入 Injector 到 orchestrator（临时方案，后续会用依赖注入框架）
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personaInjector := &persona.Injector{}
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// 健康检查与对话API的HTTP mux
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mux := http.NewServeMux()
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// 手动构建 orchestrator 用于处理（因为现有orchestrator结构体已定义但未导出构造函数）
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orch := &orchestrator.Orchestrator{}
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// 注册对话API端点
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mux.HandleFunc("/api/v1/chat", func(w http.ResponseWriter, r *http.Request) {
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handleChat(w, r, orch, ctxBuilder, llmAdapter, personaLoader, personaInjector, memRetriever, memExtractor)
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})
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mux.HandleFunc("/api/v1/health", func(w http.ResponseWriter, r *http.Request) {
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w.Header().Set("Content-Type", "application/json")
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w.Write([]byte(`{"status":"ok","service":"ai-core","model":"` + llmAdapter.ModelName() + `"}`))
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})
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// 启动HTTP服务
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srv := &http.Server{
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Addr: ":" + cfg.Port,
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Handler: mux,
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}
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go func() {
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log.Printf("🚀 AI-Core 服务已启动在端口 %s", cfg.Port)
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if err := srv.ListenAndServe(); err != nil && err != http.ErrServerClosed {
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log.Fatalf("服务启动失败: %v", err)
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}
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}()
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// 优雅关闭
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quit := make(chan os.Signal, 1)
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signal.Notify(quit, syscall.SIGINT, syscall.SIGTERM)
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<-quit
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log.Println("正在关闭 AI-Core 服务...")
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ctx, cancel := context.WithTimeout(context.Background(), 10*time.Second)
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defer cancel()
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srv.Shutdown(ctx)
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log.Println("AI-Core 服务已关闭")
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}
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// Config AI-Core配置
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type Config struct {
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Port string
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PersonaDir string
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LLMBaseURL string
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LLMAPIKey string
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LLMModel string
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LLMFallbackModel string
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DatabaseURL string
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}
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func loadConfig() Config {
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return Config{
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Port: getEnv("AI_CORE_PORT", "8081"),
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PersonaDir: getEnv("PERSONA_DIR", "./internal/persona"),
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LLMBaseURL: getEnv("LLM_API_URL", "https://api.openai.com/v1"),
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LLMAPIKey: getEnv("LLM_API_KEY", ""),
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LLMModel: getEnv("LLM_MODEL", "gpt-4o"),
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LLMFallbackModel: getEnv("LLM_FALLBACK_MODEL", "gpt-4o-mini"),
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DatabaseURL: buildDatabaseURL(),
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}
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}
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func buildDatabaseURL() string {
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host := getEnv("POSTGRES_HOST", "localhost")
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port := getEnv("POSTGRES_PORT", "5432")
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user := getEnv("POSTGRES_USER", "cyrene")
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password := getEnv("POSTGRES_PASSWORD", "change_me")
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dbname := getEnv("POSTGRES_DB", "cyrene_ai")
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sslmode := getEnv("POSTGRES_SSLMODE", "disable")
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return fmt.Sprintf("postgres://%s:%s@%s:%s/%s?sslmode=%s",
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user, password, host, port, dbname, sslmode)
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}
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func getEnv(key, fallback string) string {
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if v := os.Getenv(key); v != "" {
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return v
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}
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return fallback
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}
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// handleChat 处理对话请求
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func handleChat(
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w http.ResponseWriter,
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r *http.Request,
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_ *orchestrator.Orchestrator,
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ctxBuilder *context.Builder,
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llmAdapter *llm.Adapter,
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personaLoader *persona.Loader,
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personaInjector *persona.Injector,
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memRetriever *memory.Retriever,
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memExtractor *memory.Extractor,
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) {
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if r.Method != http.MethodPost {
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http.Error(w, "Method not allowed", http.StatusMethodNotAllowed)
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return
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}
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// 解析请求
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var req struct {
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UserID string `json:"user_id"`
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SessionID string `json:"session_id"`
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Message string `json:"message"`
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Mode string `json:"mode"`
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}
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if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
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http.Error(w, "无效的请求体", http.StatusBadRequest)
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return
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}
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if req.Mode == "" {
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req.Mode = "text"
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}
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ctx := r.Context()
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// 1. 检索相关记忆
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var memories []memory.MemoryEntry
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if memRetriever != nil {
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var err error
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memories, err = memRetriever.Retrieve(ctx, req.UserID, req.Message)
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if err != nil {
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log.Printf("[chat] 记忆检索失败: %v", err)
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}
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}
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// 2. 加载人格配置
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personaConfig, err := personaLoader.Get("cyrene")
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if err != nil {
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http.Error(w, fmt.Sprintf("加载人格失败: %v", err), http.StatusInternalServerError)
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return
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}
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// 3. 构建对话上下文
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llmMessages, err := ctxBuilder.Build(ctx, context.BuildParams{
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UserID: req.UserID,
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SessionID: req.SessionID,
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UserMessage: req.Message,
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Persona: personaConfig,
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Memories: memories,
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HistoryLimit: 20,
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})
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if err != nil {
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http.Error(w, fmt.Sprintf("构建上下文失败: %v", err), http.StatusInternalServerError)
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return
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}
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// 4. 调用LLM
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llmResp, err := llmAdapter.Chat(ctx, llmMessages)
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if err != nil {
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http.Error(w, fmt.Sprintf("LLM调用失败: %v", err), http.StatusInternalServerError)
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return
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}
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// 5. 异步提取记忆
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if memExtractor != nil {
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go memExtractor.ExtractAndStore(context.Background(), req.UserID, req.SessionID, req.Message, llmResp.Content)
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}
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// 6. 构建响应
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resp := map[string]interface{}{
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"text": llmResp.Content,
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"mode": req.Mode,
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"message_id": fmt.Sprintf("msg-%d", time.Now().UnixNano()),
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}
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// 语音助手模式断句
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if req.Mode == "voice_assistant" {
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resp["segments"] = llm.SplitIntoSegments(llmResp.Content)
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}
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w.Header().Set("Content-Type", "application/json")
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json.NewEncoder(w).Encode(resp)
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}
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// 确保未使用变量不报错
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var _ = personaInjector
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