init: 昔涟项目骨架

2026-05-15 20:10:35 +08:00
commit 6bde87f807
84 changed files with 3635 additions and 0 deletions
@@ -0,0 +1,103 @@
+package orchestrator
+
+import (
+    "context"
+    "fmt"
+
+    "github.com/yourname/cyrene-ai/ai-core/internal/persona"
+    "github.com/yourname/cyrene-ai/ai-core/internal/context"
+    "github.com/yourname/cyrene-ai/ai-core/internal/llm"
+    "github.com/yourname/cyrene-ai/ai-core/internal/memory"
+)
+
+// Orchestrator 对话编排器 —— 核心组件
+type Orchestrator struct {
+    personaInjector *persona.Injector
+    contextBuilder  *context.Builder
+    llmAdapter      *llm.Adapter
+    memoryExtractor *memory.Extractor
+    memoryRetriever *memory.Retriever
+}
+
+// ProcessInput 处理用户输入的主流程
+func (o *Orchestrator) ProcessInput(
+    ctx context.Context,
+    userID string,
+    sessionID string,
+    userMessage string,
+    mode string, // text / voice_msg / voice_assistant
+) (*Response, error) {
+
+    // 步骤1: 检索相关记忆
+    memories, err := o.memoryRetriever.Retrieve(ctx, userID, userMessage)
+    if err != nil {
+        // 记忆检索失败不阻断对话
+        memories = nil
+    }
+
+    // 步骤2: 加载人格配置
+    personaConfig, err := o.personaInjector.LoadPersona("cyrene", userID)
+    if err != nil {
+        return nil, fmt.Errorf("加载人格配置失败: %w", err)
+    }
+
+    // 步骤3: 构建对话上下文
+    llmMessages, err := o.contextBuilder.Build(ctx, context.BuildParams{
+        UserID:       userID,
+        SessionID:    sessionID,
+        UserMessage:  userMessage,
+        Persona:      personaConfig,
+        Memories:     memories,
+        HistoryLimit: 20, // 最近20轮
+    })
+    if err != nil {
+        return nil, fmt.Errorf("构建上下文失败: %w", err)
+    }
+
+    // 步骤4: 调用LLM生成回复
+    llmResponse, err := o.llmAdapter.Chat(ctx, llmMessages)
+    if err != nil {
+        return nil, fmt.Errorf("LLM调用失败: %w", err)
+    }
+
+    // 步骤5: 提取并存储新的记忆
+    go o.memoryExtractor.ExtractAndStore(
+        context.Background(),
+        userID, sessionID,
+        userMessage, llmResponse.Content,
+    )
+
+    // 步骤6: 构建响应
+    response := &Response{
+        Text:         llmResponse.Content,
+        ResponseMode: mode,
+    }
+
+    // 步骤7: 如果是语音助手模式，进行断句处理
+    if mode == "voice_assistant" {
+        response.Segments = splitIntoSegments(llmResponse.Content)
+    }
+
+    return response, nil
+}
+
+// Response 回复结构
+type Response struct {
+    Text         string
+    Segments     []Segment
+    ResponseMode string
+    ToolCalls    []ToolCall
+}
+
+type Segment struct {
+    Index int
+    Text  string
+}
+
+// splitIntoSegments 按句号断句
+func splitIntoSegments(text string) []Segment {
+    // 实现按。！？等标点断句
+    // 首句优先：第一个句号前的内容作为第一个segment
+    // 保证低延迟首句播放
+    // ...
+}