cfy666
4b731b5ac0
- graph.go: 构建 Graph 拓扑 START→STT→History→ChatModel→Splitter→TTS→Done→END - 创建 eino-ext ChatModel 对接 DashScope OpenAI 兼容接口 - 统一使用值类型（PipelineInput/PipelineOutput） - Callback 在运行时通过 Stream option 传入 - adapter.go: EinoOrchestrator 实现 orchestrator.Orchestrator 接口 - 解码 base64 音频/图片，注入 context 值 - 调用 Graph.Stream() 触发惰性执行并消费输出 - 追加用户/助手消息到历史 - main.go: 移除旧 llmService + orchestrator.New() 替换为 eino.NewPipelineGraph() + eino.NewEinoOrchestrator() - 各节点统一使用值类型，State 传递请求元数据 Co-Authored-By: Claude <noreply@anthropic.com>
119 lines
3.3 KiB
Go
119 lines
3.3 KiB
Go
package eino
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import (
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"context"
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"encoding/base64"
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"github.com/cloudwego/eino/compose"
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"github.com/cloudwego/eino/schema"
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"github.com/hhs/camtalk/internal/ai/llm"
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"github.com/hhs/camtalk/internal/logger"
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"github.com/hhs/camtalk/internal/models"
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)
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// NewHistoryLambda 创建历史组装 Lambda 节点。
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// 输入: *STTOutput → 输出: []*schema.Message
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//
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// 从 PipelineState 读取请求元数据（SessionID、Scenario、ImageData 等），
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// 构建系统提示词，组装历史消息和当前用户输入（含多模态图片）。
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func NewHistoryLambda(historyFetcher func(ctx context.Context, sessionID string, limit int) ([]models.Message, error), maxHistory int) *compose.Lambda {
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return compose.InvokableLambda(func(ctx context.Context, sttOut STTOutput) ([]*schema.Message, error) {
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log := logger.Log
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// 从 State 读取请求元数据
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state := stateFromCtx(ctx)
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if state == nil {
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return []*schema.Message{}, nil
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}
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state.mu.Lock()
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sessionID := state.SessionID
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requestID := state.RequestID
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imageData := state.ImageData
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scenario := state.Scenario
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detailLevel := state.DetailLevel
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language := sttOut.Language
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state.mu.Unlock()
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// 构建系统提示词
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scenarioPrompt := llm.GetScenarioPrompt(scenario, language)
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systemPrompt := llm.BuildSystemPrompt(language, detailLevel, scenarioPrompt)
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// 构建 system message（含图片）
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systemMsg := &schema.Message{
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Role: schema.System,
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Content: systemPrompt,
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}
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// 如果有图片，添加到 system message 的多模态内容中
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if len(imageData) > 0 {
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base64Str := base64.StdEncoding.EncodeToString(imageData)
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mimeType := detectImageMimeType(imageData)
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systemMsg.UserInputMultiContent = []schema.MessageInputPart{
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{
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Type: schema.ChatMessagePartTypeImageURL,
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Image: &schema.MessageInputImage{
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MessagePartCommon: schema.MessagePartCommon{
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Base64Data: &base64Str,
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MIMEType: mimeType,
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},
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Detail: schema.ImageURLDetailAuto,
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},
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},
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}
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}
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messages := []*schema.Message{systemMsg}
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// 获取并追加历史消息
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if historyFetcher != nil && sessionID != "" {
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history, err := historyFetcher(ctx, sessionID, maxHistory)
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if err != nil {
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log.Warnw("获取历史消息失败，继续处理", "error", err, "request_id", requestID)
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} else {
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for _, msg := range history {
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messages = append(messages, &schema.Message{
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Role: schema.RoleType(msg.Role),
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Content: msg.Content,
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})
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}
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}
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}
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// 追加当前用户输入
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messages = append(messages, &schema.Message{
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Role: schema.User,
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Content: sttOut.Text,
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})
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log.Infow("历史组装完成",
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"request_id", requestID,
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"message_count", len(messages),
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"has_image", len(imageData) > 0,
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"scenario", scenario)
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return messages, nil
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})
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}
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// detectImageMimeType 简单检测图片 MIME 类型。
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func detectImageMimeType(data []byte) string {
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if len(data) < 4 {
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return "image/jpeg"
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}
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if data[0] == 0xFF && data[1] == 0xD8 && data[2] == 0xFF {
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return "image/jpeg"
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}
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if data[0] == 0x89 && data[1] == 0x50 && data[2] == 0x4E && data[3] == 0x47 {
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return "image/png"
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}
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if data[0] == 0x47 && data[1] == 0x49 && data[2] == 0x46 {
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return "image/gif"
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}
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if data[0] == 0x52 && data[1] == 0x49 && data[2] == 0x46 && data[3] == 0x46 {
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return "image/webp"
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}
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return "image/jpeg"
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}
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