Version: 0.9.65.dev.260503
后端： 1. 阶段 1.5/1.6 收口 llm-service / rag-service，统一模型出口与检索基础设施入口，清退 backend/infra/llm 与 backend/infra/rag 旧实现； 2. 同步更新相关调用链与微服务迁移计划文档
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Losita
208
backend/services/rag/embed/eino_embedder.go
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208
backend/services/rag/embed/eino_embedder.go
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package embed
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import (
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"context"
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"errors"
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"fmt"
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"net/http"
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"strings"
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"time"
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openaiembedding "github.com/cloudwego/eino-ext/libs/acl/openai"
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einoembedding "github.com/cloudwego/eino/components/embedding"
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"github.com/volcengine/volcengine-go-sdk/service/arkruntime"
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arkmodel "github.com/volcengine/volcengine-go-sdk/service/arkruntime/model"
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)
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// EinoConfig 描述 Eino embedding 运行参数。
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type EinoConfig struct {
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APIKey string
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BaseURL string
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Model string
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TimeoutMS int
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Dimension int
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}
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// EinoEmbedder 是基于 Eino 的 embedding 适配器。
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//
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// 说明：
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// 1. 对 infra/rag 暴露统一 []float32 结果，屏蔽底层 SDK 的实现差异。
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// 2. 文本 embedding 继续走当前稳定的 OpenAI 兼容链路，避免无关模型受影响。
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// 3. 多模态 embedding 模型单独走 Ark 原生 `/embeddings/multimodal`，解决 vision 模型与标准 `/embeddings` 不兼容的问题。
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type EinoEmbedder struct {
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textClient einoembedding.Embedder
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multimodalClient *arkruntime.Client
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model string
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timeout time.Duration
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dimension int
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}
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func NewEinoEmbedder(ctx context.Context, cfg EinoConfig) (*EinoEmbedder, error) {
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if strings.TrimSpace(cfg.APIKey) == "" {
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return nil, errors.New("eino embedder api key is empty")
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}
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if strings.TrimSpace(cfg.Model) == "" {
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return nil, errors.New("eino embedder model is empty")
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}
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timeout := 1200 * time.Millisecond
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if cfg.TimeoutMS > 0 {
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timeout = time.Duration(cfg.TimeoutMS) * time.Millisecond
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}
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baseURL := normalizeEmbeddingBaseURL(cfg.BaseURL)
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model := strings.TrimSpace(cfg.Model)
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httpClient := &http.Client{Timeout: timeout}
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// 1. `doubao-embedding-vision-*` 这类模型不支持标准 `/embeddings`。
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// 2. 这里直接切到 Ark 原生多模态 embedding API，避免再依赖错误 endpoint 拼接。
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// 3. 之所以仍保留文本链路，是为了不影响普通 text embedding 模型的既有行为。
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if isMultimodalEmbeddingModel(model) {
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arkOptions := []arkruntime.ConfigOption{
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arkruntime.WithHTTPClient(httpClient),
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}
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if baseURL != "" {
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arkOptions = append(arkOptions, arkruntime.WithBaseUrl(baseURL))
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}
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return &EinoEmbedder{
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multimodalClient: arkruntime.NewClientWithApiKey(
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strings.TrimSpace(cfg.APIKey),
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arkOptions...,
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),
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model: model,
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timeout: timeout,
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dimension: cfg.Dimension,
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}, nil
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}
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clientCfg := &openaiembedding.EmbeddingConfig{
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APIKey: strings.TrimSpace(cfg.APIKey),
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BaseURL: baseURL,
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Model: model,
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HTTPClient: httpClient,
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}
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if cfg.Dimension > 0 {
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clientCfg.Dimensions = &cfg.Dimension
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}
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client, err := openaiembedding.NewEmbeddingClient(ctx, clientCfg)
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if err != nil {
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return nil, err
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}
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return &EinoEmbedder{
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textClient: client,
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model: model,
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timeout: timeout,
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dimension: cfg.Dimension,
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}, nil
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}
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func (e *EinoEmbedder) Embed(ctx context.Context, texts []string, _ string) (result [][]float32, err error) {
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if e == nil {
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return nil, errors.New("eino embedder is not initialized")
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}
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if len(texts) == 0 {
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return nil, nil
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}
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callCtx := ctx
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cancel := func() {}
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if e.timeout > 0 {
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callCtx, cancel = context.WithTimeout(ctx, e.timeout)
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}
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defer cancel()
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// 1. 第三方 SDK 一旦 panic，不应该穿透到 RAG 主链路。
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// 2. 这里统一在模型调用边界 recover，并转成 error 交给上层做降级。
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// 3. 这样 memory 主写链路和 agent 主回复链路都不会因为向量同步失败被直接打崩。
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defer func() {
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if recovered := recover(); recovered != nil {
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err = fmt.Errorf("eino embedder panic recovered: %v", recovered)
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result = nil
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}
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}()
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if e.multimodalClient != nil {
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return e.embedTextsWithMultimodalAPI(callCtx, texts)
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}
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if e.textClient == nil {
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return nil, errors.New("eino embedder client is not initialized")
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}
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vectors, err := e.textClient.EmbedStrings(callCtx, texts, einoembedding.WithModel(e.model))
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if err != nil {
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return nil, err
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}
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result = make([][]float32, 0, len(vectors))
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for _, vector := range vectors {
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converted := make([]float32, len(vector))
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for i, value := range vector {
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converted[i] = float32(value)
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}
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result = append(result, converted)
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}
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return result, nil
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}
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func (e *EinoEmbedder) embedTextsWithMultimodalAPI(ctx context.Context, texts []string) ([][]float32, error) {
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if e.multimodalClient == nil {
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return nil, errors.New("eino multimodal embedder client is not initialized")
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}
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vectors := make([][]float32, 0, len(texts))
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for _, text := range texts {
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text := text
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req := arkmodel.MultiModalEmbeddingRequest{
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Model: e.model,
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Input: []arkmodel.MultimodalEmbeddingInput{
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{
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Type: arkmodel.MultiModalEmbeddingInputTypeText,
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Text: &text,
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},
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},
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}
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if e.dimension > 0 {
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req.Dimensions = &e.dimension
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}
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// 1. Ark 的多模态 embedding 请求体是“单条内容由多个 part 组成”。
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// 2. 当前 RAG 这里只传文本，因此每段文本单独发一次，避免把多段文本错误拼成同一个 multimodal sample。
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// 3. 一旦后续真的要做批量多模态 embedding，再单独扩展 batch 接口，而不是在这里偷改语义。
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resp, err := e.multimodalClient.CreateMultiModalEmbeddings(ctx, req)
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if err != nil {
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return nil, err
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}
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converted := make([]float32, len(resp.Data.Embedding))
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copy(converted, resp.Data.Embedding)
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vectors = append(vectors, converted)
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}
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return vectors, nil
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}
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func isMultimodalEmbeddingModel(model string) bool {
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return strings.HasPrefix(strings.ToLower(strings.TrimSpace(model)), "doubao-embedding-vision-")
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}
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func normalizeEmbeddingBaseURL(raw string) string {
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baseURL := strings.TrimRight(strings.TrimSpace(raw), "/")
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if baseURL == "" {
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return ""
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}
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lowerBaseURL := strings.ToLower(baseURL)
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// 1. 配置里应填写 Ark 服务根路径，而不是具体 embedding endpoint。
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// 2. 这里兼容两类常见误配：`/embeddings` 和 `/embeddings/multimodal`。
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// 3. 统一回退到 `/api/v3` 根路径后，再由对应 SDK 自己追加正确后缀，避免最终 URL 重复拼接。
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if strings.HasSuffix(lowerBaseURL, "/embeddings/multimodal") {
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return strings.TrimSuffix(baseURL, baseURL[len(baseURL)-len("/embeddings/multimodal"):])
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}
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if strings.HasSuffix(lowerBaseURL, "/embeddings") {
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return strings.TrimSuffix(baseURL, baseURL[len(baseURL)-len("/embeddings"):])
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}
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return baseURL
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}
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46
backend/services/rag/embed/mock_embedder.go
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46
backend/services/rag/embed/mock_embedder.go
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@@ -0,0 +1,46 @@
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package embed
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import (
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"context"
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"crypto/sha256"
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"encoding/binary"
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"strings"
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)
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const defaultDim = 16
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// MockEmbedder 是本地可运行的占位向量化实现。
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//
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// 说明：
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// 1. 该实现用于开发阶段打通链路，不代表真实语义向量质量；
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// 2. 后续可替换为 Eino embedding 实现，接口保持不变。
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type MockEmbedder struct {
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dim int
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}
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func NewMockEmbedder(dim int) *MockEmbedder {
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if dim <= 0 {
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dim = defaultDim
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}
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return &MockEmbedder{dim: dim}
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}
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func (e *MockEmbedder) Embed(_ context.Context, texts []string, _ string) ([][]float32, error) {
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result := make([][]float32, 0, len(texts))
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for _, text := range texts {
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result = append(result, e.embedOne(text))
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}
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return result, nil
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}
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func (e *MockEmbedder) embedOne(text string) []float32 {
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normalized := strings.TrimSpace(strings.ToLower(text))
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sum := sha256.Sum256([]byte(normalized))
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vec := make([]float32, e.dim)
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for i := 0; i < e.dim; i++ {
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offset := (i * 4) % len(sum)
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v := binary.BigEndian.Uint32(sum[offset : offset+4])
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vec[i] = float32(v%1000) / 1000
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}
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return vec
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}
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