Merge 4907952fd1 into 8df4a2670b

relay/adaptor/vertexai/adaptor.go

@@ -78,13 +78,19 @@ func (a *Adaptor) GetRequestURL(meta *meta.Meta) (string, error) {
 		}
 	}
 
+	model := meta.ActualModelName
+	if strings.Contains(model, "?") {
+		// TODO: Maybe fix meta.ActualModelName?
+		model = strings.Split(model, "?")[0]
+	}
+
 	if meta.BaseURL != "" {
 		return fmt.Sprintf(
 			"%s/v1/projects/%s/locations/%s/publishers/google/models/%s:%s",
 			meta.BaseURL,
 			meta.Config.VertexAIProjectID,
 			meta.Config.Region,
-			meta.ActualModelName,
+			model,
 			suffix,
 		), nil
 	}
@@ -93,7 +99,7 @@ func (a *Adaptor) GetRequestURL(meta *meta.Meta) (string, error) {
 		meta.Config.Region,
 		meta.Config.VertexAIProjectID,
 		meta.Config.Region,
-		meta.ActualModelName,
+		model,
 		suffix,
 	), nil
 }

relay/adaptor/vertexai/embedding/adapter.go

@@ -4,6 +4,7 @@ import (
 	"encoding/json"
 	"io"
 	"net/http"
+	"net/url"
 	"strings"
 
 	"github.com/songquanpeng/one-api/relay/adaptor/gemini"
@@ -23,11 +24,26 @@ var ModelList = []string{
 
 type Adaptor struct {
 	model string
-	task  EmbeddingTaskType
 }
 
 var _ model2.InnerAIAdapter = (*Adaptor)(nil)
 
+func (a *Adaptor) parseEmbeddingTaskType(model string) (string, EmbeddingTaskType) {
+	modelTaskType := EmbeddingTaskTypeNone
+	if strings.Contains(model, "?") {
+		parts := strings.Split(model, "?")
+		modelName := parts[0]
+		if len(parts) >= 2 {
+			modelOptions, err := url.ParseQuery(parts[1])
+			if err == nil {
+				modelTaskType = EmbeddingTaskType(modelOptions.Get("task_type"))
+			}
+		}
+		return modelName, modelTaskType
+	}
+	return model, modelTaskType
+}
+
 func (a *Adaptor) ConvertRequest(c *gin.Context, relayMode int, request *model.GeneralOpenAIRequest) (any, error) {
 	if request == nil {
 		return nil, errors.New("request is nil")
@@ -36,18 +52,13 @@ func (a *Adaptor) ConvertRequest(c *gin.Context, relayMode int, request *model.G
 	if len(inputs) == 0 {
 		return nil, errors.New("request is nil")
 	}
-	parts := strings.Split(request.Model, "|")
-	if len(parts) >= 2 {
-		a.task = EmbeddingTaskType(parts[1])
-	} else {
-		a.task = EmbeddingTaskTypeSemanticSimilarity
-	}
-	a.model = parts[0]
+	modelName, modelTaskType := a.parseEmbeddingTaskType(request.Model)
+	a.model = modelName
 	instances := make([]EmbeddingInstance, len(inputs))
 	for i, input := range inputs {
 		instances[i] = EmbeddingInstance{
 			Content:  input,
-			TaskType: a.task,
+			TaskType: modelTaskType,
 		}
 	}
 

relay/adaptor/vertexai/embedding/model.go

@@ -3,6 +3,7 @@ package vertexai
 type EmbeddingTaskType string
 
 const (
+	EmbeddingTaskTypeNone               EmbeddingTaskType = ""
 	EmbeddingTaskTypeRetrievalQuery     EmbeddingTaskType = "RETRIEVAL_QUERY"
 	EmbeddingTaskTypeRetrievalDocument  EmbeddingTaskType = "RETRIEVAL_DOCUMENT"
 	EmbeddingTaskTypeSemanticSimilarity EmbeddingTaskType = "SEMANTIC_SIMILARITY"