From c55e23e7e263c60715aedd7716bcff19e3b38e53 Mon Sep 17 00:00:00 2001
From: Jin Hai <haijin.chn@gmail.com>
Date: Mon, 11 May 2026 14:45:30 +0800
Subject: [PATCH] Go: refactor embedding interface (#14757)

### What problem does this PR solve?

Provide embedding index according to the input text

### Type of change

- [x] Refactoring

---------

Signed-off-by: Jin Hai <haijin.chn@gmail.com>
---
 internal/cli/response.go              |  50 +++++++++-
 internal/cli/user_command.go          |   2 +-
 internal/entity/models/aliyun.go      |  55 +++++------
 internal/entity/models/baidu.go       |  83 +++++++---------
 internal/entity/models/deepseek.go    |   4 +-
 internal/entity/models/dummy.go       |   4 +-
 internal/entity/models/gitee.go       |  62 ++++++------
 internal/entity/models/google.go      |  11 ++-
 internal/entity/models/huggingface.go |  26 ++---
 internal/entity/models/lmstudio.go    |  46 ++-------
 internal/entity/models/minimax.go     |   4 +-
 internal/entity/models/moonshot.go    |   4 +-
 internal/entity/models/nvidia.go      |  37 ++-----
 internal/entity/models/ollama.go      |  46 ++-------
 internal/entity/models/openai.go      |  58 +++++------
 internal/entity/models/openrouter.go  |  50 +++++-----
 internal/entity/models/siliconflow.go | 115 ++++++++--------------
 internal/entity/models/types.go       |  13 +--
 internal/entity/models/vllm.go        |  42 +++-----
 internal/entity/models/volcengine.go  |  55 +++++++----
 internal/entity/models/xai.go         |   4 +-
 internal/entity/models/zhipu-ai.go    | 136 ++++++++++++++------------
 internal/handler/providers.go         |   4 +-
 internal/service/model_service.go     |  36 ++-----
 internal/service/nlp/retrieval.go     |   4 +-
 internal/service/skill_indexer.go     |  33 ++++---
 internal/service/skill_search.go      |   8 +-
 uv.lock                               |  18 +---
 28 files changed, 443 insertions(+), 567 deletions(-)

diff --git a/internal/cli/response.go b/internal/cli/response.go
index 4331a76adb..b505a7a53f 100644
--- a/internal/cli/response.go
+++ b/internal/cli/response.go
@@ -277,6 +277,48 @@ func (r *KeyValueResponse) PrintOut() {
 	}
 }
 
+type EmbeddingData struct {
+	Index     int       `json:"index"`
+	Embedding []float64 `json:"embedding"`
+}
+
+type EmbeddingsResponse struct {
+	Code         int             `json:"code"`
+	Data         []EmbeddingData `json:"data"`
+	Message      string          `json:"message"`
+	Duration     float64
+	OutputFormat OutputFormat
+}
+
+func (r *EmbeddingsResponse) Type() string {
+	return "common"
+}
+
+func (r *EmbeddingsResponse) TimeCost() float64 {
+	return r.Duration
+}
+
+func (r *EmbeddingsResponse) SetOutputFormat(format OutputFormat) {
+	r.OutputFormat = format
+}
+
+func (r *EmbeddingsResponse) PrintOut() {
+	var data []map[string]interface{}
+	for _, embedding := range r.Data {
+		data = append(data, map[string]interface{}{
+			"index":     formatValue(embedding.Index),
+			"dimension": len(embedding.Embedding),
+		})
+	}
+
+	if r.Code == 0 {
+		PrintTableSimpleByFormat(data, r.OutputFormat)
+	} else {
+		fmt.Println("ERROR")
+		fmt.Printf("%d, %s\n", r.Code, r.Message)
+	}
+}
+
 // ==================== ContextEngine Commands ====================
 
 // ContextListResponse represents the response for ls command
@@ -325,9 +367,9 @@ func (r *ContextSearchResponse) PrintOut() {
 
 // ContextCatResponse represents the response for cat command
 type ContextCatResponse struct {
-	Code         int          `json:"code"`
-	Content      string       `json:"content"`
-	Message      string       `json:"message"`
+	Code         int    `json:"code"`
+	Content      string `json:"content"`
+	Message      string `json:"message"`
 	Duration     float64
 	OutputFormat OutputFormat
 }
@@ -343,5 +385,3 @@ func (r *ContextCatResponse) PrintOut() {
 		fmt.Printf("%d, %s\n", r.Code, r.Message)
 	}
 }
-
-
diff --git a/internal/cli/user_command.go b/internal/cli/user_command.go
index a8394e40a6..14a058aa25 100644
--- a/internal/cli/user_command.go
+++ b/internal/cli/user_command.go
@@ -1838,7 +1838,7 @@ func (c *RAGFlowClient) EmbedUserText(cmd *Command) (ResponseIf, error) {
 	if resp.StatusCode != 200 {
 		return nil, fmt.Errorf("failed to embed text: HTTP %d, body: %s", resp.StatusCode, string(resp.Body))
 	}
-	var result CommonResponse
+	var result EmbeddingsResponse
 	if err = json.Unmarshal(resp.Body, &result); err != nil {
 		return nil, fmt.Errorf("embed text failed: invalid JSON (%w)", err)
 	}
diff --git a/internal/entity/models/aliyun.go b/internal/entity/models/aliyun.go
index 3ec313e1f0..325eb0ac6d 100644
--- a/internal/entity/models/aliyun.go
+++ b/internal/entity/models/aliyun.go
@@ -362,16 +362,28 @@ func (z *AliyunModel) ChatStreamlyWithSender(modelName string, messages []Messag
 }
 
 type aliyunEmbeddingResponse struct {
-	Data []struct {
-		Index     int           `json:"index"`
-		Embedding []interface{} `json:"embedding"`
-	} `json:"data"`
+	Data   []EmbeddingData `json:"data"`
+	Model  string          `json:"model"`
+	Object string          `json:"object"`
+	Usage  aliyunUsage     `json:"usage"`
+	ID     string          `json:"id"`
 }
 
-// Encode encodes a list of texts into embeddings
-func (z *AliyunModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+type aliyunEmbeddingData struct {
+	Embedding []float64 `json:"embedding"`
+	Index     int       `json:"index"`
+	Object    string    `json:"object"`
+}
+
+type aliyunUsage struct {
+	PromptTokens int `json:"prompt_tokens"`
+	TotalTokens  int `json:"total_tokens"`
+}
+
+// Embed embeds a list of texts into embeddings
+func (z *AliyunModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	if len(texts) == 0 {
-		return [][]float64{}, nil
+		return []EmbeddingData{}, nil
 	}
 
 	if apiConfig == nil || apiConfig.ApiKey == nil || *apiConfig.ApiKey == "" {
@@ -440,29 +452,12 @@ func (z *AliyunModel) Encode(modelName *string, texts []string, apiConfig *APICo
 		return nil, fmt.Errorf("failed to parse response: %w", err)
 	}
 
-	embeddings := make([][]float64, len(texts))
-	for _, item := range parsed.Data {
-		if item.Index < 0 || item.Index >= len(texts) {
-			return nil, fmt.Errorf("unexpected embedding index %d for %d inputs", item.Index, len(texts))
-		}
-		vec := make([]float64, len(item.Embedding))
-		for j, v := range item.Embedding {
-			switch val := v.(type) {
-			case float64:
-				vec[j] = val
-			case float32:
-				vec[j] = float64(val)
-			default:
-				return nil, fmt.Errorf("unexpected embedding value type at item %d index %d", item.Index, j)
-			}
-		}
-		embeddings[item.Index] = vec
-	}
-
-	for i, vec := range embeddings {
-		if vec == nil {
-			return nil, fmt.Errorf("missing embedding for input at index %d", i)
-		}
+	var embeddings []EmbeddingData
+	for _, dataElem := range parsed.Data {
+		var embeddingData EmbeddingData
+		embeddingData.Embedding = dataElem.Embedding
+		embeddingData.Index = dataElem.Index
+		embeddings = append(embeddings, embeddingData)
 	}
 
 	return embeddings, nil
diff --git a/internal/entity/models/baidu.go b/internal/entity/models/baidu.go
index ad24ced9b4..15fb4f4284 100644
--- a/internal/entity/models/baidu.go
+++ b/internal/entity/models/baidu.go
@@ -385,14 +385,14 @@ func (b *BaiduModel) ChatStreamlyWithSender(modelName string, messages []Message
 
 		reasoningContent, ok := delta["reasoning_content"].(string)
 		if ok && reasoningContent != "" {
-			if err := sender(nil, &reasoningContent); err != nil {
+			if err = sender(nil, &reasoningContent); err != nil {
 				return err
 			}
 		}
 
 		content, ok := delta["content"].(string)
 		if ok && content != "" {
-			if err := sender(&content, nil); err != nil {
+			if err = sender(&content, nil); err != nil {
 				return err
 			}
 		}
@@ -412,9 +412,29 @@ func (b *BaiduModel) ChatStreamlyWithSender(modelName string, messages []Message
 	return scanner.Err()
 }
 
-func (b *BaiduModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+type baiduEmbeddingResponse struct {
+	ID      string               `json:"id"`
+	Object  string               `json:"object"`
+	Created int64                `json:"created"`
+	Data    []baiduEmbeddingData `json:"data"`
+	Model   string               `json:"model"`
+	Usage   baiduUsage           `json:"usage"`
+}
+
+type baiduEmbeddingData struct {
+	Object    string    `json:"object"`
+	Embedding []float64 `json:"embedding"`
+	Index     int       `json:"index"`
+}
+
+type baiduUsage struct {
+	PromptTokens int `json:"prompt_tokens"`
+	TotalTokens  int `json:"total_tokens"`
+}
+
+func (b *BaiduModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	if len(texts) == 0 {
-		return [][]float64{}, nil
+		return []EmbeddingData{}, nil
 	}
 
 	var region = "default"
@@ -457,52 +477,17 @@ func (b *BaiduModel) Encode(modelName *string, texts []string, apiConfig *APICon
 		return nil, fmt.Errorf("Baidu embedding API error: status %d, body: %s", resp.StatusCode, string(body))
 	}
 
-	var result map[string]interface{}
-	if err = json.Unmarshal(body, &result); err != nil {
-		return nil, fmt.Errorf("failed to decode response: %w", err)
+	var parsed baiduEmbeddingResponse
+	if err = json.Unmarshal(body, &parsed); err != nil {
+		return nil, fmt.Errorf("failed to parse response: %w", err)
 	}
 
-	dataObj, ok := result["data"].([]interface{})
-	if !ok || len(dataObj) == 0 {
-		return nil, fmt.Errorf("Baidu embedding response contains no data: %s", string(body))
-	}
-
-	embeddings := make([][]float64, len(texts))
-
-	for _, item := range dataObj {
-		dataMap, ok := item.(map[string]interface{})
-		if !ok {
-			continue
-		}
-
-		indexFloat, ok := dataMap["index"].(float64)
-		if !ok {
-			continue
-		}
-		index := int(indexFloat)
-
-		if index < 0 || index >= len(texts) {
-			continue
-		}
-
-		embeddingSlice, ok := dataMap["embedding"].([]interface{})
-		if !ok {
-			continue
-		}
-
-		embedding := make([]float64, len(embeddingSlice))
-		for j, v := range embeddingSlice {
-			switch val := v.(type) {
-			case float64:
-				embedding[j] = val
-			case float32:
-				embedding[j] = float64(val)
-			default:
-				return nil, fmt.Errorf("unexpected embedding value type")
-			}
-		}
-
-		embeddings[index] = embedding
+	var embeddings []EmbeddingData
+	for _, dataElem := range parsed.Data {
+		var embeddingData EmbeddingData
+		embeddingData.Embedding = dataElem.Embedding
+		embeddingData.Index = dataElem.Index
+		embeddings = append(embeddings, embeddingData)
 	}
 
 	return embeddings, nil
@@ -567,7 +552,7 @@ func (b *BaiduModel) Rerank(modelName *string, query string, documents []string,
 		} `json:"results"`
 	}
 
-	if err := json.Unmarshal(body, &rerankResp); err != nil {
+	if err = json.Unmarshal(body, &rerankResp); err != nil {
 		return nil, fmt.Errorf("failed to decode response: %w", err)
 	}
 
diff --git a/internal/entity/models/deepseek.go b/internal/entity/models/deepseek.go
index dc06ebbfbd..1f4e107e42 100644
--- a/internal/entity/models/deepseek.go
+++ b/internal/entity/models/deepseek.go
@@ -415,8 +415,8 @@ func (z *DeepSeekModel) ChatStreamlyWithSender(modelName string, messages []Mess
 	return scanner.Err()
 }
 
-// Encode encodes a list of texts into embeddings
-func (z *DeepSeekModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+// Embed embeds a list of texts into embeddings
+func (z *DeepSeekModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	return nil, fmt.Errorf("%s, no such method", z.Name())
 }
 
diff --git a/internal/entity/models/dummy.go b/internal/entity/models/dummy.go
index ffc0f9f4b7..149c69af73 100644
--- a/internal/entity/models/dummy.go
+++ b/internal/entity/models/dummy.go
@@ -52,8 +52,8 @@ func (z *DummyModel) ChatStreamlyWithSender(modelName string, messages []Message
 	return fmt.Errorf("not implemented")
 }
 
-// Encode encodes a list of texts into embeddings
-func (z *DummyModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+// Embed embeds a list of texts into embeddings
+func (z *DummyModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	return nil, fmt.Errorf("not implemented")
 }
 
diff --git a/internal/entity/models/gitee.go b/internal/entity/models/gitee.go
index 417b7e2ddf..335ec63484 100644
--- a/internal/entity/models/gitee.go
+++ b/internal/entity/models/gitee.go
@@ -29,13 +29,6 @@ import (
 	"time"
 )
 
-type giteeEmbeddingResponse struct {
-	Data []struct {
-		Index     int           `json:"index"`
-		Embedding []interface{} `json:"embedding"`
-	} `json:"data"`
-}
-
 // GiteeModel implements ModelDriver for Gitee
 type GiteeModel struct {
 	BaseURL    map[string]string
@@ -405,10 +398,28 @@ func (z *GiteeModel) ChatStreamlyWithSender(modelName string, messages []Message
 	return scanner.Err()
 }
 
-// Encode encodes a list of texts into embeddings
-func (z *GiteeModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+type giteeEmbeddingResponse struct {
+	Object string               `json:"object"`
+	Data   []giteeEmbeddingData `json:"data"`
+	Model  string               `json:"model"`
+	Usage  giteeUsage           `json:"usage"`
+}
+
+type giteeEmbeddingData struct {
+	Object    string    `json:"object"`
+	Embedding []float64 `json:"embedding"`
+	Index     int       `json:"index"`
+}
+
+type giteeUsage struct {
+	PromptTokens int `json:"prompt_tokens"`
+	TotalTokens  int `json:"total_tokens"`
+}
+
+// Embed embeds a list of texts into embeddings
+func (z *GiteeModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	if len(texts) == 0 {
-		return [][]float64{}, nil
+		return []EmbeddingData{}, nil
 	}
 
 	if apiConfig == nil || apiConfig.ApiKey == nil || *apiConfig.ApiKey == "" {
@@ -480,29 +491,12 @@ func (z *GiteeModel) Encode(modelName *string, texts []string, apiConfig *APICon
 		return nil, fmt.Errorf("failed to parse response: %w", err)
 	}
 
-	embeddings := make([][]float64, len(texts))
-	for _, item := range parsed.Data {
-		if item.Index < 0 || item.Index >= len(texts) {
-			return nil, fmt.Errorf("unexpected embedding index %d for %d inputs", item.Index, len(texts))
-		}
-		vec := make([]float64, len(item.Embedding))
-		for j, v := range item.Embedding {
-			switch val := v.(type) {
-			case float64:
-				vec[j] = val
-			case float32:
-				vec[j] = float64(val)
-			default:
-				return nil, fmt.Errorf("unexpected embedding value type at item %d index %d", item.Index, j)
-			}
-		}
-		embeddings[item.Index] = vec
-	}
-
-	for i, vec := range embeddings {
-		if vec == nil {
-			return nil, fmt.Errorf("missing embedding for input at index %d", i)
-		}
+	var embeddings []EmbeddingData
+	for _, dataElem := range parsed.Data {
+		var embeddingData EmbeddingData
+		embeddingData.Embedding = dataElem.Embedding
+		embeddingData.Index = dataElem.Index
+		embeddings = append(embeddings, embeddingData)
 	}
 
 	return embeddings, nil
@@ -588,7 +582,7 @@ func (z *GiteeModel) Rerank(modelName *string, query string, documents []string,
 	}
 
 	if resp.StatusCode != http.StatusOK {
-		return nil, fmt.Errorf("Gitee rerank API error: %s, body: %s", resp.Status, string(body))
+		return nil, fmt.Errorf("gitee rerank API error: %s, body: %s", resp.Status, string(body))
 	}
 
 	var rerankResponse RerankResponse
diff --git a/internal/entity/models/google.go b/internal/entity/models/google.go
index a1b3a96bca..fabd51e4c3 100644
--- a/internal/entity/models/google.go
+++ b/internal/entity/models/google.go
@@ -259,9 +259,9 @@ func (z *GoogleModel) ChatStreamlyWithSender(modelName string, messages []Messag
 	return err
 }
 
-// Encode generates embeddings for a batch of texts using the Gemini embeddings API.
+// Embed generates embeddings for a batch of texts using the Gemini embeddings API.
 // The SDK routes to batchEmbedContents internally, so all texts are sent in one request.
-func (z *GoogleModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+func (z *GoogleModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	if apiConfig == nil || apiConfig.ApiKey == nil || *apiConfig.ApiKey == "" {
 		return nil, fmt.Errorf("api key is required")
 	}
@@ -303,13 +303,16 @@ func (z *GoogleModel) Encode(modelName *string, texts []string, apiConfig *APICo
 		return nil, fmt.Errorf("expected %d embeddings, got %d", len(texts), len(resp.Embeddings))
 	}
 
-	result := make([][]float64, len(resp.Embeddings))
+	result := make([]EmbeddingData, len(resp.Embeddings))
 	for i, emb := range resp.Embeddings {
 		vec := make([]float64, len(emb.Values))
 		for j, v := range emb.Values {
 			vec[j] = float64(v)
 		}
-		result[i] = vec
+		result[i] = EmbeddingData{
+			Embedding: vec,
+			Index:     i,
+		}
 	}
 
 	return result, nil
diff --git a/internal/entity/models/huggingface.go b/internal/entity/models/huggingface.go
index d1160d1c46..1dad00a565 100644
--- a/internal/entity/models/huggingface.go
+++ b/internal/entity/models/huggingface.go
@@ -351,15 +351,9 @@ func (h *HuggingFaceModel) ChatStreamlyWithSender(modelName string, messages []M
 	return scanner.Err()
 }
 
-type hfEmbeddingRequest struct {
-	Inputs []string `json:"inputs"`
-}
-
-type hfEmbeddingResponse [][]float64
-
-func (h *HuggingFaceModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+func (h *HuggingFaceModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	if len(texts) == 0 {
-		return [][]float64{}, nil
+		return []EmbeddingData{}, nil
 	}
 
 	if modelName == nil || *modelName == "" {
@@ -404,12 +398,20 @@ func (h *HuggingFaceModel) Encode(modelName *string, texts []string, apiConfig *
 		return nil, fmt.Errorf("HF embeddings API error: %s", string(body))
 	}
 
-	var result [][]float64
-	if err = json.Unmarshal(body, &result); err != nil {
-		return nil, err
+	var parsed openaiEmbeddingResponse
+	if err = json.Unmarshal(body, &parsed); err != nil {
+		return nil, fmt.Errorf("failed to parse response: %w", err)
 	}
 
-	return result, nil
+	var embeddings []EmbeddingData
+	for _, dataElem := range parsed.Data {
+		var embeddingData EmbeddingData
+		embeddingData.Embedding = dataElem.Embedding
+		embeddingData.Index = dataElem.Index
+		embeddings = append(embeddings, embeddingData)
+	}
+
+	return embeddings, nil
 }
 
 func (h *HuggingFaceModel) Rerank(modelName *string, query string, documents []string, apiConfig *APIConfig, rerankConfig *RerankConfig) (*RerankResponse, error) {
diff --git a/internal/entity/models/lmstudio.go b/internal/entity/models/lmstudio.go
index ba55cf7247..136d8bb571 100644
--- a/internal/entity/models/lmstudio.go
+++ b/internal/entity/models/lmstudio.go
@@ -362,16 +362,9 @@ func (l *LmStudioModel) ChatStreamlyWithSender(modelName string, messages []Mess
 	return scanner.Err()
 }
 
-type lmstudioEmbeddingResponse struct {
-	Data []struct {
-		Index     int           `json:"index"`
-		Embedding []interface{} `json:"embedding"`
-	} `json:"data"`
-}
-
-func (l *LmStudioModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+func (l *LmStudioModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	if len(texts) == 0 {
-		return [][]float64{}, nil
+		return []EmbeddingData{}, nil
 	}
 
 	if modelName == nil || *modelName == "" {
@@ -434,38 +427,17 @@ func (l *LmStudioModel) Encode(modelName *string, texts []string, apiConfig *API
 		return nil, fmt.Errorf("LM Studio embeddings API error: %s, body: %s", resp.Status, string(body))
 	}
 
-	var parsed lmstudioEmbeddingResponse
+	var parsed openaiEmbeddingResponse
 	if err = json.Unmarshal(body, &parsed); err != nil {
 		return nil, fmt.Errorf("failed to parse response: %w", err)
 	}
 
-	if len(parsed.Data) != len(texts) {
-		return nil, fmt.Errorf("lmstudio embeddings: expected %d results, got %d", len(texts), len(parsed.Data))
-	}
-
-	embeddings := make([][]float64, len(texts))
-	for _, item := range parsed.Data {
-		if item.Index < 0 || item.Index >= len(texts) {
-			return nil, fmt.Errorf("unexpected embedding index %d for %d inputs", item.Index, len(texts))
-		}
-		vec := make([]float64, len(item.Embedding))
-		for j, v := range item.Embedding {
-			switch val := v.(type) {
-			case float64:
-				vec[j] = val
-			case float32:
-				vec[j] = float64(val)
-			default:
-				return nil, fmt.Errorf("unexpected embedding value type at item %d index %d", item.Index, j)
-			}
-		}
-		embeddings[item.Index] = vec
-	}
-
-	for i, vec := range embeddings {
-		if vec == nil {
-			return nil, fmt.Errorf("missing embedding for input at index %d", i)
-		}
+	var embeddings []EmbeddingData
+	for _, dataElem := range parsed.Data {
+		var embeddingData EmbeddingData
+		embeddingData.Embedding = dataElem.Embedding
+		embeddingData.Index = dataElem.Index
+		embeddings = append(embeddings, embeddingData)
 	}
 
 	return embeddings, nil
diff --git a/internal/entity/models/minimax.go b/internal/entity/models/minimax.go
index d40bfef4bd..67b4e83907 100644
--- a/internal/entity/models/minimax.go
+++ b/internal/entity/models/minimax.go
@@ -344,8 +344,8 @@ func (z *MinimaxModel) ChatStreamlyWithSender(modelName string, messages []Messa
 	return scanner.Err()
 }
 
-// Encode encodes a list of texts into embeddings
-func (z *MinimaxModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+// Embed embeds a list of texts into embeddings
+func (z *MinimaxModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	return nil, fmt.Errorf("not implemented")
 }
 
diff --git a/internal/entity/models/moonshot.go b/internal/entity/models/moonshot.go
index 68af2fada8..2c1443251b 100644
--- a/internal/entity/models/moonshot.go
+++ b/internal/entity/models/moonshot.go
@@ -357,8 +357,8 @@ func (k *MoonshotModel) ChatStreamlyWithSender(modelName string, messages []Mess
 	return scanner.Err()
 }
 
-// Encode encodes a list of texts into embeddings
-func (z *MoonshotModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+// Embed embeds a list of texts into embeddings
+func (z *MoonshotModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	return nil, fmt.Errorf("not implemented")
 }
 
diff --git a/internal/entity/models/nvidia.go b/internal/entity/models/nvidia.go
index c1deac13c3..fe50dcd425 100644
--- a/internal/entity/models/nvidia.go
+++ b/internal/entity/models/nvidia.go
@@ -332,14 +332,14 @@ func (n *NvidiaModel) ChatStreamlyWithSender(modelName string, messages []Messag
 
 type nvidiaEmbeddingResponse struct {
 	Data []struct {
-		Index     int           `json:"index"`
-		Embedding []interface{} `json:"embedding"`
+		Index     int       `json:"index"`
+		Embedding []float64 `json:"embedding"`
 	} `json:"data"`
 }
 
-func (n NvidiaModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+func (n NvidiaModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	if len(texts) == 0 {
-		return [][]float64{}, nil
+		return []EmbeddingData{}, nil
 	}
 
 	if apiConfig == nil || apiConfig.ApiKey == nil || *apiConfig.ApiKey == "" {
@@ -412,29 +412,12 @@ func (n NvidiaModel) Encode(modelName *string, texts []string, apiConfig *APICon
 		return nil, fmt.Errorf("failed to parse response: %w", err)
 	}
 
-	embeddings := make([][]float64, len(texts))
-	for _, item := range parsed.Data {
-		if item.Index < 0 || item.Index >= len(texts) {
-			return nil, fmt.Errorf("unexpected embedding index %d for %d inputs", item.Index, len(texts))
-		}
-		vec := make([]float64, len(item.Embedding))
-		for j, v := range item.Embedding {
-			switch val := v.(type) {
-			case float64:
-				vec[j] = val
-			case float32:
-				vec[j] = float64(val)
-			default:
-				return nil, fmt.Errorf("unexpected embedding value type at item %d index %d", item.Index, j)
-			}
-		}
-		embeddings[item.Index] = vec
-	}
-
-	for i, vec := range embeddings {
-		if vec == nil {
-			return nil, fmt.Errorf("missing embedding for input at index %d", i)
-		}
+	var embeddings []EmbeddingData
+	for _, dataElem := range parsed.Data {
+		var embeddingData EmbeddingData
+		embeddingData.Embedding = dataElem.Embedding
+		embeddingData.Index = dataElem.Index
+		embeddings = append(embeddings, embeddingData)
 	}
 
 	return embeddings, nil
diff --git a/internal/entity/models/ollama.go b/internal/entity/models/ollama.go
index 3b22039c3b..d1b05588d7 100644
--- a/internal/entity/models/ollama.go
+++ b/internal/entity/models/ollama.go
@@ -360,16 +360,9 @@ func (o *OllamaModel) ChatStreamlyWithSender(modelName string, messages []Messag
 	return scanner.Err()
 }
 
-type ollamaEmbeddingResponse struct {
-	Data []struct {
-		Index     int           `json:"index"`
-		Embedding []interface{} `json:"embedding"`
-	} `json:"data"`
-}
-
-func (o *OllamaModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+func (o *OllamaModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	if len(texts) == 0 {
-		return [][]float64{}, nil
+		return []EmbeddingData{}, nil
 	}
 
 	if modelName == nil || *modelName == "" {
@@ -432,38 +425,17 @@ func (o *OllamaModel) Encode(modelName *string, texts []string, apiConfig *APICo
 		return nil, fmt.Errorf("Ollama embeddings API error: %s, body: %s", resp.Status, string(body))
 	}
 
-	var parsed ollamaEmbeddingResponse
+	var parsed openaiEmbeddingResponse
 	if err = json.Unmarshal(body, &parsed); err != nil {
 		return nil, fmt.Errorf("failed to parse response: %w", err)
 	}
 
-	if len(parsed.Data) != len(texts) {
-		return nil, fmt.Errorf("ollama embeddings: expected %d results, got %d", len(texts), len(parsed.Data))
-	}
-
-	embeddings := make([][]float64, len(texts))
-	for _, item := range parsed.Data {
-		if item.Index < 0 || item.Index >= len(texts) {
-			return nil, fmt.Errorf("unexpected embedding index %d for %d inputs", item.Index, len(texts))
-		}
-		vec := make([]float64, len(item.Embedding))
-		for j, v := range item.Embedding {
-			switch val := v.(type) {
-			case float64:
-				vec[j] = val
-			case float32:
-				vec[j] = float64(val)
-			default:
-				return nil, fmt.Errorf("unexpected embedding value type at item %d index %d", item.Index, j)
-			}
-		}
-		embeddings[item.Index] = vec
-	}
-
-	for i, vec := range embeddings {
-		if vec == nil {
-			return nil, fmt.Errorf("missing embedding for input at index %d", i)
-		}
+	var embeddings []EmbeddingData
+	for _, dataElem := range parsed.Data {
+		var embeddingData EmbeddingData
+		embeddingData.Embedding = dataElem.Embedding
+		embeddingData.Index = dataElem.Index
+		embeddings = append(embeddings, embeddingData)
 	}
 
 	return embeddings, nil
diff --git a/internal/entity/models/openai.go b/internal/entity/models/openai.go
index fcacb6d22b..6461444e7b 100644
--- a/internal/entity/models/openai.go
+++ b/internal/entity/models/openai.go
@@ -403,24 +403,31 @@ func (z *OpenAIModel) ChatStreamlyWithSender(modelName string, messages []Messag
 	return nil
 }
 
-// openaiEmbeddingResponse is the response shape returned by
-// /v1/embeddings. The "index" field gives the position of the embedding
-// in the input array, which we use to keep the output order stable
-// even if the API returns items in a different order.
 type openaiEmbeddingResponse struct {
-	Data []struct {
-		Index     int           `json:"index"`
-		Embedding []interface{} `json:"embedding"`
-	} `json:"data"`
+	Data   []openrouterEmbeddingData `json:"data"`
+	Model  string                    `json:"model"`
+	Object string                    `json:"object"`
+	Usage  openrouterUsage           `json:"usage"`
 }
 
-// Encode turns a list of texts into embedding vectors using the
+type openaiEmbeddingData struct {
+	Embedding []float64 `json:"embedding"`
+	Object    string    `json:"object"`
+	Index     int       `json:"index"`
+}
+
+type openaiUsage struct {
+	PromptTokens int `json:"prompt_tokens"`
+	TotalTokens  int `json:"total_tokens"`
+}
+
+// Embed turns a list of texts into embedding vectors using the
 // OpenAI /v1/embeddings endpoint (e.g. text-embedding-3-small,
 // text-embedding-3-large, text-embedding-ada-002). The output has
 // one vector per input, in the same order the inputs were given.
-func (z *OpenAIModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+func (z *OpenAIModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	if len(texts) == 0 {
-		return [][]float64{}, nil
+		return []EmbeddingData{}, nil
 	}
 
 	if apiConfig == nil || apiConfig.ApiKey == nil || *apiConfig.ApiKey == "" {
@@ -486,29 +493,12 @@ func (z *OpenAIModel) Encode(modelName *string, texts []string, apiConfig *APICo
 		return nil, fmt.Errorf("failed to parse response: %w", err)
 	}
 
-	embeddings := make([][]float64, len(texts))
-	for _, item := range parsed.Data {
-		if item.Index < 0 || item.Index >= len(texts) {
-			continue
-		}
-		vec := make([]float64, len(item.Embedding))
-		for j, v := range item.Embedding {
-			switch val := v.(type) {
-			case float64:
-				vec[j] = val
-			case float32:
-				vec[j] = float64(val)
-			default:
-				return nil, fmt.Errorf("unexpected embedding value type at item %d index %d", item.Index, j)
-			}
-		}
-		embeddings[item.Index] = vec
-	}
-
-	for i, vec := range embeddings {
-		if vec == nil {
-			return nil, fmt.Errorf("missing embedding for input at index %d", i)
-		}
+	var embeddings []EmbeddingData
+	for _, dataElem := range parsed.Data {
+		var embeddingData EmbeddingData
+		embeddingData.Embedding = dataElem.Embedding
+		embeddingData.Index = dataElem.Index
+		embeddings = append(embeddings, embeddingData)
 	}
 
 	return embeddings, nil
diff --git a/internal/entity/models/openrouter.go b/internal/entity/models/openrouter.go
index 1be3f49e56..7ebf09b5fb 100644
--- a/internal/entity/models/openrouter.go
+++ b/internal/entity/models/openrouter.go
@@ -352,15 +352,26 @@ func (o *OpenRouterModel) ChatStreamlyWithSender(modelName string, messages []Me
 }
 
 type openrouterEmbeddingResponse struct {
-	Data []struct {
-		Index     int       `json:"index"`
-		Embedding []float64 `json:"embedding"`
-	} `json:"data"`
+	Data   []openrouterEmbeddingData `json:"data"`
+	Model  string                    `json:"model"`
+	Object string                    `json:"object"`
+	Usage  openrouterUsage           `json:"usage"`
 }
 
-func (o *OpenRouterModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+type openrouterEmbeddingData struct {
+	Embedding []float64 `json:"embedding"`
+	Object    string    `json:"object"`
+	Index     int       `json:"index"`
+}
+
+type openrouterUsage struct {
+	PromptTokens int `json:"prompt_tokens"`
+	TotalTokens  int `json:"total_tokens"`
+}
+
+func (o *OpenRouterModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	if len(texts) == 0 {
-		return [][]float64{}, nil
+		return []EmbeddingData{}, nil
 	}
 	if modelName == nil || *modelName == "" {
 		return nil, fmt.Errorf("model name is required")
@@ -412,26 +423,17 @@ func (o *OpenRouterModel) Encode(modelName *string, texts []string, apiConfig *A
 		return nil, fmt.Errorf("OpenRouter embedding API error: status %d, body: %s", resp.StatusCode, string(body))
 	}
 
-	var result openrouterEmbeddingResponse
-	if err = json.Unmarshal(body, &result); err != nil {
-		return nil, fmt.Errorf("failed to decode response: %w", err)
+	var parsed openrouterEmbeddingResponse
+	if err = json.Unmarshal(body, &parsed); err != nil {
+		return nil, fmt.Errorf("failed to parse response: %w", err)
 	}
 
-	if len(result.Data) != len(texts) {
-		return nil, fmt.Errorf("expected %d embeddings, got %d", len(texts), len(result.Data))
-	}
-
-	embeddings := make([][]float64, len(texts))
-	seen := make([]bool, len(texts))
-	for _, item := range result.Data {
-		if item.Index < 0 || item.Index >= len(texts) {
-			return nil, fmt.Errorf("embedding index %d out of range", item.Index)
-		}
-		if seen[item.Index] {
-			return nil, fmt.Errorf("duplicate embedding index %d", item.Index)
-		}
-		seen[item.Index] = true
-		embeddings[item.Index] = item.Embedding
+	var embeddings []EmbeddingData
+	for _, dataElem := range parsed.Data {
+		var embeddingData EmbeddingData
+		embeddingData.Embedding = dataElem.Embedding
+		embeddingData.Index = dataElem.Index
+		embeddings = append(embeddings, embeddingData)
 	}
 
 	return embeddings, nil
diff --git a/internal/entity/models/siliconflow.go b/internal/entity/models/siliconflow.go
index 118273a8a1..3659ddef02 100644
--- a/internal/entity/models/siliconflow.go
+++ b/internal/entity/models/siliconflow.go
@@ -19,7 +19,6 @@ package models
 import (
 	"bufio"
 	"bytes"
-	"context"
 	"encoding/json"
 	"fmt"
 	"io"
@@ -370,20 +369,37 @@ func (z *SiliconflowModel) ChatStreamlyWithSender(modelName string, messages []M
 }
 
 type siliconflowEmbeddingResponse struct {
-	Data []struct {
-		Index     int       `json:"index"`
-		Embedding []float64 `json:"embedding"`
-	} `json:"data"`
+	Object []string                   `json:"object"`
+	Model  string                     `json:"model"`
+	Data   []siliconflowEmbeddingData `json:"data"`
+	Usage  siliconflowUsage           `json:"usage"`
+}
+
+type siliconflowEmbeddingData struct {
+	Object    string    `json:"object"`
+	Embedding []float64 `json:"embedding"`
+	Index     int       `json:"index"`
+}
+
+type siliconflowUsage struct {
+	PromptTokens     int `json:"prompt_tokens"`
+	CompletionTokens int `json:"completion_tokens"`
+	TotalTokens      int `json:"total_tokens"`
 }
 
 // siliconflowMaxBatchSize is the per-request input limit documented at
 // https://docs.siliconflow.cn/en/api-reference/embeddings/create-embeddings.
 const siliconflowMaxBatchSize = 32
 
-func (s *SiliconflowModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+// Embed embeds a list of texts into embeddings
+func (s *SiliconflowModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	if len(texts) == 0 {
-		return [][]float64{}, nil
+		return []EmbeddingData{}, nil
 	}
+	if len(texts) > siliconflowMaxBatchSize {
+		return nil, fmt.Errorf("siliconflow supports a maximum of %d inputs per request", siliconflowMaxBatchSize)
+	}
+
 	if modelName == nil || *modelName == "" {
 		return nil, fmt.Errorf("model name is required")
 	}
@@ -400,48 +416,19 @@ func (s *SiliconflowModel) Encode(modelName *string, texts []string, apiConfig *
 		apiKey = *apiConfig.ApiKey
 	}
 
-	dimension := 0
-	if embeddingConfig != nil {
-		dimension = embeddingConfig.Dimension
-	}
-
-	embeddings := make([][]float64, len(texts))
-	for start := 0; start < len(texts); start += siliconflowMaxBatchSize {
-		end := start + siliconflowMaxBatchSize
-		if end > len(texts) {
-			end = len(texts)
-		}
-		batch := texts[start:end]
-
-		if err := s.encodeBatch(url, *modelName, apiKey, dimension, batch, embeddings[start:end]); err != nil {
-			return nil, err
-		}
-	}
-
-	return embeddings, nil
-}
-
-func (s *SiliconflowModel) encodeBatch(url, modelName, apiKey string, dimension int, batch []string, out [][]float64) error {
 	reqBody := map[string]interface{}{
-		"model":           modelName,
-		"input":           batch,
-		"encoding_format": "float",
-	}
-	if dimension > 0 {
-		reqBody["dimensions"] = dimension
+		"model": modelName,
+		"input": texts,
 	}
 
 	jsonData, err := json.Marshal(reqBody)
 	if err != nil {
-		return fmt.Errorf("failed to marshal request: %w", err)
+		return nil, fmt.Errorf("failed to marshal request: %w", err)
 	}
 
-	ctx, cancel := context.WithTimeout(context.Background(), nonStreamCallTimeout)
-	defer cancel()
-
-	req, err := http.NewRequestWithContext(ctx, "POST", url, bytes.NewBuffer(jsonData))
+	req, err := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
 	if err != nil {
-		return fmt.Errorf("failed to create request: %w", err)
+		return nil, fmt.Errorf("failed to create request: %w", err)
 	}
 
 	req.Header.Set("Content-Type", "application/json")
@@ -451,50 +438,34 @@ func (s *SiliconflowModel) encodeBatch(url, modelName, apiKey string, dimension
 
 	resp, err := s.httpClient.Do(req)
 	if err != nil {
-		return fmt.Errorf("failed to send request: %w", err)
+		return nil, fmt.Errorf("failed to send request: %w", err)
 	}
-	defer resp.Body.Close()
 
 	body, err := io.ReadAll(resp.Body)
+	resp.Body.Close()
+
 	if err != nil {
-		return fmt.Errorf("failed to read response: %w", err)
+		return nil, fmt.Errorf("failed to read response: %w", err)
 	}
 
 	if resp.StatusCode != http.StatusOK {
-		return fmt.Errorf("SILICONFLOW API error: %s, body: %s", resp.Status, string(body))
+		return nil, fmt.Errorf("SILICONFLOW API error: %s, body: %s", resp.Status, string(body))
 	}
 
-	var result siliconflowEmbeddingResponse
-	if err = json.Unmarshal(body, &result); err != nil {
-		return fmt.Errorf("failed to parse response: %w", err)
+	var parsed siliconflowEmbeddingResponse
+	if err = json.Unmarshal(body, &parsed); err != nil {
+		return nil, fmt.Errorf("failed to parse response: %w", err)
 	}
 
-	if len(result.Data) != len(batch) {
-		return fmt.Errorf("expected %d embeddings, got %d", len(batch), len(result.Data))
+	var embeddings []EmbeddingData
+	for _, dataElem := range parsed.Data {
+		var embeddingData EmbeddingData
+		embeddingData.Embedding = dataElem.Embedding
+		embeddingData.Index = dataElem.Index
+		embeddings = append(embeddings, embeddingData)
 	}
 
-	seen := make([]bool, len(batch))
-	for _, item := range result.Data {
-		if item.Index < 0 || item.Index >= len(batch) {
-			return fmt.Errorf("embedding index %d out of range", item.Index)
-		}
-		if seen[item.Index] {
-			return fmt.Errorf("duplicate embedding index %d", item.Index)
-		}
-		if len(item.Embedding) == 0 {
-			return fmt.Errorf("empty embedding at index %d", item.Index)
-		}
-		seen[item.Index] = true
-		out[item.Index] = item.Embedding
-	}
-
-	for i, ok := range seen {
-		if !ok {
-			return fmt.Errorf("missing embedding index %d", i)
-		}
-	}
-
-	return nil
+	return embeddings, nil
 }
 
 func (z *SiliconflowModel) ListModels(apiConfig *APIConfig) ([]string, error) {
diff --git a/internal/entity/models/types.go b/internal/entity/models/types.go
index 250e41bc51..3a32cec9dd 100644
--- a/internal/entity/models/types.go
+++ b/internal/entity/models/types.go
@@ -23,7 +23,7 @@ type ModelDriver interface {
 	// messages accepts []Message which supports multimodal content (e.g., [{"type": "text", "text": "..."}, {"type": "image_url", "image_url": {"url": "..."}}])
 	ChatStreamlyWithSender(modelName string, messages []Message, apiConfig *APIConfig, modelConfig *ChatConfig, sender func(*string, *string) error) error
 	// Encode encodes a list of texts into embeddings
-	Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error)
+	Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error)
 	// Rerank calculates similarity scores between query and texts
 	Rerank(modelName *string, query string, documents []string, apiConfig *APIConfig, rerankConfig *RerankConfig) (*RerankResponse, error)
 	// ListModels List supported models
@@ -39,14 +39,9 @@ type ChatResponse struct {
 	ReasonContent *string `json:"reason_content"`
 }
 
-type EmbeddingResult struct {
-	Index     int `json:"index"`
-	Dimension int `json:"dimension"`
-	//Embedding []float64 `json:"embedding"`
-}
-
-type EmbeddingResponse struct {
-	Data []EmbeddingResult `json:"data"`
+type EmbeddingData struct {
+	Embedding []float64 `json:"embedding"`
+	Index     int       `json:"index"`
 }
 
 type RerankResult struct {
diff --git a/internal/entity/models/vllm.go b/internal/entity/models/vllm.go
index aabf597f0f..a7e3e118fb 100644
--- a/internal/entity/models/vllm.go
+++ b/internal/entity/models/vllm.go
@@ -381,14 +381,15 @@ func (z *VllmModel) ChatStreamlyWithSender(modelName string, messages []Message,
 // Encode encodes a list of texts into embeddings
 type vllmEmbeddingResponse struct {
 	Data []struct {
-		Index     int           `json:"index"`
-		Embedding []interface{} `json:"embedding"`
+		Index     int       `json:"index"`
+		Embedding []float64 `json:"embedding"`
 	} `json:"data"`
 }
 
-func (z *VllmModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+// Embed embeds a list of texts into embeddings
+func (z *VllmModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	if len(texts) == 0 {
-		return [][]float64{}, nil
+		return []EmbeddingData{}, nil
 	}
 
 	if modelName == nil || *modelName == "" {
@@ -456,33 +457,12 @@ func (z *VllmModel) Encode(modelName *string, texts []string, apiConfig *APIConf
 		return nil, fmt.Errorf("failed to parse response: %w", err)
 	}
 
-	if len(parsed.Data) != len(texts) {
-		return nil, fmt.Errorf("vllm embeddings: expected %d results, got %d", len(texts), len(parsed.Data))
-	}
-
-	embeddings := make([][]float64, len(texts))
-	for _, item := range parsed.Data {
-		if item.Index < 0 || item.Index >= len(texts) {
-			return nil, fmt.Errorf("unexpected embedding index %d for %d inputs", item.Index, len(texts))
-		}
-		vec := make([]float64, len(item.Embedding))
-		for j, v := range item.Embedding {
-			switch val := v.(type) {
-			case float64:
-				vec[j] = val
-			case float32:
-				vec[j] = float64(val)
-			default:
-				return nil, fmt.Errorf("unexpected embedding value type at item %d index %d", item.Index, j)
-			}
-		}
-		embeddings[item.Index] = vec
-	}
-
-	for i, vec := range embeddings {
-		if vec == nil {
-			return nil, fmt.Errorf("missing embedding for input at index %d", i)
-		}
+	var embeddings []EmbeddingData
+	for _, dataElem := range parsed.Data {
+		var embeddingData EmbeddingData
+		embeddingData.Embedding = dataElem.Embedding
+		embeddingData.Index = dataElem.Index
+		embeddings = append(embeddings, embeddingData)
 	}
 
 	return embeddings, nil
diff --git a/internal/entity/models/volcengine.go b/internal/entity/models/volcengine.go
index d03cebaa1a..22da539936 100644
--- a/internal/entity/models/volcengine.go
+++ b/internal/entity/models/volcengine.go
@@ -406,10 +406,35 @@ func (z *VolcEngine) ChatStreamlyWithSender(modelName string, messages []Message
 	return scanner.Err()
 }
 
-// Encode encodes a list of texts into embeddings
-func (z *VolcEngine) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+type volcengineEmbeddingResponse struct {
+	Created int64                   `json:"created"`
+	Data    volcengineEmbeddingData `json:"data"`
+	ID      string                  `json:"id"`
+	Model   string                  `json:"model"`
+	Object  string                  `json:"object"`
+	Usage   volcengineUsage         `json:"usage"`
+}
+
+type volcengineEmbeddingData struct {
+	Embedding []float64 `json:"embedding"`
+	Object    string    `json:"object"`
+}
+
+type volcengineUsage struct {
+	PromptTokens        int                            `json:"prompt_tokens"`
+	TotalTokens         int                            `json:"total_tokens"`
+	PromptTokensDetails *volcenginePromptTokensDetails `json:"prompt_tokens_details,omitempty"`
+}
+
+type volcenginePromptTokensDetails struct {
+	ImageTokens int `json:"image_tokens"`
+	TextTokens  int `json:"text_tokens"`
+}
+
+// Embed embeds a list of texts into embeddings
+func (z *VolcEngine) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	if len(texts) == 0 {
-		return [][]float64{}, nil
+		return []EmbeddingData{}, nil
 	}
 
 	var region = "default"
@@ -419,7 +444,7 @@ func (z *VolcEngine) Encode(modelName *string, texts []string, apiConfig *APICon
 
 	url := fmt.Sprintf("%s/%s", z.BaseURL[region], z.URLSuffix.Embedding)
 
-	embeddings := make([][]float64, len(texts))
+	var embeddings []EmbeddingData
 
 	for i, text := range texts {
 
@@ -466,25 +491,15 @@ func (z *VolcEngine) Encode(modelName *string, texts []string, apiConfig *APICon
 			return nil, fmt.Errorf("API request failed with status %d: %s", resp.StatusCode, string(body))
 		}
 
-		// Volcengine multimodal embedding response
-		type VolcengineEmbeddingResponse struct {
-			Data struct {
-				Embedding []float64 `json:"embedding"`
-				Object    string    `json:"object"`
-			} `json:"data"`
-		}
-
-		var result VolcengineEmbeddingResponse
-
-		if err = json.Unmarshal(body, &result); err != nil {
+		var parsed volcengineEmbeddingResponse
+		if err = json.Unmarshal(body, &parsed); err != nil {
 			return nil, fmt.Errorf("failed to parse response: %w", err)
 		}
 
-		if len(result.Data.Embedding) == 0 {
-			return nil, fmt.Errorf("empty embedding in response")
-		}
-
-		embeddings[i] = result.Data.Embedding
+		var embeddingData EmbeddingData
+		embeddingData.Index = i
+		embeddingData.Embedding = parsed.Data.Embedding
+		embeddings = append(embeddings, embeddingData)
 	}
 
 	return embeddings, nil
diff --git a/internal/entity/models/xai.go b/internal/entity/models/xai.go
index 96617320cf..1b3175d4b7 100644
--- a/internal/entity/models/xai.go
+++ b/internal/entity/models/xai.go
@@ -397,9 +397,9 @@ func (z *XAIModel) ChatStreamlyWithSender(modelName string, messages []Message,
 	return nil
 }
 
-// Encode encodes a list of texts into embeddings. xAI does not expose a
+// Embed embeds a list of texts into embeddings. xAI does not expose a
 // public embedding API yet, so this is left unimplemented.
-func (z *XAIModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+func (z *XAIModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
 	return nil, fmt.Errorf("not implemented")
 }
 
diff --git a/internal/entity/models/zhipu-ai.go b/internal/entity/models/zhipu-ai.go
index 98bd5a7a52..adccae7024 100644
--- a/internal/entity/models/zhipu-ai.go
+++ b/internal/entity/models/zhipu-ai.go
@@ -362,8 +362,39 @@ func (z *ZhipuAIModel) ChatStreamlyWithSender(modelName string, messages []Messa
 	return scanner.Err()
 }
 
+type zhipuEmbeddingResponse struct {
+	Data   []zhipuEmbeddingData `json:"data"`
+	Model  string               `json:"model"`
+	Object string               `json:"object"`
+	Usage  zhipuUsage           `json:"usage"`
+}
+
+type zhipuEmbeddingData struct {
+	Embedding []float64 `json:"embedding"`
+	Index     int       `json:"index"`
+	Object    string    `json:"object"`
+}
+
+type zhipuUsage struct {
+	CompletionTokens int `json:"completion_tokens"`
+	PromptTokens     int `json:"prompt_tokens"`
+	TotalTokens      int `json:"total_tokens"`
+}
+
 // Encode encodes a list of texts into embeddings
-func (z *ZhipuAIModel) Encode(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([][]float64, error) {
+func (z *ZhipuAIModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
+	if len(texts) == 0 {
+		return []EmbeddingData{}, nil
+	}
+
+	if apiConfig == nil || apiConfig.ApiKey == nil || *apiConfig.ApiKey == "" {
+		return nil, fmt.Errorf("api key is required")
+	}
+
+	if modelName == nil || *modelName == "" {
+		return nil, fmt.Errorf("model name is required")
+	}
+
 	var region = "default"
 	if apiConfig.Region != nil {
 		region = *apiConfig.Region
@@ -371,79 +402,54 @@ func (z *ZhipuAIModel) Encode(modelName *string, texts []string, apiConfig *APIC
 
 	url := fmt.Sprintf("%s/%s", strings.TrimSuffix(z.BaseURL[region], "/"), z.URLSuffix.Embedding)
 
-	embeddings := make([][]float64, len(texts))
+	reqBody := map[string]interface{}{}
+	reqBody["model"] = modelName
+	reqBody["input"] = texts
+	if embeddingConfig.Dimension > 0 {
+		reqBody["dimensions"] = embeddingConfig.Dimension
+	}
 
-	for i, text := range texts {
-		reqBody := map[string]interface{}{}
-		reqBody["model"] = modelName
-		reqBody["input"] = text
-		if embeddingConfig.Dimension > 0 {
-			reqBody["dimensions"] = embeddingConfig.Dimension
-		}
+	jsonData, err := json.Marshal(reqBody)
+	if err != nil {
+		return nil, fmt.Errorf("failed to marshal request: %w", err)
+	}
 
-		jsonData, err := json.Marshal(reqBody)
-		if err != nil {
-			return nil, fmt.Errorf("failed to marshal request: %w", err)
-		}
+	req, err := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
+	if err != nil {
+		return nil, fmt.Errorf("failed to create request: %w", err)
+	}
 
-		req, err := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
-		if err != nil {
-			return nil, fmt.Errorf("failed to create request: %w", err)
-		}
+	req.Header.Set("Content-Type", "application/json")
+	req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
 
-		req.Header.Set("Content-Type", "application/json")
-		req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
+	resp, err := z.httpClient.Do(req)
+	if err != nil {
+		return nil, fmt.Errorf("failed to send request: %w", err)
+	}
 
-		resp, err := z.httpClient.Do(req)
-		if err != nil {
-			return nil, fmt.Errorf("failed to send request: %w", err)
-		}
+	body, err := io.ReadAll(resp.Body)
+	resp.Body.Close()
 
-		body, err := io.ReadAll(resp.Body)
-		resp.Body.Close()
+	if err != nil {
+		return nil, fmt.Errorf("failed to read response: %w", err)
+	}
 
-		if err != nil {
-			return nil, fmt.Errorf("failed to read response: %w", err)
-		}
+	if resp.StatusCode != http.StatusOK {
+		return nil, fmt.Errorf("API request failed with status %d: %s", resp.StatusCode, string(body))
+	}
 
-		if resp.StatusCode != http.StatusOK {
-			return nil, fmt.Errorf("API request failed with status %d: %s", resp.StatusCode, string(body))
-		}
+	// Parse response
+	var zhipuResp zhipuEmbeddingResponse
+	if err = json.Unmarshal(body, &zhipuResp); err != nil {
+		return nil, fmt.Errorf("failed to parse response: %w", err)
+	}
 
-		// Parse response
-		var result map[string]interface{}
-		if err = json.Unmarshal(body, &result); err != nil {
-			return nil, fmt.Errorf("failed to parse response: %w", err)
-		}
-
-		data, ok := result["data"].([]interface{})
-		if !ok || len(data) == 0 {
-			return nil, fmt.Errorf("no data in response")
-		}
-
-		firstData, ok := data[0].(map[string]interface{})
-		if !ok {
-			return nil, fmt.Errorf("invalid data format")
-		}
-
-		embeddingSlice, ok := firstData["embedding"].([]interface{})
-		if !ok {
-			return nil, fmt.Errorf("invalid embedding format")
-		}
-
-		embedding := make([]float64, len(embeddingSlice))
-		for j, v := range embeddingSlice {
-			switch val := v.(type) {
-			case float64:
-				embedding[j] = val
-			case float32:
-				embedding[j] = float64(val)
-			default:
-				return nil, fmt.Errorf("unexpected embedding value type")
-			}
-		}
-
-		embeddings[i] = embedding
+	var embeddings []EmbeddingData
+	for _, dataElem := range zhipuResp.Data {
+		var embeddingData EmbeddingData
+		embeddingData.Embedding = dataElem.Embedding
+		embeddingData.Index = dataElem.Index
+		embeddings = append(embeddings, embeddingData)
 	}
 
 	return embeddings, nil
diff --git a/internal/handler/providers.go b/internal/handler/providers.go
index 758919f406..af101c60e3 100644
--- a/internal/handler/providers.go
+++ b/internal/handler/providers.go
@@ -950,7 +950,7 @@ func (h *ProviderHandler) EmbedText(c *gin.Context) {
 	}
 
 	// Non-stream response
-	var response *models.EmbeddingResponse
+	var response []models.EmbeddingData
 	var errorCode common.ErrorCode
 	var err error
 
@@ -966,7 +966,7 @@ func (h *ProviderHandler) EmbedText(c *gin.Context) {
 
 	c.JSON(http.StatusOK, gin.H{
 		"code":    0,
-		"data":    response.Data,
+		"data":    response,
 		"message": "success",
 	})
 }
diff --git a/internal/service/model_service.go b/internal/service/model_service.go
index 1a107d4231..a32daa7eeb 100644
--- a/internal/service/model_service.go
+++ b/internal/service/model_service.go
@@ -891,7 +891,7 @@ func (m *ModelProviderService) ChatToModelStreamWithSender(providerName, instanc
 }
 
 // EmbedText sends texts to the embedding model
-func (m *ModelProviderService) EmbedText(providerName, instanceName, modelName, userID string, texts []string, apiConfig *modelModule.APIConfig, modelConfig *modelModule.EmbeddingConfig) (*modelModule.EmbeddingResponse, common.ErrorCode, error) {
+func (m *ModelProviderService) EmbedText(providerName, instanceName, modelName, userID string, texts []string, apiConfig *modelModule.APIConfig, modelConfig *modelModule.EmbeddingConfig) ([]modelModule.EmbeddingData, common.ErrorCode, error) {
 	if apiConfig == nil {
 		apiConfig = &modelModule.APIConfig{}
 	}
@@ -949,26 +949,15 @@ func (m *ModelProviderService) EmbedText(providerName, instanceName, modelName,
 		apiConfig.Region = &region
 		apiConfig.ApiKey = &instance.APIKey
 
-		var embeddingList [][]float64
-		embeddingList, err = providerInfo.ModelDriver.Encode(&modelName, texts, apiConfig, modelConfig)
+		var response []modelModule.EmbeddingData
+		response, err = providerInfo.ModelDriver.Embed(&modelName, texts, apiConfig, modelConfig)
 		if err != nil {
 			return nil, common.CodeServerError, err
 		}
-		if embeddingList == nil {
+		if response == nil || len(response) == 0 {
 			return nil, common.CodeServerError, errors.New("empty embed response")
 		}
 
-		response := &modelModule.EmbeddingResponse{
-			Data: make([]modelModule.EmbeddingResult, len(embeddingList)),
-		}
-		for i, embedding := range embeddingList {
-			response.Data[i] = modelModule.EmbeddingResult{
-				Index:     i,
-				Dimension: len(embedding),
-				//Embedding: embedding,
-			}
-		}
-
 		return response, common.CodeSuccess, nil
 	}
 
@@ -994,26 +983,15 @@ func (m *ModelProviderService) EmbedText(providerName, instanceName, modelName,
 		}
 		newProviderInfo := providerInfo.ModelDriver.NewInstance(newURL)
 
-		var embeddingList [][]float64
-		embeddingList, err = newProviderInfo.Encode(&modelName, texts, apiConfig, modelConfig)
+		var response []modelModule.EmbeddingData
+		response, err = newProviderInfo.Embed(&modelName, texts, apiConfig, modelConfig)
 		if err != nil {
 			return nil, common.CodeServerError, err
 		}
-		if embeddingList == nil {
+		if response == nil || len(response) == 0 {
 			return nil, common.CodeServerError, errors.New("empty embed response")
 		}
 
-		response := &modelModule.EmbeddingResponse{
-			Data: make([]modelModule.EmbeddingResult, len(embeddingList)),
-		}
-		for i, embedding := range embeddingList {
-			response.Data[i] = modelModule.EmbeddingResult{
-				Index:     i,
-				Dimension: len(embedding),
-				//Embedding: embedding,
-			}
-		}
-
 		return response, common.CodeSuccess, nil
 	}
 
diff --git a/internal/service/nlp/retrieval.go b/internal/service/nlp/retrieval.go
index 2754571120..a3a2e8debe 100644
--- a/internal/service/nlp/retrieval.go
+++ b/internal/service/nlp/retrieval.go
@@ -607,12 +607,12 @@ func (s *RetrievalService) Search(ctx context.Context, req *RetrievalSearchReque
 
 // GetVector computes query vector and returns MatchDenseExpr for hybrid search
 func (s *RetrievalService) GetVector(txt string, embModel *models.EmbeddingModel, topk int, similarity float64) (*types.MatchDenseExpr, error) {
-	embeddings, err := embModel.ModelDriver.Encode(embModel.ModelName, []string{txt}, embModel.APIConfig, nil)
+	embeddings, err := embModel.ModelDriver.Embed(embModel.ModelName, []string{txt}, embModel.APIConfig, nil)
 	if err != nil {
 		return nil, err
 	}
 
-	vector := embeddings[0]
+	vector := embeddings[0].Embedding
 	vectorSize := len(vector)
 	vectorColumnName := fmt.Sprintf("q_%d_vec", vectorSize)
 
diff --git a/internal/service/skill_indexer.go b/internal/service/skill_indexer.go
index ec36a7948e..8c234e0986 100644
--- a/internal/service/skill_indexer.go
+++ b/internal/service/skill_indexer.go
@@ -25,6 +25,7 @@ import (
 	"ragflow/internal/dao"
 	"ragflow/internal/engine"
 	"ragflow/internal/entity"
+	"ragflow/internal/entity/models"
 	"ragflow/internal/storage"
 	"ragflow/internal/tokenizer"
 	"strings"
@@ -237,7 +238,8 @@ func (s *SkillIndexerService) BatchIndexSkills(ctx context.Context, tenantID, sp
 
 	// Generate embeddings in batch
 	common.Info(fmt.Sprintf("Generating embeddings for %d skills with embdID=%s", len(skills), embdID))
-	vectors, err := s.generateEmbeddings(ctx, vectorTexts, embdID, tenantID)
+	var vectors []models.EmbeddingData
+	vectors, err = s.generateEmbeddings(ctx, vectorTexts, embdID, tenantID)
 	if err != nil {
 		common.Warn(fmt.Sprintf("Failed to generate embeddings: %v. Continuing with text-only index.", err))
 		vectors = nil // Continue without vectors
@@ -311,7 +313,7 @@ func (s *SkillIndexerService) BatchIndexSkills(ctx context.Context, tenantID, sp
 
 		// Add vector only if available
 		if vectors != nil && i < len(vectors) {
-			doc[vectorField] = vectors[i]
+			doc[vectorField] = vectors[i].Embedding
 		} else {
 			common.Info(fmt.Sprintf("No vector for skill %s, creating text-only index", skill.ID))
 			// For Infinity: use zero vector as placeholder (table schema requires vector column)
@@ -932,20 +934,21 @@ func (s *SkillIndexerService) generateEmbedding(ctx context.Context, text, embdI
 	}
 	truncatedText := truncate(text, maxLen-10)
 
-	vectors, err := embeddingModel.ModelDriver.Encode(embeddingModel.ModelName, []string{truncatedText}, embeddingModel.APIConfig, nil)
+	var response []models.EmbeddingData
+	response, err = embeddingModel.ModelDriver.Embed(embeddingModel.ModelName, []string{truncatedText}, embeddingModel.APIConfig, nil)
 	if err != nil {
 		return nil, fmt.Errorf("failed to encode text: %w", err)
 	}
-	if len(vectors) == 0 {
+	if len(response) == 0 {
 		return nil, fmt.Errorf("embedding returned empty result")
 	}
 
-	return vectors[0], nil
+	return response[0].Embedding, nil
 }
 
 // generateEmbeddings generates embeddings for multiple texts in batch
 // This is more efficient than calling generateEmbedding individually
-func (s *SkillIndexerService) generateEmbeddings(ctx context.Context, texts []string, embdID, tenantID string) ([][]float64, error) {
+func (s *SkillIndexerService) generateEmbeddings(ctx context.Context, texts []string, embdID, tenantID string) ([]models.EmbeddingData, error) {
 	common.Info(fmt.Sprintf("generateEmbeddings called: texts=%d, embdID=%s, tenantID=%s", len(texts), embdID, tenantID))
 
 	if s.modelProvider == nil {
@@ -975,18 +978,19 @@ func (s *SkillIndexerService) generateEmbeddings(ctx context.Context, texts []st
 
 	common.Info(fmt.Sprintf("Encoding %d texts", len(truncatedTexts)))
 	// Use batch encode API (consistent with Python's encode(texts: list))
-	vectors, err := embeddingModel.ModelDriver.Encode(embeddingModel.ModelName, truncatedTexts, embeddingModel.APIConfig, nil)
+	var response []models.EmbeddingData
+	response, err = embeddingModel.ModelDriver.Embed(embeddingModel.ModelName, truncatedTexts, embeddingModel.APIConfig, nil)
 	if err != nil {
 		common.Error(fmt.Sprintf("Failed to encode texts: %v", err), err)
 		return nil, fmt.Errorf("failed to encode texts: %w", err)
 	}
 
-	common.Info(fmt.Sprintf("Encoded successfully, got %d vectors", len(vectors)))
-	if len(vectors) > 0 {
-		common.Info(fmt.Sprintf("Vector dimension: %d", len(vectors[0])))
+	common.Info(fmt.Sprintf("Encoded successfully, got %d vectors", len(response)))
+	if len(response) > 0 {
+		common.Info(fmt.Sprintf("Vector dimension: %d", len(response[0].Embedding)))
 	}
 
-	return vectors, nil
+	return response, nil
 }
 
 // truncate truncates text to maxLen characters
@@ -1021,16 +1025,17 @@ func (s *SkillIndexerService) getEmbeddingDimension(ctx context.Context, tenantI
 
 	// Use simple test text like Python does: embedding_model.encode(["ok"])
 	testText := "ok"
-	vectors, err := embeddingModel.ModelDriver.Encode(embeddingModel.ModelName, []string{testText}, embeddingModel.APIConfig, nil)
+	var response []models.EmbeddingData
+	response, err = embeddingModel.ModelDriver.Embed(embeddingModel.ModelName, []string{testText}, embeddingModel.APIConfig, nil)
 	if err != nil {
 		return 0, fmt.Errorf("failed to encode test text: %w", err)
 	}
 
-	if len(vectors) == 0 || len(vectors[0]) == 0 {
+	if len(response) == 0 || len(response[0].Embedding) == 0 {
 		return 0, fmt.Errorf("embedding returned empty vector")
 	}
 
-	dimension := len(vectors[0])
+	dimension := len(response[0].Embedding)
 	common.Info(fmt.Sprintf("Got embedding dimension from API: %d", dimension))
 	return dimension, nil
 }
diff --git a/internal/service/skill_search.go b/internal/service/skill_search.go
index c48d0f1314..d7a91a6011 100644
--- a/internal/service/skill_search.go
+++ b/internal/service/skill_search.go
@@ -27,6 +27,7 @@ import (
 	"ragflow/internal/engine"
 	"ragflow/internal/engine/types"
 	"ragflow/internal/entity"
+	"ragflow/internal/entity/models"
 	"ragflow/internal/utility"
 	"strings"
 
@@ -679,15 +680,16 @@ func (s *SkillSearchService) getEmbedding(ctx context.Context, text, embdID, ten
 	}
 	truncatedText := truncate(text, maxLen-10)
 
-	vectors, err := embeddingModel.ModelDriver.Encode(embeddingModel.ModelName, []string{truncatedText}, embeddingModel.APIConfig, nil)
+	var response []models.EmbeddingData
+	response, err = embeddingModel.ModelDriver.Embed(embeddingModel.ModelName, []string{truncatedText}, embeddingModel.APIConfig, nil)
 	if err != nil {
 		return nil, fmt.Errorf("failed to encode query: %w", err)
 	}
-	if len(vectors) == 0 {
+	if len(response) == 0 {
 		return nil, fmt.Errorf("embedding returned empty result")
 	}
 
-	return vectors[0], nil
+	return response[0].Embedding, nil
 }
 
 // Helper functions
diff --git a/uv.lock b/uv.lock
index 44fe6fca92..9bf11d19a0 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,4 +1,5 @@
 version = 1
+revision = 3
 requires-python = ">=3.12, <3.15"
 resolution-markers = [
     "python_full_version >= '3.14' and sys_platform == 'darwin'",
@@ -3624,10 +3625,6 @@ wheels = [
     { url = "https://mirrors.aliyun.com/pypi/packages/47/66/eea81dfff765ed66c68fd2ed8c96245109e13c896c2a5015c7839c92367e/jiter-0.13.0-cp314-cp314t-win32.whl", hash = "sha256:24dc96eca9f84da4131cdf87a95e6ce36765c3b156fc9ae33280873b1c32d5f6" },
     { url = "https://mirrors.aliyun.com/pypi/packages/ff/32/4ac9c7a76402f8f00d00842a7f6b83b284d0cf7c1e9d4227bc95aa6d17fa/jiter-0.13.0-cp314-cp314t-win_amd64.whl", hash = "sha256:0a8d76c7524087272c8ae913f5d9d608bd839154b62c4322ef65723d2e5bb0b8" },
     { url = "https://mirrors.aliyun.com/pypi/packages/f9/8e/7def204fea9f9be8b3c21a6f2dd6c020cf56c7d5ff753e0e23ed7f9ea57e/jiter-0.13.0-cp314-cp314t-win_arm64.whl", hash = "sha256:2c26cf47e2cad140fa23b6d58d435a7c0161f5c514284802f25e87fddfe11024" },
-    { url = "https://mirrors.aliyun.com/pypi/packages/79/b3/3c29819a27178d0e461a8571fb63c6ae38be6dc36b78b3ec2876bbd6a910/jiter-0.13.0-graalpy311-graalpy242_311_native-macosx_10_12_x86_64.whl", hash = "sha256:b1cbfa133241d0e6bdab48dcdc2604e8ba81512f6bbd68ec3e8e1357dd3c316c" },
-    { url = "https://mirrors.aliyun.com/pypi/packages/eb/ae/60993e4b07b1ac5ebe46da7aa99fdbb802eb986c38d26e3883ac0125c4e0/jiter-0.13.0-graalpy311-graalpy242_311_native-macosx_11_0_arm64.whl", hash = "sha256:db367d8be9fad6e8ebbac4a7578b7af562e506211036cba2c06c3b998603c3d2" },
-    { url = "https://mirrors.aliyun.com/pypi/packages/77/fa/2227e590e9cf98803db2811f172b2d6460a21539ab73006f251c66f44b14/jiter-0.13.0-graalpy311-graalpy242_311_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:45f6f8efb2f3b0603092401dc2df79fa89ccbc027aaba4174d2d4133ed661434" },
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