support deepseek

Signed-off-by: Patrick Zhao <[email protected]>

go.mod

@@ -77,7 +77,7 @@ require (
 	github.com/rfyiamcool/cronlib v1.2.1
 	github.com/robfig/cron/v3 v3.0.1
 	github.com/samber/lo v1.37.0
-	github.com/sashabaranov/go-openai v1.24.0
+	github.com/sashabaranov/go-openai v1.37.0
 	github.com/segmentio/encoding v0.4.1
 	github.com/shirou/gopsutil v3.21.11+incompatible
 	github.com/shirou/gopsutil/v3 v3.22.8

go.sum

@@ -1010,6 +1010,8 @@ github.com/samber/lo v1.37.0 h1:XjVcB8g6tgUp8rsPsJ2CvhClfImrpL04YpQHXeHPhRw=
 github.com/samber/lo v1.37.0/go.mod h1:9vaz2O4o8oOnK23pd2TrXufcbdbJIa3b6cstBWKpopA=
 github.com/sashabaranov/go-openai v1.24.0 h1:4H4Pg8Bl2RH/YSnU8DYumZbuHnnkfioor/dtNlB20D4=
 github.com/sashabaranov/go-openai v1.24.0/go.mod h1:lj5b/K+zjTSFxVLijLSTDZuP7adOgerWeFyZLUhAKRg=
+github.com/sashabaranov/go-openai v1.37.0 h1:hQQowgYm4OXJ1Z/wTrE+XZaO20BYsL0R3uRPSpfNZkY=
+github.com/sashabaranov/go-openai v1.37.0/go.mod h1:lj5b/K+zjTSFxVLijLSTDZuP7adOgerWeFyZLUhAKRg=
 github.com/sean-/seed v0.0.0-20170313163322-e2103e2c3529/go.mod h1:DxrIzT+xaE7yg65j358z/aeFdxmN0P9QXhEzd20vsDc=
 github.com/sebdah/goldie/v2 v2.5.3 h1:9ES/mNN+HNUbNWpVAlrzuZ7jE+Nrczbj8uFRjM7624Y=
 github.com/sebdah/goldie/v2 v2.5.3/go.mod h1:oZ9fp0+se1eapSRjfYbsV/0Hqhbuu3bJVvKI/NNtssI=

pkg/microservice/aslan/core/common/repository/models/llm_integration.go

@@ -27,6 +27,7 @@ type LLMIntegration struct {
 	ProviderName llm.Provider       `bson:"provider_name"  json:"provider_name"`
 	Token        string             `bson:"token"          json:"token"`
 	BaseURL      string             `bson:"base_url"       json:"base_url"`
+	Model        string             `bson:"model"          json:"model"`
 	EnableProxy  bool               `bson:"enable_proxy"   json:"enable_proxy"`
 	IsDefault    bool               `bson:"is_default"     json:"is_default"`
 	UpdatedBy    string             `bson:"updated_by"     json:"updated_by"`

pkg/microservice/aslan/core/common/service/llm.go

@@ -33,6 +33,7 @@ func newLLMClient(llmIntegration *models.LLMIntegration) (llm.ILLM, error) {
 		ProviderName: llmIntegration.ProviderName,
 		Token:        llmIntegration.Token,
 		BaseURL:      llmIntegration.BaseURL,
+		Model:        llmIntegration.Model,
 	}
 	if llmIntegration.EnableProxy {
 		llmConfig.Proxy = config.ProxyHTTPSAddr()

pkg/microservice/aslan/core/common/service/llm_test.go

@@ -0,0 +1,35 @@
+package service
+
+import (
+	"reflect"
+	"testing"
+
+	"github.com/koderover/zadig/v2/pkg/microservice/aslan/core/common/repository/models"
+	"github.com/koderover/zadig/v2/pkg/tool/llm"
+)
+
+func Test_newLLMClient(t *testing.T) {
+	type args struct {
+		llmIntegration *models.LLMIntegration
+	}
+	tests := []struct {
+		name    string
+		args    args
+		want    llm.ILLM
+		wantErr bool
+	}{
+		// TODO: Add test cases.
+	}
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			got, err := newLLMClient(tt.args.llmIntegration)
+			if (err != nil) != tt.wantErr {
+				t.Errorf("newLLMClient() error = %v, wantErr %v", err, tt.wantErr)
+				return
+			}
+			if !reflect.DeepEqual(got, tt.want) {
+				t.Errorf("newLLMClient() = %v, want %v", got, tt.want)
+			}
+		})
+	}
+}

pkg/microservice/aslan/core/log/service/ai/build.go

@@ -28,7 +28,13 @@ func AnalyzeBuildLog(args *BuildLogAnalysisArgs, project, pipeline, job string,
 	log := args.Log
 	prompt := fmt.Sprintf("%s; 构建日志数据: \"\"\"%s\"\"\"", BuildLogAnalysisPrompt, util.RemoveExtraSpaces(splitBuildLogByRowNum(log, 500)))
 
-	answer, err := client.GetCompletion(ctx, prompt, llm.WithModel(openapi.GPT4o))
+	options := []llm.ParamOption{}
+	if client.GetModel() != "" {
+		options = append(options, llm.WithModel(client.GetModel()))
+	} else {
+		options = append(options, llm.WithModel(openapi.GPT4o))
+	}
+	answer, err := client.GetCompletion(ctx, prompt, options...)
 	if err != nil {
 		logger.Errorf("failed to get answer from ai: %v, the error is: %+v", client.GetName(), err)
 		return "", err

pkg/microservice/aslan/core/stat/service/ai/ai_analysis.go

@@ -112,7 +112,13 @@ func AnalyzeProjectStats(args *AiAnalysisReq, logger *zap.SugaredLogger) (*AiAna
 			"分析要求:%s;你的回答需要使用text格式输出,输出内容不要包含\"三重引号分割的项目数据\"这个名称,也不要复述分析要求中的内容,在你的回答中禁止包含 "+
 			"\\\"data_description\\\"、\\\"jenkins\\\" 等字段; 项目数据：\"\"\"%s\"\"\"", args.Prompt, overAllInput)
 	}
-	answer, err := client.GetCompletion(context.TODO(), util.RemoveExtraSpaces(prompt), llm.WithTemperature(float32(0.2)), llm.WithModel(AnalysisModel))
+	options := []llm.ParamOption{llm.WithTemperature(float32(0.2))}
+	if client.GetModel() != "" {
+		options = append(options, llm.WithModel(client.GetModel()))
+	} else {
+		options = append(options, llm.WithModel(AnalysisModel))
+	}
+	answer, err := client.GetCompletion(context.TODO(), util.RemoveExtraSpaces(prompt), options...)
 	if err != nil {
 		logger.Errorf("failed to get answer from ai: %v, the error is: %+v", client.GetName(), err)
 		return nil, err
@@ -137,7 +143,13 @@ func AnalyzeProject(userPrompt string, project *ProjectData, client llm.ILLM, an
 	}
 
 	prompt := fmt.Sprintf("假设你是资深Devops专家，我需要你根据以下分析要求来分析用三重引号分割的项目数据，最后根据你的分析来生成分析报告，分析要求：%s； 项目数据：\"\"\"%s\"\"\";你的回答不能超过400个汉字，同时回答内容要符合text格式，不要存在换行和空行;", util.RemoveExtraSpaces(EveryProjectAnalysisPrompt), string(pData))
-	answer, err := client.GetCompletion(context.TODO(), util.RemoveExtraSpaces(prompt), llm.WithTemperature(float32(0.1)), llm.WithModel(AnalysisModel))
+	options := []llm.ParamOption{llm.WithTemperature(float32(0.1))}
+	if client.GetModel() != "" {
+		options = append(options, llm.WithModel(client.GetModel()))
+	} else {
+		options = append(options, llm.WithModel(AnalysisModel))
+	}
+	answer, err := client.GetCompletion(context.TODO(), util.RemoveExtraSpaces(prompt), options...)
 	if err != nil {
 		logger.Errorf("failed to get answer from ai: %v, the error is: %+v", client.GetName(), err)
 		return
@@ -189,7 +201,13 @@ func parseUserPrompt(args *AiAnalysisReq, aiClient llm.ILLM, logger *zap.Sugared
 	}
 
 	prompt := fmt.Sprintf("%s;\"\"\"%s\"\"\"", util.RemoveExtraSpaces(ParseUserPromptPrompt), args.Prompt)
-	resp, err := aiClient.GetCompletion(context.TODO(), prompt)
+	options := []llm.ParamOption{}
+	if aiClient.GetModel() != "" {
+		options = append(options, llm.WithModel(aiClient.GetModel()))
+	} else {
+		options = append(options, llm.WithModel(AnalysisModel))
+	}
+	resp, err := aiClient.GetCompletion(context.TODO(), prompt, options...)
 	if err != nil {
 		return input, fmt.Errorf("failed to get completion, error: %v", err)
 	}
@@ -457,7 +475,13 @@ func AnalyzeMonthAttention(start, end int64, data []*service2.MonthAttention, lo
 	retryTime := 0
 	answer := ""
 	for retryTime < 3 {
-		answer, err = client.GetCompletion(context.TODO(), util.RemoveExtraSpaces(prompt), llm.WithTemperature(float32(0.2)), llm.WithModel(AnalysisModel))
+		options := []llm.ParamOption{llm.WithTemperature(float32(0.2))}
+		if client.GetModel() != "" {
+			options = append(options, llm.WithModel(client.GetModel()))
+		} else {
+			options = append(options, llm.WithModel(AnalysisModel))
+		}
+		answer, err = client.GetCompletion(context.TODO(), util.RemoveExtraSpaces(prompt), options...)
 		if err != nil {
 			retryTime++
 			if strings.Contains(err.Error(), "create chat completion failed") && retryTime < 3 {

pkg/microservice/aslan/core/system/handler/llm.go

@@ -33,6 +33,7 @@ type CreateLLMIntegrationRequest struct {
 	ProviderName llm.Provider `json:"provider_name"`
 	Token        string       `json:"token"`
 	BaseURL      string       `json:"base_url"`
+	Model        string       `json:"model"`
 	EnableProxy  bool         `json:"enable_proxy"`
 }
 
@@ -189,6 +190,7 @@ func convertLLMArgToModel(args *CreateLLMIntegrationRequest) *commonmodels.LLMIn
 		Token:        args.Token,
 		BaseURL:      args.BaseURL,
 		EnableProxy:  args.EnableProxy,
+		Model:        args.Model,
 		IsDefault:    true,
 	}
 }

pkg/tool/analysis/analysis.go

@@ -212,7 +212,8 @@ func (a *Analysis) GetAIResults(anonymize bool) error {
 			texts = append(texts, failure.Text)
 		}
 		prompt := fmt.Sprintf(analysisPrompt, "Chinese", strings.Join(texts, " "))
-		parsedText, err := a.AIClient.Parse(a.Context, prompt, a.Cache, llm.WithTemperature(0.3))
+		options := []llm.ParamOption{llm.WithTemperature(0.3), llm.WithModel(a.AIClient.GetModel())}
+		parsedText, err := a.AIClient.Parse(a.Context, prompt, a.Cache, options...)
 		if err != nil {
 			// Check for exhaustion
 			if strings.Contains(err.Error(), "status code: 429") {

pkg/tool/llm/illm.go

@@ -27,16 +27,18 @@ import (
 type Provider string
 
 const (
-	ProviderOpenAI  Provider = "openai"
-	ProviderAzure   Provider = "azure_openai"
-	ProviderAzureAD Provider = "azure_ad_openai"
+	ProviderOpenAI   Provider = "openai"
+	ProviderDeepSeek Provider = "deepseek"
+	ProviderAzure    Provider = "azure_openai"
+	ProviderAzureAD  Provider = "azure_ad_openai"
 )
 
 var (
 	clients = map[Provider]ILLM{
-		ProviderOpenAI:  &OpenAIClient{},
-		ProviderAzure:   &OpenAIClient{},
-		ProviderAzureAD: &OpenAIClient{},
+		ProviderOpenAI:   &OpenAIClient{},
+		ProviderDeepSeek: &OpenAIClient{},
+		ProviderAzure:    &OpenAIClient{},
+		ProviderAzureAD:  &OpenAIClient{},
 	}
 )
 
@@ -45,6 +47,7 @@ type ILLM interface {
 	GetCompletion(ctx context.Context, prompt string, options ...ParamOption) (string, error)
 	Parse(ctx context.Context, prompt string, cache cache.ICache, options ...ParamOption) (string, error)
 	GetName() string
+	GetModel() string
 }
 
 func NewClient(provider Provider) (ILLM, error) {

pkg/tool/llm/openai.go

@@ -31,7 +31,7 @@ import (
 )
 
 const (
-	DefaultOpenAIModel           = openai.GPT4o
+	DefaultOpenAIModel           = openai.O1
 	DefaultOpenAIModelTokenLimit = "128000"
 )
 
@@ -180,6 +180,10 @@ func (a *OpenAIClient) GetName() string {
 	return a.name
 }
 
+func (a *OpenAIClient) GetModel() string {
+	return a.model
+}
+
 func NumTokensFromMessages(messages []openai.ChatCompletionMessage, model string) (num_tokens int, err error) {
 	tkm, err := tiktoken.NewEncodingForModel(model)
 	if err != nil {
@@ -198,7 +202,6 @@ func NumTokensFromMessages(messages []openai.ChatCompletionMessage, model string
 	} else {
 		tokens_per_message = 3
 		tokens_per_name = 1
-		log.Warnf("Warning: model not found. Using cl100k_base encoding.")
 	}
 
 	calcTokens := func(message string) (int, error) {