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Posted to notifications@dubbo.apache.org by "stringl1l1l1l (via GitHub)" <gi...@apache.org> on 2025/09/01 07:37:06 UTC
[PR] [feat]: Integrating AI Agent Capabilities into dubbo-admin [dubbo-admin]
stringl1l1l1l opened a new pull request, #1319:
URL: https://github.com/apache/dubbo-admin/pull/1319
A preliminary prototype of an agent designed to to assist users in diagnosing issues in Dubbo microservices.
### **Description of this PR**
This pull request introduces the foundational structure for an AI-powered ReAct agent system built with `Go` and the `Genkit` framework. All changes are contained within the `ai` directory.
### **Key Features Added**
- Configuration management with support for environment variables
- Core agent orchestration logic
- Third-party LLM API plugin integration
- Prompt design for ReAct workflows
- Input & output schema definitions
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Re: [PR] [feat]: Integrating AI Agent Capabilities into dubbo-admin [dubbo-admin]
Posted by "Copilot (via GitHub)" <gi...@apache.org>.
Copilot commented on code in PR #1319:
URL: https://github.com/apache/dubbo-admin/pull/1319#discussion_r2314112281
##########
ai/internal/agent/flow.go:
##########
@@ -0,0 +1,179 @@
+package agent
+
+import (
+ "context"
+
+ "dubbo-admin-ai/internal/config"
+ "dubbo-admin-ai/internal/manager"
+ "dubbo-admin-ai/internal/schema"
+ "dubbo-admin-ai/internal/tools"
+ "errors"
+ "fmt"
+ "log"
+ "os"
+
+ "github.com/firebase/genkit/go/core/logger"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/core"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// 公开的 Flow 变量，以便在编排器中调用
+var (
+ ReActFlow *core.Flow[schema.ReActIn, schema.ReActOut, struct{}]
+ ThinkingFlow *core.Flow[schema.ThinkIn, *schema.ThinkOut, struct{}]
+ ActFlow *core.Flow[*schema.ActIn, schema.ActOut, struct{}]
+
+ ThinkPrompt *ai.Prompt
+)
+
+var g *genkit.Genkit
+
+// The order of initialization cannot change
+func InitAgent() (err error) {
+ if err = manager.LoadEnvVars(); err != nil {
+ return err
+ }
+
+ manager.InitLogger()
+
+ if g, err = manager.GetGlobalGenkit(); err != nil {
+ return err
+ }
+
+ tools.RegisterAllMockTools(g)
+
+ if err = InitFlows(g); err != nil {
+ return err
+ }
+
+ return nil
+}
+
+func InitFlows(registry *genkit.Genkit) error {
+ if registry == nil {
+ return fmt.Errorf("registry is nil")
+ }
+ g = registry
+
+ data, err := os.ReadFile(config.PROMPT_DIR_PATH + "/agentSystem.prompt")
+ if err != nil {
+ return fmt.Errorf("failed to read agentSystem prompt: %w", err)
+ }
+ systemPromptText := string(data)
+
+ mockTools, err := tools.AllMockToolRef()
+ if err != nil {
+ log.Fatalf("failed to get mock mock_tools: %v", err)
+ }
+ ThinkPrompt, err = genkit.DefinePrompt(g, "agentThinking",
+ ai.WithSystem(systemPromptText),
+ ai.WithInputType(schema.ThinkIn{}),
+ ai.WithOutputType(schema.ThinkOut{}),
+ ai.WithPrompt("{{userInput}}"),
+ ai.WithTools(mockTools...),
+ )
+
+ if err != nil {
+ return fmt.Errorf("failed to define agentThink prompt: %w", err)
+ }
+
+ ReActFlow = genkit.DefineFlow(g, "reAct", reAct)
+ ThinkingFlow = genkit.DefineFlow(g, "thinking", thinking)
+ ActFlow = genkit.DefineFlow(g, "act", act)
+
+ return nil
+}
+
+// Flow 的核心函数实现 `fn` (不对外导出)
+// ----------------------------------------------------------------------------
+// 1. agentOrchestrator: 总指挥/编排器的核心逻辑
+// ----------------------------------------------------------------------------
+func reAct(ctx context.Context, reActInput schema.ReActIn) (reActOut schema.ReActOut, err error) {
+ //TODO: 输入数据意图解析
+
+ thinkingInput := reActInput
+ // 主协调循环 (Reconciliation Loop)
+ for i := 0; i < config.MAX_REACT_ITERATIONS; i++ {
+
+ // a. 调用 thinkingFlow
+ thinkingResp, err := ThinkingFlow.Run(ctx, thinkingInput)
+ if err != nil {
+ manager.GetLogger().Error("failed to run thinking flow", "error", err)
+ return "", err
+ }
+ if thinkingResp == nil {
+ manager.GetLogger().Error("expected non-nil response")
+ return "", errors.New("expected non-nil response")
+ }
+
+ for _, r := range thinkingResp.ToolRequests {
+ manager.GetLogger().Info(r.String())
+ }
+
+ reActOut = thinkingResp.String()
+
+ // b. 检查是否有最终答案
+ if thinkingResp.IsStop() {
+ break
+ }
+
+ // c. 调用 actFlow
+ actOutArray, err := ActFlow.Run(ctx, thinkingResp)
+ if err != nil {
+ logger.FromContext(ctx).Error("failed to run act flow", "error", err)
+ return "", err
+ }
+
+ // TODO: 这里将来会集成SessionMemory，暂时简化处理
+ _ = actOutArray // 占位符，避免未使用变量错误
+ }
+
+ return reActOut, nil
+}
+
+// ----------------------------------------------------------------------------
+// 2. thinking: 大脑/思考者的核心逻辑
+// ----------------------------------------------------------------------------
+func thinking(ctx context.Context, input schema.ThinkIn) (*schema.ThinkOut, error) {
+ resp, err := ThinkPrompt.Execute(ctx,
+ ai.WithInput(input),
+ )
+
+ if err != nil {
+ return nil, fmt.Errorf("failed to execute agentThink prompt: %w", err)
+ }
+
+ // 解析输出
+ var response *schema.ThinkOut = nil
Review Comment:
[nitpick] Explicit initialization to nil is unnecessary for pointer types. Simply declare as `var response *schema.ThinkOut` for cleaner code.
```suggestion
var response *schema.ThinkOut
```
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+ }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+ ToolName string `json:"toolName"`
+ RequestRateQPS float64 `json:"requestRateQPS"`
+ ErrorRatePercentage float64 `json:"errorRatePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_traffic' called for service: %s", input.ServiceName)
+
+ return PrometheusServiceTrafficOutput{
+ ToolName: "prometheus_query_service_traffic",
+ RequestRateQPS: 250.0,
+ ErrorRatePercentage: 5.2,
+ Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
+ }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+ PromqlQuery string `json:"promqlQuery" jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+ Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+ Timestamp int64 `json:"timestamp"`
+ Value string `json:"value"`
+}
+
+type TimeseriesResult struct {
+ Metric TimeseriesMetric `json:"metric"`
+ Value TimeseriesValue `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ Query string `json:"query"`
+ Results []TimeseriesResult `json:"results"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+ log.Printf("Tool 'query_timeseries_database' called with query: %s", input.PromqlQuery)
+
+ return QueryTimeseriesDatabaseOutput{
+ ToolName: "query_timeseries_database",
+ Query: input.PromqlQuery,
+ Results: []TimeseriesResult{
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-1"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.5"},
+ },
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-2"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.2"},
+ },
+ },
+ Summary: "查询返回了 2 个时间序列",
+ }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to profile"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to profile"`
+ DurationSeconds int `json:"durationSeconds" jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+ CPUTimePercentage float64 `json:"cpuTimePercentage"`
+ StackTrace []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+ ToolName string `json:"toolName"`
+ Status string `json:"status"`
+ TotalSamples int `json:"totalSamples"`
+ Hotspots []PerformanceHotspot `json:"hotspots"`
+ Summary string `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+ return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, error) {
+ log.Printf("Tool 'application_performance_profiling' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return ApplicationPerformanceProfilingOutput{
+ ToolName: "application_performance_profiling",
+ Status: "completed",
+ TotalSamples: 10000,
+ Hotspots: []PerformanceHotspot{
+ {
+ CPUTimePercentage: 45.5,
+ StackTrace: []string{
+ "com.example.OrderService.processOrder()",
+ "com.example.DatabaseClient.query()",
+ "java.sql.PreparedStatement.executeQuery()",
+ },
+ },
+ },
+ Summary: "性能分析显示，45.5%的CPU时间消耗在数据库查询调用链上",
+ }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Java service to analyze"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ FullGcCountLastHour int `json:"fullGcCountLastHour"`
+ FullGcTimeAvgMillis int `json:"fullGcTimeAvgMillis"`
+ HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+ log.Printf("Tool 'jvm_performance_analysis' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return JVMPerformanceAnalysisOutput{
+ ToolName: "jvm_performance_analysis",
+ FullGcCountLastHour: 15,
+ FullGcTimeAvgMillis: 1200,
+ HeapUsagePercentage: 85.5,
+ Summary: "GC activity is high, average Full GC time is 1200ms",
+ }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+ ToolName string `json:"toolName"`
+ UpstreamServices []string `json:"upstreamServices"`
+ DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) (TraceDependencyViewOutput, error) {
+ log.Printf("Tool 'trace_dependency_view' called for service: %s", input.ServiceName)
+
+ return TraceDependencyViewOutput{
+ ToolName: "trace_dependency_view",
+ UpstreamServices: []string{"api-gateway", "user-service"},
+ DownstreamServices: []string{"mysql-orders-db", "redis-cache", "payment-service"},
+ }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+ DownstreamService string `json:"downstreamService"`
+ LatencyAvgMillis int `json:"latencyAvgMillis"`
+ ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ TotalLatencyAvgMillis int `json:"totalLatencyAvgMillis"`
+ Bottlenecks []LatencyBottleneck `json:"bottlenecks"`
+ Summary string `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+ log.Printf("Tool 'trace_latency_analysis' called for service: %s", input.ServiceName)
+
+ return TraceLatencyAnalysisOutput{
+ ToolName: "trace_latency_analysis",
+ TotalLatencyAvgMillis: 3200,
+ Bottlenecks: []LatencyBottleneck{
+ {
+ DownstreamService: "mysql-orders-db",
+ LatencyAvgMillis: 3050,
+ ContributionPercentage: 95.3,
+ },
+ {
+ DownstreamService: "user-service",
+ LatencyAvgMillis: 150,
+ ContributionPercentage: 4.7,
+ },
+ },
+ Summary: "平均总延迟为 3200ms。瓶颈已定位，95.3% 的延迟来自对下游 'mysql-orders-db' 的调用",
+ }, nil
+}
+
+// ================================================
+// Database Connection Pool Analysis Tool
+// ================================================
+
+type DatabaseConnectionPoolAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+}
+
+type DatabaseConnectionPoolAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ MaxConnections int `json:"maxConnections"`
+ ActiveConnections int `json:"activeConnections"`
+ IdleConnections int `json:"idleConnections"`
+ PendingRequests int `json:"pendingRequests"`
+ Summary string `json:"summary"`
+}
+
+func (o DatabaseConnectionPoolAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func databaseConnectionPoolAnalysis(ctx *ai.ToolContext, input DatabaseConnectionPoolAnalysisInput) (DatabaseConnectionPoolAnalysisOutput, error) {
+ log.Printf("Tool 'database_connection_pool_analysis' called for service: %s", input.ServiceName)
+
+ return DatabaseConnectionPoolAnalysisOutput{
+ ToolName: "database_connection_pool_analysis",
+ MaxConnections: 100,
+ ActiveConnections: 100,
+ IdleConnections: 0,
+ PendingRequests: 58,
+ Summary: "数据库连接池已完全耗尽 (100/100)，当前有 58 个请求正在排队等待连接",
+ }, nil
+}
+
+// ================================================
+// Kubernetes Get Pod Resources Tool
+// ================================================
+
+type KubernetesGetPodResourcesInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Namespace string `json:"namespace" jsonschema:"required,description=The namespace of the service"`
+}
+
+type PodResource struct {
+ PodName string `json:"podName"`
+ CPUUsageCores float64 `json:"cpuUsageCores"`
+ CPURequestCores float64 `json:"cpuRequestCores"`
+ CPULimitCores float64 `json:"cpuLimitCores"`
+ MemoryUsageMi int `json:"memoryUsageMi"`
+ MemoryRequestMi int `json:"memoryRequestMi"`
+ MemoryLimitMi int `json:"memoryLimitMi"`
+}
+
+type KubernetesGetPodResourcesOutput struct {
+ ToolName string `json:"toolName"`
+ Pods []PodResource `json:"pods"`
+ Summary string `json:"summary"`
+}
+
+func (o KubernetesGetPodResourcesOutput) Tool() string {
+ return o.ToolName
+}
+
+func kubernetesGetPodResources(ctx *ai.ToolContext, input KubernetesGetPodResourcesInput) (KubernetesGetPodResourcesOutput, error) {
+ log.Printf("Tool 'kubernetes_get_pod_resources' called for service: %s in namespace: %s", input.ServiceName, input.Namespace)
+
+ return KubernetesGetPodResourcesOutput{
+ ToolName: "kubernetes_get_pod_resources",
+ Pods: []PodResource{
+ {
+ PodName: "order-service-pod-1",
+ CPUUsageCores: 0.8,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1800,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ {
+ PodName: "order-service-pod-2",
+ CPUUsageCores: 0.9,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1950,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ },
+ Summary: "2 out of 2 pods are near their memory limits",
+ }, nil
+}
+
+// ================================================
+// Dubbo Service Status Tool
+// ================================================
+
+type DubboServiceStatusInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Dubbo service"`
+}
+
+type DubboProvider struct {
+ IP string `json:"ip"`
+ Port int `json:"port"`
+ Status string `json:"status"`
+}
+
+type DubboConsumer struct {
+ IP string `json:"ip"`
+ Application string `json:"application"`
+ Status string `json:"status"`
+}
+
+type DubboServiceStatusOutput struct {
+ ToolName string `json:"toolName"`
+ Providers []DubboProvider `json:"providers"`
+ Consumers []DubboConsumer `json:"consumers"`
+}
+
+func (o DubboServiceStatusOutput) Tool() string {
+ return o.ToolName
+}
+
+func dubboServiceStatus(ctx *ai.ToolContext, input DubboServiceStatusInput) (DubboServiceStatusOutput, error) {
+ log.Printf("Tool 'dubbo_service_status' called for service: %s", input.ServiceName)
+
+ return DubboServiceStatusOutput{
+ ToolName: "dubbo_service_status",
+ Providers: []DubboProvider{
+ {IP: "192.168.1.10", Port: 20880, Status: "healthy"},
+ {IP: "192.168.1.11", Port: 20880, Status: "healthy"},
+ },
+ Consumers: []DubboConsumer{
+ {IP: "192.168.1.20", Application: "web-frontend", Status: "connected"},
+ {IP: "192.168.1.21", Application: "api-gateway", Status: "connected"},
+ },
+ }, nil
+}
+
+// ================================================
+// Query Log Database Tool
+// ================================================
+
+type QueryLogDatabaseInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Keyword string `json:"keyword" jsonschema:"required,description=Keyword to search for"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LogEntry struct {
+ Timestamp string `json:"timestamp"`
+ Level string `json:"level"`
+ Message string `json:"message"`
+}
+
+type QueryLogDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ TotalHits int `json:"totalHits"`
+ Logs []LogEntry `json:"logs"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryLogDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryLogDatabase(ctx *ai.ToolContext, input QueryLogDatabaseInput) (QueryLogDatabaseOutput, error) {
+ log.Printf("Tool 'query_log_database' called for service: %s, keyword: %s", input.ServiceName, input.Keyword)
+
+ return QueryLogDatabaseOutput{
+ ToolName: "query_log_database",
+ TotalHits: 152,
+ Logs: []LogEntry{
+ {
+ Timestamp: "2025-08-16T15:32:05Z",
+ Level: "WARN",
+ Message: "Timeout waiting for idle object in database connection pool.",
+ },
+ {
+ Timestamp: "2025-08-16T15:32:08Z",
+ Level: "WARN",
+ Message: "Timeout waiting for idle object in database connection pool.",
+ },
+ },
+ Summary: fmt.Sprintf("在过去%d分钟内，发现 152 条关于 '%s' 的日志条目", input.TimeRangeMinutes, input.Keyword),
+ }, nil
+}
+
+// ================================================
+// Search Archived Logs Tool
+// ================================================
+
+type SearchArchivedLogsInput struct {
+ FilePathPattern string `json:"filePathPattern" jsonschema:"required,description=File path pattern to search"`
+ GrepKeyword string `json:"grepKeyword" jsonschema:"required,description=Keyword to grep for"`
+}
+
+type MatchingLine struct {
+ FilePath string `json:"filePath"`
+ LineNumber int `json:"lineNumber"`
+ LineContent string `json:"lineContent"`
+}
+
+type SearchArchivedLogsOutput struct {
+ ToolName string `json:"toolName"`
+ FilesSearched int `json:"filesSearched"`
+ MatchingLines []MatchingLine `json:"matchingLines"`
+ Summary string `json:"summary"`
+}
+
+func (o SearchArchivedLogsOutput) Tool() string {
+ return o.ToolName
+}
+
+func searchArchivedLogs(ctx *ai.ToolContext, input SearchArchivedLogsInput) (SearchArchivedLogsOutput, error) {
+ log.Printf("Tool 'search_archived_logs' called with pattern: %s, keyword: %s", input.FilePathPattern, input.GrepKeyword)
+
+ return SearchArchivedLogsOutput{
+ ToolName: "search_archived_logs",
+ FilesSearched: 5,
+ MatchingLines: []MatchingLine{
+ {
+ FilePath: "/logs/mysql-orders-db/slow-query-2025-08-16.log.gz",
+ LineNumber: 1024,
+ LineContent: "Query_time: 25.3s | SELECT COUNT(id), SUM(price) FROM orders WHERE user_id = 'VIP_USER_123';",
+ },
+ {
+ FilePath: "/logs/mysql-orders-db/slow-query-2025-08-16.log.gz",
+ LineNumber: 1029,
+ LineContent: "Query_time: 28.1s | SELECT COUNT(id), SUM(price) FROM orders WHERE user_id = 'VIP_USER_456';",
+ },
+ },
+ Summary: "在归档的日志文件中，发现了多条查询，搜索了 5 个文件，找到了 2 条匹配行",
+ }, nil
+}
+
+// ================================================
+// Query Knowledge Base Tool
+// ================================================
+
+type QueryKnowledgeBaseInput struct {
+ QueryText string `json:"queryText" jsonschema:"required,description=Query text to search for"`
+}
+
+type KnowledgeDocument struct {
+ Source string `json:"source"`
+ ContentSnippet string `json:"contentSnippet"`
+ SimilarityScore float64 `json:"similarityScore"`
+}
+
+type QueryKnowledgeBaseOutput struct {
+ ToolName string `json:"toolName"`
+ Documents []KnowledgeDocument `json:"documents"`
+}
+
+func (o QueryKnowledgeBaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryKnowledgeBase(ctx *ai.ToolContext, input QueryKnowledgeBaseInput) (QueryKnowledgeBaseOutput, error) {
+ log.Printf("Tool 'query_knowledge_base' called with query: %s", input.QueryText)
+
+ return QueryKnowledgeBaseOutput{
+ ToolName: "query_knowledge_base",
+ Documents: []KnowledgeDocument{
+ {
+ Source: "Project-VIP-Feature-Design-Doc.md",
+ ContentSnippet: "The 'Lifetime Achievement' badge requires calculating total user spending. Note: This may cause slow queries on the orders table if the user_id column is not properly indexed.",
+ SimilarityScore: 0.92,
+ },
+ },
+ }, nil
+}
+
+// ================================================
+// Tool Registration Function
+// ================================================
+
+var registeredTools []ai.Tool = nil
Review Comment:
[nitpick] Explicit initialization to nil is unnecessary for slice types. Simply declare as `var registeredTools []ai.Tool` for cleaner code.
```suggestion
var registeredTools []ai.Tool
```
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Re: [PR] [feat]: Integrating AI Agent Capabilities into dubbo-admin [dubbo-admin]
Posted by "sonarqubecloud[bot] (via GitHub)" <gi...@apache.org>.
sonarqubecloud[bot] commented on PR #1319:
URL: https://github.com/apache/dubbo-admin/pull/1319#issuecomment-3242572940
## [](https://sonarcloud.io/dashboard?id=apache_dubbo-admin&pullRequest=1319) **Quality Gate passed**
Issues
 [0 New issues](https://sonarcloud.io/project/issues?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=OPEN,CONFIRMED&sinceLeakPeriod=true)
 [0 Accepted issues](https://sonarcloud.io/project/issues?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=ACCEPTED)
Measures
 [0 Security Hotspots](https://sonarcloud.io/project/security_hotspots?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=OPEN,CONFIRMED&sinceLeakPeriod=true)
 [0.0% Coverage on New Code](https://sonarcloud.io/component_measures?id=apache_dubbo-admin&pullRequest=1319&metric=new_coverage&view=list)
 [0.0% Duplication on New Code](https://sonarcloud.io/component_measures?id=apache_dubbo-admin&pullRequest=1319&metric=new_duplicated_lines_density&view=list)
[See analysis details on SonarQube Cloud](https://sonarcloud.io/dashboard?id=apache_dubbo-admin&pullRequest=1319)
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Re: [PR] [feat]: Integrating AI Agent Capabilities into dubbo-admin [dubbo-admin]
Posted by "Copilot (via GitHub)" <gi...@apache.org>.
Copilot commented on code in PR #1319:
URL: https://github.com/apache/dubbo-admin/pull/1319#discussion_r2313972851
##########
ai/config/config.go:
##########
@@ -0,0 +1,24 @@
+package config
+
+import (
+ "dubbo-admin-ai/plugins/siliconflow"
+ "os"
+ "path/filepath"
+ "runtime"
+)
+
+var (
+ // API keys
+ GEMINI_API_KEY string = os.Getenv("GEMINI_API_KEY")
+ SILICONFLOW_API_KEY string = os.Getenv("SILICONFLOW_API_KEY")
+
+ // Configuration
+ // 自动获取项目根目录
+ _, b, _, _ = runtime.Caller(0)
+ PROJECT_ROOT = filepath.Join(filepath.Dir(b), "..")
Review Comment:
Using runtime.Caller(0) to determine project root in a global variable can be fragile and may not work correctly when the package is imported from different contexts. Consider using go:embed or a more explicit configuration approach.
##########
ai/internal/agent/flow.go:
##########
@@ -0,0 +1,178 @@
+package agent
+
+import (
+ "context"
+ "dubbo-admin-ai/config"
+ "dubbo-admin-ai/internal/manager"
+ "dubbo-admin-ai/internal/schema"
+ "dubbo-admin-ai/internal/tools"
+ "errors"
+ "fmt"
+ "log"
+ "os"
+
+ "github.com/firebase/genkit/go/core/logger"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/core"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// 公开的 Flow 变量，以便在编排器中调用
+var (
+ ReActFlow *core.Flow[schema.ReActIn, schema.ReActOut, struct{}]
+ ThinkingFlow *core.Flow[schema.ThinkIn, *schema.ThinkOut, struct{}]
+ ActFlow *core.Flow[*schema.ActIn, schema.ActOut, struct{}]
+
+ ThinkPrompt *ai.Prompt
+)
+
+var g *genkit.Genkit
+
+// The order of initialization cannot change
+func InitAgent() (err error) {
+ if err = manager.LoadEnvVars(); err != nil {
+ return err
+ }
+
+ manager.InitLogger()
+
+ if g, err = manager.GetGlobalGenkit(); err != nil {
+ return err
+ }
+
+ tools.RegisterAllMockTools(g)
+
+ if err = InitFlows(g); err != nil {
+ return err
+ }
+
+ return nil
+}
+
+func InitFlows(registry *genkit.Genkit) error {
+ if registry == nil {
+ return fmt.Errorf("registry is nil")
+ }
+ g = registry
+
+ data, err := os.ReadFile(config.PROMPT_DIR_PATH + "/agentSystem.prompt")
+ if err != nil {
+ return fmt.Errorf("failed to read agentSystem prompt: %w", err)
+ }
+ systemPromptText := string(data)
+
+ mockTools, err := tools.AllMockToolRef()
+ if err != nil {
+ log.Fatalf("failed to get mock mock_tools: %v", err)
+ }
+ ThinkPrompt, err = genkit.DefinePrompt(g, "agentThinking",
+ ai.WithSystem(systemPromptText),
+ ai.WithInputType(schema.ThinkIn{}),
+ ai.WithOutputType(schema.ThinkOut{}),
+ ai.WithPrompt("{{userInput}}"),
+ ai.WithTools(mockTools...),
+ )
+
+ if err != nil {
+ return fmt.Errorf("failed to define agentThink prompt: %w", err)
+ }
+
+ ReActFlow = genkit.DefineFlow(g, "reAct", reAct)
+ ThinkingFlow = genkit.DefineFlow(g, "thinking", thinking)
+ ActFlow = genkit.DefineFlow(g, "act", act)
+
+ return nil
+}
+
+// Flow 的核心函数实现 `fn` (不对外导出)
+// ----------------------------------------------------------------------------
+// 1. agentOrchestrator: 总指挥/编排器的核心逻辑
+// ----------------------------------------------------------------------------
+func reAct(ctx context.Context, reActInput schema.ReActIn) (reActOut schema.ReActOut, err error) {
+ //TODO: 输入数据意图解析
+
+ thinkingInput := reActInput
+ // 主协调循环 (Reconciliation Loop)
+ for i := 0; i < config.MAX_REACT_ITERATIONS; i++ {
+
+ // a. 调用 thinkingFlow
+ thinkingResp, err := ThinkingFlow.Run(ctx, thinkingInput)
+ if err != nil {
+ manager.GetLogger().Error("failed to run thinking flow", "error", err)
+ return "", err
+ }
+ if thinkingResp == nil {
+ manager.GetLogger().Error("expected non-nil response")
+ return "", errors.New("expected non-nil response")
+ }
+
+ for _, r := range thinkingResp.ToolRequests {
+ manager.GetLogger().Info(r.String())
+ }
+
+ reActOut = thinkingResp.String()
+
+ // b. 检查是否有最终答案
+ if thinkingResp.IsStop() {
+ break
+ }
+
+ // c. 调用 actFlow
+ actOutArray, err := ActFlow.Run(ctx, thinkingResp)
+ if err != nil {
+ logger.FromContext(ctx).Error("failed to run act flow", "error", err)
+ return "", err
+ }
+
+ // TODO: 这里将来会集成SessionMemory，暂时简化处理
+ _ = actOutArray // 占位符，避免未使用变量错误
Review Comment:
Using a blank identifier to suppress unused variable warnings indicates incomplete implementation. Either implement the session memory integration or remove the variable assignment until it's needed.
```suggestion
_, err := ActFlow.Run(ctx, thinkingResp)
if err != nil {
logger.FromContext(ctx).Error("failed to run act flow", "error", err)
return "", err
}
// TODO: 这里将来会集成SessionMemory，暂时简化处理
// actOutArray is not used yet
```
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+ }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+ ToolName string `json:"toolName"`
+ RequestRateQPS float64 `json:"requestRateQPS"`
+ ErrorRatePercentage float64 `json:"errorRatePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_traffic' called for service: %s", input.ServiceName)
+
+ return PrometheusServiceTrafficOutput{
+ ToolName: "prometheus_query_service_traffic",
+ RequestRateQPS: 250.0,
+ ErrorRatePercentage: 5.2,
+ Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
+ }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+ PromqlQuery string `json:"promqlQuery" jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+ Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+ Timestamp int64 `json:"timestamp"`
+ Value string `json:"value"`
+}
+
+type TimeseriesResult struct {
+ Metric TimeseriesMetric `json:"metric"`
+ Value TimeseriesValue `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ Query string `json:"query"`
+ Results []TimeseriesResult `json:"results"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+ log.Printf("Tool 'query_timeseries_database' called with query: %s", input.PromqlQuery)
+
+ return QueryTimeseriesDatabaseOutput{
+ ToolName: "query_timeseries_database",
+ Query: input.PromqlQuery,
+ Results: []TimeseriesResult{
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-1"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.5"},
+ },
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-2"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.2"},
+ },
+ },
+ Summary: "查询返回了 2 个时间序列",
+ }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to profile"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to profile"`
+ DurationSeconds int `json:"durationSeconds" jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+ CPUTimePercentage float64 `json:"cpuTimePercentage"`
+ StackTrace []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+ ToolName string `json:"toolName"`
+ Status string `json:"status"`
+ TotalSamples int `json:"totalSamples"`
+ Hotspots []PerformanceHotspot `json:"hotspots"`
+ Summary string `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+ return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, error) {
+ log.Printf("Tool 'application_performance_profiling' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return ApplicationPerformanceProfilingOutput{
+ ToolName: "application_performance_profiling",
+ Status: "completed",
+ TotalSamples: 10000,
+ Hotspots: []PerformanceHotspot{
+ {
+ CPUTimePercentage: 45.5,
+ StackTrace: []string{
+ "com.example.OrderService.processOrder()",
+ "com.example.DatabaseClient.query()",
+ "java.sql.PreparedStatement.executeQuery()",
+ },
+ },
+ },
+ Summary: "性能分析显示，45.5%的CPU时间消耗在数据库查询调用链上",
+ }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Java service to analyze"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ FullGcCountLastHour int `json:"fullGcCountLastHour"`
+ FullGcTimeAvgMillis int `json:"fullGcTimeAvgMillis"`
+ HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+ log.Printf("Tool 'jvm_performance_analysis' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return JVMPerformanceAnalysisOutput{
+ ToolName: "jvm_performance_analysis",
+ FullGcCountLastHour: 15,
+ FullGcTimeAvgMillis: 1200,
+ HeapUsagePercentage: 85.5,
+ Summary: "GC activity is high, average Full GC time is 1200ms",
+ }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+ ToolName string `json:"toolName"`
+ UpstreamServices []string `json:"upstreamServices"`
+ DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) (TraceDependencyViewOutput, error) {
+ log.Printf("Tool 'trace_dependency_view' called for service: %s", input.ServiceName)
+
+ return TraceDependencyViewOutput{
+ ToolName: "trace_dependency_view",
+ UpstreamServices: []string{"api-gateway", "user-service"},
+ DownstreamServices: []string{"mysql-orders-db", "redis-cache", "payment-service"},
+ }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+ DownstreamService string `json:"downstreamService"`
+ LatencyAvgMillis int `json:"latencyAvgMillis"`
+ ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ TotalLatencyAvgMillis int `json:"totalLatencyAvgMillis"`
+ Bottlenecks []LatencyBottleneck `json:"bottlenecks"`
+ Summary string `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+ log.Printf("Tool 'trace_latency_analysis' called for service: %s", input.ServiceName)
+
+ return TraceLatencyAnalysisOutput{
+ ToolName: "trace_latency_analysis",
+ TotalLatencyAvgMillis: 3200,
+ Bottlenecks: []LatencyBottleneck{
+ {
+ DownstreamService: "mysql-orders-db",
+ LatencyAvgMillis: 3050,
+ ContributionPercentage: 95.3,
+ },
+ {
+ DownstreamService: "user-service",
+ LatencyAvgMillis: 150,
+ ContributionPercentage: 4.7,
+ },
+ },
+ Summary: "平均总延迟为 3200ms。瓶颈已定位，95.3% 的延迟来自对下游 'mysql-orders-db' 的调用",
+ }, nil
+}
+
+// ================================================
+// Database Connection Pool Analysis Tool
+// ================================================
+
+type DatabaseConnectionPoolAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+}
+
+type DatabaseConnectionPoolAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ MaxConnections int `json:"maxConnections"`
+ ActiveConnections int `json:"activeConnections"`
+ IdleConnections int `json:"idleConnections"`
+ PendingRequests int `json:"pendingRequests"`
+ Summary string `json:"summary"`
+}
+
+func (o DatabaseConnectionPoolAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func databaseConnectionPoolAnalysis(ctx *ai.ToolContext, input DatabaseConnectionPoolAnalysisInput) (DatabaseConnectionPoolAnalysisOutput, error) {
+ log.Printf("Tool 'database_connection_pool_analysis' called for service: %s", input.ServiceName)
+
+ return DatabaseConnectionPoolAnalysisOutput{
+ ToolName: "database_connection_pool_analysis",
+ MaxConnections: 100,
+ ActiveConnections: 100,
+ IdleConnections: 0,
+ PendingRequests: 58,
+ Summary: "数据库连接池已完全耗尽 (100/100)，当前有 58 个请求正在排队等待连接",
+ }, nil
+}
+
+// ================================================
+// Kubernetes Get Pod Resources Tool
+// ================================================
+
+type KubernetesGetPodResourcesInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Namespace string `json:"namespace" jsonschema:"required,description=The namespace of the service"`
+}
+
+type PodResource struct {
+ PodName string `json:"podName"`
+ CPUUsageCores float64 `json:"cpuUsageCores"`
+ CPURequestCores float64 `json:"cpuRequestCores"`
+ CPULimitCores float64 `json:"cpuLimitCores"`
+ MemoryUsageMi int `json:"memoryUsageMi"`
+ MemoryRequestMi int `json:"memoryRequestMi"`
+ MemoryLimitMi int `json:"memoryLimitMi"`
+}
+
+type KubernetesGetPodResourcesOutput struct {
+ ToolName string `json:"toolName"`
+ Pods []PodResource `json:"pods"`
+ Summary string `json:"summary"`
+}
+
+func (o KubernetesGetPodResourcesOutput) Tool() string {
+ return o.ToolName
+}
+
+func kubernetesGetPodResources(ctx *ai.ToolContext, input KubernetesGetPodResourcesInput) (KubernetesGetPodResourcesOutput, error) {
+ log.Printf("Tool 'kubernetes_get_pod_resources' called for service: %s in namespace: %s", input.ServiceName, input.Namespace)
+
+ return KubernetesGetPodResourcesOutput{
+ ToolName: "kubernetes_get_pod_resources",
+ Pods: []PodResource{
+ {
+ PodName: "order-service-pod-1",
+ CPUUsageCores: 0.8,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1800,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ {
+ PodName: "order-service-pod-2",
+ CPUUsageCores: 0.9,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1950,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ },
+ Summary: "2 out of 2 pods are near their memory limits",
+ }, nil
+}
+
+// ================================================
+// Dubbo Service Status Tool
+// ================================================
+
+type DubboServiceStatusInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Dubbo service"`
+}
+
+type DubboProvider struct {
+ IP string `json:"ip"`
+ Port int `json:"port"`
+ Status string `json:"status"`
+}
+
+type DubboConsumer struct {
+ IP string `json:"ip"`
+ Application string `json:"application"`
+ Status string `json:"status"`
+}
+
+type DubboServiceStatusOutput struct {
+ ToolName string `json:"toolName"`
+ Providers []DubboProvider `json:"providers"`
+ Consumers []DubboConsumer `json:"consumers"`
+}
+
+func (o DubboServiceStatusOutput) Tool() string {
+ return o.ToolName
+}
+
+func dubboServiceStatus(ctx *ai.ToolContext, input DubboServiceStatusInput) (DubboServiceStatusOutput, error) {
+ log.Printf("Tool 'dubbo_service_status' called for service: %s", input.ServiceName)
+
+ return DubboServiceStatusOutput{
+ ToolName: "dubbo_service_status",
+ Providers: []DubboProvider{
+ {IP: "192.168.1.10", Port: 20880, Status: "healthy"},
+ {IP: "192.168.1.11", Port: 20880, Status: "healthy"},
+ },
+ Consumers: []DubboConsumer{
+ {IP: "192.168.1.20", Application: "web-frontend", Status: "connected"},
+ {IP: "192.168.1.21", Application: "api-gateway", Status: "connected"},
+ },
+ }, nil
+}
+
+// ================================================
+// Query Log Database Tool
+// ================================================
+
+type QueryLogDatabaseInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Keyword string `json:"keyword" jsonschema:"required,description=Keyword to search for"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LogEntry struct {
+ Timestamp string `json:"timestamp"`
+ Level string `json:"level"`
+ Message string `json:"message"`
+}
+
+type QueryLogDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ TotalHits int `json:"totalHits"`
+ Logs []LogEntry `json:"logs"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryLogDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryLogDatabase(ctx *ai.ToolContext, input QueryLogDatabaseInput) (QueryLogDatabaseOutput, error) {
+ log.Printf("Tool 'query_log_database' called for service: %s, keyword: %s", input.ServiceName, input.Keyword)
+
+ return QueryLogDatabaseOutput{
+ ToolName: "query_log_database",
+ TotalHits: 152,
+ Logs: []LogEntry{
+ {
+ Timestamp: "2025-08-16T15:32:05Z",
+ Level: "WARN",
+ Message: "Timeout waiting for idle object in database connection pool.",
+ },
+ {
+ Timestamp: "2025-08-16T15:32:08Z",
+ Level: "WARN",
+ Message: "Timeout waiting for idle object in database connection pool.",
+ },
+ },
+ Summary: fmt.Sprintf("在过去%d分钟内，发现 152 条关于 '%s' 的日志条目", input.TimeRangeMinutes, input.Keyword),
+ }, nil
+}
+
+// ================================================
+// Search Archived Logs Tool
+// ================================================
+
+type SearchArchivedLogsInput struct {
+ FilePathPattern string `json:"filePathPattern" jsonschema:"required,description=File path pattern to search"`
+ GrepKeyword string `json:"grepKeyword" jsonschema:"required,description=Keyword to grep for"`
+}
+
+type MatchingLine struct {
+ FilePath string `json:"filePath"`
+ LineNumber int `json:"lineNumber"`
+ LineContent string `json:"lineContent"`
+}
+
+type SearchArchivedLogsOutput struct {
+ ToolName string `json:"toolName"`
+ FilesSearched int `json:"filesSearched"`
+ MatchingLines []MatchingLine `json:"matchingLines"`
+ Summary string `json:"summary"`
+}
+
+func (o SearchArchivedLogsOutput) Tool() string {
+ return o.ToolName
+}
+
+func searchArchivedLogs(ctx *ai.ToolContext, input SearchArchivedLogsInput) (SearchArchivedLogsOutput, error) {
+ log.Printf("Tool 'search_archived_logs' called with pattern: %s, keyword: %s", input.FilePathPattern, input.GrepKeyword)
+
+ return SearchArchivedLogsOutput{
+ ToolName: "search_archived_logs",
+ FilesSearched: 5,
+ MatchingLines: []MatchingLine{
+ {
+ FilePath: "/logs/mysql-orders-db/slow-query-2025-08-16.log.gz",
+ LineNumber: 1024,
+ LineContent: "Query_time: 25.3s | SELECT COUNT(id), SUM(price) FROM orders WHERE user_id = 'VIP_USER_123';",
+ },
+ {
+ FilePath: "/logs/mysql-orders-db/slow-query-2025-08-16.log.gz",
+ LineNumber: 1029,
+ LineContent: "Query_time: 28.1s | SELECT COUNT(id), SUM(price) FROM orders WHERE user_id = 'VIP_USER_456';",
Review Comment:
The mock SQL queries contain hardcoded user IDs that could be considered sensitive information. Even in mock data, consider using anonymized or clearly fictional identifiers to avoid potential security concerns.
```suggestion
LineContent: "Query_time: 25.3s | SELECT COUNT(id), SUM(price) FROM orders WHERE user_id = 'USER_X';",
},
{
FilePath: "/logs/mysql-orders-db/slow-query-2025-08-16.log.gz",
LineNumber: 1029,
LineContent: "Query_time: 28.1s | SELECT COUNT(id), SUM(price) FROM orders WHERE user_id = 'USER_Y';",
```
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+ }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+ ToolName string `json:"toolName"`
+ RequestRateQPS float64 `json:"requestRateQPS"`
+ ErrorRatePercentage float64 `json:"errorRatePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_traffic' called for service: %s", input.ServiceName)
+
+ return PrometheusServiceTrafficOutput{
+ ToolName: "prometheus_query_service_traffic",
+ RequestRateQPS: 250.0,
+ ErrorRatePercentage: 5.2,
+ Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
+ }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+ PromqlQuery string `json:"promqlQuery" jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+ Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+ Timestamp int64 `json:"timestamp"`
+ Value string `json:"value"`
+}
+
+type TimeseriesResult struct {
+ Metric TimeseriesMetric `json:"metric"`
+ Value TimeseriesValue `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ Query string `json:"query"`
+ Results []TimeseriesResult `json:"results"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+ log.Printf("Tool 'query_timeseries_database' called with query: %s", input.PromqlQuery)
+
+ return QueryTimeseriesDatabaseOutput{
+ ToolName: "query_timeseries_database",
+ Query: input.PromqlQuery,
+ Results: []TimeseriesResult{
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-1"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.5"},
+ },
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-2"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.2"},
+ },
+ },
+ Summary: "查询返回了 2 个时间序列",
+ }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to profile"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to profile"`
+ DurationSeconds int `json:"durationSeconds" jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+ CPUTimePercentage float64 `json:"cpuTimePercentage"`
+ StackTrace []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+ ToolName string `json:"toolName"`
+ Status string `json:"status"`
+ TotalSamples int `json:"totalSamples"`
+ Hotspots []PerformanceHotspot `json:"hotspots"`
+ Summary string `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+ return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, error) {
+ log.Printf("Tool 'application_performance_profiling' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return ApplicationPerformanceProfilingOutput{
+ ToolName: "application_performance_profiling",
+ Status: "completed",
+ TotalSamples: 10000,
+ Hotspots: []PerformanceHotspot{
+ {
+ CPUTimePercentage: 45.5,
+ StackTrace: []string{
+ "com.example.OrderService.processOrder()",
+ "com.example.DatabaseClient.query()",
+ "java.sql.PreparedStatement.executeQuery()",
+ },
+ },
+ },
+ Summary: "性能分析显示，45.5%的CPU时间消耗在数据库查询调用链上",
+ }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Java service to analyze"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ FullGcCountLastHour int `json:"fullGcCountLastHour"`
+ FullGcTimeAvgMillis int `json:"fullGcTimeAvgMillis"`
+ HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+ log.Printf("Tool 'jvm_performance_analysis' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return JVMPerformanceAnalysisOutput{
+ ToolName: "jvm_performance_analysis",
+ FullGcCountLastHour: 15,
+ FullGcTimeAvgMillis: 1200,
+ HeapUsagePercentage: 85.5,
+ Summary: "GC activity is high, average Full GC time is 1200ms",
+ }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+ ToolName string `json:"toolName"`
+ UpstreamServices []string `json:"upstreamServices"`
+ DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) (TraceDependencyViewOutput, error) {
+ log.Printf("Tool 'trace_dependency_view' called for service: %s", input.ServiceName)
+
+ return TraceDependencyViewOutput{
+ ToolName: "trace_dependency_view",
+ UpstreamServices: []string{"api-gateway", "user-service"},
+ DownstreamServices: []string{"mysql-orders-db", "redis-cache", "payment-service"},
+ }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+ DownstreamService string `json:"downstreamService"`
+ LatencyAvgMillis int `json:"latencyAvgMillis"`
+ ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ TotalLatencyAvgMillis int `json:"totalLatencyAvgMillis"`
+ Bottlenecks []LatencyBottleneck `json:"bottlenecks"`
+ Summary string `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+ log.Printf("Tool 'trace_latency_analysis' called for service: %s", input.ServiceName)
+
+ return TraceLatencyAnalysisOutput{
+ ToolName: "trace_latency_analysis",
+ TotalLatencyAvgMillis: 3200,
+ Bottlenecks: []LatencyBottleneck{
+ {
+ DownstreamService: "mysql-orders-db",
+ LatencyAvgMillis: 3050,
+ ContributionPercentage: 95.3,
+ },
+ {
+ DownstreamService: "user-service",
+ LatencyAvgMillis: 150,
+ ContributionPercentage: 4.7,
+ },
+ },
+ Summary: "平均总延迟为 3200ms。瓶颈已定位，95.3% 的延迟来自对下游 'mysql-orders-db' 的调用",
+ }, nil
+}
+
+// ================================================
+// Database Connection Pool Analysis Tool
+// ================================================
+
+type DatabaseConnectionPoolAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+}
+
+type DatabaseConnectionPoolAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ MaxConnections int `json:"maxConnections"`
+ ActiveConnections int `json:"activeConnections"`
+ IdleConnections int `json:"idleConnections"`
+ PendingRequests int `json:"pendingRequests"`
+ Summary string `json:"summary"`
+}
+
+func (o DatabaseConnectionPoolAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func databaseConnectionPoolAnalysis(ctx *ai.ToolContext, input DatabaseConnectionPoolAnalysisInput) (DatabaseConnectionPoolAnalysisOutput, error) {
+ log.Printf("Tool 'database_connection_pool_analysis' called for service: %s", input.ServiceName)
+
+ return DatabaseConnectionPoolAnalysisOutput{
+ ToolName: "database_connection_pool_analysis",
+ MaxConnections: 100,
+ ActiveConnections: 100,
+ IdleConnections: 0,
+ PendingRequests: 58,
+ Summary: "数据库连接池已完全耗尽 (100/100)，当前有 58 个请求正在排队等待连接",
+ }, nil
+}
+
+// ================================================
+// Kubernetes Get Pod Resources Tool
+// ================================================
+
+type KubernetesGetPodResourcesInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Namespace string `json:"namespace" jsonschema:"required,description=The namespace of the service"`
+}
+
+type PodResource struct {
+ PodName string `json:"podName"`
+ CPUUsageCores float64 `json:"cpuUsageCores"`
+ CPURequestCores float64 `json:"cpuRequestCores"`
+ CPULimitCores float64 `json:"cpuLimitCores"`
+ MemoryUsageMi int `json:"memoryUsageMi"`
+ MemoryRequestMi int `json:"memoryRequestMi"`
+ MemoryLimitMi int `json:"memoryLimitMi"`
+}
+
+type KubernetesGetPodResourcesOutput struct {
+ ToolName string `json:"toolName"`
+ Pods []PodResource `json:"pods"`
+ Summary string `json:"summary"`
+}
+
+func (o KubernetesGetPodResourcesOutput) Tool() string {
+ return o.ToolName
+}
+
+func kubernetesGetPodResources(ctx *ai.ToolContext, input KubernetesGetPodResourcesInput) (KubernetesGetPodResourcesOutput, error) {
+ log.Printf("Tool 'kubernetes_get_pod_resources' called for service: %s in namespace: %s", input.ServiceName, input.Namespace)
+
+ return KubernetesGetPodResourcesOutput{
+ ToolName: "kubernetes_get_pod_resources",
+ Pods: []PodResource{
+ {
+ PodName: "order-service-pod-1",
+ CPUUsageCores: 0.8,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1800,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ {
+ PodName: "order-service-pod-2",
+ CPUUsageCores: 0.9,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1950,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ },
+ Summary: "2 out of 2 pods are near their memory limits",
+ }, nil
+}
+
+// ================================================
+// Dubbo Service Status Tool
+// ================================================
+
+type DubboServiceStatusInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Dubbo service"`
+}
+
+type DubboProvider struct {
+ IP string `json:"ip"`
+ Port int `json:"port"`
+ Status string `json:"status"`
+}
+
+type DubboConsumer struct {
+ IP string `json:"ip"`
+ Application string `json:"application"`
+ Status string `json:"status"`
+}
+
+type DubboServiceStatusOutput struct {
+ ToolName string `json:"toolName"`
+ Providers []DubboProvider `json:"providers"`
+ Consumers []DubboConsumer `json:"consumers"`
+}
+
+func (o DubboServiceStatusOutput) Tool() string {
+ return o.ToolName
+}
+
+func dubboServiceStatus(ctx *ai.ToolContext, input DubboServiceStatusInput) (DubboServiceStatusOutput, error) {
+ log.Printf("Tool 'dubbo_service_status' called for service: %s", input.ServiceName)
+
+ return DubboServiceStatusOutput{
+ ToolName: "dubbo_service_status",
+ Providers: []DubboProvider{
+ {IP: "192.168.1.10", Port: 20880, Status: "healthy"},
+ {IP: "192.168.1.11", Port: 20880, Status: "healthy"},
+ },
+ Consumers: []DubboConsumer{
+ {IP: "192.168.1.20", Application: "web-frontend", Status: "connected"},
+ {IP: "192.168.1.21", Application: "api-gateway", Status: "connected"},
+ },
+ }, nil
+}
+
+// ================================================
+// Query Log Database Tool
+// ================================================
+
+type QueryLogDatabaseInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Keyword string `json:"keyword" jsonschema:"required,description=Keyword to search for"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LogEntry struct {
+ Timestamp string `json:"timestamp"`
+ Level string `json:"level"`
+ Message string `json:"message"`
+}
+
+type QueryLogDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ TotalHits int `json:"totalHits"`
+ Logs []LogEntry `json:"logs"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryLogDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryLogDatabase(ctx *ai.ToolContext, input QueryLogDatabaseInput) (QueryLogDatabaseOutput, error) {
+ log.Printf("Tool 'query_log_database' called for service: %s, keyword: %s", input.ServiceName, input.Keyword)
+
+ return QueryLogDatabaseOutput{
+ ToolName: "query_log_database",
+ TotalHits: 152,
+ Logs: []LogEntry{
+ {
+ Timestamp: "2025-08-16T15:32:05Z",
+ Level: "WARN",
+ Message: "Timeout waiting for idle object in database connection pool.",
+ },
+ {
+ Timestamp: "2025-08-16T15:32:08Z",
+ Level: "WARN",
+ Message: "Timeout waiting for idle object in database connection pool.",
+ },
+ },
+ Summary: fmt.Sprintf("在过去%d分钟内，发现 152 条关于 '%s' 的日志条目", input.TimeRangeMinutes, input.Keyword),
+ }, nil
+}
+
+// ================================================
+// Search Archived Logs Tool
+// ================================================
+
+type SearchArchivedLogsInput struct {
+ FilePathPattern string `json:"filePathPattern" jsonschema:"required,description=File path pattern to search"`
+ GrepKeyword string `json:"grepKeyword" jsonschema:"required,description=Keyword to grep for"`
+}
+
+type MatchingLine struct {
+ FilePath string `json:"filePath"`
+ LineNumber int `json:"lineNumber"`
+ LineContent string `json:"lineContent"`
+}
+
+type SearchArchivedLogsOutput struct {
+ ToolName string `json:"toolName"`
+ FilesSearched int `json:"filesSearched"`
+ MatchingLines []MatchingLine `json:"matchingLines"`
+ Summary string `json:"summary"`
+}
+
+func (o SearchArchivedLogsOutput) Tool() string {
+ return o.ToolName
+}
+
+func searchArchivedLogs(ctx *ai.ToolContext, input SearchArchivedLogsInput) (SearchArchivedLogsOutput, error) {
+ log.Printf("Tool 'search_archived_logs' called with pattern: %s, keyword: %s", input.FilePathPattern, input.GrepKeyword)
+
+ return SearchArchivedLogsOutput{
+ ToolName: "search_archived_logs",
+ FilesSearched: 5,
+ MatchingLines: []MatchingLine{
+ {
+ FilePath: "/logs/mysql-orders-db/slow-query-2025-08-16.log.gz",
+ LineNumber: 1024,
+ LineContent: "Query_time: 25.3s | SELECT COUNT(id), SUM(price) FROM orders WHERE user_id = 'VIP_USER_123';",
+ },
+ {
+ FilePath: "/logs/mysql-orders-db/slow-query-2025-08-16.log.gz",
+ LineNumber: 1029,
+ LineContent: "Query_time: 28.1s | SELECT COUNT(id), SUM(price) FROM orders WHERE user_id = 'VIP_USER_456';",
Review Comment:
The mock SQL queries contain hardcoded user IDs that could be considered sensitive information. Even in mock data, consider using anonymized or clearly fictional identifiers to avoid potential security concerns.
```suggestion
LineContent: "Query_time: 25.3s | SELECT COUNT(id), SUM(price) FROM orders WHERE user_id = 'USER_001';",
},
{
FilePath: "/logs/mysql-orders-db/slow-query-2025-08-16.log.gz",
LineNumber: 1029,
LineContent: "Query_time: 28.1s | SELECT COUNT(id), SUM(price) FROM orders WHERE user_id = 'USER_002';",
```
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Re: [PR] [feat]: Integrating AI Agent Capabilities into dubbo-admin [dubbo-admin]
Posted by "Copilot (via GitHub)" <gi...@apache.org>.
Copilot commented on code in PR #1319:
URL: https://github.com/apache/dubbo-admin/pull/1319#discussion_r2314122132
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+ }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+ ToolName string `json:"toolName"`
+ RequestRateQPS float64 `json:"requestRateQPS"`
+ ErrorRatePercentage float64 `json:"errorRatePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_traffic' called for service: %s", input.ServiceName)
+
+ return PrometheusServiceTrafficOutput{
+ ToolName: "prometheus_query_service_traffic",
+ RequestRateQPS: 250.0,
+ ErrorRatePercentage: 5.2,
+ Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
+ }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+ PromqlQuery string `json:"promqlQuery" jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+ Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+ Timestamp int64 `json:"timestamp"`
+ Value string `json:"value"`
+}
+
+type TimeseriesResult struct {
+ Metric TimeseriesMetric `json:"metric"`
+ Value TimeseriesValue `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ Query string `json:"query"`
+ Results []TimeseriesResult `json:"results"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+ log.Printf("Tool 'query_timeseries_database' called with query: %s", input.PromqlQuery)
+
+ return QueryTimeseriesDatabaseOutput{
+ ToolName: "query_timeseries_database",
+ Query: input.PromqlQuery,
+ Results: []TimeseriesResult{
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-1"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.5"},
+ },
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-2"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.2"},
+ },
+ },
+ Summary: "查询返回了 2 个时间序列",
+ }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to profile"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to profile"`
+ DurationSeconds int `json:"durationSeconds" jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+ CPUTimePercentage float64 `json:"cpuTimePercentage"`
+ StackTrace []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+ ToolName string `json:"toolName"`
+ Status string `json:"status"`
+ TotalSamples int `json:"totalSamples"`
+ Hotspots []PerformanceHotspot `json:"hotspots"`
+ Summary string `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+ return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, error) {
+ log.Printf("Tool 'application_performance_profiling' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return ApplicationPerformanceProfilingOutput{
+ ToolName: "application_performance_profiling",
+ Status: "completed",
+ TotalSamples: 10000,
+ Hotspots: []PerformanceHotspot{
+ {
+ CPUTimePercentage: 45.5,
+ StackTrace: []string{
+ "com.example.OrderService.processOrder()",
+ "com.example.DatabaseClient.query()",
+ "java.sql.PreparedStatement.executeQuery()",
+ },
+ },
+ },
+ Summary: "性能分析显示，45.5%的CPU时间消耗在数据库查询调用链上",
+ }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Java service to analyze"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ FullGcCountLastHour int `json:"fullGcCountLastHour"`
+ FullGcTimeAvgMillis int `json:"fullGcTimeAvgMillis"`
+ HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+ log.Printf("Tool 'jvm_performance_analysis' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return JVMPerformanceAnalysisOutput{
+ ToolName: "jvm_performance_analysis",
+ FullGcCountLastHour: 15,
+ FullGcTimeAvgMillis: 1200,
+ HeapUsagePercentage: 85.5,
+ Summary: "GC activity is high, average Full GC time is 1200ms",
+ }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+ ToolName string `json:"toolName"`
+ UpstreamServices []string `json:"upstreamServices"`
+ DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) (TraceDependencyViewOutput, error) {
+ log.Printf("Tool 'trace_dependency_view' called for service: %s", input.ServiceName)
+
+ return TraceDependencyViewOutput{
+ ToolName: "trace_dependency_view",
+ UpstreamServices: []string{"api-gateway", "user-service"},
+ DownstreamServices: []string{"mysql-orders-db", "redis-cache", "payment-service"},
+ }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+ DownstreamService string `json:"downstreamService"`
+ LatencyAvgMillis int `json:"latencyAvgMillis"`
+ ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ TotalLatencyAvgMillis int `json:"totalLatencyAvgMillis"`
+ Bottlenecks []LatencyBottleneck `json:"bottlenecks"`
+ Summary string `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+ log.Printf("Tool 'trace_latency_analysis' called for service: %s", input.ServiceName)
+
+ return TraceLatencyAnalysisOutput{
+ ToolName: "trace_latency_analysis",
+ TotalLatencyAvgMillis: 3200,
+ Bottlenecks: []LatencyBottleneck{
+ {
+ DownstreamService: "mysql-orders-db",
+ LatencyAvgMillis: 3050,
+ ContributionPercentage: 95.3,
+ },
+ {
+ DownstreamService: "user-service",
+ LatencyAvgMillis: 150,
+ ContributionPercentage: 4.7,
+ },
+ },
+ Summary: "平均总延迟为 3200ms。瓶颈已定位，95.3% 的延迟来自对下游 'mysql-orders-db' 的调用",
+ }, nil
+}
+
+// ================================================
+// Database Connection Pool Analysis Tool
+// ================================================
+
+type DatabaseConnectionPoolAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+}
+
+type DatabaseConnectionPoolAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ MaxConnections int `json:"maxConnections"`
+ ActiveConnections int `json:"activeConnections"`
+ IdleConnections int `json:"idleConnections"`
+ PendingRequests int `json:"pendingRequests"`
+ Summary string `json:"summary"`
+}
+
+func (o DatabaseConnectionPoolAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func databaseConnectionPoolAnalysis(ctx *ai.ToolContext, input DatabaseConnectionPoolAnalysisInput) (DatabaseConnectionPoolAnalysisOutput, error) {
+ log.Printf("Tool 'database_connection_pool_analysis' called for service: %s", input.ServiceName)
+
+ return DatabaseConnectionPoolAnalysisOutput{
+ ToolName: "database_connection_pool_analysis",
+ MaxConnections: 100,
+ ActiveConnections: 100,
+ IdleConnections: 0,
+ PendingRequests: 58,
+ Summary: "数据库连接池已完全耗尽 (100/100)，当前有 58 个请求正在排队等待连接",
+ }, nil
+}
+
+// ================================================
+// Kubernetes Get Pod Resources Tool
+// ================================================
+
+type KubernetesGetPodResourcesInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Namespace string `json:"namespace" jsonschema:"required,description=The namespace of the service"`
+}
+
+type PodResource struct {
+ PodName string `json:"podName"`
+ CPUUsageCores float64 `json:"cpuUsageCores"`
+ CPURequestCores float64 `json:"cpuRequestCores"`
+ CPULimitCores float64 `json:"cpuLimitCores"`
+ MemoryUsageMi int `json:"memoryUsageMi"`
+ MemoryRequestMi int `json:"memoryRequestMi"`
+ MemoryLimitMi int `json:"memoryLimitMi"`
+}
+
+type KubernetesGetPodResourcesOutput struct {
+ ToolName string `json:"toolName"`
+ Pods []PodResource `json:"pods"`
+ Summary string `json:"summary"`
+}
+
+func (o KubernetesGetPodResourcesOutput) Tool() string {
+ return o.ToolName
+}
+
+func kubernetesGetPodResources(ctx *ai.ToolContext, input KubernetesGetPodResourcesInput) (KubernetesGetPodResourcesOutput, error) {
+ log.Printf("Tool 'kubernetes_get_pod_resources' called for service: %s in namespace: %s", input.ServiceName, input.Namespace)
+
+ return KubernetesGetPodResourcesOutput{
+ ToolName: "kubernetes_get_pod_resources",
+ Pods: []PodResource{
+ {
+ PodName: "order-service-pod-1",
+ CPUUsageCores: 0.8,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1800,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ {
+ PodName: "order-service-pod-2",
+ CPUUsageCores: 0.9,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1950,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ },
+ Summary: "2 out of 2 pods are near their memory limits",
+ }, nil
+}
+
+// ================================================
+// Dubbo Service Status Tool
+// ================================================
+
+type DubboServiceStatusInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Dubbo service"`
+}
+
+type DubboProvider struct {
+ IP string `json:"ip"`
+ Port int `json:"port"`
+ Status string `json:"status"`
+}
+
+type DubboConsumer struct {
+ IP string `json:"ip"`
+ Application string `json:"application"`
+ Status string `json:"status"`
+}
+
+type DubboServiceStatusOutput struct {
+ ToolName string `json:"toolName"`
+ Providers []DubboProvider `json:"providers"`
+ Consumers []DubboConsumer `json:"consumers"`
+}
+
+func (o DubboServiceStatusOutput) Tool() string {
+ return o.ToolName
+}
+
+func dubboServiceStatus(ctx *ai.ToolContext, input DubboServiceStatusInput) (DubboServiceStatusOutput, error) {
+ log.Printf("Tool 'dubbo_service_status' called for service: %s", input.ServiceName)
+
+ return DubboServiceStatusOutput{
+ ToolName: "dubbo_service_status",
+ Providers: []DubboProvider{
+ {IP: "192.168.1.10", Port: 20880, Status: "healthy"},
+ {IP: "192.168.1.11", Port: 20880, Status: "healthy"},
+ },
+ Consumers: []DubboConsumer{
+ {IP: "192.168.1.20", Application: "web-frontend", Status: "connected"},
+ {IP: "192.168.1.21", Application: "api-gateway", Status: "connected"},
+ },
+ }, nil
+}
+
+// ================================================
+// Query Log Database Tool
+// ================================================
+
+type QueryLogDatabaseInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Keyword string `json:"keyword" jsonschema:"required,description=Keyword to search for"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LogEntry struct {
+ Timestamp string `json:"timestamp"`
+ Level string `json:"level"`
+ Message string `json:"message"`
+}
+
+type QueryLogDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ TotalHits int `json:"totalHits"`
+ Logs []LogEntry `json:"logs"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryLogDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryLogDatabase(ctx *ai.ToolContext, input QueryLogDatabaseInput) (QueryLogDatabaseOutput, error) {
+ log.Printf("Tool 'query_log_database' called for service: %s, keyword: %s", input.ServiceName, input.Keyword)
+
+ return QueryLogDatabaseOutput{
+ ToolName: "query_log_database",
+ TotalHits: 152,
+ Logs: []LogEntry{
+ {
+ Timestamp: "2025-08-16T15:32:05Z",
+ Level: "WARN",
+ Message: "Timeout waiting for idle object in database connection pool.",
+ },
+ {
+ Timestamp: "2025-08-16T15:32:08Z",
Review Comment:
The hardcoded timestamps reference August 2025, which may be confusing since the current date context is September 2025. Consider using relative timestamps or the current date range for more realistic mock data.
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+ }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+ ToolName string `json:"toolName"`
+ RequestRateQPS float64 `json:"requestRateQPS"`
+ ErrorRatePercentage float64 `json:"errorRatePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_traffic' called for service: %s", input.ServiceName)
+
+ return PrometheusServiceTrafficOutput{
+ ToolName: "prometheus_query_service_traffic",
+ RequestRateQPS: 250.0,
+ ErrorRatePercentage: 5.2,
+ Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
+ }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+ PromqlQuery string `json:"promqlQuery" jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+ Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+ Timestamp int64 `json:"timestamp"`
+ Value string `json:"value"`
+}
+
+type TimeseriesResult struct {
+ Metric TimeseriesMetric `json:"metric"`
+ Value TimeseriesValue `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ Query string `json:"query"`
+ Results []TimeseriesResult `json:"results"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+ log.Printf("Tool 'query_timeseries_database' called with query: %s", input.PromqlQuery)
+
+ return QueryTimeseriesDatabaseOutput{
+ ToolName: "query_timeseries_database",
+ Query: input.PromqlQuery,
+ Results: []TimeseriesResult{
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-1"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.5"},
+ },
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-2"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.2"},
+ },
+ },
+ Summary: "查询返回了 2 个时间序列",
+ }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to profile"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to profile"`
+ DurationSeconds int `json:"durationSeconds" jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+ CPUTimePercentage float64 `json:"cpuTimePercentage"`
+ StackTrace []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+ ToolName string `json:"toolName"`
+ Status string `json:"status"`
+ TotalSamples int `json:"totalSamples"`
+ Hotspots []PerformanceHotspot `json:"hotspots"`
+ Summary string `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+ return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, error) {
+ log.Printf("Tool 'application_performance_profiling' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return ApplicationPerformanceProfilingOutput{
+ ToolName: "application_performance_profiling",
+ Status: "completed",
+ TotalSamples: 10000,
+ Hotspots: []PerformanceHotspot{
+ {
+ CPUTimePercentage: 45.5,
+ StackTrace: []string{
+ "com.example.OrderService.processOrder()",
+ "com.example.DatabaseClient.query()",
+ "java.sql.PreparedStatement.executeQuery()",
+ },
+ },
+ },
+ Summary: "性能分析显示，45.5%的CPU时间消耗在数据库查询调用链上",
+ }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Java service to analyze"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ FullGcCountLastHour int `json:"fullGcCountLastHour"`
+ FullGcTimeAvgMillis int `json:"fullGcTimeAvgMillis"`
+ HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+ log.Printf("Tool 'jvm_performance_analysis' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return JVMPerformanceAnalysisOutput{
+ ToolName: "jvm_performance_analysis",
+ FullGcCountLastHour: 15,
+ FullGcTimeAvgMillis: 1200,
+ HeapUsagePercentage: 85.5,
+ Summary: "GC activity is high, average Full GC time is 1200ms",
+ }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+ ToolName string `json:"toolName"`
+ UpstreamServices []string `json:"upstreamServices"`
+ DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) (TraceDependencyViewOutput, error) {
+ log.Printf("Tool 'trace_dependency_view' called for service: %s", input.ServiceName)
+
+ return TraceDependencyViewOutput{
+ ToolName: "trace_dependency_view",
+ UpstreamServices: []string{"api-gateway", "user-service"},
+ DownstreamServices: []string{"mysql-orders-db", "redis-cache", "payment-service"},
+ }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+ DownstreamService string `json:"downstreamService"`
+ LatencyAvgMillis int `json:"latencyAvgMillis"`
+ ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ TotalLatencyAvgMillis int `json:"totalLatencyAvgMillis"`
+ Bottlenecks []LatencyBottleneck `json:"bottlenecks"`
+ Summary string `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+ log.Printf("Tool 'trace_latency_analysis' called for service: %s", input.ServiceName)
+
+ return TraceLatencyAnalysisOutput{
+ ToolName: "trace_latency_analysis",
+ TotalLatencyAvgMillis: 3200,
+ Bottlenecks: []LatencyBottleneck{
+ {
+ DownstreamService: "mysql-orders-db",
+ LatencyAvgMillis: 3050,
+ ContributionPercentage: 95.3,
+ },
+ {
+ DownstreamService: "user-service",
+ LatencyAvgMillis: 150,
+ ContributionPercentage: 4.7,
+ },
+ },
+ Summary: "平均总延迟为 3200ms。瓶颈已定位，95.3% 的延迟来自对下游 'mysql-orders-db' 的调用",
+ }, nil
+}
+
+// ================================================
+// Database Connection Pool Analysis Tool
+// ================================================
+
+type DatabaseConnectionPoolAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+}
+
+type DatabaseConnectionPoolAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ MaxConnections int `json:"maxConnections"`
+ ActiveConnections int `json:"activeConnections"`
+ IdleConnections int `json:"idleConnections"`
+ PendingRequests int `json:"pendingRequests"`
+ Summary string `json:"summary"`
+}
+
+func (o DatabaseConnectionPoolAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func databaseConnectionPoolAnalysis(ctx *ai.ToolContext, input DatabaseConnectionPoolAnalysisInput) (DatabaseConnectionPoolAnalysisOutput, error) {
+ log.Printf("Tool 'database_connection_pool_analysis' called for service: %s", input.ServiceName)
+
+ return DatabaseConnectionPoolAnalysisOutput{
+ ToolName: "database_connection_pool_analysis",
+ MaxConnections: 100,
+ ActiveConnections: 100,
+ IdleConnections: 0,
+ PendingRequests: 58,
+ Summary: "数据库连接池已完全耗尽 (100/100)，当前有 58 个请求正在排队等待连接",
+ }, nil
+}
+
+// ================================================
+// Kubernetes Get Pod Resources Tool
+// ================================================
+
+type KubernetesGetPodResourcesInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Namespace string `json:"namespace" jsonschema:"required,description=The namespace of the service"`
+}
+
+type PodResource struct {
+ PodName string `json:"podName"`
+ CPUUsageCores float64 `json:"cpuUsageCores"`
+ CPURequestCores float64 `json:"cpuRequestCores"`
+ CPULimitCores float64 `json:"cpuLimitCores"`
+ MemoryUsageMi int `json:"memoryUsageMi"`
+ MemoryRequestMi int `json:"memoryRequestMi"`
+ MemoryLimitMi int `json:"memoryLimitMi"`
+}
+
+type KubernetesGetPodResourcesOutput struct {
+ ToolName string `json:"toolName"`
+ Pods []PodResource `json:"pods"`
+ Summary string `json:"summary"`
+}
+
+func (o KubernetesGetPodResourcesOutput) Tool() string {
+ return o.ToolName
+}
+
+func kubernetesGetPodResources(ctx *ai.ToolContext, input KubernetesGetPodResourcesInput) (KubernetesGetPodResourcesOutput, error) {
+ log.Printf("Tool 'kubernetes_get_pod_resources' called for service: %s in namespace: %s", input.ServiceName, input.Namespace)
+
+ return KubernetesGetPodResourcesOutput{
+ ToolName: "kubernetes_get_pod_resources",
+ Pods: []PodResource{
+ {
+ PodName: "order-service-pod-1",
+ CPUUsageCores: 0.8,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1800,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ {
+ PodName: "order-service-pod-2",
+ CPUUsageCores: 0.9,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1950,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ },
+ Summary: "2 out of 2 pods are near their memory limits",
+ }, nil
+}
+
+// ================================================
+// Dubbo Service Status Tool
+// ================================================
+
+type DubboServiceStatusInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Dubbo service"`
+}
+
+type DubboProvider struct {
+ IP string `json:"ip"`
+ Port int `json:"port"`
+ Status string `json:"status"`
+}
+
+type DubboConsumer struct {
+ IP string `json:"ip"`
+ Application string `json:"application"`
+ Status string `json:"status"`
+}
+
+type DubboServiceStatusOutput struct {
+ ToolName string `json:"toolName"`
+ Providers []DubboProvider `json:"providers"`
+ Consumers []DubboConsumer `json:"consumers"`
+}
+
+func (o DubboServiceStatusOutput) Tool() string {
+ return o.ToolName
+}
+
+func dubboServiceStatus(ctx *ai.ToolContext, input DubboServiceStatusInput) (DubboServiceStatusOutput, error) {
+ log.Printf("Tool 'dubbo_service_status' called for service: %s", input.ServiceName)
+
+ return DubboServiceStatusOutput{
+ ToolName: "dubbo_service_status",
+ Providers: []DubboProvider{
+ {IP: "192.168.1.10", Port: 20880, Status: "healthy"},
+ {IP: "192.168.1.11", Port: 20880, Status: "healthy"},
+ },
+ Consumers: []DubboConsumer{
+ {IP: "192.168.1.20", Application: "web-frontend", Status: "connected"},
+ {IP: "192.168.1.21", Application: "api-gateway", Status: "connected"},
+ },
+ }, nil
+}
+
+// ================================================
+// Query Log Database Tool
+// ================================================
+
+type QueryLogDatabaseInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Keyword string `json:"keyword" jsonschema:"required,description=Keyword to search for"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LogEntry struct {
+ Timestamp string `json:"timestamp"`
+ Level string `json:"level"`
+ Message string `json:"message"`
+}
+
+type QueryLogDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ TotalHits int `json:"totalHits"`
+ Logs []LogEntry `json:"logs"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryLogDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryLogDatabase(ctx *ai.ToolContext, input QueryLogDatabaseInput) (QueryLogDatabaseOutput, error) {
+ log.Printf("Tool 'query_log_database' called for service: %s, keyword: %s", input.ServiceName, input.Keyword)
+
+ return QueryLogDatabaseOutput{
+ ToolName: "query_log_database",
+ TotalHits: 152,
+ Logs: []LogEntry{
+ {
+ Timestamp: "2025-08-16T15:32:05Z",
Review Comment:
The hardcoded timestamps reference August 2025, which may be confusing since the current date context is September 2025. Consider using relative timestamps or the current date range for more realistic mock data.
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+ }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+ ToolName string `json:"toolName"`
+ RequestRateQPS float64 `json:"requestRateQPS"`
+ ErrorRatePercentage float64 `json:"errorRatePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_traffic' called for service: %s", input.ServiceName)
+
+ return PrometheusServiceTrafficOutput{
+ ToolName: "prometheus_query_service_traffic",
+ RequestRateQPS: 250.0,
+ ErrorRatePercentage: 5.2,
+ Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
+ }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+ PromqlQuery string `json:"promqlQuery" jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+ Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+ Timestamp int64 `json:"timestamp"`
+ Value string `json:"value"`
+}
+
+type TimeseriesResult struct {
+ Metric TimeseriesMetric `json:"metric"`
+ Value TimeseriesValue `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ Query string `json:"query"`
+ Results []TimeseriesResult `json:"results"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+ log.Printf("Tool 'query_timeseries_database' called with query: %s", input.PromqlQuery)
+
+ return QueryTimeseriesDatabaseOutput{
+ ToolName: "query_timeseries_database",
+ Query: input.PromqlQuery,
+ Results: []TimeseriesResult{
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-1"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.5"},
+ },
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-2"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.2"},
+ },
+ },
+ Summary: "查询返回了 2 个时间序列",
+ }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to profile"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to profile"`
+ DurationSeconds int `json:"durationSeconds" jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+ CPUTimePercentage float64 `json:"cpuTimePercentage"`
+ StackTrace []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+ ToolName string `json:"toolName"`
+ Status string `json:"status"`
+ TotalSamples int `json:"totalSamples"`
+ Hotspots []PerformanceHotspot `json:"hotspots"`
+ Summary string `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+ return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, error) {
+ log.Printf("Tool 'application_performance_profiling' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return ApplicationPerformanceProfilingOutput{
+ ToolName: "application_performance_profiling",
+ Status: "completed",
+ TotalSamples: 10000,
+ Hotspots: []PerformanceHotspot{
+ {
+ CPUTimePercentage: 45.5,
+ StackTrace: []string{
+ "com.example.OrderService.processOrder()",
+ "com.example.DatabaseClient.query()",
+ "java.sql.PreparedStatement.executeQuery()",
+ },
+ },
+ },
+ Summary: "性能分析显示，45.5%的CPU时间消耗在数据库查询调用链上",
+ }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Java service to analyze"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ FullGcCountLastHour int `json:"fullGcCountLastHour"`
+ FullGcTimeAvgMillis int `json:"fullGcTimeAvgMillis"`
+ HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+ log.Printf("Tool 'jvm_performance_analysis' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return JVMPerformanceAnalysisOutput{
+ ToolName: "jvm_performance_analysis",
+ FullGcCountLastHour: 15,
+ FullGcTimeAvgMillis: 1200,
+ HeapUsagePercentage: 85.5,
+ Summary: "GC activity is high, average Full GC time is 1200ms",
+ }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+ ToolName string `json:"toolName"`
+ UpstreamServices []string `json:"upstreamServices"`
+ DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) (TraceDependencyViewOutput, error) {
+ log.Printf("Tool 'trace_dependency_view' called for service: %s", input.ServiceName)
+
+ return TraceDependencyViewOutput{
+ ToolName: "trace_dependency_view",
+ UpstreamServices: []string{"api-gateway", "user-service"},
+ DownstreamServices: []string{"mysql-orders-db", "redis-cache", "payment-service"},
+ }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+ DownstreamService string `json:"downstreamService"`
+ LatencyAvgMillis int `json:"latencyAvgMillis"`
+ ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ TotalLatencyAvgMillis int `json:"totalLatencyAvgMillis"`
+ Bottlenecks []LatencyBottleneck `json:"bottlenecks"`
+ Summary string `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+ log.Printf("Tool 'trace_latency_analysis' called for service: %s", input.ServiceName)
+
+ return TraceLatencyAnalysisOutput{
+ ToolName: "trace_latency_analysis",
+ TotalLatencyAvgMillis: 3200,
+ Bottlenecks: []LatencyBottleneck{
+ {
+ DownstreamService: "mysql-orders-db",
+ LatencyAvgMillis: 3050,
+ ContributionPercentage: 95.3,
+ },
+ {
+ DownstreamService: "user-service",
+ LatencyAvgMillis: 150,
+ ContributionPercentage: 4.7,
+ },
+ },
+ Summary: "平均总延迟为 3200ms。瓶颈已定位，95.3% 的延迟来自对下游 'mysql-orders-db' 的调用",
+ }, nil
+}
+
+// ================================================
+// Database Connection Pool Analysis Tool
+// ================================================
+
+type DatabaseConnectionPoolAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+}
+
+type DatabaseConnectionPoolAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ MaxConnections int `json:"maxConnections"`
+ ActiveConnections int `json:"activeConnections"`
+ IdleConnections int `json:"idleConnections"`
+ PendingRequests int `json:"pendingRequests"`
+ Summary string `json:"summary"`
+}
+
+func (o DatabaseConnectionPoolAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func databaseConnectionPoolAnalysis(ctx *ai.ToolContext, input DatabaseConnectionPoolAnalysisInput) (DatabaseConnectionPoolAnalysisOutput, error) {
+ log.Printf("Tool 'database_connection_pool_analysis' called for service: %s", input.ServiceName)
+
+ return DatabaseConnectionPoolAnalysisOutput{
+ ToolName: "database_connection_pool_analysis",
+ MaxConnections: 100,
+ ActiveConnections: 100,
+ IdleConnections: 0,
+ PendingRequests: 58,
+ Summary: "数据库连接池已完全耗尽 (100/100)，当前有 58 个请求正在排队等待连接",
+ }, nil
+}
+
+// ================================================
+// Kubernetes Get Pod Resources Tool
+// ================================================
+
+type KubernetesGetPodResourcesInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Namespace string `json:"namespace" jsonschema:"required,description=The namespace of the service"`
+}
+
+type PodResource struct {
+ PodName string `json:"podName"`
+ CPUUsageCores float64 `json:"cpuUsageCores"`
+ CPURequestCores float64 `json:"cpuRequestCores"`
+ CPULimitCores float64 `json:"cpuLimitCores"`
+ MemoryUsageMi int `json:"memoryUsageMi"`
+ MemoryRequestMi int `json:"memoryRequestMi"`
+ MemoryLimitMi int `json:"memoryLimitMi"`
+}
+
+type KubernetesGetPodResourcesOutput struct {
+ ToolName string `json:"toolName"`
+ Pods []PodResource `json:"pods"`
+ Summary string `json:"summary"`
+}
+
+func (o KubernetesGetPodResourcesOutput) Tool() string {
+ return o.ToolName
+}
+
+func kubernetesGetPodResources(ctx *ai.ToolContext, input KubernetesGetPodResourcesInput) (KubernetesGetPodResourcesOutput, error) {
+ log.Printf("Tool 'kubernetes_get_pod_resources' called for service: %s in namespace: %s", input.ServiceName, input.Namespace)
+
+ return KubernetesGetPodResourcesOutput{
+ ToolName: "kubernetes_get_pod_resources",
+ Pods: []PodResource{
+ {
+ PodName: "order-service-pod-1",
+ CPUUsageCores: 0.8,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1800,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ {
+ PodName: "order-service-pod-2",
+ CPUUsageCores: 0.9,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1950,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ },
+ Summary: "2 out of 2 pods are near their memory limits",
+ }, nil
+}
+
+// ================================================
+// Dubbo Service Status Tool
+// ================================================
+
+type DubboServiceStatusInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Dubbo service"`
+}
+
+type DubboProvider struct {
+ IP string `json:"ip"`
+ Port int `json:"port"`
+ Status string `json:"status"`
+}
+
+type DubboConsumer struct {
+ IP string `json:"ip"`
+ Application string `json:"application"`
+ Status string `json:"status"`
+}
+
+type DubboServiceStatusOutput struct {
+ ToolName string `json:"toolName"`
+ Providers []DubboProvider `json:"providers"`
+ Consumers []DubboConsumer `json:"consumers"`
+}
+
+func (o DubboServiceStatusOutput) Tool() string {
+ return o.ToolName
+}
+
+func dubboServiceStatus(ctx *ai.ToolContext, input DubboServiceStatusInput) (DubboServiceStatusOutput, error) {
+ log.Printf("Tool 'dubbo_service_status' called for service: %s", input.ServiceName)
+
+ return DubboServiceStatusOutput{
+ ToolName: "dubbo_service_status",
+ Providers: []DubboProvider{
+ {IP: "192.168.1.10", Port: 20880, Status: "healthy"},
+ {IP: "192.168.1.11", Port: 20880, Status: "healthy"},
+ },
+ Consumers: []DubboConsumer{
+ {IP: "192.168.1.20", Application: "web-frontend", Status: "connected"},
+ {IP: "192.168.1.21", Application: "api-gateway", Status: "connected"},
+ },
+ }, nil
+}
+
+// ================================================
+// Query Log Database Tool
+// ================================================
+
+type QueryLogDatabaseInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Keyword string `json:"keyword" jsonschema:"required,description=Keyword to search for"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LogEntry struct {
+ Timestamp string `json:"timestamp"`
+ Level string `json:"level"`
+ Message string `json:"message"`
+}
+
+type QueryLogDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ TotalHits int `json:"totalHits"`
+ Logs []LogEntry `json:"logs"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryLogDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryLogDatabase(ctx *ai.ToolContext, input QueryLogDatabaseInput) (QueryLogDatabaseOutput, error) {
+ log.Printf("Tool 'query_log_database' called for service: %s, keyword: %s", input.ServiceName, input.Keyword)
+
+ return QueryLogDatabaseOutput{
+ ToolName: "query_log_database",
+ TotalHits: 152,
+ Logs: []LogEntry{
+ {
+ Timestamp: "2025-08-16T15:32:05Z",
+ Level: "WARN",
+ Message: "Timeout waiting for idle object in database connection pool.",
+ },
+ {
+ Timestamp: "2025-08-16T15:32:08Z",
+ Level: "WARN",
+ Message: "Timeout waiting for idle object in database connection pool.",
+ },
+ },
+ Summary: fmt.Sprintf("在过去%d分钟内，发现 152 条关于 '%s' 的日志条目", input.TimeRangeMinutes, input.Keyword),
+ }, nil
+}
+
+// ================================================
+// Search Archived Logs Tool
+// ================================================
+
+type SearchArchivedLogsInput struct {
+ FilePathPattern string `json:"filePathPattern" jsonschema:"required,description=File path pattern to search"`
+ GrepKeyword string `json:"grepKeyword" jsonschema:"required,description=Keyword to grep for"`
+}
+
+type MatchingLine struct {
+ FilePath string `json:"filePath"`
+ LineNumber int `json:"lineNumber"`
+ LineContent string `json:"lineContent"`
+}
+
+type SearchArchivedLogsOutput struct {
+ ToolName string `json:"toolName"`
+ FilesSearched int `json:"filesSearched"`
+ MatchingLines []MatchingLine `json:"matchingLines"`
+ Summary string `json:"summary"`
+}
+
+func (o SearchArchivedLogsOutput) Tool() string {
+ return o.ToolName
+}
+
+func searchArchivedLogs(ctx *ai.ToolContext, input SearchArchivedLogsInput) (SearchArchivedLogsOutput, error) {
+ log.Printf("Tool 'search_archived_logs' called with pattern: %s, keyword: %s", input.FilePathPattern, input.GrepKeyword)
+
+ return SearchArchivedLogsOutput{
+ ToolName: "search_archived_logs",
+ FilesSearched: 5,
+ MatchingLines: []MatchingLine{
+ {
+ FilePath: "/logs/mysql-orders-db/slow-query-2025-08-16.log.gz",
+ LineNumber: 1024,
+ LineContent: "Query_time: 25.3s | SELECT COUNT(id), SUM(price) FROM orders WHERE user_id = 'VIP_USER_123';",
Review Comment:
The hardcoded timestamps in mock data reference dates from August 2025. For consistency and to avoid confusion, consider using relative timestamps or current date ranges.
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+ }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+ ToolName string `json:"toolName"`
+ RequestRateQPS float64 `json:"requestRateQPS"`
+ ErrorRatePercentage float64 `json:"errorRatePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_traffic' called for service: %s", input.ServiceName)
+
+ return PrometheusServiceTrafficOutput{
+ ToolName: "prometheus_query_service_traffic",
+ RequestRateQPS: 250.0,
+ ErrorRatePercentage: 5.2,
+ Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
+ }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+ PromqlQuery string `json:"promqlQuery" jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+ Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+ Timestamp int64 `json:"timestamp"`
+ Value string `json:"value"`
+}
+
+type TimeseriesResult struct {
+ Metric TimeseriesMetric `json:"metric"`
+ Value TimeseriesValue `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ Query string `json:"query"`
+ Results []TimeseriesResult `json:"results"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+ log.Printf("Tool 'query_timeseries_database' called with query: %s", input.PromqlQuery)
+
+ return QueryTimeseriesDatabaseOutput{
+ ToolName: "query_timeseries_database",
+ Query: input.PromqlQuery,
+ Results: []TimeseriesResult{
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-1"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.5"},
+ },
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-2"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.2"},
+ },
+ },
+ Summary: "查询返回了 2 个时间序列",
+ }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to profile"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to profile"`
+ DurationSeconds int `json:"durationSeconds" jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+ CPUTimePercentage float64 `json:"cpuTimePercentage"`
+ StackTrace []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+ ToolName string `json:"toolName"`
+ Status string `json:"status"`
+ TotalSamples int `json:"totalSamples"`
+ Hotspots []PerformanceHotspot `json:"hotspots"`
+ Summary string `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+ return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, error) {
+ log.Printf("Tool 'application_performance_profiling' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return ApplicationPerformanceProfilingOutput{
+ ToolName: "application_performance_profiling",
+ Status: "completed",
+ TotalSamples: 10000,
+ Hotspots: []PerformanceHotspot{
+ {
+ CPUTimePercentage: 45.5,
+ StackTrace: []string{
+ "com.example.OrderService.processOrder()",
+ "com.example.DatabaseClient.query()",
+ "java.sql.PreparedStatement.executeQuery()",
+ },
+ },
+ },
+ Summary: "性能分析显示，45.5%的CPU时间消耗在数据库查询调用链上",
+ }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Java service to analyze"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ FullGcCountLastHour int `json:"fullGcCountLastHour"`
+ FullGcTimeAvgMillis int `json:"fullGcTimeAvgMillis"`
+ HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+ log.Printf("Tool 'jvm_performance_analysis' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return JVMPerformanceAnalysisOutput{
+ ToolName: "jvm_performance_analysis",
+ FullGcCountLastHour: 15,
+ FullGcTimeAvgMillis: 1200,
+ HeapUsagePercentage: 85.5,
+ Summary: "GC activity is high, average Full GC time is 1200ms",
+ }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+ ToolName string `json:"toolName"`
+ UpstreamServices []string `json:"upstreamServices"`
+ DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) (TraceDependencyViewOutput, error) {
+ log.Printf("Tool 'trace_dependency_view' called for service: %s", input.ServiceName)
+
+ return TraceDependencyViewOutput{
+ ToolName: "trace_dependency_view",
+ UpstreamServices: []string{"api-gateway", "user-service"},
+ DownstreamServices: []string{"mysql-orders-db", "redis-cache", "payment-service"},
+ }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+ DownstreamService string `json:"downstreamService"`
+ LatencyAvgMillis int `json:"latencyAvgMillis"`
+ ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ TotalLatencyAvgMillis int `json:"totalLatencyAvgMillis"`
+ Bottlenecks []LatencyBottleneck `json:"bottlenecks"`
+ Summary string `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+ log.Printf("Tool 'trace_latency_analysis' called for service: %s", input.ServiceName)
+
+ return TraceLatencyAnalysisOutput{
+ ToolName: "trace_latency_analysis",
+ TotalLatencyAvgMillis: 3200,
+ Bottlenecks: []LatencyBottleneck{
+ {
+ DownstreamService: "mysql-orders-db",
+ LatencyAvgMillis: 3050,
+ ContributionPercentage: 95.3,
+ },
+ {
+ DownstreamService: "user-service",
+ LatencyAvgMillis: 150,
+ ContributionPercentage: 4.7,
+ },
+ },
+ Summary: "平均总延迟为 3200ms。瓶颈已定位，95.3% 的延迟来自对下游 'mysql-orders-db' 的调用",
+ }, nil
+}
+
+// ================================================
+// Database Connection Pool Analysis Tool
+// ================================================
+
+type DatabaseConnectionPoolAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+}
+
+type DatabaseConnectionPoolAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ MaxConnections int `json:"maxConnections"`
+ ActiveConnections int `json:"activeConnections"`
+ IdleConnections int `json:"idleConnections"`
+ PendingRequests int `json:"pendingRequests"`
+ Summary string `json:"summary"`
+}
+
+func (o DatabaseConnectionPoolAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func databaseConnectionPoolAnalysis(ctx *ai.ToolContext, input DatabaseConnectionPoolAnalysisInput) (DatabaseConnectionPoolAnalysisOutput, error) {
+ log.Printf("Tool 'database_connection_pool_analysis' called for service: %s", input.ServiceName)
+
+ return DatabaseConnectionPoolAnalysisOutput{
+ ToolName: "database_connection_pool_analysis",
+ MaxConnections: 100,
+ ActiveConnections: 100,
+ IdleConnections: 0,
+ PendingRequests: 58,
+ Summary: "数据库连接池已完全耗尽 (100/100)，当前有 58 个请求正在排队等待连接",
+ }, nil
+}
+
+// ================================================
+// Kubernetes Get Pod Resources Tool
+// ================================================
+
+type KubernetesGetPodResourcesInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Namespace string `json:"namespace" jsonschema:"required,description=The namespace of the service"`
+}
+
+type PodResource struct {
+ PodName string `json:"podName"`
+ CPUUsageCores float64 `json:"cpuUsageCores"`
+ CPURequestCores float64 `json:"cpuRequestCores"`
+ CPULimitCores float64 `json:"cpuLimitCores"`
+ MemoryUsageMi int `json:"memoryUsageMi"`
+ MemoryRequestMi int `json:"memoryRequestMi"`
+ MemoryLimitMi int `json:"memoryLimitMi"`
+}
+
+type KubernetesGetPodResourcesOutput struct {
+ ToolName string `json:"toolName"`
+ Pods []PodResource `json:"pods"`
+ Summary string `json:"summary"`
+}
+
+func (o KubernetesGetPodResourcesOutput) Tool() string {
+ return o.ToolName
+}
+
+func kubernetesGetPodResources(ctx *ai.ToolContext, input KubernetesGetPodResourcesInput) (KubernetesGetPodResourcesOutput, error) {
+ log.Printf("Tool 'kubernetes_get_pod_resources' called for service: %s in namespace: %s", input.ServiceName, input.Namespace)
+
+ return KubernetesGetPodResourcesOutput{
+ ToolName: "kubernetes_get_pod_resources",
+ Pods: []PodResource{
+ {
+ PodName: "order-service-pod-1",
+ CPUUsageCores: 0.8,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1800,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ {
+ PodName: "order-service-pod-2",
+ CPUUsageCores: 0.9,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1950,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ },
+ Summary: "2 out of 2 pods are near their memory limits",
+ }, nil
+}
+
+// ================================================
+// Dubbo Service Status Tool
+// ================================================
+
+type DubboServiceStatusInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Dubbo service"`
+}
+
+type DubboProvider struct {
+ IP string `json:"ip"`
+ Port int `json:"port"`
+ Status string `json:"status"`
+}
+
+type DubboConsumer struct {
+ IP string `json:"ip"`
+ Application string `json:"application"`
+ Status string `json:"status"`
+}
+
+type DubboServiceStatusOutput struct {
+ ToolName string `json:"toolName"`
+ Providers []DubboProvider `json:"providers"`
+ Consumers []DubboConsumer `json:"consumers"`
+}
+
+func (o DubboServiceStatusOutput) Tool() string {
+ return o.ToolName
+}
+
+func dubboServiceStatus(ctx *ai.ToolContext, input DubboServiceStatusInput) (DubboServiceStatusOutput, error) {
+ log.Printf("Tool 'dubbo_service_status' called for service: %s", input.ServiceName)
+
+ return DubboServiceStatusOutput{
+ ToolName: "dubbo_service_status",
+ Providers: []DubboProvider{
+ {IP: "192.168.1.10", Port: 20880, Status: "healthy"},
+ {IP: "192.168.1.11", Port: 20880, Status: "healthy"},
+ },
+ Consumers: []DubboConsumer{
+ {IP: "192.168.1.20", Application: "web-frontend", Status: "connected"},
+ {IP: "192.168.1.21", Application: "api-gateway", Status: "connected"},
+ },
+ }, nil
+}
+
+// ================================================
+// Query Log Database Tool
+// ================================================
+
+type QueryLogDatabaseInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Keyword string `json:"keyword" jsonschema:"required,description=Keyword to search for"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LogEntry struct {
+ Timestamp string `json:"timestamp"`
+ Level string `json:"level"`
+ Message string `json:"message"`
+}
+
+type QueryLogDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ TotalHits int `json:"totalHits"`
+ Logs []LogEntry `json:"logs"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryLogDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryLogDatabase(ctx *ai.ToolContext, input QueryLogDatabaseInput) (QueryLogDatabaseOutput, error) {
+ log.Printf("Tool 'query_log_database' called for service: %s, keyword: %s", input.ServiceName, input.Keyword)
+
+ return QueryLogDatabaseOutput{
+ ToolName: "query_log_database",
+ TotalHits: 152,
+ Logs: []LogEntry{
+ {
+ Timestamp: "2025-08-16T15:32:05Z",
+ Level: "WARN",
+ Message: "Timeout waiting for idle object in database connection pool.",
+ },
+ {
+ Timestamp: "2025-08-16T15:32:08Z",
+ Level: "WARN",
+ Message: "Timeout waiting for idle object in database connection pool.",
+ },
+ },
+ Summary: fmt.Sprintf("在过去%d分钟内，发现 152 条关于 '%s' 的日志条目", input.TimeRangeMinutes, input.Keyword),
+ }, nil
+}
+
+// ================================================
+// Search Archived Logs Tool
+// ================================================
+
+type SearchArchivedLogsInput struct {
+ FilePathPattern string `json:"filePathPattern" jsonschema:"required,description=File path pattern to search"`
+ GrepKeyword string `json:"grepKeyword" jsonschema:"required,description=Keyword to grep for"`
+}
+
+type MatchingLine struct {
+ FilePath string `json:"filePath"`
+ LineNumber int `json:"lineNumber"`
+ LineContent string `json:"lineContent"`
+}
+
+type SearchArchivedLogsOutput struct {
+ ToolName string `json:"toolName"`
+ FilesSearched int `json:"filesSearched"`
+ MatchingLines []MatchingLine `json:"matchingLines"`
+ Summary string `json:"summary"`
+}
+
+func (o SearchArchivedLogsOutput) Tool() string {
+ return o.ToolName
+}
+
+func searchArchivedLogs(ctx *ai.ToolContext, input SearchArchivedLogsInput) (SearchArchivedLogsOutput, error) {
+ log.Printf("Tool 'search_archived_logs' called with pattern: %s, keyword: %s", input.FilePathPattern, input.GrepKeyword)
+
+ return SearchArchivedLogsOutput{
+ ToolName: "search_archived_logs",
+ FilesSearched: 5,
+ MatchingLines: []MatchingLine{
+ {
+ FilePath: "/logs/mysql-orders-db/slow-query-2025-08-16.log.gz",
+ LineNumber: 1024,
+ LineContent: "Query_time: 25.3s | SELECT COUNT(id), SUM(price) FROM orders WHERE user_id = 'VIP_USER_123';",
+ },
+ {
+ FilePath: "/logs/mysql-orders-db/slow-query-2025-08-16.log.gz",
+ LineNumber: 1029,
+ LineContent: "Query_time: 28.1s | SELECT COUNT(id), SUM(price) FROM orders WHERE user_id = 'VIP_USER_456';",
Review Comment:
The hardcoded timestamps in mock data reference dates from August 2025. For consistency and to avoid confusion, consider using relative timestamps or current date ranges.
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Re: [PR] [feat]: Integrating AI Agent Capabilities into dubbo-admin [dubbo-admin]
Posted by "Copilot (via GitHub)" <gi...@apache.org>.
Copilot commented on code in PR #1319:
URL: https://github.com/apache/dubbo-admin/pull/1319#discussion_r2313943736
##########
ai/internal/manager/manager.go:
##########
@@ -0,0 +1,124 @@
+package manager
+
+import (
+ "context"
+ "dubbo-admin-ai/config"
+ "dubbo-admin-ai/plugins/siliconflow"
+ "dubbo-admin-ai/utils"
+ "fmt"
+ "log"
+ "log/slog"
+ "os"
+ "path/filepath"
+ "strings"
+ "time"
+
+ "github.com/firebase/genkit/go/core/logger"
+ "github.com/firebase/genkit/go/genkit"
+ "github.com/firebase/genkit/go/plugins/googlegenai"
+ "github.com/joho/godotenv"
+ "github.com/lmittmann/tint"
+)
+
+var (
+ globalGenkit *genkit.Genkit
+ rootContext *context.Context
+ globalLogger *slog.Logger
+)
+
+func InitGlobalGenkit(defaultModel string) (err error) {
+ ctx := context.Background()
+ if rootContext == nil {
+ rootContext = &ctx
+ }
+ g, err := genkit.Init(*rootContext,
+ genkit.WithPlugins(
+ &siliconflow.SiliconFlow{
+ APIKey: config.SILICONFLOW_API_KEY,
+ },
+ &googlegenai.GoogleAI{
+ APIKey: config.GEMINI_API_KEY,
+ },
+ ),
+ genkit.WithDefaultModel(defaultModel),
+ genkit.WithPromptDir(config.PROMPT_DIR_PATH),
+ )
+
+ if g == nil {
+ return fmt.Errorf("fail to initialize global genkit")
+ }
+
+ globalGenkit = g
+ return err
+}
+
+func InitLogger() {
+ logLevel := slog.LevelInfo
+ if envLevel := config.LOG_LEVEL; envLevel != "" {
+ switch strings.ToUpper(envLevel) {
+ case "DEBUG":
+ logLevel = slog.LevelDebug
+ case "INFO":
+ logLevel = slog.LevelInfo
+ case "WARN", "WARNING":
+ logLevel = slog.LevelWarn
+ case "ERROR":
+ logLevel = slog.LevelError
+ }
+ }
+ logger.SetLevel(logLevel)
+
+ slog.SetDefault(
+ slog.New(
+ tint.NewHandler(os.Stderr, &tint.Options{
+ Level: slog.LevelDebug,
+ AddSource: true,
+ TimeFormat: time.Kitchen,
+ }),
+ ),
+ )
+ globalLogger = slog.Default()
+}
+
+func GetGlobalGenkit() (*genkit.Genkit, error) {
+ var err error
+ if globalGenkit == nil {
+ err = InitGlobalGenkit(config.DEFAULT_MODEL)
+ if err != nil {
+ log.Fatalf("Failed to initialize global genkit: %v", err)
+ }
+ }
+ return globalGenkit, err
+}
+
+func GetLogger() *slog.Logger {
+ if globalLogger == nil {
+ InitLogger()
+ }
+ return globalLogger
+}
+
+func GetRootContext() context.Context {
+ ctx := context.Background()
+ if rootContext == nil {
+ rootContext = &ctx
+ }
+ return *rootContext
+}
+
+// Load environment variables from PROJECT_ROOT/.env file
+func LoadEnvVars() (err error) {
+ dotEnvFilePath := filepath.Join(config.PROJECT_ROOT, ".env")
+ dotEnvExampleFilePath := filepath.Join(config.PROJECT_ROOT, ".env.example")
+
+ // Check if the .env file exists，if not, copy .env.example to .env
Review Comment:
Mixed punctuation style - there's a Chinese comma (，) followed by English text. Should be: 'Check if the .env file exists, if not, copy .env.example to .env'
```suggestion
// Check if the .env file exists, if not, copy .env.example to .env
```
##########
ai/internal/agent/flow.go:
##########
@@ -0,0 +1,178 @@
+package agent
+
+import (
+ "context"
+ "dubbo-admin-ai/config"
+ "dubbo-admin-ai/internal/manager"
+ "dubbo-admin-ai/internal/schema"
+ "dubbo-admin-ai/internal/tools"
+ "errors"
+ "fmt"
+ "log"
+ "os"
+
+ "github.com/firebase/genkit/go/core/logger"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/core"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// 公开的 Flow 变量，以便在编排器中调用
+var (
+ ReActFlow *core.Flow[schema.ReActIn, schema.ReActOut, struct{}]
+ ThinkingFlow *core.Flow[schema.ThinkIn, *schema.ThinkOut, struct{}]
+ ActFlow *core.Flow[*schema.ActIn, schema.ActOut, struct{}]
+
+ ThinkPrompt *ai.Prompt
+)
+
+var g *genkit.Genkit
+
+// The order of initialization cannot change
+func InitAgent() (err error) {
+ if err = manager.LoadEnvVars(); err != nil {
+ return err
+ }
+
+ manager.InitLogger()
+
+ if g, err = manager.GetGlobalGenkit(); err != nil {
+ return err
+ }
+
+ tools.RegisterAllMockTools(g)
+
+ if err = InitFlows(g); err != nil {
+ return err
+ }
+
+ return nil
+}
+
+func InitFlows(registry *genkit.Genkit) error {
+ if registry == nil {
+ return fmt.Errorf("registry is nil")
+ }
+ g = registry
+
+ data, err := os.ReadFile(config.PROMPT_DIR_PATH + "/agentSystem.prompt")
+ if err != nil {
+ return fmt.Errorf("failed to read agentSystem prompt: %w", err)
+ }
+ systemPromptText := string(data)
+
+ mockTools, err := tools.AllMockToolRef()
+ if err != nil {
+ log.Fatalf("failed to get mock mock_tools: %v", err)
+ }
+ ThinkPrompt, err = genkit.DefinePrompt(g, "agentThinking",
+ ai.WithSystem(systemPromptText),
+ ai.WithInputType(schema.ThinkIn{}),
+ ai.WithOutputType(schema.ThinkOut{}),
+ ai.WithPrompt("{{userInput}}"),
+ ai.WithTools(mockTools...),
+ )
+
+ if err != nil {
+ return fmt.Errorf("failed to define agentThink prompt: %w", err)
+ }
+
+ ReActFlow = genkit.DefineFlow(g, "reAct", reAct)
+ ThinkingFlow = genkit.DefineFlow(g, "thinking", thinking)
+ ActFlow = genkit.DefineFlow(g, "act", act)
+
+ return nil
+}
+
+// Flow 的核心函数实现 `fn` (不对外导出)
+// ----------------------------------------------------------------------------
+// 1. agentOrchestrator: 总指挥/编排器的核心逻辑
+// ----------------------------------------------------------------------------
+func reAct(ctx context.Context, reActInput schema.ReActIn) (reActOut schema.ReActOut, err error) {
+ //TODO: 输入数据意图解析
+
+ thinkingInput := reActInput
+ // 主协调循环 (Reconciliation Loop)
+ for range config.MAX_REACT_ITERATIONS {
Review Comment:
[nitpick] Using an unnamed range variable in the loop makes the iteration count implicit. Consider using a named variable to make the iteration logic more explicit: `for i := 0; i < config.MAX_REACT_ITERATIONS; i++`
```suggestion
for i := 0; i < config.MAX_REACT_ITERATIONS; i++ {
```
##########
ai/prompts/agentThink.prompt:
##########
@@ -0,0 +1,110 @@
+---
+# -------------------------------------------------------------
+# Agent "Brain" Prompt - agentThink.prompt
+# -------------------------------------------------------------
+# This prompt is the core reasoning engine for our ReAct agent.
+# It takes the current state and decides the next action or provides the final answer.
+# -------------------------------------------------------------
+
+# model: googleai/gemini-2.5-pro
+model: siliconflow/deepseek-ai/DeepSeek-V3
Review Comment:
The model specification appears to have inconsistent naming. Based on the plugin configuration, it should be 'siliconflow/deepseek-ai/DeepSeek-V3' but verify this matches the actual model identifier used by the SiliconFlow API.
```suggestion
model: siliconflow/deepseek-ai/deepseek-v3
```
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Re: [PR] [feat]: Integrating AI Agent Capabilities into dubbo-admin [dubbo-admin]
Posted by "robocanic (via GitHub)" <gi...@apache.org>.
robocanic merged PR #1319:
URL: https://github.com/apache/dubbo-admin/pull/1319
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Re: [PR] [feat]: Integrating AI Agent Capabilities into dubbo-admin [dubbo-admin]
Posted by "sonarqubecloud[bot] (via GitHub)" <gi...@apache.org>.
sonarqubecloud[bot] commented on PR #1319:
URL: https://github.com/apache/dubbo-admin/pull/1319#issuecomment-3241209614
## [](https://sonarcloud.io/dashboard?id=apache_dubbo-admin&pullRequest=1319) **Quality Gate passed**
Issues
 [0 New issues](https://sonarcloud.io/project/issues?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=OPEN,CONFIRMED&sinceLeakPeriod=true)
 [0 Accepted issues](https://sonarcloud.io/project/issues?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=ACCEPTED)
Measures
 [0 Security Hotspots](https://sonarcloud.io/project/security_hotspots?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=OPEN,CONFIRMED&sinceLeakPeriod=true)
 [0.0% Coverage on New Code](https://sonarcloud.io/component_measures?id=apache_dubbo-admin&pullRequest=1319&metric=new_coverage&view=list)
 [0.0% Duplication on New Code](https://sonarcloud.io/component_measures?id=apache_dubbo-admin&pullRequest=1319&metric=new_duplicated_lines_density&view=list)
[See analysis details on SonarQube Cloud](https://sonarcloud.io/dashboard?id=apache_dubbo-admin&pullRequest=1319)
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Re: [PR] [feat]: Integrating AI Agent Capabilities into dubbo-admin [dubbo-admin]
Posted by "sonarqubecloud[bot] (via GitHub)" <gi...@apache.org>.
sonarqubecloud[bot] commented on PR #1319:
URL: https://github.com/apache/dubbo-admin/pull/1319#issuecomment-3242386282
## [](https://sonarcloud.io/dashboard?id=apache_dubbo-admin&pullRequest=1319) **Quality Gate passed**
Issues
 [0 New issues](https://sonarcloud.io/project/issues?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=OPEN,CONFIRMED&sinceLeakPeriod=true)
 [0 Accepted issues](https://sonarcloud.io/project/issues?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=ACCEPTED)
Measures
 [0 Security Hotspots](https://sonarcloud.io/project/security_hotspots?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=OPEN,CONFIRMED&sinceLeakPeriod=true)
 [0.0% Coverage on New Code](https://sonarcloud.io/component_measures?id=apache_dubbo-admin&pullRequest=1319&metric=new_coverage&view=list)
 [0.0% Duplication on New Code](https://sonarcloud.io/component_measures?id=apache_dubbo-admin&pullRequest=1319&metric=new_duplicated_lines_density&view=list)
[See analysis details on SonarQube Cloud](https://sonarcloud.io/dashboard?id=apache_dubbo-admin&pullRequest=1319)
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Re: [PR] [feat]: Integrating AI Agent Capabilities into dubbo-admin [dubbo-admin]
Posted by "Copilot (via GitHub)" <gi...@apache.org>.
Copilot commented on code in PR #1319:
URL: https://github.com/apache/dubbo-admin/pull/1319#discussion_r2314408258
##########
ai/internal/agent/flow.go:
##########
@@ -0,0 +1,182 @@
+package agent
+
+import (
+ "context"
+
+ "dubbo-admin-ai/internal/config"
+ "dubbo-admin-ai/internal/manager"
+ "dubbo-admin-ai/internal/schema"
+ "dubbo-admin-ai/internal/tools"
+ "errors"
+ "fmt"
+ "log"
+ "os"
+
+ "github.com/firebase/genkit/go/core/logger"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/core"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// 公开的 Flow 变量，以便在编排器中调用
+var (
+ ReActFlow *core.Flow[schema.ReActIn, schema.ReActOut, struct{}]
+ ThinkingFlow *core.Flow[schema.ThinkIn, *schema.ThinkOut, struct{}]
+ ActFlow *core.Flow[*schema.ActIn, schema.ActOut, struct{}]
+
+ ThinkPrompt *ai.Prompt
+)
Review Comment:
Global variables for flows create tight coupling and make testing difficult. Consider encapsulating these in a struct or using dependency injection to manage flow instances.
##########
ai/internal/config/config.go:
##########
@@ -0,0 +1,25 @@
+package config
+
+import (
+ "dubbo-admin-ai/plugins/siliconflow"
+ "os"
+ "path/filepath"
+ "runtime"
+)
+
+var (
+ // API keys
+ GEMINI_API_KEY string = os.Getenv("GEMINI_API_KEY")
+ SILICONFLOW_API_KEY string = os.Getenv("SILICONFLOW_API_KEY")
+ DASHSCOPE_API_KEY string = os.Getenv("DASHSCOPE_API_KEY")
+
+ // Configuration
+ // 自动获取项目根目录
+ _, b, _, _ = runtime.Caller(0)
+ PROJECT_ROOT = filepath.Join(filepath.Dir(b), "..", "..")
Review Comment:
Using runtime.Caller(0) to determine project root at package level creates fragile path dependencies. Consider using go:embed or making PROJECT_ROOT configurable via environment variable to improve maintainability and testing.
##########
ai/internal/manager/manager.go:
##########
@@ -0,0 +1,126 @@
+package manager
+
+import (
+ "context"
+
+ "dubbo-admin-ai/internal/config"
+
+ "dubbo-admin-ai/plugins/dashscope"
+ "dubbo-admin-ai/plugins/siliconflow"
+ "dubbo-admin-ai/utils"
+ "fmt"
+ "log/slog"
+ "os"
+ "path/filepath"
+ "strings"
+ "time"
+
+ "github.com/firebase/genkit/go/core/logger"
+ "github.com/firebase/genkit/go/genkit"
+ "github.com/firebase/genkit/go/plugins/googlegenai"
+ "github.com/joho/godotenv"
+ "github.com/lmittmann/tint"
+)
+
+var (
+ globalGenkit *genkit.Genkit
+ rootContext *context.Context
+ globalLogger *slog.Logger
+)
Review Comment:
Using global variables for dependency management violates dependency injection principles and makes testing difficult. Consider using a struct-based approach or dependency injection container to manage these dependencies.
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Re: [PR] [feat]: Integrating AI Agent Capabilities into dubbo-admin [dubbo-admin]
Posted by "Copilot (via GitHub)" <gi...@apache.org>.
Copilot commented on code in PR #1319:
URL: https://github.com/apache/dubbo-admin/pull/1319#discussion_r2313485913
##########
ai/internal/schema/llm_schema.go:
##########
@@ -0,0 +1,102 @@
+package schema
+
+import (
+ "dubbo-admin-ai/internal/tools"
+ "encoding/json"
+ "fmt"
+)
+
+// 表示 LLM 的响应结构
+type ReActIn = ReActInput
+type ReActOut = string
+
+type ThinkIn = ReActInput
+type ThinkOut = ThinkAggregation
+
+type ActIn = ThinkOut
+type ActOut = []string
+
+type ReActInput struct {
+ UserInput string `json:"userInput"`
+ // 移除SessionID和SessionMemory，这些由Session管理
+}
+
+type Status string
+
+const (
+ Continued Status = "CONTINUED"
+ Finished Status = "FINISHED"
+ Pending Status = "PENDING"
+)
+
+type ToolRequest struct {
+ Thought string `json:"thought"`
+ ToolDesc tools.ToolDesc `json:"tool_desc"`
+}
+
+type ThinkAggregation struct {
+ ToolRequests []ToolRequest `json:"tool_requests"`
+ Status Status `json:"status" jsonschema:"enum=CONTINUED,enum=FINISHED,enum=PENDING"`
+ Thought string `json:"thought"`
+ FinalAnswer string `json:"final_answer,omitempty" jsonschema:"required=false"`
+}
+
+// ReActInput
+func (a ReActInput) String() string {
+ data, err := json.MarshalIndent(a, "", " ")
+ if err != nil {
+ return fmt.Sprintf("ReActInput{error: %v}", err)
+ }
+ return string(data)
+}
+
+// ToolRequest
+// HasAction 检查是否包含行动指令
+func (tr ToolRequest) HasAction() bool {
+ return tr.ToolDesc.ToolInput != nil && tr.ToolDesc.ToolName != ""
+}
+
+// ValidateToolDesc 验证行动指令的有效性
+func (tr ToolRequest) ValidateToolDesc() error {
+ if !tr.HasAction() {
+ return fmt.Errorf("no valid action found")
+ }
+
+ if tr.ToolDesc.ToolName == "" {
+ return fmt.Errorf("tool_name cannot be empty")
+ }
+
+ // 验证支持的工具名称
+ supportedTools, err := tools.AllMockToolNames()
+ if err != nil {
+ return fmt.Errorf("failed to get supported tools: %w", err)
+ }
+
+ if _, ok := supportedTools[tr.ToolDesc.ToolName]; !ok {
+ return fmt.Errorf("unsupported tool: %s", tr.ToolDesc.ToolName)
+ }
+
+ return nil
+}
+
+// String 实现 fmt.Stringer 接口，返回格式化的 JSON
+func (tr ToolRequest) String() string {
+ data, err := json.MarshalIndent(tr, "", " ")
+ if err != nil {
+ return fmt.Sprintf("ThinkAggregation{error: %v}", err)
Review Comment:
The error message incorrectly references 'ThinkAggregation' but this is the String() method for ToolRequest. It should return 'ToolRequest{error: %v}' instead.
```suggestion
return fmt.Sprintf("ToolRequest{error: %v}", err)
```
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ // Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+ }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+ ToolName string `json:"toolName"`
+ RequestRateQPS float64 `json:"requestRateQPS"`
+ ErrorRatePercentage float64 `json:"errorRatePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_traffic' called for service: %s", input.ServiceName)
+
+ return PrometheusServiceTrafficOutput{
+ ToolName: "prometheus_query_service_traffic",
+ RequestRateQPS: 250.0,
+ ErrorRatePercentage: 5.2,
+ // Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
Review Comment:
This line is commented out but still contains the fmt.Sprintf call. Either remove the entire line or uncomment it if the Summary field should be populated.
```suggestion
Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
```
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ // Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+ }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+ ToolName string `json:"toolName"`
+ RequestRateQPS float64 `json:"requestRateQPS"`
+ ErrorRatePercentage float64 `json:"errorRatePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_traffic' called for service: %s", input.ServiceName)
+
+ return PrometheusServiceTrafficOutput{
+ ToolName: "prometheus_query_service_traffic",
+ RequestRateQPS: 250.0,
+ ErrorRatePercentage: 5.2,
+ // Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
+ }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+ PromqlQuery string `json:"promqlQuery" jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+ Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+ Timestamp int64 `json:"timestamp"`
+ Value string `json:"value"`
+}
+
+type TimeseriesResult struct {
+ Metric TimeseriesMetric `json:"metric"`
+ Value TimeseriesValue `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ Query string `json:"query"`
+ Results []TimeseriesResult `json:"results"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+ log.Printf("Tool 'query_timeseries_database' called with query: %s", input.PromqlQuery)
+
+ return QueryTimeseriesDatabaseOutput{
+ ToolName: "query_timeseries_database",
+ Query: input.PromqlQuery,
+ Results: []TimeseriesResult{
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-1"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.5"},
+ },
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-2"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.2"},
+ },
+ },
+ // Summary: "查询返回了 2 个时间序列",
+ }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to profile"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to profile"`
+ DurationSeconds int `json:"durationSeconds" jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+ CPUTimePercentage float64 `json:"cpuTimePercentage"`
+ StackTrace []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+ ToolName string `json:"toolName"`
+ Status string `json:"status"`
+ TotalSamples int `json:"totalSamples"`
+ Hotspots []PerformanceHotspot `json:"hotspots"`
+ Summary string `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+ return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, error) {
+ log.Printf("Tool 'application_performance_profiling' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return ApplicationPerformanceProfilingOutput{
+ ToolName: "application_performance_profiling",
+ Status: "completed",
+ TotalSamples: 10000,
+ Hotspots: []PerformanceHotspot{
+ {
+ CPUTimePercentage: 45.5,
+ StackTrace: []string{
+ "com.example.OrderService.processOrder()",
+ "com.example.DatabaseClient.query()",
+ "java.sql.PreparedStatement.executeQuery()",
+ },
+ },
+ },
+ // Summary: "性能分析显示，45.5%的CPU时间消耗在数据库查询调用链上",
+ }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Java service to analyze"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ FullGcCountLastHour int `json:"fullGcCountLastHour"`
+ FullGcTimeAvgMillis int `json:"fullGcTimeAvgMillis"`
+ HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+ log.Printf("Tool 'jvm_performance_analysis' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return JVMPerformanceAnalysisOutput{
+ ToolName: "jvm_performance_analysis",
+ FullGcCountLastHour: 15,
+ FullGcTimeAvgMillis: 1200,
+ HeapUsagePercentage: 85.5,
+ // Summary: "GC activity is high, average Full GC time is 1200ms",
+ }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+ ToolName string `json:"toolName"`
+ UpstreamServices []string `json:"upstreamServices"`
+ DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) (TraceDependencyViewOutput, error) {
+ log.Printf("Tool 'trace_dependency_view' called for service: %s", input.ServiceName)
+
+ return TraceDependencyViewOutput{
+ ToolName: "trace_dependency_view",
+ UpstreamServices: []string{"api-gateway", "user-service"},
+ DownstreamServices: []string{"mysql-orders-db", "redis-cache", "payment-service"},
+ }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+ DownstreamService string `json:"downstreamService"`
+ LatencyAvgMillis int `json:"latencyAvgMillis"`
+ ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ TotalLatencyAvgMillis int `json:"totalLatencyAvgMillis"`
+ Bottlenecks []LatencyBottleneck `json:"bottlenecks"`
+ Summary string `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+ log.Printf("Tool 'trace_latency_analysis' called for service: %s", input.ServiceName)
+
+ return TraceLatencyAnalysisOutput{
+ ToolName: "trace_latency_analysis",
+ TotalLatencyAvgMillis: 3200,
+ Bottlenecks: []LatencyBottleneck{
+ {
+ DownstreamService: "mysql-orders-db",
+ LatencyAvgMillis: 3050,
+ ContributionPercentage: 95.3,
+ },
+ {
+ DownstreamService: "user-service",
+ LatencyAvgMillis: 150,
+ ContributionPercentage: 4.7,
+ },
+ },
+ // Summary: "平均总延迟为 3200ms。瓶颈已定位，95.3% 的延迟来自对下游 'mysql-orders-db' 的调用",
Review Comment:
This line is commented out but still contains a string literal. Either remove the entire line or uncomment it if the Summary field should be populated.
```suggestion
Summary: "平均总延迟为 3200ms。瓶颈已定位，95.3% 的延迟来自对下游 'mysql-orders-db' 的调用",
```
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ // Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+ }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+ ToolName string `json:"toolName"`
+ RequestRateQPS float64 `json:"requestRateQPS"`
+ ErrorRatePercentage float64 `json:"errorRatePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_traffic' called for service: %s", input.ServiceName)
+
+ return PrometheusServiceTrafficOutput{
+ ToolName: "prometheus_query_service_traffic",
+ RequestRateQPS: 250.0,
+ ErrorRatePercentage: 5.2,
+ // Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
+ }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+ PromqlQuery string `json:"promqlQuery" jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+ Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+ Timestamp int64 `json:"timestamp"`
+ Value string `json:"value"`
+}
+
+type TimeseriesResult struct {
+ Metric TimeseriesMetric `json:"metric"`
+ Value TimeseriesValue `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ Query string `json:"query"`
+ Results []TimeseriesResult `json:"results"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+ log.Printf("Tool 'query_timeseries_database' called with query: %s", input.PromqlQuery)
+
+ return QueryTimeseriesDatabaseOutput{
+ ToolName: "query_timeseries_database",
+ Query: input.PromqlQuery,
+ Results: []TimeseriesResult{
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-1"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.5"},
+ },
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-2"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.2"},
+ },
+ },
+ // Summary: "查询返回了 2 个时间序列",
+ }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to profile"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to profile"`
+ DurationSeconds int `json:"durationSeconds" jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+ CPUTimePercentage float64 `json:"cpuTimePercentage"`
+ StackTrace []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+ ToolName string `json:"toolName"`
+ Status string `json:"status"`
+ TotalSamples int `json:"totalSamples"`
+ Hotspots []PerformanceHotspot `json:"hotspots"`
+ Summary string `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+ return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, error) {
+ log.Printf("Tool 'application_performance_profiling' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return ApplicationPerformanceProfilingOutput{
+ ToolName: "application_performance_profiling",
+ Status: "completed",
+ TotalSamples: 10000,
+ Hotspots: []PerformanceHotspot{
+ {
+ CPUTimePercentage: 45.5,
+ StackTrace: []string{
+ "com.example.OrderService.processOrder()",
+ "com.example.DatabaseClient.query()",
+ "java.sql.PreparedStatement.executeQuery()",
+ },
+ },
+ },
+ // Summary: "性能分析显示，45.5%的CPU时间消耗在数据库查询调用链上",
+ }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Java service to analyze"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ FullGcCountLastHour int `json:"fullGcCountLastHour"`
+ FullGcTimeAvgMillis int `json:"fullGcTimeAvgMillis"`
+ HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+ log.Printf("Tool 'jvm_performance_analysis' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return JVMPerformanceAnalysisOutput{
+ ToolName: "jvm_performance_analysis",
+ FullGcCountLastHour: 15,
+ FullGcTimeAvgMillis: 1200,
+ HeapUsagePercentage: 85.5,
+ // Summary: "GC activity is high, average Full GC time is 1200ms",
Review Comment:
This line is commented out but still contains a string literal. Either remove the entire line or uncomment it if the Summary field should be populated.
```suggestion
```
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ // Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+ }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+ ToolName string `json:"toolName"`
+ RequestRateQPS float64 `json:"requestRateQPS"`
+ ErrorRatePercentage float64 `json:"errorRatePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_traffic' called for service: %s", input.ServiceName)
+
+ return PrometheusServiceTrafficOutput{
+ ToolName: "prometheus_query_service_traffic",
+ RequestRateQPS: 250.0,
+ ErrorRatePercentage: 5.2,
+ // Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
+ }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+ PromqlQuery string `json:"promqlQuery" jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+ Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+ Timestamp int64 `json:"timestamp"`
+ Value string `json:"value"`
+}
+
+type TimeseriesResult struct {
+ Metric TimeseriesMetric `json:"metric"`
+ Value TimeseriesValue `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ Query string `json:"query"`
+ Results []TimeseriesResult `json:"results"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+ log.Printf("Tool 'query_timeseries_database' called with query: %s", input.PromqlQuery)
+
+ return QueryTimeseriesDatabaseOutput{
+ ToolName: "query_timeseries_database",
+ Query: input.PromqlQuery,
+ Results: []TimeseriesResult{
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-1"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.5"},
+ },
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-2"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.2"},
+ },
+ },
+ // Summary: "查询返回了 2 个时间序列",
+ }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to profile"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to profile"`
+ DurationSeconds int `json:"durationSeconds" jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+ CPUTimePercentage float64 `json:"cpuTimePercentage"`
+ StackTrace []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+ ToolName string `json:"toolName"`
+ Status string `json:"status"`
+ TotalSamples int `json:"totalSamples"`
+ Hotspots []PerformanceHotspot `json:"hotspots"`
+ Summary string `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+ return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, error) {
+ log.Printf("Tool 'application_performance_profiling' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return ApplicationPerformanceProfilingOutput{
+ ToolName: "application_performance_profiling",
+ Status: "completed",
+ TotalSamples: 10000,
+ Hotspots: []PerformanceHotspot{
+ {
+ CPUTimePercentage: 45.5,
+ StackTrace: []string{
+ "com.example.OrderService.processOrder()",
+ "com.example.DatabaseClient.query()",
+ "java.sql.PreparedStatement.executeQuery()",
+ },
+ },
+ },
+ // Summary: "性能分析显示，45.5%的CPU时间消耗在数据库查询调用链上",
+ }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Java service to analyze"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ FullGcCountLastHour int `json:"fullGcCountLastHour"`
+ FullGcTimeAvgMillis int `json:"fullGcTimeAvgMillis"`
+ HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+ log.Printf("Tool 'jvm_performance_analysis' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return JVMPerformanceAnalysisOutput{
+ ToolName: "jvm_performance_analysis",
+ FullGcCountLastHour: 15,
+ FullGcTimeAvgMillis: 1200,
+ HeapUsagePercentage: 85.5,
+ // Summary: "GC activity is high, average Full GC time is 1200ms",
+ }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+ ToolName string `json:"toolName"`
+ UpstreamServices []string `json:"upstreamServices"`
+ DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) (TraceDependencyViewOutput, error) {
+ log.Printf("Tool 'trace_dependency_view' called for service: %s", input.ServiceName)
+
+ return TraceDependencyViewOutput{
+ ToolName: "trace_dependency_view",
+ UpstreamServices: []string{"api-gateway", "user-service"},
+ DownstreamServices: []string{"mysql-orders-db", "redis-cache", "payment-service"},
+ }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+ DownstreamService string `json:"downstreamService"`
+ LatencyAvgMillis int `json:"latencyAvgMillis"`
+ ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ TotalLatencyAvgMillis int `json:"totalLatencyAvgMillis"`
+ Bottlenecks []LatencyBottleneck `json:"bottlenecks"`
+ Summary string `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+ log.Printf("Tool 'trace_latency_analysis' called for service: %s", input.ServiceName)
+
+ return TraceLatencyAnalysisOutput{
+ ToolName: "trace_latency_analysis",
+ TotalLatencyAvgMillis: 3200,
+ Bottlenecks: []LatencyBottleneck{
+ {
+ DownstreamService: "mysql-orders-db",
+ LatencyAvgMillis: 3050,
+ ContributionPercentage: 95.3,
+ },
+ {
+ DownstreamService: "user-service",
+ LatencyAvgMillis: 150,
+ ContributionPercentage: 4.7,
+ },
+ },
+ // Summary: "平均总延迟为 3200ms。瓶颈已定位，95.3% 的延迟来自对下游 'mysql-orders-db' 的调用",
+ }, nil
+}
+
+// ================================================
+// Database Connection Pool Analysis Tool
+// ================================================
+
+type DatabaseConnectionPoolAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+}
+
+type DatabaseConnectionPoolAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ MaxConnections int `json:"maxConnections"`
+ ActiveConnections int `json:"activeConnections"`
+ IdleConnections int `json:"idleConnections"`
+ PendingRequests int `json:"pendingRequests"`
+ Summary string `json:"summary"`
+}
+
+func (o DatabaseConnectionPoolAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func databaseConnectionPoolAnalysis(ctx *ai.ToolContext, input DatabaseConnectionPoolAnalysisInput) (DatabaseConnectionPoolAnalysisOutput, error) {
+ log.Printf("Tool 'database_connection_pool_analysis' called for service: %s", input.ServiceName)
+
+ return DatabaseConnectionPoolAnalysisOutput{
+ ToolName: "database_connection_pool_analysis",
+ MaxConnections: 100,
+ ActiveConnections: 100,
+ IdleConnections: 0,
+ PendingRequests: 58,
+ // Summary: "数据库连接池已完全耗尽 (100/100)，当前有 58 个请求正在排队等待连接",
+ }, nil
+}
+
+// ================================================
+// Kubernetes Get Pod Resources Tool
+// ================================================
+
+type KubernetesGetPodResourcesInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Namespace string `json:"namespace" jsonschema:"required,description=The namespace of the service"`
+}
+
+type PodResource struct {
+ PodName string `json:"podName"`
+ CPUUsageCores float64 `json:"cpuUsageCores"`
+ CPURequestCores float64 `json:"cpuRequestCores"`
+ CPULimitCores float64 `json:"cpuLimitCores"`
+ MemoryUsageMi int `json:"memoryUsageMi"`
+ MemoryRequestMi int `json:"memoryRequestMi"`
+ MemoryLimitMi int `json:"memoryLimitMi"`
+}
+
+type KubernetesGetPodResourcesOutput struct {
+ ToolName string `json:"toolName"`
+ Pods []PodResource `json:"pods"`
+ Summary string `json:"summary"`
+}
+
+func (o KubernetesGetPodResourcesOutput) Tool() string {
+ return o.ToolName
+}
+
+func kubernetesGetPodResources(ctx *ai.ToolContext, input KubernetesGetPodResourcesInput) (KubernetesGetPodResourcesOutput, error) {
+ log.Printf("Tool 'kubernetes_get_pod_resources' called for service: %s in namespace: %s", input.ServiceName, input.Namespace)
+
+ return KubernetesGetPodResourcesOutput{
+ ToolName: "kubernetes_get_pod_resources",
+ Pods: []PodResource{
+ {
+ PodName: "order-service-pod-1",
+ CPUUsageCores: 0.8,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1800,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ {
+ PodName: "order-service-pod-2",
+ CPUUsageCores: 0.9,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1950,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ },
+ // Summary: "2 out of 2 pods are near their memory limits",
+ }, nil
+}
+
+// ================================================
+// Dubbo Service Status Tool
+// ================================================
+
+type DubboServiceStatusInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Dubbo service"`
+}
+
+type DubboProvider struct {
+ IP string `json:"ip"`
+ Port int `json:"port"`
+ Status string `json:"status"`
+}
+
+type DubboConsumer struct {
+ IP string `json:"ip"`
+ Application string `json:"application"`
+ Status string `json:"status"`
+}
+
+type DubboServiceStatusOutput struct {
+ ToolName string `json:"toolName"`
+ Providers []DubboProvider `json:"providers"`
+ Consumers []DubboConsumer `json:"consumers"`
+}
+
+func (o DubboServiceStatusOutput) Tool() string {
+ return o.ToolName
+}
+
+func dubboServiceStatus(ctx *ai.ToolContext, input DubboServiceStatusInput) (DubboServiceStatusOutput, error) {
+ log.Printf("Tool 'dubbo_service_status' called for service: %s", input.ServiceName)
+
+ return DubboServiceStatusOutput{
+ ToolName: "dubbo_service_status",
+ Providers: []DubboProvider{
+ {IP: "192.168.1.10", Port: 20880, Status: "healthy"},
+ {IP: "192.168.1.11", Port: 20880, Status: "healthy"},
+ },
+ Consumers: []DubboConsumer{
+ {IP: "192.168.1.20", Application: "web-frontend", Status: "connected"},
+ {IP: "192.168.1.21", Application: "api-gateway", Status: "connected"},
+ },
+ }, nil
+}
+
+// ================================================
+// Query Log Database Tool
+// ================================================
+
+type QueryLogDatabaseInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Keyword string `json:"keyword" jsonschema:"required,description=Keyword to search for"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LogEntry struct {
+ Timestamp string `json:"timestamp"`
+ Level string `json:"level"`
+ Message string `json:"message"`
+}
+
+type QueryLogDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ TotalHits int `json:"totalHits"`
+ Logs []LogEntry `json:"logs"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryLogDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryLogDatabase(ctx *ai.ToolContext, input QueryLogDatabaseInput) (QueryLogDatabaseOutput, error) {
+ log.Printf("Tool 'query_log_database' called for service: %s, keyword: %s", input.ServiceName, input.Keyword)
+
+ return QueryLogDatabaseOutput{
+ ToolName: "query_log_database",
+ TotalHits: 152,
+ Logs: []LogEntry{
+ {
+ Timestamp: "2025-08-16T15:32:05Z",
+ Level: "WARN",
+ Message: "Timeout waiting for idle object in database connection pool.",
+ },
+ {
+ Timestamp: "2025-08-16T15:32:08Z",
+ Level: "WARN",
+ Message: "Timeout waiting for idle object in database connection pool.",
+ },
+ },
+ // Summary: fmt.Sprintf("在过去%d分钟内，发现 152 条关于 '%s' 的日志条目", input.TimeRangeMinutes, input.Keyword),
Review Comment:
This line is commented out but still contains the fmt.Sprintf call. Either remove the entire line or uncomment it if the Summary field should be populated.
```suggestion
Summary: fmt.Sprintf("在过去%d分钟内，发现 152 条关于 '%s' 的日志条目", input.TimeRangeMinutes, input.Keyword),
```
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ // Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+ }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+ ToolName string `json:"toolName"`
+ RequestRateQPS float64 `json:"requestRateQPS"`
+ ErrorRatePercentage float64 `json:"errorRatePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_traffic' called for service: %s", input.ServiceName)
+
+ return PrometheusServiceTrafficOutput{
+ ToolName: "prometheus_query_service_traffic",
+ RequestRateQPS: 250.0,
+ ErrorRatePercentage: 5.2,
+ // Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
+ }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+ PromqlQuery string `json:"promqlQuery" jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+ Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+ Timestamp int64 `json:"timestamp"`
+ Value string `json:"value"`
+}
+
+type TimeseriesResult struct {
+ Metric TimeseriesMetric `json:"metric"`
+ Value TimeseriesValue `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ Query string `json:"query"`
+ Results []TimeseriesResult `json:"results"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+ log.Printf("Tool 'query_timeseries_database' called with query: %s", input.PromqlQuery)
+
+ return QueryTimeseriesDatabaseOutput{
+ ToolName: "query_timeseries_database",
+ Query: input.PromqlQuery,
+ Results: []TimeseriesResult{
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-1"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.5"},
+ },
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-2"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.2"},
+ },
+ },
+ // Summary: "查询返回了 2 个时间序列",
+ }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to profile"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to profile"`
+ DurationSeconds int `json:"durationSeconds" jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+ CPUTimePercentage float64 `json:"cpuTimePercentage"`
+ StackTrace []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+ ToolName string `json:"toolName"`
+ Status string `json:"status"`
+ TotalSamples int `json:"totalSamples"`
+ Hotspots []PerformanceHotspot `json:"hotspots"`
+ Summary string `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+ return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, error) {
+ log.Printf("Tool 'application_performance_profiling' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return ApplicationPerformanceProfilingOutput{
+ ToolName: "application_performance_profiling",
+ Status: "completed",
+ TotalSamples: 10000,
+ Hotspots: []PerformanceHotspot{
+ {
+ CPUTimePercentage: 45.5,
+ StackTrace: []string{
+ "com.example.OrderService.processOrder()",
+ "com.example.DatabaseClient.query()",
+ "java.sql.PreparedStatement.executeQuery()",
+ },
+ },
+ },
+ // Summary: "性能分析显示，45.5%的CPU时间消耗在数据库查询调用链上",
+ }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Java service to analyze"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ FullGcCountLastHour int `json:"fullGcCountLastHour"`
+ FullGcTimeAvgMillis int `json:"fullGcTimeAvgMillis"`
+ HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+ log.Printf("Tool 'jvm_performance_analysis' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return JVMPerformanceAnalysisOutput{
+ ToolName: "jvm_performance_analysis",
+ FullGcCountLastHour: 15,
+ FullGcTimeAvgMillis: 1200,
+ HeapUsagePercentage: 85.5,
+ // Summary: "GC activity is high, average Full GC time is 1200ms",
+ }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+ ToolName string `json:"toolName"`
+ UpstreamServices []string `json:"upstreamServices"`
+ DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) (TraceDependencyViewOutput, error) {
+ log.Printf("Tool 'trace_dependency_view' called for service: %s", input.ServiceName)
+
+ return TraceDependencyViewOutput{
+ ToolName: "trace_dependency_view",
+ UpstreamServices: []string{"api-gateway", "user-service"},
+ DownstreamServices: []string{"mysql-orders-db", "redis-cache", "payment-service"},
+ }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+ DownstreamService string `json:"downstreamService"`
+ LatencyAvgMillis int `json:"latencyAvgMillis"`
+ ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ TotalLatencyAvgMillis int `json:"totalLatencyAvgMillis"`
+ Bottlenecks []LatencyBottleneck `json:"bottlenecks"`
+ Summary string `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+ log.Printf("Tool 'trace_latency_analysis' called for service: %s", input.ServiceName)
+
+ return TraceLatencyAnalysisOutput{
+ ToolName: "trace_latency_analysis",
+ TotalLatencyAvgMillis: 3200,
+ Bottlenecks: []LatencyBottleneck{
+ {
+ DownstreamService: "mysql-orders-db",
+ LatencyAvgMillis: 3050,
+ ContributionPercentage: 95.3,
+ },
+ {
+ DownstreamService: "user-service",
+ LatencyAvgMillis: 150,
+ ContributionPercentage: 4.7,
+ },
+ },
+ // Summary: "平均总延迟为 3200ms。瓶颈已定位，95.3% 的延迟来自对下游 'mysql-orders-db' 的调用",
+ }, nil
+}
+
+// ================================================
+// Database Connection Pool Analysis Tool
+// ================================================
+
+type DatabaseConnectionPoolAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+}
+
+type DatabaseConnectionPoolAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ MaxConnections int `json:"maxConnections"`
+ ActiveConnections int `json:"activeConnections"`
+ IdleConnections int `json:"idleConnections"`
+ PendingRequests int `json:"pendingRequests"`
+ Summary string `json:"summary"`
+}
+
+func (o DatabaseConnectionPoolAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func databaseConnectionPoolAnalysis(ctx *ai.ToolContext, input DatabaseConnectionPoolAnalysisInput) (DatabaseConnectionPoolAnalysisOutput, error) {
+ log.Printf("Tool 'database_connection_pool_analysis' called for service: %s", input.ServiceName)
+
+ return DatabaseConnectionPoolAnalysisOutput{
+ ToolName: "database_connection_pool_analysis",
+ MaxConnections: 100,
+ ActiveConnections: 100,
+ IdleConnections: 0,
+ PendingRequests: 58,
+ // Summary: "数据库连接池已完全耗尽 (100/100)，当前有 58 个请求正在排队等待连接",
+ }, nil
+}
+
+// ================================================
+// Kubernetes Get Pod Resources Tool
+// ================================================
+
+type KubernetesGetPodResourcesInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Namespace string `json:"namespace" jsonschema:"required,description=The namespace of the service"`
+}
+
+type PodResource struct {
+ PodName string `json:"podName"`
+ CPUUsageCores float64 `json:"cpuUsageCores"`
+ CPURequestCores float64 `json:"cpuRequestCores"`
+ CPULimitCores float64 `json:"cpuLimitCores"`
+ MemoryUsageMi int `json:"memoryUsageMi"`
+ MemoryRequestMi int `json:"memoryRequestMi"`
+ MemoryLimitMi int `json:"memoryLimitMi"`
+}
+
+type KubernetesGetPodResourcesOutput struct {
+ ToolName string `json:"toolName"`
+ Pods []PodResource `json:"pods"`
+ Summary string `json:"summary"`
+}
+
+func (o KubernetesGetPodResourcesOutput) Tool() string {
+ return o.ToolName
+}
+
+func kubernetesGetPodResources(ctx *ai.ToolContext, input KubernetesGetPodResourcesInput) (KubernetesGetPodResourcesOutput, error) {
+ log.Printf("Tool 'kubernetes_get_pod_resources' called for service: %s in namespace: %s", input.ServiceName, input.Namespace)
+
+ return KubernetesGetPodResourcesOutput{
+ ToolName: "kubernetes_get_pod_resources",
+ Pods: []PodResource{
+ {
+ PodName: "order-service-pod-1",
+ CPUUsageCores: 0.8,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1800,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ {
+ PodName: "order-service-pod-2",
+ CPUUsageCores: 0.9,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1950,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ },
+ // Summary: "2 out of 2 pods are near their memory limits",
Review Comment:
This line is commented out but still contains a string literal. Either remove the entire line or uncomment it if the Summary field should be populated.
```suggestion
```
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ // Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
Review Comment:
This line is commented out but still contains the fmt.Sprintf call. Either remove the entire line or uncomment it if the Summary field should be populated.
```suggestion
Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
```
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ // Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+ }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+ ToolName string `json:"toolName"`
+ RequestRateQPS float64 `json:"requestRateQPS"`
+ ErrorRatePercentage float64 `json:"errorRatePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_traffic' called for service: %s", input.ServiceName)
+
+ return PrometheusServiceTrafficOutput{
+ ToolName: "prometheus_query_service_traffic",
+ RequestRateQPS: 250.0,
+ ErrorRatePercentage: 5.2,
+ // Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
+ }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+ PromqlQuery string `json:"promqlQuery" jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+ Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+ Timestamp int64 `json:"timestamp"`
+ Value string `json:"value"`
+}
+
+type TimeseriesResult struct {
+ Metric TimeseriesMetric `json:"metric"`
+ Value TimeseriesValue `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ Query string `json:"query"`
+ Results []TimeseriesResult `json:"results"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+ log.Printf("Tool 'query_timeseries_database' called with query: %s", input.PromqlQuery)
+
+ return QueryTimeseriesDatabaseOutput{
+ ToolName: "query_timeseries_database",
+ Query: input.PromqlQuery,
+ Results: []TimeseriesResult{
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-1"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.5"},
+ },
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-2"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.2"},
+ },
+ },
+ // Summary: "查询返回了 2 个时间序列",
Review Comment:
This line is commented out but still contains a string literal. Either remove the entire line or uncomment it if the Summary field should be populated.
```suggestion
Summary: "查询返回了 2 个时间序列",
```
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ // Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+ }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+ ToolName string `json:"toolName"`
+ RequestRateQPS float64 `json:"requestRateQPS"`
+ ErrorRatePercentage float64 `json:"errorRatePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_traffic' called for service: %s", input.ServiceName)
+
+ return PrometheusServiceTrafficOutput{
+ ToolName: "prometheus_query_service_traffic",
+ RequestRateQPS: 250.0,
+ ErrorRatePercentage: 5.2,
+ // Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
+ }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+ PromqlQuery string `json:"promqlQuery" jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+ Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+ Timestamp int64 `json:"timestamp"`
+ Value string `json:"value"`
+}
+
+type TimeseriesResult struct {
+ Metric TimeseriesMetric `json:"metric"`
+ Value TimeseriesValue `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ Query string `json:"query"`
+ Results []TimeseriesResult `json:"results"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+ log.Printf("Tool 'query_timeseries_database' called with query: %s", input.PromqlQuery)
+
+ return QueryTimeseriesDatabaseOutput{
+ ToolName: "query_timeseries_database",
+ Query: input.PromqlQuery,
+ Results: []TimeseriesResult{
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-1"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.5"},
+ },
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-2"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.2"},
+ },
+ },
+ // Summary: "查询返回了 2 个时间序列",
+ }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to profile"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to profile"`
+ DurationSeconds int `json:"durationSeconds" jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+ CPUTimePercentage float64 `json:"cpuTimePercentage"`
+ StackTrace []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+ ToolName string `json:"toolName"`
+ Status string `json:"status"`
+ TotalSamples int `json:"totalSamples"`
+ Hotspots []PerformanceHotspot `json:"hotspots"`
+ Summary string `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+ return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, error) {
+ log.Printf("Tool 'application_performance_profiling' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return ApplicationPerformanceProfilingOutput{
+ ToolName: "application_performance_profiling",
+ Status: "completed",
+ TotalSamples: 10000,
+ Hotspots: []PerformanceHotspot{
+ {
+ CPUTimePercentage: 45.5,
+ StackTrace: []string{
+ "com.example.OrderService.processOrder()",
+ "com.example.DatabaseClient.query()",
+ "java.sql.PreparedStatement.executeQuery()",
+ },
+ },
+ },
+ // Summary: "性能分析显示，45.5%的CPU时间消耗在数据库查询调用链上",
Review Comment:
This line is commented out but still contains a string literal. Either remove the entire line or uncomment it if the Summary field should be populated.
```suggestion
Summary: "性能分析显示，45.5%的CPU时间消耗在数据库查询调用链上",
```
##########
ai/internal/agent/flow.go:
##########
@@ -0,0 +1,157 @@
+package agent
+
+import (
+ "context"
+ "dubbo-admin-ai/config"
+ "dubbo-admin-ai/internal/schema"
+ "dubbo-admin-ai/internal/tools"
+ "errors"
+ "fmt"
+ "log"
+ "os"
+
+ "github.com/firebase/genkit/go/core/logger"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/core"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// 公开的 Flow 变量，以便在编排器中调用
+var (
+ ReActFlow *core.Flow[schema.ReActIn, schema.ReActOut, struct{}]
+ ThinkingFlow *core.Flow[schema.ThinkIn, *schema.ThinkOut, struct{}]
+ ActFlow *core.Flow[*schema.ActIn, schema.ActOut, struct{}]
+
+ ThinkPrompt *ai.Prompt
+)
+
+var g *genkit.Genkit
+
+func InitFlows(registry *genkit.Genkit) error {
+ if registry == nil {
+ return fmt.Errorf("registry is nil")
+ }
+ g = registry
+
+ data, err := os.ReadFile(config.PROMPT_DIR_PATH + "/agentSystem.prompt")
+ if err != nil {
+ return fmt.Errorf("failed to read agentSystem prompt: %w", err)
+ }
+ systemPromptText := string(data)
+
+ mockTools, err := tools.AllMockToolRef()
+ if err != nil {
+ log.Fatalf("failed to get mock mock_tools: %v", err)
+ }
+ ThinkPrompt, err = genkit.DefinePrompt(g, "agentThinking",
+ ai.WithSystem(systemPromptText),
+ ai.WithInputType(schema.ThinkIn{}),
+ ai.WithOutputType(schema.ThinkOut{}),
+ ai.WithPrompt("{{userInput}}"),
+ ai.WithTools(mockTools...),
+ ai.WithToolChoice(ai.ToolChoiceNone),
+ )
+
+ if err != nil {
+ return fmt.Errorf("failed to define agentThink prompt: %w", err)
+ }
+
+ ReActFlow = genkit.DefineFlow(g, "reAct", reAct)
+ ThinkingFlow = genkit.DefineFlow(g, "thinking", thinking)
+ ActFlow = genkit.DefineFlow(g, "act", act)
+
+ return nil
+}
+
+// Flow 的核心函数实现 `fn` (不对外导出)
+// ----------------------------------------------------------------------------
+// 1. agentOrchestrator: 总指挥/编排器的核心逻辑
+// ----------------------------------------------------------------------------
+func reAct(ctx context.Context, reActInput schema.ReActIn) (reActOut schema.ReActOut, err error) {
+ //TODO: 输入数据意图解析
+
+ thinkingInput := reActInput
+ // 主协调循环 (Reconciliation Loop)
+ for range 5 { // 设置最大循环次数
Review Comment:
The magic number 5 should be defined as a named constant to improve code readability and maintainability. Consider defining something like `const maxReActIterations = 5`.
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ // Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+ }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+ ToolName string `json:"toolName"`
+ RequestRateQPS float64 `json:"requestRateQPS"`
+ ErrorRatePercentage float64 `json:"errorRatePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_traffic' called for service: %s", input.ServiceName)
+
+ return PrometheusServiceTrafficOutput{
+ ToolName: "prometheus_query_service_traffic",
+ RequestRateQPS: 250.0,
+ ErrorRatePercentage: 5.2,
+ // Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
+ }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+ PromqlQuery string `json:"promqlQuery" jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+ Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+ Timestamp int64 `json:"timestamp"`
+ Value string `json:"value"`
+}
+
+type TimeseriesResult struct {
+ Metric TimeseriesMetric `json:"metric"`
+ Value TimeseriesValue `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ Query string `json:"query"`
+ Results []TimeseriesResult `json:"results"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+ log.Printf("Tool 'query_timeseries_database' called with query: %s", input.PromqlQuery)
+
+ return QueryTimeseriesDatabaseOutput{
+ ToolName: "query_timeseries_database",
+ Query: input.PromqlQuery,
+ Results: []TimeseriesResult{
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-1"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.5"},
+ },
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-2"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.2"},
+ },
+ },
+ // Summary: "查询返回了 2 个时间序列",
+ }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to profile"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to profile"`
+ DurationSeconds int `json:"durationSeconds" jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+ CPUTimePercentage float64 `json:"cpuTimePercentage"`
+ StackTrace []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+ ToolName string `json:"toolName"`
+ Status string `json:"status"`
+ TotalSamples int `json:"totalSamples"`
+ Hotspots []PerformanceHotspot `json:"hotspots"`
+ Summary string `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+ return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, error) {
+ log.Printf("Tool 'application_performance_profiling' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return ApplicationPerformanceProfilingOutput{
+ ToolName: "application_performance_profiling",
+ Status: "completed",
+ TotalSamples: 10000,
+ Hotspots: []PerformanceHotspot{
+ {
+ CPUTimePercentage: 45.5,
+ StackTrace: []string{
+ "com.example.OrderService.processOrder()",
+ "com.example.DatabaseClient.query()",
+ "java.sql.PreparedStatement.executeQuery()",
+ },
+ },
+ },
+ // Summary: "性能分析显示，45.5%的CPU时间消耗在数据库查询调用链上",
+ }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Java service to analyze"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ FullGcCountLastHour int `json:"fullGcCountLastHour"`
+ FullGcTimeAvgMillis int `json:"fullGcTimeAvgMillis"`
+ HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+ log.Printf("Tool 'jvm_performance_analysis' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return JVMPerformanceAnalysisOutput{
+ ToolName: "jvm_performance_analysis",
+ FullGcCountLastHour: 15,
+ FullGcTimeAvgMillis: 1200,
+ HeapUsagePercentage: 85.5,
+ // Summary: "GC activity is high, average Full GC time is 1200ms",
+ }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+ ToolName string `json:"toolName"`
+ UpstreamServices []string `json:"upstreamServices"`
+ DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) (TraceDependencyViewOutput, error) {
+ log.Printf("Tool 'trace_dependency_view' called for service: %s", input.ServiceName)
+
+ return TraceDependencyViewOutput{
+ ToolName: "trace_dependency_view",
+ UpstreamServices: []string{"api-gateway", "user-service"},
+ DownstreamServices: []string{"mysql-orders-db", "redis-cache", "payment-service"},
+ }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+ DownstreamService string `json:"downstreamService"`
+ LatencyAvgMillis int `json:"latencyAvgMillis"`
+ ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ TotalLatencyAvgMillis int `json:"totalLatencyAvgMillis"`
+ Bottlenecks []LatencyBottleneck `json:"bottlenecks"`
+ Summary string `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+ log.Printf("Tool 'trace_latency_analysis' called for service: %s", input.ServiceName)
+
+ return TraceLatencyAnalysisOutput{
+ ToolName: "trace_latency_analysis",
+ TotalLatencyAvgMillis: 3200,
+ Bottlenecks: []LatencyBottleneck{
+ {
+ DownstreamService: "mysql-orders-db",
+ LatencyAvgMillis: 3050,
+ ContributionPercentage: 95.3,
+ },
+ {
+ DownstreamService: "user-service",
+ LatencyAvgMillis: 150,
+ ContributionPercentage: 4.7,
+ },
+ },
+ // Summary: "平均总延迟为 3200ms。瓶颈已定位，95.3% 的延迟来自对下游 'mysql-orders-db' 的调用",
+ }, nil
+}
+
+// ================================================
+// Database Connection Pool Analysis Tool
+// ================================================
+
+type DatabaseConnectionPoolAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+}
+
+type DatabaseConnectionPoolAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ MaxConnections int `json:"maxConnections"`
+ ActiveConnections int `json:"activeConnections"`
+ IdleConnections int `json:"idleConnections"`
+ PendingRequests int `json:"pendingRequests"`
+ Summary string `json:"summary"`
+}
+
+func (o DatabaseConnectionPoolAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func databaseConnectionPoolAnalysis(ctx *ai.ToolContext, input DatabaseConnectionPoolAnalysisInput) (DatabaseConnectionPoolAnalysisOutput, error) {
+ log.Printf("Tool 'database_connection_pool_analysis' called for service: %s", input.ServiceName)
+
+ return DatabaseConnectionPoolAnalysisOutput{
+ ToolName: "database_connection_pool_analysis",
+ MaxConnections: 100,
+ ActiveConnections: 100,
+ IdleConnections: 0,
+ PendingRequests: 58,
+ // Summary: "数据库连接池已完全耗尽 (100/100)，当前有 58 个请求正在排队等待连接",
Review Comment:
This line is commented out but still contains a string literal. Either remove the entire line or uncomment it if the Summary field should be populated.
```suggestion
```
##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+ "fmt"
+ "log"
+
+ "github.com/firebase/genkit/go/ai"
+ "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+ Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+ Quantile float64 `json:"quantile" jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+ ToolName string `json:"toolName"`
+ Quantile float64 `json:"quantile"`
+ ValueMillis int `json:"valueMillis"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_latency' called for service: %s", input.ServiceName)
+
+ // Mock data based on the example in prompt
+ valueMillis := 3500
+ if input.ServiceName != "order-service" {
+ valueMillis = 850
+ }
+
+ return PrometheusServiceLatencyOutput{
+ ToolName: "prometheus_query_service_latency",
+ Quantile: input.Quantile,
+ ValueMillis: valueMillis,
+ // Summary: fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+ }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to query"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+ ToolName string `json:"toolName"`
+ RequestRateQPS float64 `json:"requestRateQPS"`
+ ErrorRatePercentage float64 `json:"errorRatePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+ return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+ log.Printf("Tool 'prometheus_query_service_traffic' called for service: %s", input.ServiceName)
+
+ return PrometheusServiceTrafficOutput{
+ ToolName: "prometheus_query_service_traffic",
+ RequestRateQPS: 250.0,
+ ErrorRatePercentage: 5.2,
+ // Summary: fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 5.2%%", input.ServiceName),
+ }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+ PromqlQuery string `json:"promqlQuery" jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+ Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+ Timestamp int64 `json:"timestamp"`
+ Value string `json:"value"`
+}
+
+type TimeseriesResult struct {
+ Metric TimeseriesMetric `json:"metric"`
+ Value TimeseriesValue `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ Query string `json:"query"`
+ Results []TimeseriesResult `json:"results"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+ log.Printf("Tool 'query_timeseries_database' called with query: %s", input.PromqlQuery)
+
+ return QueryTimeseriesDatabaseOutput{
+ ToolName: "query_timeseries_database",
+ Query: input.PromqlQuery,
+ Results: []TimeseriesResult{
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-1"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.5"},
+ },
+ {
+ Metric: TimeseriesMetric{Pod: "order-service-pod-2"},
+ Value: TimeseriesValue{Timestamp: 1692192000, Value: "3.2"},
+ },
+ },
+ // Summary: "查询返回了 2 个时间序列",
+ }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to profile"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to profile"`
+ DurationSeconds int `json:"durationSeconds" jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+ CPUTimePercentage float64 `json:"cpuTimePercentage"`
+ StackTrace []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+ ToolName string `json:"toolName"`
+ Status string `json:"status"`
+ TotalSamples int `json:"totalSamples"`
+ Hotspots []PerformanceHotspot `json:"hotspots"`
+ Summary string `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+ return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, error) {
+ log.Printf("Tool 'application_performance_profiling' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return ApplicationPerformanceProfilingOutput{
+ ToolName: "application_performance_profiling",
+ Status: "completed",
+ TotalSamples: 10000,
+ Hotspots: []PerformanceHotspot{
+ {
+ CPUTimePercentage: 45.5,
+ StackTrace: []string{
+ "com.example.OrderService.processOrder()",
+ "com.example.DatabaseClient.query()",
+ "java.sql.PreparedStatement.executeQuery()",
+ },
+ },
+ },
+ // Summary: "性能分析显示，45.5%的CPU时间消耗在数据库查询调用链上",
+ }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Java service to analyze"`
+ PodName string `json:"podName" jsonschema:"required,description=The specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ FullGcCountLastHour int `json:"fullGcCountLastHour"`
+ FullGcTimeAvgMillis int `json:"fullGcTimeAvgMillis"`
+ HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+ Summary string `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+ log.Printf("Tool 'jvm_performance_analysis' called for service: %s, pod: %s", input.ServiceName, input.PodName)
+
+ return JVMPerformanceAnalysisOutput{
+ ToolName: "jvm_performance_analysis",
+ FullGcCountLastHour: 15,
+ FullGcTimeAvgMillis: 1200,
+ HeapUsagePercentage: 85.5,
+ // Summary: "GC activity is high, average Full GC time is 1200ms",
+ }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+ ToolName string `json:"toolName"`
+ UpstreamServices []string `json:"upstreamServices"`
+ DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) (TraceDependencyViewOutput, error) {
+ log.Printf("Tool 'trace_dependency_view' called for service: %s", input.ServiceName)
+
+ return TraceDependencyViewOutput{
+ ToolName: "trace_dependency_view",
+ UpstreamServices: []string{"api-gateway", "user-service"},
+ DownstreamServices: []string{"mysql-orders-db", "redis-cache", "payment-service"},
+ }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+ DownstreamService string `json:"downstreamService"`
+ LatencyAvgMillis int `json:"latencyAvgMillis"`
+ ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ TotalLatencyAvgMillis int `json:"totalLatencyAvgMillis"`
+ Bottlenecks []LatencyBottleneck `json:"bottlenecks"`
+ Summary string `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+ log.Printf("Tool 'trace_latency_analysis' called for service: %s", input.ServiceName)
+
+ return TraceLatencyAnalysisOutput{
+ ToolName: "trace_latency_analysis",
+ TotalLatencyAvgMillis: 3200,
+ Bottlenecks: []LatencyBottleneck{
+ {
+ DownstreamService: "mysql-orders-db",
+ LatencyAvgMillis: 3050,
+ ContributionPercentage: 95.3,
+ },
+ {
+ DownstreamService: "user-service",
+ LatencyAvgMillis: 150,
+ ContributionPercentage: 4.7,
+ },
+ },
+ // Summary: "平均总延迟为 3200ms。瓶颈已定位，95.3% 的延迟来自对下游 'mysql-orders-db' 的调用",
+ }, nil
+}
+
+// ================================================
+// Database Connection Pool Analysis Tool
+// ================================================
+
+type DatabaseConnectionPoolAnalysisInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service to analyze"`
+}
+
+type DatabaseConnectionPoolAnalysisOutput struct {
+ ToolName string `json:"toolName"`
+ MaxConnections int `json:"maxConnections"`
+ ActiveConnections int `json:"activeConnections"`
+ IdleConnections int `json:"idleConnections"`
+ PendingRequests int `json:"pendingRequests"`
+ Summary string `json:"summary"`
+}
+
+func (o DatabaseConnectionPoolAnalysisOutput) Tool() string {
+ return o.ToolName
+}
+
+func databaseConnectionPoolAnalysis(ctx *ai.ToolContext, input DatabaseConnectionPoolAnalysisInput) (DatabaseConnectionPoolAnalysisOutput, error) {
+ log.Printf("Tool 'database_connection_pool_analysis' called for service: %s", input.ServiceName)
+
+ return DatabaseConnectionPoolAnalysisOutput{
+ ToolName: "database_connection_pool_analysis",
+ MaxConnections: 100,
+ ActiveConnections: 100,
+ IdleConnections: 0,
+ PendingRequests: 58,
+ // Summary: "数据库连接池已完全耗尽 (100/100)，当前有 58 个请求正在排队等待连接",
+ }, nil
+}
+
+// ================================================
+// Kubernetes Get Pod Resources Tool
+// ================================================
+
+type KubernetesGetPodResourcesInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Namespace string `json:"namespace" jsonschema:"required,description=The namespace of the service"`
+}
+
+type PodResource struct {
+ PodName string `json:"podName"`
+ CPUUsageCores float64 `json:"cpuUsageCores"`
+ CPURequestCores float64 `json:"cpuRequestCores"`
+ CPULimitCores float64 `json:"cpuLimitCores"`
+ MemoryUsageMi int `json:"memoryUsageMi"`
+ MemoryRequestMi int `json:"memoryRequestMi"`
+ MemoryLimitMi int `json:"memoryLimitMi"`
+}
+
+type KubernetesGetPodResourcesOutput struct {
+ ToolName string `json:"toolName"`
+ Pods []PodResource `json:"pods"`
+ Summary string `json:"summary"`
+}
+
+func (o KubernetesGetPodResourcesOutput) Tool() string {
+ return o.ToolName
+}
+
+func kubernetesGetPodResources(ctx *ai.ToolContext, input KubernetesGetPodResourcesInput) (KubernetesGetPodResourcesOutput, error) {
+ log.Printf("Tool 'kubernetes_get_pod_resources' called for service: %s in namespace: %s", input.ServiceName, input.Namespace)
+
+ return KubernetesGetPodResourcesOutput{
+ ToolName: "kubernetes_get_pod_resources",
+ Pods: []PodResource{
+ {
+ PodName: "order-service-pod-1",
+ CPUUsageCores: 0.8,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1800,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ {
+ PodName: "order-service-pod-2",
+ CPUUsageCores: 0.9,
+ CPURequestCores: 0.5,
+ CPULimitCores: 1.0,
+ MemoryUsageMi: 1950,
+ MemoryRequestMi: 1024,
+ MemoryLimitMi: 2048,
+ },
+ },
+ // Summary: "2 out of 2 pods are near their memory limits",
+ }, nil
+}
+
+// ================================================
+// Dubbo Service Status Tool
+// ================================================
+
+type DubboServiceStatusInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the Dubbo service"`
+}
+
+type DubboProvider struct {
+ IP string `json:"ip"`
+ Port int `json:"port"`
+ Status string `json:"status"`
+}
+
+type DubboConsumer struct {
+ IP string `json:"ip"`
+ Application string `json:"application"`
+ Status string `json:"status"`
+}
+
+type DubboServiceStatusOutput struct {
+ ToolName string `json:"toolName"`
+ Providers []DubboProvider `json:"providers"`
+ Consumers []DubboConsumer `json:"consumers"`
+}
+
+func (o DubboServiceStatusOutput) Tool() string {
+ return o.ToolName
+}
+
+func dubboServiceStatus(ctx *ai.ToolContext, input DubboServiceStatusInput) (DubboServiceStatusOutput, error) {
+ log.Printf("Tool 'dubbo_service_status' called for service: %s", input.ServiceName)
+
+ return DubboServiceStatusOutput{
+ ToolName: "dubbo_service_status",
+ Providers: []DubboProvider{
+ {IP: "192.168.1.10", Port: 20880, Status: "healthy"},
+ {IP: "192.168.1.11", Port: 20880, Status: "healthy"},
+ },
+ Consumers: []DubboConsumer{
+ {IP: "192.168.1.20", Application: "web-frontend", Status: "connected"},
+ {IP: "192.168.1.21", Application: "api-gateway", Status: "connected"},
+ },
+ }, nil
+}
+
+// ================================================
+// Query Log Database Tool
+// ================================================
+
+type QueryLogDatabaseInput struct {
+ ServiceName string `json:"serviceName" jsonschema:"required,description=The name of the service"`
+ Keyword string `json:"keyword" jsonschema:"required,description=Keyword to search for"`
+ TimeRangeMinutes int `json:"timeRangeMinutes" jsonschema:"required,description=Time range in minutes"`
+}
+
+type LogEntry struct {
+ Timestamp string `json:"timestamp"`
+ Level string `json:"level"`
+ Message string `json:"message"`
+}
+
+type QueryLogDatabaseOutput struct {
+ ToolName string `json:"toolName"`
+ TotalHits int `json:"totalHits"`
+ Logs []LogEntry `json:"logs"`
+ Summary string `json:"summary"`
+}
+
+func (o QueryLogDatabaseOutput) Tool() string {
+ return o.ToolName
+}
+
+func queryLogDatabase(ctx *ai.ToolContext, input QueryLogDatabaseInput) (QueryLogDatabaseOutput, error) {
+ log.Printf("Tool 'query_log_database' called for service: %s, keyword: %s", input.ServiceName, input.Keyword)
+
+ return QueryLogDatabaseOutput{
+ ToolName: "query_log_database",
+ TotalHits: 152,
+ Logs: []LogEntry{
+ {
+ Timestamp: "2025-08-16T15:32:05Z",
+ Level: "WARN",
+ Message: "Timeout waiting for idle object in database connection pool.",
+ },
+ {
+ Timestamp: "2025-08-16T15:32:08Z",
+ Level: "WARN",
+ Message: "Timeout waiting for idle object in database connection pool.",
+ },
+ },
+ // Summary: fmt.Sprintf("在过去%d分钟内，发现 152 条关于 '%s' 的日志条目", input.TimeRangeMinutes, input.Keyword),
+ }, nil
+}
+
+// ================================================
+// Search Archived Logs Tool
+// ================================================
+
+type SearchArchivedLogsInput struct {
+ FilePathPattern string `json:"filePathPattern" jsonschema:"required,description=File path pattern to search"`
+ GrepKeyword string `json:"grepKeyword" jsonschema:"required,description=Keyword to grep for"`
+}
+
+type MatchingLine struct {
+ FilePath string `json:"filePath"`
+ LineNumber int `json:"lineNumber"`
+ LineContent string `json:"lineContent"`
+}
+
+type SearchArchivedLogsOutput struct {
+ ToolName string `json:"toolName"`
+ FilesSearched int `json:"filesSearched"`
+ MatchingLines []MatchingLine `json:"matchingLines"`
+ Summary string `json:"summary"`
+}
+
+func (o SearchArchivedLogsOutput) Tool() string {
+ return o.ToolName
+}
+
+func searchArchivedLogs(ctx *ai.ToolContext, input SearchArchivedLogsInput) (SearchArchivedLogsOutput, error) {
+ log.Printf("Tool 'search_archived_logs' called with pattern: %s, keyword: %s", input.FilePathPattern, input.GrepKeyword)
+
+ return SearchArchivedLogsOutput{
+ ToolName: "search_archived_logs",
+ FilesSearched: 5,
+ MatchingLines: []MatchingLine{
+ {
+ FilePath: "/logs/mysql-orders-db/slow-query-2025-08-16.log.gz",
+ LineNumber: 1024,
+ LineContent: "Query_time: 25.3s | SELECT COUNT(id), SUM(price) FROM orders WHERE user_id = 'VIP_USER_123';",
+ },
+ {
+ FilePath: "/logs/mysql-orders-db/slow-query-2025-08-16.log.gz",
+ LineNumber: 1029,
+ LineContent: "Query_time: 28.1s | SELECT COUNT(id), SUM(price) FROM orders WHERE user_id = 'VIP_USER_456';",
+ },
+ },
+ // Summary: "在归档的日志文件中，发现了多条查询，搜索了 5 个文件，找到了 2 条匹配行",
Review Comment:
This line is commented out but still contains a string literal. Either remove the entire line or uncomment it if the Summary field should be populated.
```suggestion
```
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Re: [PR] [feat]: Integrating AI Agent Capabilities into dubbo-admin [dubbo-admin]
Posted by "sonarqubecloud[bot] (via GitHub)" <gi...@apache.org>.
sonarqubecloud[bot] commented on PR #1319:
URL: https://github.com/apache/dubbo-admin/pull/1319#issuecomment-3243007037
## [](https://sonarcloud.io/dashboard?id=apache_dubbo-admin&pullRequest=1319) **Quality Gate passed**
Issues
 [0 New issues](https://sonarcloud.io/project/issues?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=OPEN,CONFIRMED&sinceLeakPeriod=true)
 [0 Accepted issues](https://sonarcloud.io/project/issues?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=ACCEPTED)
Measures
 [0 Security Hotspots](https://sonarcloud.io/project/security_hotspots?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=OPEN,CONFIRMED&sinceLeakPeriod=true)
 [0.0% Coverage on New Code](https://sonarcloud.io/component_measures?id=apache_dubbo-admin&pullRequest=1319&metric=new_coverage&view=list)
 [0.0% Duplication on New Code](https://sonarcloud.io/component_measures?id=apache_dubbo-admin&pullRequest=1319&metric=new_duplicated_lines_density&view=list)
[See analysis details on SonarQube Cloud](https://sonarcloud.io/dashboard?id=apache_dubbo-admin&pullRequest=1319)
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Re: [PR] [feat]: Integrating AI Agent Capabilities into dubbo-admin [dubbo-admin]
Posted by "sonarqubecloud[bot] (via GitHub)" <gi...@apache.org>.
sonarqubecloud[bot] commented on PR #1319:
URL: https://github.com/apache/dubbo-admin/pull/1319#issuecomment-3242586304
## [](https://sonarcloud.io/dashboard?id=apache_dubbo-admin&pullRequest=1319) **Quality Gate passed**
Issues
 [0 New issues](https://sonarcloud.io/project/issues?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=OPEN,CONFIRMED&sinceLeakPeriod=true)
 [0 Accepted issues](https://sonarcloud.io/project/issues?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=ACCEPTED)
Measures
 [0 Security Hotspots](https://sonarcloud.io/project/security_hotspots?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=OPEN,CONFIRMED&sinceLeakPeriod=true)
 [0.0% Coverage on New Code](https://sonarcloud.io/component_measures?id=apache_dubbo-admin&pullRequest=1319&metric=new_coverage&view=list)
 [0.0% Duplication on New Code](https://sonarcloud.io/component_measures?id=apache_dubbo-admin&pullRequest=1319&metric=new_duplicated_lines_density&view=list)
[See analysis details on SonarQube Cloud](https://sonarcloud.io/dashboard?id=apache_dubbo-admin&pullRequest=1319)
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Re: [PR] [feat]: Integrating AI Agent Capabilities into dubbo-admin [dubbo-admin]
Posted by "sonarqubecloud[bot] (via GitHub)" <gi...@apache.org>.
sonarqubecloud[bot] commented on PR #1319:
URL: https://github.com/apache/dubbo-admin/pull/1319#issuecomment-3242341456
## [](https://sonarcloud.io/dashboard?id=apache_dubbo-admin&pullRequest=1319) **Quality Gate passed**
Issues
 [0 New issues](https://sonarcloud.io/project/issues?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=OPEN,CONFIRMED&sinceLeakPeriod=true)
 [0 Accepted issues](https://sonarcloud.io/project/issues?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=ACCEPTED)
Measures
 [0 Security Hotspots](https://sonarcloud.io/project/security_hotspots?id=apache_dubbo-admin&pullRequest=1319&issueStatuses=OPEN,CONFIRMED&sinceLeakPeriod=true)
 [0.0% Coverage on New Code](https://sonarcloud.io/component_measures?id=apache_dubbo-admin&pullRequest=1319&metric=new_coverage&view=list)
 [0.0% Duplication on New Code](https://sonarcloud.io/component_measures?id=apache_dubbo-admin&pullRequest=1319&metric=new_duplicated_lines_density&view=list)
[See analysis details on SonarQube Cloud](https://sonarcloud.io/dashboard?id=apache_dubbo-admin&pullRequest=1319)
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