package handlers import ( "net/http" "strings" "time" "ezops/internal/models" "github.com/gin-gonic/gin" "gorm.io/gorm" ) // LLMHandler 大语言模型配置 + 对话代理 // Logan.Li type LLMHandler struct { db *gorm.DB client *http.Client } // NewLLMHandler 创建 LLM 处理器 // Logan.Li func NewLLMHandler(db *gorm.DB) *LLMHandler { return &LLMHandler{ db: db, // 超时控制:LLM 推理可能较慢,给 120s client: &http.Client{Timeout: 120 * time.Second}, } } // maskAPIKey 脱敏 API Key(仅保留后 4 位) // Logan.Li func maskAPIKey(key string) string { if len(key) <= 4 { return strings.Repeat("*", len(key)) } return strings.Repeat("*", len(key)-4) + key[len(key)-4:] } // getActiveConfig 读取启用的配置(脱敏后) // Logan.Li func (h *LLMHandler) getActiveConfig(maskKey bool) (models.LLMConfig, error) { var cfg models.LLMConfig if err := h.db.First(&cfg).Error; err != nil { return cfg, err } if maskKey { cfg.APIKey = maskAPIKey(cfg.APIKey) } return cfg, nil } // GetLLMConfig 获取 LLM 配置(API Key 脱敏) // Logan.Li // GET /api/v1/aiops/llm-config func (h *LLMHandler) GetLLMConfig(c *gin.Context) { cfg, err := h.getActiveConfig(true) if err != nil { // 未配置返回空对象(前端渲染空表单) c.JSON(http.StatusOK, models.Response{Code: 200, Data: gin.H{ "provider": "", "model": "", "api_key": "", "endpoint": "", "temperature": 0.7, "max_tokens": 2000, "system_prompt": "", "enabled": false, "configured": false, }}) return } c.JSON(http.StatusOK, models.Response{Code: 200, Data: gin.H{ "id": cfg.ID, "provider": cfg.Provider, "model": cfg.Model, "api_key": cfg.APIKey, "endpoint": cfg.Endpoint, "temperature": cfg.Temperature, "max_tokens": cfg.MaxTokens, "system_prompt": cfg.SystemPrompt, "enabled": cfg.Enabled, "configured": true, }}) } // SaveLLMConfig 保存 LLM 配置(upsert 单行) // Logan.Li // PUT /api/v1/aiops/llm-config func (h *LLMHandler) SaveLLMConfig(c *gin.Context) { var req models.SaveLLMConfigRequest if err := c.ShouldBindJSON(&req); err != nil { c.JSON(http.StatusBadRequest, models.Response{Code: 400, Message: "请求参数错误: " + err.Error()}) return } var cfg models.LLMConfig h.db.First(&cfg) // 若前端回传脱敏值(含 ****),保留原 Key if strings.Contains(req.APIKey, "****") && cfg.ID != 0 { req.APIKey = cfg.APIKey } cfg.Provider = req.Provider cfg.Model = req.Model cfg.APIKey = req.APIKey cfg.Endpoint = req.Endpoint cfg.Temperature = req.Temperature cfg.MaxTokens = req.MaxTokens cfg.SystemPrompt = req.SystemPrompt cfg.Enabled = req.Enabled if cfg.ID == 0 { if err := h.db.Create(&cfg).Error; err != nil { c.JSON(http.StatusInternalServerError, models.Response{Code: 500, Message: "保存失败: " + err.Error()}) return } } else { if err := h.db.Save(&cfg).Error; err != nil { c.JSON(http.StatusInternalServerError, models.Response{Code: 500, Message: "保存失败: " + err.Error()}) return } } // 返回脱敏后的配置 cfg.APIKey = maskAPIKey(cfg.APIKey) c.JSON(http.StatusOK, models.Response{Code: 200, Message: "保存成功", Data: gin.H{ "id": cfg.ID, "provider": cfg.Provider, "model": cfg.Model, "api_key": cfg.APIKey, "endpoint": cfg.Endpoint, "temperature": cfg.Temperature, "max_tokens": cfg.MaxTokens, "system_prompt": cfg.SystemPrompt, "enabled": cfg.Enabled, "configured": true, }}) } // OpenAI 兼容请求/响应结构(仅取必要字段) // Logan.Li type openaiChatRequest struct { Model string `json:"model"` Messages []models.ChatMessage `json:"messages"` Temperature float64 `json:"temperature"` MaxTokens int `json:"max_tokens,omitempty"` } type openaiChoice struct { Message models.ChatMessage `json:"message"` } type openaiChatResponse struct { Choices []openaiChoice `json:"choices"` Usage struct { TotalTokens int `json:"total_tokens"` } `json:"usage"` } // resolveEndpoint 根据提供商补全默认 endpoint // Logan.Li func resolveEndpoint(provider, endpoint string) string { if endpoint != "" { return strings.TrimRight(endpoint, "/") } switch provider { case "deepseek": return "https://api.deepseek.com/v1" case "qwen": return "https://dashscope.aliyuncs.com/compatible-mode/v1" case "moonshot": return "https://api.moonshot.cn/v1" case "ollama": return "http://localhost:11434/v1" default: // openai / custom return "https://api.openai.com/v1" } } // defaultSystemPrompt AIOps 运维助手默认系统提示词 // Logan.Li const defaultSystemPrompt = `你是 AIOps 智能运维助手,专注于企业级运维场景。你可以: 1. 分析服务器、容器、K8s 集群的性能瓶颈与异常 2. 解读告警事件并给出根因分析与处置建议 3. 生成 Shell / Ansible / Python 运维脚本 4. 提供容量规划、成本优化、高可用架构建议 回答请简洁、专业、可执行,优先给出具体命令或步骤。使用中文回答。`