refactor: 拆分 llm.go(526行) 为三文件(llm.go配置/llm_chat.go对话流式/llm_history.go历史),符合400行handler规范
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@@ -1,16 +1,10 @@
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package handlers
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package handlers
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import (
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import (
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"bufio"
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"bytes"
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"encoding/json"
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"fmt"
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"io"
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"net/http"
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"net/http"
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"strings"
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"strings"
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"time"
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"time"
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"ezops/internal/api/middleware"
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"ezops/internal/models"
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"ezops/internal/models"
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"github.com/gin-gonic/gin"
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"github.com/gin-gonic/gin"
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@@ -130,10 +124,10 @@ func (h *LLMHandler) SaveLLMConfig(c *gin.Context) {
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// OpenAI 兼容请求/响应结构（仅取必要字段） // Logan.Li
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// OpenAI 兼容请求/响应结构（仅取必要字段） // Logan.Li
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type openaiChatRequest struct {
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type openaiChatRequest struct {
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Model string `json:"model"`
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Model string `json:"model"`
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Messages []models.ChatMessage `json:"messages"`
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Messages []models.ChatMessage `json:"messages"`
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Temperature float64 `json:"temperature"`
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Temperature float64 `json:"temperature"`
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MaxTokens int `json:"max_tokens,omitempty"`
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MaxTokens int `json:"max_tokens,omitempty"`
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}
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}
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type openaiChoice struct {
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type openaiChoice struct {
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Message models.ChatMessage `json:"message"`
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Message models.ChatMessage `json:"message"`
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@@ -171,356 +165,3 @@ const defaultSystemPrompt = `你是 EZOps AIOps 智能运维助手，专注于
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3. 生成 Shell / Ansible / Python 运维脚本
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3. 生成 Shell / Ansible / Python 运维脚本
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4. 提供容量规划、成本优化、高可用架构建议
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4. 提供容量规划、成本优化、高可用架构建议
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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。`
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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。`
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// Chat AI 对话代理（OpenAI 兼容接口） // Logan.Li
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// POST /api/v1/aiops/chat
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func (h *LLMHandler) Chat(c *gin.Context) {
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var cfg models.LLMConfig
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if err := h.db.First(&cfg).Error; err != nil || !cfg.Enabled {
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c.JSON(http.StatusOK, models.Response{Code: 400, Message: "LLM 服务未配置或未启用，请在「模型配置」中完成设置"})
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return
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}
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var req models.ChatRequest
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if err := c.ShouldBindJSON(&req); err != nil {
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c.JSON(http.StatusBadRequest, models.Response{Code: 400, Message: "请求参数错误: " + err.Error()})
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return
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}
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// 组装系统提示词
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systemPrompt := cfg.SystemPrompt
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if strings.TrimSpace(systemPrompt) == "" {
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systemPrompt = defaultSystemPrompt
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}
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messages := append([]models.ChatMessage{{Role: "system", Content: systemPrompt}}, req.Messages...)
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// 构造 OpenAI 兼容请求
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payload := openaiChatRequest{
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Model: cfg.Model,
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Messages: messages,
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Temperature: cfg.Temperature,
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MaxTokens: cfg.MaxTokens,
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}
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body, _ := json.Marshal(payload)
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endpoint := resolveEndpoint(cfg.Provider, cfg.Endpoint)
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url := endpoint + "/chat/completions"
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httpReq, err := http.NewRequestWithContext(c.Request.Context(), http.MethodPost, url, bytes.NewReader(body))
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if err != nil {
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c.JSON(http.StatusOK, models.Response{Code: 500, Message: "构造请求失败: " + err.Error()})
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return
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}
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httpReq.Header.Set("Content-Type", "application/json")
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httpReq.Header.Set("Authorization", "Bearer "+cfg.APIKey)
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resp, err := h.client.Do(httpReq)
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if err != nil {
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c.JSON(http.StatusOK, models.Response{Code: 502, Message: "LLM 服务连接失败，请检查网络或 Endpoint 配置: " + err.Error()})
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return
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}
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defer resp.Body.Close()
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raw, _ := io.ReadAll(resp.Body)
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if resp.StatusCode != http.StatusOK {
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// 提取上游错误信息
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msg := fmt.Sprintf("LLM 服务返回错误 (HTTP %d)", resp.StatusCode)
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if upErr := parseOpenAIError(raw); upErr != "" {
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msg += ": " + upErr
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}
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c.JSON(http.StatusOK, models.Response{Code: resp.StatusCode, Message: msg})
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return
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}
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var chatResp openaiChatResponse
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if err := json.Unmarshal(raw, &chatResp); err != nil || len(chatResp.Choices) == 0 {
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c.JSON(http.StatusOK, models.Response{Code: 500, Message: "解析 LLM 响应失败"})
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return
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}
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replyContent := chatResp.Choices[0].Message.Content
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// 持久化对话历史（按用户隔离，成对写入 user + assistant） // Logan.Li
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// 仅在成功时入库；错误气泡为瞬时 UI 不持久化
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uid := middleware.GetUserID(c)
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if uid != 0 && len(req.Messages) > 0 {
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// 取最后一条用户消息（前端已附加当前提问）
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lastUser := req.Messages[len(req.Messages)-1]
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now := time.Now()
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h.db.Create(&[]models.ChatHistory{
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{UserID: uid, Role: "user", Content: lastUser.Content, CreatedAt: now},
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{UserID: uid, Role: "assistant", Content: replyContent, Model: cfg.Model, CreatedAt: now.Add(time.Millisecond)},
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})
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}
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c.JSON(http.StatusOK, models.Response{Code: 200, Data: models.ChatResponse{
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Content: replyContent,
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Model: cfg.Model,
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TokensUsed: chatResp.Usage.TotalTokens,
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}})
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}
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// ChatStream AI 流式对话代理（SSE） // Logan.Li
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// POST /api/v1/aiops/chat/stream
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// 客户端用 EventSource/fetch-stream 消费，每条 SSE data 为 {"content": "..."}
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// 出错时发送 event: error，data 为 {"message": "..."}
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// 完成后服务端持久化 user + assistant 两条历史，data: [DONE] 结束
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func (h *LLMHandler) ChatStream(c *gin.Context) {
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var cfg models.LLMConfig
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if err := h.db.First(&cfg).Error; err != nil || !cfg.Enabled {
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writeSSEError(c, 400, "LLM 服务未配置或未启用，请在「模型配置」中完成设置")
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return
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}
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var req models.ChatRequest
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if err := c.ShouldBindJSON(&req); err != nil {
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writeSSEError(c, 400, "请求参数错误: "+err.Error())
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return
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}
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if len(req.Messages) == 0 {
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writeSSEError(c, 400, "消息不能为空")
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return
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}
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// 设置 SSE 响应头 // Logan.Li
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c.Writer.Header().Set("Content-Type", "text/event-stream")
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c.Writer.Header().Set("Cache-Control", "no-cache")
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c.Writer.Header().Set("Connection", "keep-alive")
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c.Writer.Header().Set("X-Accel-Buffering", "no") // Nginx 关闭缓冲
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c.Writer.WriteHeader(http.StatusOK)
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// 注册写入心跳（立即 flush 一个注释行让客户端确认连接建立）
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c.Writer.Flush()
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// 组装系统提示词 + 上下文
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systemPrompt := cfg.SystemPrompt
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if strings.TrimSpace(systemPrompt) == "" {
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systemPrompt = defaultSystemPrompt
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}
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messages := append([]models.ChatMessage{{Role: "system", Content: systemPrompt}}, req.Messages...)
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// 构造 OpenAI 兼容流式请求
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payload := struct {
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Model string `json:"model"`
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Messages []models.ChatMessage `json:"messages"`
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Temperature float64 `json:"temperature"`
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MaxTokens int `json:"max_tokens,omitempty"`
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Stream bool `json:"stream"`
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}{
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Model: cfg.Model,
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Messages: messages,
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Temperature: cfg.Temperature,
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MaxTokens: cfg.MaxTokens,
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Stream: true,
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}
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body, _ := json.Marshal(payload)
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endpoint := resolveEndpoint(cfg.Provider, cfg.Endpoint)
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url := endpoint + "/chat/completions"
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httpReq, err := http.NewRequestWithContext(c.Request.Context(), http.MethodPost, url, bytes.NewReader(body))
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if err != nil {
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writeSSEError(c, 500, "构造请求失败: "+err.Error())
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return
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}
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httpReq.Header.Set("Content-Type", "application/json")
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httpReq.Header.Set("Authorization", "Bearer "+cfg.APIKey)
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httpReq.Header.Set("Accept", "text/event-stream")
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// 流式请求不能用全局 120s 超时客户端，构造无超时 client 让 ctx 控制 // Logan.Li
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streamClient := &http.Client{Timeout: 0}
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resp, err := streamClient.Do(httpReq)
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if err != nil {
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writeSSEError(c, 502, "LLM 服务连接失败，请检查网络或 Endpoint 配置: "+err.Error())
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return
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}
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defer resp.Body.Close()
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if resp.StatusCode != http.StatusOK {
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raw, _ := io.ReadAll(resp.Body)
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msg := fmt.Sprintf("LLM 服务返回错误 (HTTP %d)", resp.StatusCode)
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if e := parseOpenAIError(raw); e != "" {
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msg += ": " + e
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}
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writeSSEError(c, resp.StatusCode, msg)
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return
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}
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// 逐行解析上游 SSE，转发增量内容给前端 // Logan.Li
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var contentBuilder strings.Builder
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reader := bufio.NewReader(resp.Body)
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clientGone := false
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for {
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// 客户端断开时停止读取（c.Request.Context().Done() 在客户端断开时触发） // Logan.Li
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select {
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case <-c.Request.Context().Done():
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clientGone = true
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default:
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}
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if clientGone {
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break
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}
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line, readErr := reader.ReadString('\n')
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line = strings.TrimSpace(line)
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if line != "" {
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// 仅处理 data: 开头的行
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if strings.HasPrefix(line, "data:") {
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data := strings.TrimSpace(strings.TrimPrefix(line, "data:"))
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if data == "[DONE]" {
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// 上游结束，跳出循环准备持久化 + 发送 [DONE]
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break
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}
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// 解析 {"choices":[{"delta":{"content":"..."}}]}
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var chunk struct {
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Choices []struct {
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Delta struct {
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Content string `json:"content"`
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} `json:"delta"`
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} `json:"choices"`
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}
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if json.Unmarshal([]byte(data), &chunk) == nil && len(chunk.Choices) > 0 {
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delta := chunk.Choices[0].Delta.Content
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if delta != "" {
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contentBuilder.WriteString(delta)
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// 转发给前端：data: {"content":"..."}
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writeSSEChunk(c, delta)
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}
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}
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}
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}
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if readErr != nil {
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if readErr != io.EOF {
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// 读取出错（非正常结束）
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if contentBuilder.Len() == 0 {
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writeSSEError(c, 502, "LLM 流式响应读取失败: "+readErr.Error())
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return
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}
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// 已有部分内容则正常结束
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}
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break
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}
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}
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fullContent := contentBuilder.String()
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// 持久化对话历史（仅在成功且非空时入库；错误/中断不入库避免污染历史） // Logan.Li
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if fullContent != "" && !clientGone {
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uid := middleware.GetUserID(c)
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if uid != 0 {
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lastUser := req.Messages[len(req.Messages)-1]
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now := time.Now()
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h.db.Create(&[]models.ChatHistory{
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{UserID: uid, Role: "user", Content: lastUser.Content, CreatedAt: now},
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{UserID: uid, Role: "assistant", Content: fullContent, Model: cfg.Model, CreatedAt: now.Add(time.Millisecond)},
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})
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}
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// 发送结束标志
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c.Writer.WriteString("event: done\ndata: {\"model\":\"" + cfg.Model + "\"}\n\n")
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c.Writer.Flush()
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} else if !clientGone {
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// 无内容时通知前端结束（避免前端无限等待）
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c.Writer.WriteString("event: done\ndata: {}\n\n")
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c.Writer.Flush()
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}
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}
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// writeSSEChunk 写入一条内容增量 // Logan.Li
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func writeSSEChunk(c *gin.Context, content string) {
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// 转义为 JSON 字符串避免换行符破坏 SSE 协议
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b, _ := json.Marshal(map[string]string{"content": content})
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c.Writer.WriteString("data: " + string(b) + "\n\n")
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c.Writer.Flush()
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}
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// writeSSEError 发送一个 error 事件（写入后立即结束流） // Logan.Li
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func writeSSEError(c *gin.Context, code int, message string) {
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// 若 header 尚未写入（连接前错误），需先设置 SSE 头
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if !c.Writer.Written() {
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c.Writer.Header().Set("Content-Type", "text/event-stream")
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c.Writer.Header().Set("Cache-Control", "no-cache")
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c.Writer.Header().Set("Connection", "keep-alive")
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c.Writer.WriteHeader(http.StatusOK)
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}
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b, _ := json.Marshal(map[string]any{"code": code, "message": message})
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c.Writer.WriteString("event: error\ndata: " + string(b) + "\n\n")
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c.Writer.Flush()
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}
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// parseOpenAIError 从上游错误响应中提取 message 字段 // Logan.Li
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func parseOpenAIError(raw []byte) string {
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var m struct {
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Error struct {
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Message string `json:"message"`
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} `json:"error"`
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}
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if json.Unmarshal(raw, &m) == nil && m.Error.Message != "" {
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return m.Error.Message
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}
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return ""
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}
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// TestLLMConnection 测试 LLM 连接（发送一条 ping 消息） // Logan.Li
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// POST /api/v1/aiops/llm-config/test
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func (h *LLMHandler) TestLLMConnection(c *gin.Context) {
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var cfg models.LLMConfig
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if err := h.db.First(&cfg).Error; err != nil {
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c.JSON(http.StatusOK, models.Response{Code: 400, Message: "请先保存配置"})
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return
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}
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||||||
payload := openaiChatRequest{
|
|
||||||
Model: cfg.Model,
|
|
||||||
Messages: []models.ChatMessage{{Role: "user", Content: "ping"}},
|
|
||||||
Temperature: 0,
|
|
||||||
MaxTokens: 16,
|
|
||||||
}
|
|
||||||
body, _ := json.Marshal(payload)
|
|
||||||
endpoint := resolveEndpoint(cfg.Provider, cfg.Endpoint)
|
|
||||||
httpReq, _ := http.NewRequestWithContext(c.Request.Context(), http.MethodPost, endpoint+"/chat/completions", bytes.NewReader(body))
|
|
||||||
httpReq.Header.Set("Content-Type", "application/json")
|
|
||||||
httpReq.Header.Set("Authorization", "Bearer "+cfg.APIKey)
|
|
||||||
resp, err := h.client.Do(httpReq)
|
|
||||||
if err != nil {
|
|
||||||
c.JSON(http.StatusOK, models.Response{Code: 502, Message: "连接失败: " + err.Error()})
|
|
||||||
return
|
|
||||||
}
|
|
||||||
defer resp.Body.Close()
|
|
||||||
if resp.StatusCode != http.StatusOK {
|
|
||||||
raw, _ := io.ReadAll(resp.Body)
|
|
||||||
msg := fmt.Sprintf("HTTP %d", resp.StatusCode)
|
|
||||||
if e := parseOpenAIError(raw); e != "" {
|
|
||||||
msg += ": " + e
|
|
||||||
}
|
|
||||||
c.JSON(http.StatusOK, models.Response{Code: resp.StatusCode, Message: msg})
|
|
||||||
return
|
|
||||||
}
|
|
||||||
c.JSON(http.StatusOK, models.Response{Code: 200, Message: "连接成功"})
|
|
||||||
}
|
|
||||||
|
|
||||||
// GetChatHistory 获取当前用户的对话历史（按时间正序，仅返回最近 100 条避免过大） // Logan.Li
|
|
||||||
// GET /api/v1/aiops/chat-history
|
|
||||||
func (h *LLMHandler) GetChatHistory(c *gin.Context) {
|
|
||||||
uid := middleware.GetUserID(c)
|
|
||||||
var rows []models.ChatHistory
|
|
||||||
// 子查询取最近 100 条后再正序返回，保证前端渲染顺序正确 // Logan.Li
|
|
||||||
h.db.Where("user_id = ?", uid).
|
|
||||||
Order("id DESC").
|
|
||||||
Limit(100).
|
|
||||||
Find(&rows)
|
|
||||||
// 反转为时间正序（最早在前）
|
|
||||||
for i, j := 0, len(rows)-1; i < j; i, j = i+1, j-1 {
|
|
||||||
rows[i], rows[j] = rows[j], rows[i]
|
|
||||||
}
|
|
||||||
c.JSON(http.StatusOK, models.Response{Code: 200, Data: gin.H{
|
|
||||||
"list": rows,
|
|
||||||
"total": len(rows),
|
|
||||||
}})
|
|
||||||
}
|
|
||||||
|
|
||||||
// ClearChatHistory 清空当前用户的对话历史 // Logan.Li
|
|
||||||
// DELETE /api/v1/aiops/chat-history
|
|
||||||
func (h *LLMHandler) ClearChatHistory(c *gin.Context) {
|
|
||||||
uid := middleware.GetUserID(c)
|
|
||||||
if err := h.db.Where("user_id = ?", uid).Delete(&models.ChatHistory{}).Error; err != nil {
|
|
||||||
c.JSON(http.StatusInternalServerError, models.Response{Code: 500, Message: "清除失败: " + err.Error()})
|
|
||||||
return
|
|
||||||
}
|
|
||||||
c.JSON(http.StatusOK, models.Response{Code: 200, Message: "对话历史已清空"})
|
|
||||||
}
|
|
||||||
@@ -0,0 +1,339 @@
|
|||||||
|
package handlers
|
||||||
|
|
||||||
|
import (
|
||||||
|
"bufio"
|
||||||
|
"bytes"
|
||||||
|
"encoding/json"
|
||||||
|
"fmt"
|
||||||
|
"io"
|
||||||
|
"net/http"
|
||||||
|
"strings"
|
||||||
|
"time"
|
||||||
|
|
||||||
|
"ezops/internal/api/middleware"
|
||||||
|
"ezops/internal/models"
|
||||||
|
|
||||||
|
"github.com/gin-gonic/gin"
|
||||||
|
)
|
||||||
|
|
||||||
|
// Chat AI 对话代理（OpenAI 兼容接口） // Logan.Li
|
||||||
|
// POST /api/v1/aiops/chat
|
||||||
|
func (h *LLMHandler) Chat(c *gin.Context) {
|
||||||
|
var cfg models.LLMConfig
|
||||||
|
if err := h.db.First(&cfg).Error; err != nil || !cfg.Enabled {
|
||||||
|
c.JSON(http.StatusOK, models.Response{Code: 400, Message: "LLM 服务未配置或未启用，请在「模型配置」中完成设置"})
|
||||||
|
return
|
||||||
|
}
|
||||||
|
|
||||||
|
var req models.ChatRequest
|
||||||
|
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
|
||||||
|
}
|
||||||
|
|
||||||
|
// 组装系统提示词
|
||||||
|
systemPrompt := cfg.SystemPrompt
|
||||||
|
if strings.TrimSpace(systemPrompt) == "" {
|
||||||
|
systemPrompt = defaultSystemPrompt
|
||||||
|
}
|
||||||
|
messages := append([]models.ChatMessage{{Role: "system", Content: systemPrompt}}, req.Messages...)
|
||||||
|
|
||||||
|
// 构造 OpenAI 兼容请求
|
||||||
|
payload := openaiChatRequest{
|
||||||
|
Model: cfg.Model,
|
||||||
|
Messages: messages,
|
||||||
|
Temperature: cfg.Temperature,
|
||||||
|
MaxTokens: cfg.MaxTokens,
|
||||||
|
}
|
||||||
|
body, _ := json.Marshal(payload)
|
||||||
|
|
||||||
|
endpoint := resolveEndpoint(cfg.Provider, cfg.Endpoint)
|
||||||
|
url := endpoint + "/chat/completions"
|
||||||
|
|
||||||
|
httpReq, err := http.NewRequestWithContext(c.Request.Context(), http.MethodPost, url, bytes.NewReader(body))
|
||||||
|
if err != nil {
|
||||||
|
c.JSON(http.StatusOK, models.Response{Code: 500, Message: "构造请求失败: " + err.Error()})
|
||||||
|
return
|
||||||
|
}
|
||||||
|
httpReq.Header.Set("Content-Type", "application/json")
|
||||||
|
httpReq.Header.Set("Authorization", "Bearer "+cfg.APIKey)
|
||||||
|
|
||||||
|
resp, err := h.client.Do(httpReq)
|
||||||
|
if err != nil {
|
||||||
|
c.JSON(http.StatusOK, models.Response{Code: 502, Message: "LLM 服务连接失败，请检查网络或 Endpoint 配置: " + err.Error()})
|
||||||
|
return
|
||||||
|
}
|
||||||
|
defer resp.Body.Close()
|
||||||
|
|
||||||
|
raw, _ := io.ReadAll(resp.Body)
|
||||||
|
if resp.StatusCode != http.StatusOK {
|
||||||
|
// 提取上游错误信息
|
||||||
|
msg := fmt.Sprintf("LLM 服务返回错误 (HTTP %d)", resp.StatusCode)
|
||||||
|
if upErr := parseOpenAIError(raw); upErr != "" {
|
||||||
|
msg += ": " + upErr
|
||||||
|
}
|
||||||
|
c.JSON(http.StatusOK, models.Response{Code: resp.StatusCode, Message: msg})
|
||||||
|
return
|
||||||
|
}
|
||||||
|
|
||||||
|
var chatResp openaiChatResponse
|
||||||
|
if err := json.Unmarshal(raw, &chatResp); err != nil || len(chatResp.Choices) == 0 {
|
||||||
|
c.JSON(http.StatusOK, models.Response{Code: 500, Message: "解析 LLM 响应失败"})
|
||||||
|
return
|
||||||
|
}
|
||||||
|
replyContent := chatResp.Choices[0].Message.Content
|
||||||
|
|
||||||
|
// 持久化对话历史（按用户隔离，成对写入 user + assistant） // Logan.Li
|
||||||
|
// 仅在成功时入库；错误气泡为瞬时 UI 不持久化
|
||||||
|
uid := middleware.GetUserID(c)
|
||||||
|
if uid != 0 && len(req.Messages) > 0 {
|
||||||
|
// 取最后一条用户消息（前端已附加当前提问）
|
||||||
|
lastUser := req.Messages[len(req.Messages)-1]
|
||||||
|
now := time.Now()
|
||||||
|
h.db.Create(&[]models.ChatHistory{
|
||||||
|
{UserID: uid, Role: "user", Content: lastUser.Content, CreatedAt: now},
|
||||||
|
{UserID: uid, Role: "assistant", Content: replyContent, Model: cfg.Model, CreatedAt: now.Add(time.Millisecond)},
|
||||||
|
})
|
||||||
|
}
|
||||||
|
|
||||||
|
c.JSON(http.StatusOK, models.Response{Code: 200, Data: models.ChatResponse{
|
||||||
|
Content: replyContent,
|
||||||
|
Model: cfg.Model,
|
||||||
|
TokensUsed: chatResp.Usage.TotalTokens,
|
||||||
|
}})
|
||||||
|
}
|
||||||
|
|
||||||
|
// ChatStream AI 流式对话代理（SSE） // Logan.Li
|
||||||
|
// POST /api/v1/aiops/chat/stream
|
||||||
|
// 客户端用 EventSource/fetch-stream 消费，每条 SSE data 为 {"content": "..."}
|
||||||
|
// 出错时发送 event: error，data 为 {"message": "..."}
|
||||||
|
// 完成后服务端持久化 user + assistant 两条历史，event: done 结束
|
||||||
|
func (h *LLMHandler) ChatStream(c *gin.Context) {
|
||||||
|
var cfg models.LLMConfig
|
||||||
|
if err := h.db.First(&cfg).Error; err != nil || !cfg.Enabled {
|
||||||
|
writeSSEError(c, 400, "LLM 服务未配置或未启用，请在「模型配置」中完成设置")
|
||||||
|
return
|
||||||
|
}
|
||||||
|
|
||||||
|
var req models.ChatRequest
|
||||||
|
if err := c.ShouldBindJSON(&req); err != nil {
|
||||||
|
writeSSEError(c, 400, "请求参数错误: "+err.Error())
|
||||||
|
return
|
||||||
|
}
|
||||||
|
if len(req.Messages) == 0 {
|
||||||
|
writeSSEError(c, 400, "消息不能为空")
|
||||||
|
return
|
||||||
|
}
|
||||||
|
|
||||||
|
// 设置 SSE 响应头 // Logan.Li
|
||||||
|
c.Writer.Header().Set("Content-Type", "text/event-stream")
|
||||||
|
c.Writer.Header().Set("Cache-Control", "no-cache")
|
||||||
|
c.Writer.Header().Set("Connection", "keep-alive")
|
||||||
|
c.Writer.Header().Set("X-Accel-Buffering", "no") // Nginx 关闭缓冲
|
||||||
|
c.Writer.WriteHeader(http.StatusOK)
|
||||||
|
// 注册写入心跳（立即 flush 一个注释行让客户端确认连接建立）
|
||||||
|
c.Writer.Flush()
|
||||||
|
|
||||||
|
// 组装系统提示词 + 上下文
|
||||||
|
systemPrompt := cfg.SystemPrompt
|
||||||
|
if strings.TrimSpace(systemPrompt) == "" {
|
||||||
|
systemPrompt = defaultSystemPrompt
|
||||||
|
}
|
||||||
|
messages := append([]models.ChatMessage{{Role: "system", Content: systemPrompt}}, req.Messages...)
|
||||||
|
// 构造 OpenAI 兼容流式请求
|
||||||
|
payload := struct {
|
||||||
|
Model string `json:"model"`
|
||||||
|
Messages []models.ChatMessage `json:"messages"`
|
||||||
|
Temperature float64 `json:"temperature"`
|
||||||
|
MaxTokens int `json:"max_tokens,omitempty"`
|
||||||
|
Stream bool `json:"stream"`
|
||||||
|
}{
|
||||||
|
Model: cfg.Model,
|
||||||
|
Messages: messages,
|
||||||
|
Temperature: cfg.Temperature,
|
||||||
|
MaxTokens: cfg.MaxTokens,
|
||||||
|
Stream: true,
|
||||||
|
}
|
||||||
|
body, _ := json.Marshal(payload)
|
||||||
|
|
||||||
|
endpoint := resolveEndpoint(cfg.Provider, cfg.Endpoint)
|
||||||
|
url := endpoint + "/chat/completions"
|
||||||
|
|
||||||
|
httpReq, err := http.NewRequestWithContext(c.Request.Context(), http.MethodPost, url, bytes.NewReader(body))
|
||||||
|
if err != nil {
|
||||||
|
writeSSEError(c, 500, "构造请求失败: "+err.Error())
|
||||||
|
return
|
||||||
|
}
|
||||||
|
httpReq.Header.Set("Content-Type", "application/json")
|
||||||
|
httpReq.Header.Set("Authorization", "Bearer "+cfg.APIKey)
|
||||||
|
httpReq.Header.Set("Accept", "text/event-stream")
|
||||||
|
|
||||||
|
// 流式请求不能用全局 120s 超时客户端，构造无超时 client 让 ctx 控制 // Logan.Li
|
||||||
|
streamClient := &http.Client{Timeout: 0}
|
||||||
|
resp, err := streamClient.Do(httpReq)
|
||||||
|
if err != nil {
|
||||||
|
writeSSEError(c, 502, "LLM 服务连接失败，请检查网络或 Endpoint 配置: "+err.Error())
|
||||||
|
return
|
||||||
|
}
|
||||||
|
defer resp.Body.Close()
|
||||||
|
|
||||||
|
if resp.StatusCode != http.StatusOK {
|
||||||
|
raw, _ := io.ReadAll(resp.Body)
|
||||||
|
msg := fmt.Sprintf("LLM 服务返回错误 (HTTP %d)", resp.StatusCode)
|
||||||
|
if e := parseOpenAIError(raw); e != "" {
|
||||||
|
msg += ": " + e
|
||||||
|
}
|
||||||
|
writeSSEError(c, resp.StatusCode, msg)
|
||||||
|
return
|
||||||
|
}
|
||||||
|
|
||||||
|
// 逐行解析上游 SSE，转发增量内容给前端 // Logan.Li
|
||||||
|
var contentBuilder strings.Builder
|
||||||
|
reader := bufio.NewReader(resp.Body)
|
||||||
|
clientGone := false
|
||||||
|
for {
|
||||||
|
// 客户端断开时停止读取（c.Request.Context().Done() 在客户端断开时触发） // Logan.Li
|
||||||
|
select {
|
||||||
|
case <-c.Request.Context().Done():
|
||||||
|
clientGone = true
|
||||||
|
default:
|
||||||
|
}
|
||||||
|
if clientGone {
|
||||||
|
break
|
||||||
|
}
|
||||||
|
|
||||||
|
line, readErr := reader.ReadString('\n')
|
||||||
|
line = strings.TrimSpace(line)
|
||||||
|
if line != "" {
|
||||||
|
// 仅处理 data: 开头的行
|
||||||
|
if strings.HasPrefix(line, "data:") {
|
||||||
|
data := strings.TrimSpace(strings.TrimPrefix(line, "data:"))
|
||||||
|
if data == "[DONE]" {
|
||||||
|
// 上游结束，跳出循环准备持久化 + 发送 [DONE]
|
||||||
|
break
|
||||||
|
}
|
||||||
|
// 解析 {"choices":[{"delta":{"content":"..."}}]}
|
||||||
|
var chunk struct {
|
||||||
|
Choices []struct {
|
||||||
|
Delta struct {
|
||||||
|
Content string `json:"content"`
|
||||||
|
} `json:"delta"`
|
||||||
|
} `json:"choices"`
|
||||||
|
}
|
||||||
|
if json.Unmarshal([]byte(data), &chunk) == nil && len(chunk.Choices) > 0 {
|
||||||
|
delta := chunk.Choices[0].Delta.Content
|
||||||
|
if delta != "" {
|
||||||
|
contentBuilder.WriteString(delta)
|
||||||
|
// 转发给前端：data: {"content":"..."}
|
||||||
|
writeSSEChunk(c, delta)
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
if readErr != nil {
|
||||||
|
if readErr != io.EOF {
|
||||||
|
// 读取出错（非正常结束）
|
||||||
|
if contentBuilder.Len() == 0 {
|
||||||
|
writeSSEError(c, 502, "LLM 流式响应读取失败: "+readErr.Error())
|
||||||
|
return
|
||||||
|
}
|
||||||
|
// 已有部分内容则正常结束
|
||||||
|
}
|
||||||
|
break
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
fullContent := contentBuilder.String()
|
||||||
|
|
||||||
|
// 持久化对话历史（仅在成功且非空时入库；错误/中断不入库避免污染历史） // Logan.Li
|
||||||
|
if fullContent != "" && !clientGone {
|
||||||
|
uid := middleware.GetUserID(c)
|
||||||
|
if uid != 0 {
|
||||||
|
lastUser := req.Messages[len(req.Messages)-1]
|
||||||
|
now := time.Now()
|
||||||
|
h.db.Create(&[]models.ChatHistory{
|
||||||
|
{UserID: uid, Role: "user", Content: lastUser.Content, CreatedAt: now},
|
||||||
|
{UserID: uid, Role: "assistant", Content: fullContent, Model: cfg.Model, CreatedAt: now.Add(time.Millisecond)},
|
||||||
|
})
|
||||||
|
}
|
||||||
|
// 发送结束标志
|
||||||
|
c.Writer.WriteString("event: done\ndata: {\"model\":\"" + cfg.Model + "\"}\n\n")
|
||||||
|
c.Writer.Flush()
|
||||||
|
} else if !clientGone {
|
||||||
|
// 无内容时通知前端结束（避免前端无限等待）
|
||||||
|
c.Writer.WriteString("event: done\ndata: {}\n\n")
|
||||||
|
c.Writer.Flush()
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
// writeSSEChunk 写入一条内容增量 // Logan.Li
|
||||||
|
func writeSSEChunk(c *gin.Context, content string) {
|
||||||
|
// 转义为 JSON 字符串避免换行符破坏 SSE 协议
|
||||||
|
b, _ := json.Marshal(map[string]string{"content": content})
|
||||||
|
c.Writer.WriteString("data: " + string(b) + "\n\n")
|
||||||
|
c.Writer.Flush()
|
||||||
|
}
|
||||||
|
|
||||||
|
// writeSSEError 发送一个 error 事件（写入后立即结束流） // Logan.Li
|
||||||
|
func writeSSEError(c *gin.Context, code int, message string) {
|
||||||
|
// 若 header 尚未写入（连接前错误），需先设置 SSE 头
|
||||||
|
if !c.Writer.Written() {
|
||||||
|
c.Writer.Header().Set("Content-Type", "text/event-stream")
|
||||||
|
c.Writer.Header().Set("Cache-Control", "no-cache")
|
||||||
|
c.Writer.Header().Set("Connection", "keep-alive")
|
||||||
|
c.Writer.WriteHeader(http.StatusOK)
|
||||||
|
}
|
||||||
|
b, _ := json.Marshal(map[string]any{"code": code, "message": message})
|
||||||
|
c.Writer.WriteString("event: error\ndata: " + string(b) + "\n\n")
|
||||||
|
c.Writer.Flush()
|
||||||
|
}
|
||||||
|
|
||||||
|
// parseOpenAIError 从上游错误响应中提取 message 字段 // Logan.Li
|
||||||
|
func parseOpenAIError(raw []byte) string {
|
||||||
|
var m struct {
|
||||||
|
Error struct {
|
||||||
|
Message string `json:"message"`
|
||||||
|
} `json:"error"`
|
||||||
|
}
|
||||||
|
if json.Unmarshal(raw, &m) == nil && m.Error.Message != "" {
|
||||||
|
return m.Error.Message
|
||||||
|
}
|
||||||
|
return ""
|
||||||
|
}
|
||||||
|
|
||||||
|
// TestLLMConnection 测试 LLM 连接（发送一条 ping 消息） // Logan.Li
|
||||||
|
// POST /api/v1/aiops/llm-config/test
|
||||||
|
func (h *LLMHandler) TestLLMConnection(c *gin.Context) {
|
||||||
|
var cfg models.LLMConfig
|
||||||
|
if err := h.db.First(&cfg).Error; err != nil {
|
||||||
|
c.JSON(http.StatusOK, models.Response{Code: 400, Message: "请先保存配置"})
|
||||||
|
return
|
||||||
|
}
|
||||||
|
payload := openaiChatRequest{
|
||||||
|
Model: cfg.Model,
|
||||||
|
Messages: []models.ChatMessage{{Role: "user", Content: "ping"}},
|
||||||
|
Temperature: 0,
|
||||||
|
MaxTokens: 16,
|
||||||
|
}
|
||||||
|
body, _ := json.Marshal(payload)
|
||||||
|
endpoint := resolveEndpoint(cfg.Provider, cfg.Endpoint)
|
||||||
|
httpReq, _ := http.NewRequestWithContext(c.Request.Context(), http.MethodPost, endpoint+"/chat/completions", bytes.NewReader(body))
|
||||||
|
httpReq.Header.Set("Content-Type", "application/json")
|
||||||
|
httpReq.Header.Set("Authorization", "Bearer "+cfg.APIKey)
|
||||||
|
resp, err := h.client.Do(httpReq)
|
||||||
|
if err != nil {
|
||||||
|
c.JSON(http.StatusOK, models.Response{Code: 502, Message: "连接失败: " + err.Error()})
|
||||||
|
return
|
||||||
|
}
|
||||||
|
defer resp.Body.Close()
|
||||||
|
if resp.StatusCode != http.StatusOK {
|
||||||
|
raw, _ := io.ReadAll(resp.Body)
|
||||||
|
msg := fmt.Sprintf("HTTP %d", resp.StatusCode)
|
||||||
|
if e := parseOpenAIError(raw); e != "" {
|
||||||
|
msg += ": " + e
|
||||||
|
}
|
||||||
|
c.JSON(http.StatusOK, models.Response{Code: resp.StatusCode, Message: msg})
|
||||||
|
return
|
||||||
|
}
|
||||||
|
c.JSON(http.StatusOK, models.Response{Code: 200, Message: "连接成功"})
|
||||||
|
}
|
||||||
@@ -0,0 +1,41 @@
|
|||||||
|
package handlers
|
||||||
|
|
||||||
|
import (
|
||||||
|
"net/http"
|
||||||
|
|
||||||
|
"ezops/internal/api/middleware"
|
||||||
|
"ezops/internal/models"
|
||||||
|
|
||||||
|
"github.com/gin-gonic/gin"
|
||||||
|
)
|
||||||
|
|
||||||
|
// GetChatHistory 获取当前用户的对话历史（按时间正序，仅返回最近 100 条避免过大） // Logan.Li
|
||||||
|
// GET /api/v1/aiops/chat-history
|
||||||
|
func (h *LLMHandler) GetChatHistory(c *gin.Context) {
|
||||||
|
uid := middleware.GetUserID(c)
|
||||||
|
var rows []models.ChatHistory
|
||||||
|
// 子查询取最近 100 条后再正序返回，保证前端渲染顺序正确 // Logan.Li
|
||||||
|
h.db.Where("user_id = ?", uid).
|
||||||
|
Order("id DESC").
|
||||||
|
Limit(100).
|
||||||
|
Find(&rows)
|
||||||
|
// 反转为时间正序（最早在前）
|
||||||
|
for i, j := 0, len(rows)-1; i < j; i, j = i+1, j-1 {
|
||||||
|
rows[i], rows[j] = rows[j], rows[i]
|
||||||
|
}
|
||||||
|
c.JSON(http.StatusOK, models.Response{Code: 200, Data: gin.H{
|
||||||
|
"list": rows,
|
||||||
|
"total": len(rows),
|
||||||
|
}})
|
||||||
|
}
|
||||||
|
|
||||||
|
// ClearChatHistory 清空当前用户的对话历史 // Logan.Li
|
||||||
|
// DELETE /api/v1/aiops/chat-history
|
||||||
|
func (h *LLMHandler) ClearChatHistory(c *gin.Context) {
|
||||||
|
uid := middleware.GetUserID(c)
|
||||||
|
if err := h.db.Where("user_id = ?", uid).Delete(&models.ChatHistory{}).Error; err != nil {
|
||||||
|
c.JSON(http.StatusInternalServerError, models.Response{Code: 500, Message: "清除失败: " + err.Error()})
|
||||||
|
return
|
||||||
|
}
|
||||||
|
c.JSON(http.StatusOK, models.Response{Code: 200, Message: "对话历史已清空"})
|
||||||
|
}
|
||||||
Reference in new issue
Block a user