后端双协议: 新增 anthropic.go(Complete/Stream/工具转换) + client.go 工厂按 Protocol 路由; llm.Client 加 Stream; llm_chat 三方法收敛复用 llm.Client; resolveProtocol 按 provider 路由; Agent CLI 注入协议。编码套餐(GLM-5.2/Kimi/MiMo/Anthropic)走 Anthropic /v1/messages。 SSH凭证修复: applyCredential 正确解析凭证 JSON 的 private_key(旧实现把整个 JSON 当私钥 → ssh.ParsePrivateKey 失败 → ssh-key 登录不通); AssignCredential/批量导入/单台 CRUD 三处统一; 单台补齐 credential_id 字段(原被忽略)。 容量预测: 新增 AI 深度解读(buildCapacityInsightPrompt + PredictiveCapacityTab 按钮, 复用 aiApi.chat)。 其他: DeepSeek 模型名更新为 deepseek-v4-flash/pro; 智能助手去掉重复模型配置按钮; LLMConfig 精简生成参数(Claude Code 式)。 Co-Authored-By: Claude <noreply@anthropic.com>
208 lines
7.5 KiB
Go
208 lines
7.5 KiB
Go
package controller
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import (
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"encoding/json"
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"fmt"
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"net/http"
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"strings"
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"time"
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"ezops/middleware"
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"ezops/model"
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"ezops/pkg/agentcli/llm"
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"github.com/gin-gonic/gin"
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)
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// buildLLMClient 从数据库配置构造 LLM 客户端(按 provider 协议自动路由 OpenAI/Anthropic) // Logan.Li
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func (h *LLMHandler) buildLLMClient(cfg model.LLMConfig) llm.Client {
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return llm.NewClient(llm.Config{
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Protocol: resolveProtocol(cfg.Provider),
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Endpoint: resolveEndpoint(cfg.Provider, cfg.Endpoint),
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APIKey: cfg.APIKey,
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Model: cfg.Model,
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Temperature: cfg.Temperature,
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MaxTokens: cfg.MaxTokens,
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})
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}
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// toLLMMessages model.ChatMessage[] → llm.Message[](智能助手纯对话,仅填 Role/Content) // Logan.Li
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func toLLMMessages(msgs []model.ChatMessage) []llm.Message {
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out := make([]llm.Message, len(msgs))
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for i, m := range msgs {
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out[i] = llm.Message{Role: m.Role, Content: m.Content}
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}
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return out
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}
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// Chat AI 对话代理(统一走 llm.Client,按配置协议自动适配 OpenAI/Anthropic) // 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 model.LLMConfig
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if err := h.db.First(&cfg).Error; err != nil || !cfg.Enabled {
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c.JSON(http.StatusOK, model.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 model.ChatRequest
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if err := c.ShouldBindJSON(&req); err != nil {
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c.JSON(http.StatusBadRequest, model.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([]model.ChatMessage{{Role: "system", Content: systemPrompt}}, req.Messages...)
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resp, err := h.buildLLMClient(cfg).Complete(c.Request.Context(), &llm.CompletionRequest{
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Messages: toLLMMessages(messages),
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})
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if err != nil {
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c.JSON(http.StatusOK, model.Response{Code: 502, Message: "LLM 调用失败: " + err.Error()})
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return
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}
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replyContent := resp.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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lastUser := req.Messages[len(req.Messages)-1]
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now := time.Now()
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sid := req.SessionID // 前端传入或后端生成(兼容旧版客户端)
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if sid == "" {
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sid = fmt.Sprintf("sess-%d", now.UnixMilli())
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}
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h.db.Create(&[]model.ChatHistory{
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{UserID: uid, SessionID: sid, Role: "user", Content: lastUser.Content, CreatedAt: now},
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{UserID: uid, SessionID: sid, 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, model.Response{Code: 200, Data: model.ChatResponse{
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Content: replyContent,
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Model: cfg.Model,
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TokensUsed: resp.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 fetch-stream 消费,每条 SSE data 为 {"content": "..."};出错发 event: error;完成发 event: done。
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// 上游协议差异(OpenAI delta / Anthropic content_block_delta)由 llm.Client.Stream 屏蔽,
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// controller 只负责 SSE 转发 + 客户端断开检测 + 历史持久化。
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func (h *LLMHandler) ChatStream(c *gin.Context) {
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var cfg model.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 model.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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c.Writer.Flush() // 立即 flush 让客户端确认连接建立
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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([]model.ChatMessage{{Role: "system", Content: systemPrompt}}, req.Messages...)
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// 流式补全:逐 token 回调转发 SSE;ctx 取消(客户端断开)由 llm.Client 内部终止上游读取
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var contentBuilder strings.Builder
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_, streamErr := h.buildLLMClient(cfg).Stream(c.Request.Context(), &llm.CompletionRequest{
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Messages: toLLMMessages(messages),
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}, func(delta string) {
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contentBuilder.WriteString(delta)
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writeSSEChunk(c, delta)
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})
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fullContent := contentBuilder.String()
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// 出错且无任何内容 → 发 error 事件
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if streamErr != nil && fullContent == "" {
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writeSSEError(c, 502, "LLM 流式响应失败: "+streamErr.Error())
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return
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}
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// 持久化 + 结束事件(仅在非空且客户端未断开时入库;错误/中断不入库避免污染历史) // Logan.Li
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clientGone := c.Request.Context().Err() != nil
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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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sid := req.SessionID
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if sid == "" {
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sid = fmt.Sprintf("sess-%d", now.UnixMilli())
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}
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h.db.Create(&[]model.ChatHistory{
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{UserID: uid, SessionID: sid, Role: "user", Content: lastUser.Content, CreatedAt: now},
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{UserID: uid, SessionID: sid, Role: "assistant", Content: fullContent, Model: cfg.Model, CreatedAt: now.Add(time.Millisecond)},
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})
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}
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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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// 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 model.LLMConfig
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if err := h.db.First(&cfg).Error; err != nil {
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c.JSON(http.StatusOK, model.Response{Code: 400, Message: "请先保存配置"})
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return
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}
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_, err := h.buildLLMClient(cfg).Complete(c.Request.Context(), &llm.CompletionRequest{
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Messages: []llm.Message{{Role: "user", Content: "ping"}},
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})
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if err != nil {
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c.JSON(http.StatusOK, model.Response{Code: 502, Message: "连接失败: " + err.Error()})
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return
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}
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c.JSON(http.StatusOK, model.Response{Code: 200, Message: "连接成功"})
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}
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