257 lines
8.9 KiB
Go
257 lines
8.9 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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// 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 := buildLLMClientFromConfig(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 := buildLLMClientFromConfig(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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// llmConfigFromTestRequest 将测试请求转为运行时配置（脱敏 Key 回退已保存值） // Logan.Li
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func (h *LLMHandler) llmConfigFromTestRequest(req model.SaveLLMConfigRequest) (model.LLMConfig, string) {
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cfg := model.LLMConfig{
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Provider: req.Provider,
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Model: req.Model,
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APIKey: req.APIKey,
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Endpoint: req.Endpoint,
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Temperature: req.Temperature,
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MaxTokens: req.MaxTokens,
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ReasoningEnabled: req.ReasoningEnabled,
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}
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if cfg.Temperature == 0 {
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cfg.Temperature = 0.7
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}
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if cfg.MaxTokens == 0 {
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cfg.MaxTokens = 8192
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}
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if strings.Contains(req.APIKey, "****") {
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var saved model.LLMConfig
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if err := h.db.First(&saved).Error; err != nil {
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if !isLocalLLMProvider(req.Provider) {
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return cfg, "请填写 API Key"
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}
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} else {
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cfg.APIKey = saved.APIKey
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}
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}
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if cfg.Provider == "" {
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return cfg, "请选择提供商"
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}
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if cfg.Model == "" {
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return cfg, "请填写模型名"
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}
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if cfg.APIKey == "" && !isLocalLLMProvider(cfg.Provider) {
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return cfg, "请填写 API Key"
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}
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return cfg, ""
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}
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// TestLLMConnection 测试 LLM 连接（支持草稿配置，保存前即可验证） // 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 req model.SaveLLMConfigRequest
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_ = c.ShouldBindJSON(&req) // 空 body 时回退已保存配置 // Logan.Li
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var cfg model.LLMConfig
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var errMsg string
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if req.Provider != "" {
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cfg, errMsg = h.llmConfigFromTestRequest(req)
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} else {
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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: "请先填写配置并测试连接"})
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return
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}
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if cfg.APIKey == "" && !isLocalLLMProvider(cfg.Provider) {
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c.JSON(http.StatusOK, model.Response{Code: 400, Message: "请填写 API Key"})
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return
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}
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}
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if errMsg != "" {
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c.JSON(http.StatusOK, model.Response{Code: 400, Message: errMsg})
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return
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}
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resp, err := buildLLMClientFromConfig(cfg).Complete(c.Request.Context(), &llm.CompletionRequest{
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Messages: []llm.Message{{Role: "user", Content: "你是什么模型？请简短回答。"}},
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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", Data: gin.H{
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"answer": resp.Message.Content,
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"model": resp.Model,
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"tokens_used": resp.Usage.TotalTokens,
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"provider": cfg.Provider,
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"reasoning_enabled": cfg.ReasoningEnabled,
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}})
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}
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