diff --git a/backend/internal/api/handlers/llm.go b/backend/internal/api/handlers/llm.go index e7cc8a3..9a4a39e 100644 --- a/backend/internal/api/handlers/llm.go +++ b/backend/internal/api/handlers/llm.go @@ -1,16 +1,10 @@ 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" @@ -130,10 +124,10 @@ func (h *LLMHandler) SaveLLMConfig(c *gin.Context) { // OpenAI 兼容请求/响应结构（仅取必要字段） // Logan.Li type openaiChatRequest struct { - Model string `json:"model"` + Model string `json:"model"` Messages []models.ChatMessage `json:"messages"` - Temperature float64 `json:"temperature"` - MaxTokens int `json:"max_tokens,omitempty"` + Temperature float64 `json:"temperature"` + MaxTokens int `json:"max_tokens,omitempty"` } type openaiChoice struct { Message models.ChatMessage `json:"message"` @@ -171,356 +165,3 @@ const defaultSystemPrompt = `你是 EZOps AIOps 智能运维助手，专注于 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。` - -// 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，data: [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"}) -} - -// 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"}) -} diff --git a/backend/internal/api/handlers/llm_chat.go b/backend/internal/api/handlers/llm_chat.go new file mode 100644 index 0000000..e93c450 --- /dev/null +++ b/backend/internal/api/handlers/llm_chat.go @@ -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"}) +} diff --git a/backend/internal/api/handlers/llm_history.go b/backend/internal/api/handlers/llm_history.go new file mode 100644 index 0000000..ca4b35f --- /dev/null +++ b/backend/internal/api/handlers/llm_history.go @@ -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"}) +}