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

This commit is contained in:
attacker committed 2026-06-18 08:04:27 +08:00
1 parent 94e40ebd3f
commit d4fe62f053
3 files changed
+383 -362

No files matched your search

+3 -362
View File
@@ -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"})
}
+339
View File
@@ -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"})
}