package main import ( "bufio" "bytes" "encoding/json" "fmt" "io" "log" "net/http" "os" "regexp" "strings" "time" ) // 配置变量(从环境变量读取) var ( UPSTREAM_URL string DEFAULT_KEY string UPSTREAM_TOKEN string MODEL_NAME string PORT string DEBUG_MODE bool DEFAULT_STREAM bool ) // 思考内容处理策略 const ( THINK_TAGS_MODE = "strip" // strip: 去除
标签;think: 转为标签;raw: 保留原样 ) // 伪装前端头部(来自抓包) const ( X_FE_VERSION = "prod-fe-1.0.70" BROWSER_UA = "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/139.0.0.0 Safari/537.36 Edg/139.0.0.0" SEC_CH_UA = "\"Not;A=Brand\";v=\"99\", \"Microsoft Edge\";v=\"139\", \"Chromium\";v=\"139\"" SEC_CH_UA_MOB = "?0" SEC_CH_UA_PLAT = "\"Windows\"" ORIGIN_BASE = "https://chat.z.ai" ) // 匿名token开关 const ANON_TOKEN_ENABLED = true // 从环境变量初始化配置 func initConfig() { UPSTREAM_URL = getEnv("UPSTREAM_URL", "https://chat.z.ai/api/chat/completions") DEFAULT_KEY = getEnv("DEFAULT_KEY", "sk-your-key") UPSTREAM_TOKEN = getEnv("UPSTREAM_TOKEN", "eyJhbGciOiJFUzI1NiIsInR5cCI6IkpXVCJ9.eyJpZCI6IjMxNmJjYjQ4LWZmMmYtNGExNS04NTNkLWYyYTI5YjY3ZmYwZiIsImVtYWlsIjoiR3Vlc3QtMTc1NTg0ODU4ODc4OEBndWVzdC5jb20ifQ.PktllDySS3trlyuFpTeIZf-7hl8Qu1qYF3BxjgIul0BrNux2nX9hVzIjthLXKMWAf9V0qM8Vm_iyDqkjPGsaiQ") MODEL_NAME = getEnv("MODEL_NAME", "GLM-4.5") PORT = getEnv("PORT", "8080") // 处理PORT格式,确保有冒号前缀 if !strings.HasPrefix(PORT, ":") { PORT = ":" + PORT } DEBUG_MODE = getEnv("DEBUG_MODE", "true") == "true" DEFAULT_STREAM = getEnv("DEFAULT_STREAM", "true") == "true" } // 获取环境变量,如果不存在则返回默认值 func getEnv(key, defaultValue string) string { if value := os.Getenv(key); value != "" { return value } return defaultValue } // OpenAI 请求结构 type OpenAIRequest struct { Model string `json:"model"` Messages []Message `json:"messages"` Stream bool `json:"stream,omitempty"` Temperature float64 `json:"temperature,omitempty"` MaxTokens int `json:"max_tokens,omitempty"` } type Message struct { Role string `json:"role"` Content string `json:"content"` } // 上游请求结构 type UpstreamRequest struct { Stream bool `json:"stream"` Model string `json:"model"` Messages []Message `json:"messages"` Params map[string]interface{} `json:"params"` Features map[string]interface{} `json:"features"` BackgroundTasks map[string]bool `json:"background_tasks,omitempty"` ChatID string `json:"chat_id,omitempty"` ID string `json:"id,omitempty"` MCPServers []string `json:"mcp_servers,omitempty"` ModelItem struct { ID string `json:"id"` Name string `json:"name"` OwnedBy string `json:"owned_by"` } `json:"model_item,omitempty"` ToolServers []string `json:"tool_servers,omitempty"` Variables map[string]string `json:"variables,omitempty"` } // OpenAI 响应结构 type OpenAIResponse struct { ID string `json:"id"` Object string `json:"object"` Created int64 `json:"created"` Model string `json:"model"` Choices []Choice `json:"choices"` Usage Usage `json:"usage,omitempty"` } type Choice struct { Index int `json:"index"` Message Message `json:"message,omitempty"` Delta Delta `json:"delta,omitempty"` FinishReason string `json:"finish_reason,omitempty"` } type Delta struct { Role string `json:"role,omitempty"` Content string `json:"content,omitempty"` } type Usage struct { PromptTokens int `json:"prompt_tokens"` CompletionTokens int `json:"completion_tokens"` TotalTokens int `json:"total_tokens"` } // 上游SSE响应结构 type UpstreamData struct { Type string `json:"type"` Data struct { DeltaContent string `json:"delta_content"` Phase string `json:"phase"` Done bool `json:"done"` Usage Usage `json:"usage,omitempty"` Error *UpstreamError `json:"error,omitempty"` Inner *struct { Error *UpstreamError `json:"error,omitempty"` } `json:"data,omitempty"` } `json:"data"` Error *UpstreamError `json:"error,omitempty"` } type UpstreamError struct { Detail string `json:"detail"` Code int `json:"code"` } // 模型列表响应 type ModelsResponse struct { Object string `json:"object"` Data []Model `json:"data"` } type Model struct { ID string `json:"id"` Object string `json:"object"` Created int64 `json:"created"` OwnedBy string `json:"owned_by"` } // debug日志函数 func debugLog(format string, args ...interface{}) { if DEBUG_MODE { log.Printf("[DEBUG] "+format, args...) } } // 获取匿名token(每次对话使用不同token,避免共享记忆) func getAnonymousToken() (string, error) { client := &http.Client{Timeout: 10 * time.Second} req, err := http.NewRequest("GET", ORIGIN_BASE+"/api/v1/auths/", nil) if err != nil { return "", err } // 伪装浏览器头 req.Header.Set("User-Agent", BROWSER_UA) req.Header.Set("Accept", "*/*") req.Header.Set("Accept-Language", "zh-CN,zh;q=0.9") req.Header.Set("X-FE-Version", X_FE_VERSION) req.Header.Set("sec-ch-ua", SEC_CH_UA) req.Header.Set("sec-ch-ua-mobile", SEC_CH_UA_MOB) req.Header.Set("sec-ch-ua-platform", SEC_CH_UA_PLAT) req.Header.Set("Origin", ORIGIN_BASE) req.Header.Set("Referer", ORIGIN_BASE+"/") resp, err := client.Do(req) if err != nil { return "", err } defer resp.Body.Close() if resp.StatusCode != http.StatusOK { return "", fmt.Errorf("anon token status=%d", resp.StatusCode) } var body struct { Token string `json:"token"` } if err := json.NewDecoder(resp.Body).Decode(&body); err != nil { return "", err } if body.Token == "" { return "", fmt.Errorf("anon token empty") } return body.Token, nil } func main() { // 初始化配置 initConfig() http.HandleFunc("/v1/models", handleModels) http.HandleFunc("/v1/chat/completions", handleChatCompletions) http.HandleFunc("/", handleOptions) log.Printf("OpenAI兼容API服务器启动在端口%s", PORT) log.Printf("模型: %s", MODEL_NAME) log.Printf("上游: %s", UPSTREAM_URL) log.Printf("Debug模式: %v", DEBUG_MODE) log.Printf("默认流式响应: %v", DEFAULT_STREAM) log.Fatal(http.ListenAndServe(PORT, nil)) } func handleOptions(w http.ResponseWriter, r *http.Request) { setCORSHeaders(w) if r.Method == "OPTIONS" { w.WriteHeader(http.StatusOK) return } w.WriteHeader(http.StatusNotFound) } func setCORSHeaders(w http.ResponseWriter) { w.Header().Set("Access-Control-Allow-Origin", "*") w.Header().Set("Access-Control-Allow-Methods", "GET, POST, PUT, DELETE, OPTIONS") w.Header().Set("Access-Control-Allow-Headers", "Content-Type, Authorization") w.Header().Set("Access-Control-Allow-Credentials", "true") } func handleModels(w http.ResponseWriter, r *http.Request) { setCORSHeaders(w) if r.Method == "OPTIONS" { w.WriteHeader(http.StatusOK) return } response := ModelsResponse{ Object: "list", Data: []Model{ { ID: MODEL_NAME, Object: "model", Created: time.Now().Unix(), OwnedBy: "z.ai", }, }, } w.Header().Set("Content-Type", "application/json") json.NewEncoder(w).Encode(response) } func handleChatCompletions(w http.ResponseWriter, r *http.Request) { setCORSHeaders(w) if r.Method == "OPTIONS" { w.WriteHeader(http.StatusOK) return } debugLog("收到chat completions请求") // 验证API Key authHeader := r.Header.Get("Authorization") if !strings.HasPrefix(authHeader, "Bearer ") { debugLog("缺少或无效的Authorization头") http.Error(w, "Missing or invalid Authorization header", http.StatusUnauthorized) return } apiKey := strings.TrimPrefix(authHeader, "Bearer ") if apiKey != DEFAULT_KEY { debugLog("无效的API key: %s", apiKey) http.Error(w, "Invalid API key", http.StatusUnauthorized) return } debugLog("API key验证通过") // 读取请求体 body, err := io.ReadAll(r.Body) if err != nil { debugLog("读取请求体失败: %v", err) http.Error(w, "Failed to read request body", http.StatusBadRequest) return } // 解析请求 var req OpenAIRequest if err := json.Unmarshal(body, &req); err != nil { debugLog("JSON解析失败: %v", err) http.Error(w, "Invalid JSON", http.StatusBadRequest) return } // 如果客户端没有明确指定stream参数,使用默认值 if !bytes.Contains(body, []byte(`"stream"`)) { req.Stream = DEFAULT_STREAM debugLog("客户端未指定stream参数,使用默认值: %v", DEFAULT_STREAM) } debugLog("请求解析成功 - 模型: %s, 流式: %v, 消息数: %d", req.Model, req.Stream, len(req.Messages)) // 生成会话相关ID chatID := fmt.Sprintf("%d-%d", time.Now().UnixNano(), time.Now().Unix()) msgID := fmt.Sprintf("%d", time.Now().UnixNano()) // 构造上游请求 upstreamReq := UpstreamRequest{ Stream: true, // 总是使用流式从上游获取 ChatID: chatID, ID: msgID, Model: "0727-360B-API", // 上游实际模型ID Messages: req.Messages, Params: map[string]interface{}{}, Features: map[string]interface{}{ "enable_thinking": true, }, BackgroundTasks: map[string]bool{ "title_generation": false, "tags_generation": false, }, MCPServers: []string{}, ModelItem: struct { ID string `json:"id"` Name string `json:"name"` OwnedBy string `json:"owned_by"` }{ID: "0727-360B-API", Name: "GLM-4.5", OwnedBy: "openai"}, ToolServers: []string{}, Variables: map[string]string{ "{{USER_NAME}}": "User", "{{USER_LOCATION}}": "Unknown", "{{CURRENT_DATETIME}}": time.Now().Format("2006-01-02 15:04:05"), }, } // 选择本次对话使用的token authToken := UPSTREAM_TOKEN if ANON_TOKEN_ENABLED { if t, err := getAnonymousToken(); err == nil { authToken = t debugLog("匿名token获取成功: %s...", func() string { if len(t) > 10 { return t[:10] } return t }()) } else { debugLog("匿名token获取失败,回退固定token: %v", err) } } // 调用上游API if req.Stream { handleStreamResponseWithIDs(w, upstreamReq, chatID, authToken) } else { handleNonStreamResponseWithIDs(w, upstreamReq, chatID, authToken) } } func callUpstreamWithHeaders(upstreamReq UpstreamRequest, refererChatID string, authToken string) (*http.Response, error) { reqBody, err := json.Marshal(upstreamReq) if err != nil { debugLog("上游请求序列化失败: %v", err) return nil, err } debugLog("调用上游API: %s", UPSTREAM_URL) debugLog("上游请求体: %s", string(reqBody)) req, err := http.NewRequest("POST", UPSTREAM_URL, bytes.NewBuffer(reqBody)) if err != nil { debugLog("创建HTTP请求失败: %v", err) return nil, err } req.Header.Set("Content-Type", "application/json") req.Header.Set("Accept", "application/json, text/event-stream") req.Header.Set("User-Agent", BROWSER_UA) req.Header.Set("Authorization", "Bearer "+authToken) req.Header.Set("Accept-Language", "zh-CN") req.Header.Set("sec-ch-ua", SEC_CH_UA) req.Header.Set("sec-ch-ua-mobile", SEC_CH_UA_MOB) req.Header.Set("sec-ch-ua-platform", SEC_CH_UA_PLAT) req.Header.Set("X-FE-Version", X_FE_VERSION) req.Header.Set("Origin", ORIGIN_BASE) req.Header.Set("Referer", ORIGIN_BASE+"/c/"+refererChatID) client := &http.Client{Timeout: 60 * time.Second} resp, err := client.Do(req) if err != nil { debugLog("上游请求失败: %v", err) return nil, err } debugLog("上游响应状态: %d %s", resp.StatusCode, resp.Status) return resp, nil } func handleStreamResponseWithIDs(w http.ResponseWriter, upstreamReq UpstreamRequest, chatID string, authToken string) { debugLog("开始处理流式响应 (chat_id=%s)", chatID) resp, err := callUpstreamWithHeaders(upstreamReq, chatID, authToken) if err != nil { debugLog("调用上游失败: %v", err) http.Error(w, "Failed to call upstream", http.StatusBadGateway) return } defer resp.Body.Close() if resp.StatusCode != http.StatusOK { debugLog("上游返回错误状态: %d", resp.StatusCode) // 读取错误响应体 if DEBUG_MODE { body, _ := io.ReadAll(resp.Body) debugLog("上游错误响应: %s", string(body)) } http.Error(w, "Upstream error", http.StatusBadGateway) return } // 用于策略2:总是展示thinking(配合标签处理) transformThinking := func(s string) string { // 去 s = regexp.MustCompile(`(?s).*?`).ReplaceAllString(s, "") // 清理残留自定义标签,如 、 等 s = strings.ReplaceAll(s, "", "") s = strings.ReplaceAll(s, "", "") s = strings.ReplaceAll(s, "", "") s = strings.TrimSpace(s) switch THINK_TAGS_MODE { case "think": s = regexp.MustCompile(`]*>`).ReplaceAllString(s, "") s = strings.ReplaceAll(s, "
", "") case "strip": s = regexp.MustCompile(`]*>`).ReplaceAllString(s, "") s = strings.ReplaceAll(s, "", "") } // 处理每行前缀 "> "(包括起始位置) s = strings.TrimPrefix(s, "> ") s = strings.ReplaceAll(s, "\n> ", "\n") return strings.TrimSpace(s) } // 设置SSE头部 w.Header().Set("Content-Type", "text/event-stream") w.Header().Set("Cache-Control", "no-cache") w.Header().Set("Connection", "keep-alive") flusher, ok := w.(http.Flusher) if !ok { http.Error(w, "Streaming unsupported", http.StatusInternalServerError) return } // 发送第一个chunk(role) firstChunk := OpenAIResponse{ ID: fmt.Sprintf("chatcmpl-%d", time.Now().Unix()), Object: "chat.completion.chunk", Created: time.Now().Unix(), Model: MODEL_NAME, Choices: []Choice{ { Index: 0, Delta: Delta{Role: "assistant"}, }, }, } writeSSEChunk(w, firstChunk) flusher.Flush() // 读取上游SSE流 debugLog("开始读取上游SSE流") scanner := bufio.NewScanner(resp.Body) lineCount := 0 for scanner.Scan() { line := scanner.Text() lineCount++ if !strings.HasPrefix(line, "data: ") { continue } dataStr := strings.TrimPrefix(line, "data: ") if dataStr == "" { continue } debugLog("收到SSE数据 (第%d行): %s", lineCount, dataStr) var upstreamData UpstreamData if err := json.Unmarshal([]byte(dataStr), &upstreamData); err != nil { debugLog("SSE数据解析失败: %v", err) continue } // 错误检测(data.error 或 data.data.error 或 顶层error) if (upstreamData.Error != nil) || (upstreamData.Data.Error != nil) || (upstreamData.Data.Inner != nil && upstreamData.Data.Inner.Error != nil) { errObj := upstreamData.Error if errObj == nil { errObj = upstreamData.Data.Error } if errObj == nil && upstreamData.Data.Inner != nil { errObj = upstreamData.Data.Inner.Error } debugLog("上游错误: code=%d, detail=%s", errObj.Code, errObj.Detail) // 结束下游流 endChunk := OpenAIResponse{ ID: fmt.Sprintf("chatcmpl-%d", time.Now().Unix()), Object: "chat.completion.chunk", Created: time.Now().Unix(), Model: MODEL_NAME, Choices: []Choice{{Index: 0, Delta: Delta{}, FinishReason: "stop"}}, } writeSSEChunk(w, endChunk) fmt.Fprintf(w, "data: [DONE]\n\n") flusher.Flush() break } debugLog("解析成功 - 类型: %s, 阶段: %s, 内容长度: %d, 完成: %v", upstreamData.Type, upstreamData.Data.Phase, len(upstreamData.Data.DeltaContent), upstreamData.Data.Done) // 策略2:总是展示thinking + answer if upstreamData.Data.DeltaContent != "" { var out = upstreamData.Data.DeltaContent if upstreamData.Data.Phase == "thinking" { out = transformThinking(out) } if out != "" { debugLog("发送内容(%s): %s", upstreamData.Data.Phase, out) chunk := OpenAIResponse{ ID: fmt.Sprintf("chatcmpl-%d", time.Now().Unix()), Object: "chat.completion.chunk", Created: time.Now().Unix(), Model: MODEL_NAME, Choices: []Choice{ { Index: 0, Delta: Delta{Content: out}, }, }, } writeSSEChunk(w, chunk) flusher.Flush() } } // 检查是否结束 if upstreamData.Data.Done || upstreamData.Data.Phase == "done" { debugLog("检测到流结束信号") // 发送结束chunk endChunk := OpenAIResponse{ ID: fmt.Sprintf("chatcmpl-%d", time.Now().Unix()), Object: "chat.completion.chunk", Created: time.Now().Unix(), Model: MODEL_NAME, Choices: []Choice{ { Index: 0, Delta: Delta{}, FinishReason: "stop", }, }, } writeSSEChunk(w, endChunk) flusher.Flush() // 发送[DONE] fmt.Fprintf(w, "data: [DONE]\n\n") flusher.Flush() debugLog("流式响应完成,共处理%d行", lineCount) break } } if err := scanner.Err(); err != nil { debugLog("扫描器错误: %v", err) } } func writeSSEChunk(w http.ResponseWriter, chunk OpenAIResponse) { data, _ := json.Marshal(chunk) fmt.Fprintf(w, "data: %s\n\n", data) } func handleNonStreamResponseWithIDs(w http.ResponseWriter, upstreamReq UpstreamRequest, chatID string, authToken string) { debugLog("开始处理非流式响应 (chat_id=%s)", chatID) resp, err := callUpstreamWithHeaders(upstreamReq, chatID, authToken) if err != nil { debugLog("调用上游失败: %v", err) http.Error(w, "Failed to call upstream", http.StatusBadGateway) return } defer resp.Body.Close() if resp.StatusCode != http.StatusOK { debugLog("上游返回错误状态: %d", resp.StatusCode) // 读取错误响应体 if DEBUG_MODE { body, _ := io.ReadAll(resp.Body) debugLog("上游错误响应: %s", string(body)) } http.Error(w, "Upstream error", http.StatusBadGateway) return } // 收集完整响应(策略2:thinking与answer都纳入,thinking转换) var fullContent strings.Builder scanner := bufio.NewScanner(resp.Body) debugLog("开始收集完整响应内容") for scanner.Scan() { line := scanner.Text() if !strings.HasPrefix(line, "data: ") { continue } dataStr := strings.TrimPrefix(line, "data: ") if dataStr == "" { continue } var upstreamData UpstreamData if err := json.Unmarshal([]byte(dataStr), &upstreamData); err != nil { continue } if upstreamData.Data.DeltaContent != "" { out := upstreamData.Data.DeltaContent if upstreamData.Data.Phase == "thinking" { out = func(s string) string { // 同步一份转换逻辑(与流式一致) s = regexp.MustCompile(`(?s).*?`).ReplaceAllString(s, "") s = strings.ReplaceAll(s, "", "") s = strings.ReplaceAll(s, "", "") s = strings.ReplaceAll(s, "", "") s = strings.TrimSpace(s) switch THINK_TAGS_MODE { case "think": s = regexp.MustCompile(`]*>`).ReplaceAllString(s, "") s = strings.ReplaceAll(s, "", "") case "strip": s = regexp.MustCompile(`]*>`).ReplaceAllString(s, "") s = strings.ReplaceAll(s, "", "") } s = strings.TrimPrefix(s, "> ") s = strings.ReplaceAll(s, "\n> ", "\n") return strings.TrimSpace(s) }(out) } if out != "" { fullContent.WriteString(out) } } if upstreamData.Data.Done || upstreamData.Data.Phase == "done" { debugLog("检测到完成信号,停止收集") break } } finalContent := fullContent.String() debugLog("内容收集完成,最终长度: %d", len(finalContent)) // 构造完整响应 response := OpenAIResponse{ ID: fmt.Sprintf("chatcmpl-%d", time.Now().Unix()), Object: "chat.completion", Created: time.Now().Unix(), Model: MODEL_NAME, Choices: []Choice{ { Index: 0, Message: Message{ Role: "assistant", Content: finalContent, }, FinishReason: "stop", }, }, Usage: Usage{ PromptTokens: 0, CompletionTokens: 0, TotalTokens: 0, }, } w.Header().Set("Content-Type", "application/json") json.NewEncoder(w).Encode(response) debugLog("非流式响应发送完成") }