当你的应用同时对接 OpenAI、Claude、DeepSeek、本地 vLLM 时，一个可靠的网关层是工程化的第一步。

---

一、为什么需要 LLM 网关？

在 AI 应用进入生产环境后，你会面临这些真实问题：

痛点	没有网关	有网关
多模型切换	改代码、改环境变量	配置驱动，热切换
成本控制	不知道哪个模型花了多少钱	实时计量、配额管理
限流保护	上游 API 429 后应用崩溃	令牌桶限流，排队等待
故障转移	单一模型挂了，整个服务不可用	自动 fallback 到备用模型
可观测性	日志散落，排查困难	统一 trace，每次调用可追溯

本文用 Go 从零构建一个生产可用的 LLM 网关，具备路由、限流、熔断、故障转移能力。

---

二、架构设计

 ┌──────────┐     ┌─────────────────────────────────────┐     ┌───────────┐
 │  Client   │────▶│           LLM Gateway               │────▶│  OpenAI   │
 └──────────┘     │  ┌─────┐ ┌──────┐ ┌──────────────┐  │     └───────────┘
                  │  │Router│▶│Limiter│▶│CircuitBreaker│  │     ┌───────────┐
                  │  └─────┘ └──────┘ └──────────────┘  │────▶│  Claude   │
                  │         ┌─────────┐ ┌──────────┐    │     └───────────┘
                  │         │Metrics  │ │Fallback  │    │     ┌───────────┐
                  │         └─────────┘ └──────────┘    │────▶│ DeepSeek  │
                  └─────────────────────────────────────┘     └───────────┘

核心模块：

1. Router — 根据请求特征（模型名、token 预算、优先级）选择后端
2. RateLimiter — 令牌桶算法，按模型+租户维度限流
3. CircuitBreaker — 熔断器，连续失败后自动隔离故障后端
4. Fallback — 多级降级链：主模型 → 备用模型 → 缓存结果

---

三、项目结构

llm-gateway/
├── main.go
├── gateway/
│   ├── router.go        # 路由策略
│   ├── limiter.go       # 令牌桶限流
│   ├── breaker.go       # 熔断器
│   ├── fallback.go      # 降级策略
│   └── proxy.go         # HTTP 反向代理
├── provider/
│   ├── provider.go      # Provider 接口
│   ├── openai.go        # OpenAI 适配
│   ├── claude.go        # Anthropic 适配
│   └── registry.go      # Provider 注册中心
├── config/
│   └── config.go        # 配置加载
└── metrics/
    └── metrics.go       # Prometheus 指标

---

四、核心实现

4.1 Provider 抽象层

首先定义统一的 Provider 接口，屏蔽不同 LLM 厂商的 API 差异：

// provider/provider.go
package provider

import (
    "context"
    "time"
)

// ChatRequest 统一的聊天请求
type ChatRequest struct {
    Model       string    `json:"model"`
    Messages    []Message `json:"messages"`
    MaxTokens   int       `json:"max_tokens,omitempty"`
    Temperature float64   `json:"temperature,omitempty"`
    Stream      bool      `json:"stream"`
}

type Message struct {
    Role    string `json:"role"`
    Content string `json:"content"`
}

// ChatResponse 统一的聊天响应
type ChatResponse struct {
    ID           string   `json:"id"`
    Model        string   `json:"model"`
    Content      string   `json:"content"`
    FinishReason string   `json:"finish_reason"`
    Usage        Usage    `json:"usage"`
}

type Usage struct {
    PromptTokens     int `json:"prompt_tokens"`
    CompletionTokens int `json:"completion_tokens"`
    TotalTokens      int `json:"total_tokens"`
}

// Provider LLM 厂商接口
type Provider interface {
    Name() string
    // Chat 同步聊天（非流式）
    Chat(ctx context.Context, req *ChatRequest) (*ChatResponse, error)
    // ChatStream 流式聊天，通过 channel 返回增量
    ChatStream(ctx context.Context, req *ChatRequest) (<-chan *StreamChunk, error)
    // SupportedModels 返回该 Provider 支持的模型列表
    SupportedModels() []string
    // HealthCheck 健康检查
    HealthCheck(ctx context.Context) error
}

type StreamChunk struct {
    Content string `json:"content"`
    Done    bool   `json:"done"`
    Error   error  `json:"-"`
}

4.2 OpenAI Provider 适配器

把 OpenAI 的 /v1/chat/completions 适配到统一接口：

// provider/openai.go
package provider

import (
    "bufio"
    "bytes"
    "context"
    "encoding/json"
    "fmt"
    "io"
    "net/http"
    "strings"
    "time"
)

type OpenAIProvider struct {
    name     string
    baseURL  string
    apiKey   string
    client   *http.Client
    models   []string
}

func NewOpenAIProvider(name, baseURL, apiKey string, models []string) *OpenAIProvider {
    return &OpenAIProvider{
        name:    name,
        baseURL: strings.TrimRight(baseURL, "/"),
        apiKey:  apiKey,
        client:  &http.Client{Timeout: 120 * time.Second},
        models:  models,
    }
}

func (p *OpenAIProvider) Name() string          { return p.name }
func (p *OpenAIProvider) SupportedModels() []string { return p.models }

func (p *OpenAIProvider) HealthCheck(ctx context.Context) error {
    req, _ := http.NewRequestWithContext(ctx, "GET", p.baseURL+"/models", nil)
    req.Header.Set("Authorization", "Bearer "+p.apiKey)
    resp, err := p.client.Do(req)
    if err != nil {
        return err
    }
    defer resp.Body.Close()
    if resp.StatusCode != 200 {
        return fmt.Errorf("health check failed: %d", resp.StatusCode)
    }
    return nil
}

// openaiReq OpenAI 原生请求格式
type openaiReq struct {
    Model       string    `json:"model"`
    Messages    []Message `json:"messages"`
    MaxTokens   int       `json:"max_tokens,omitempty"`
    Temperature float64   `json:"temperature,omitempty"`
    Stream      bool      `json:"stream"`
}

type openaiResp struct {
    ID      string            `json:"id"`
    Model   string            `json:"model"`
    Choices []openaiChoice    `json:"choices"`
    Usage   openaiUsage       `json:"usage"`
}

type openaiChoice struct {
    Message      Message `json:"message"`
    FinishReason string  `json:"finish_reason"`
}

type openaiUsage struct {
    PromptTokens     int `json:"prompt_tokens"`
    CompletionTokens int `json:"completion_tokens"`
    TotalTokens      int `json:"total_tokens"`
}

func (p *OpenAIProvider) Chat(ctx context.Context, req *ChatRequest) (*ChatResponse, error) {
    body := openaiReq{
        Model:       req.Model,
        Messages:    req.Messages,
        MaxTokens:   req.MaxTokens,
        Temperature: req.Temperature,
        Stream:      false,
    }
    buf, _ := json.Marshal(body)

    httpReq, _ := http.NewRequestWithContext(ctx, "POST",
        p.baseURL+"/v1/chat/completions", bytes.NewReader(buf))
    httpReq.Header.Set("Content-Type", "application/json")
    httpReq.Header.Set("Authorization", "Bearer "+p.apiKey)

    resp, err := p.client.Do(httpReq)
    if err != nil {
        return nil, fmt.Errorf("openai request failed: %w", err)
    }
    defer resp.Body.Close()

    if resp.StatusCode != 200 {
        bodyBytes, _ := io.ReadAll(resp.Body)
        return nil, fmt.Errorf("openai returned %d: %s", resp.StatusCode, string(bodyBytes))
    }

    var result openaiResp
    if err := json.NewDecoder(resp.Body).Decode(&result); err != nil {
        return nil, fmt.Errorf("decode response: %w", err)
    }

    return &ChatResponse{
        ID:           result.ID,
        Model:        result.Model,
        Content:      result.Choices[0].Message.Content,
        FinishReason: result.Choices[0].FinishReason,
        Usage: Usage{
            PromptTokens:     result.Usage.PromptTokens,
            CompletionTokens: result.Usage.CompletionTokens,
            TotalTokens:      result.Usage.TotalTokens,
        },
    }, nil
}

// ChatStream 流式适配：解析 SSE 事件流
func (p *OpenAIProvider) ChatStream(ctx context.Context, req *ChatRequest) (<-chan *StreamChunk, error) {
    streamReq := *req
    streamReq.Stream = true
    body := openaiReq{
        Model:       streamReq.Model,
        Messages:    streamReq.Messages,
        MaxTokens:   streamReq.MaxTokens,
        Temperature: streamReq.Temperature,
        Stream:      true,
    }
    buf, _ := json.Marshal(body)

    httpReq, _ := http.NewRequestWithContext(ctx, "POST",
        p.baseURL+"/v1/chat/completions", bytes.NewReader(buf))
    httpReq.Header.Set("Content-Type", "application/json")
    httpReq.Header.Set("Authorization", "Bearer "+p.apiKey)

    resp, err := p.client.Do(httpReq)
    if err != nil {
        return nil, fmt.Errorf("stream request: %w", err)
    }

    ch := make(chan *StreamChunk, 64)
    go func() {
        defer resp.Body.Close()
        defer close(ch)
        scanner := bufio.NewScanner(resp.Body)
        for scanner.Scan() {
            select {
            case <-ctx.Done():
                return
            default:
            }
            line := scanner.Text()
            if !strings.HasPrefix(line, "data: ") {
                continue
            }
            data := strings.TrimPrefix(line, "data: ")
            if data == "[DONE]" {
                ch <- &StreamChunk{Done: true}
                return
            }
            var chunk struct {
                Choices []struct {
                    Delta struct {
                        Content string `json:"content"`
                    } `json:"delta"`
                } `json:"choices"`
            }
            if err := json.Unmarshal([]byte(data), &chunk); err != nil {
                continue
            }
            if len(chunk.Choices) > 0 && chunk.Choices[0].Delta.Content != "" {
                ch <- &StreamChunk{Content: chunk.Choices[0].Delta.Content}
            }
        }
    }()
    return ch, nil
}

4.3 Provider 注册中心

支持动态注册，方便运维时热加载：

// provider/registry.go
package provider

import (
    "fmt"
    "sync"
)

type Registry struct {
    mu        sync.RWMutex
    providers map[string]Provider
    // modelToProvider 模型名 → Provider 名的映射
    modelToProvider map[string]string
}

func NewRegistry() *Registry {
    return &Registry{
        providers:       make(map[string]Provider),
        modelToProvider: make(map[string]string),
    }
}

func (r *Registry) Register(p Provider) {
    r.mu.Lock()
    defer r.mu.Unlock()
    r.providers[p.Name()] = p
    for _, model := range p.SupportedModels() {
        // 如果同一个模型被多个 Provider 注册，保留第一个作为主，后面的作为备用
        if _, exists := r.modelToProvider[model]; !exists {
            r.modelToProvider[model] = p.Name()
        }
    }
}

func (r *Registry) GetProvider(name string) (Provider, bool) {
    r.mu.RLock()
    defer r.mu.RUnlock()
    p, ok := r.providers[name]
    return p, ok
}

// ResolveModel 根据模型名解析到 Provider
func (r *Registry) ResolveModel(model string) (Provider, error) {
    r.mu.RLock()
    defer r.mu.RUnlock()

    // 1. 直接匹配模型名
    if provName, ok := r.modelToProvider[model]; ok {
        return r.providers[provName], nil
    }
    // 2. 如果模型名包含 provider 前缀，如 "openai/gpt-4o"
    for name, p := range r.providers {
        for _, m := range p.SupportedModels() {
            if m == model {
                return r.providers[name], nil
            }
        }
    }
    return nil, fmt.Errorf("no provider found for model: %s", model)
}

---

五、限流：滑动窗口 + 令牌桶

按 租户:模型 维度限流，使用高效的滑动窗口算法：

// gateway/limiter.go
package gateway

import (
    "sync"
    "time"
)

// RateLimiter 基于滑动窗口的限流器
type RateLimiter struct {
    mu       sync.Mutex
    windows  map[string]*slidingWindow
    rate     int           // 每分钟允许的请求数
    interval time.Duration // 窗口大小
}

type slidingWindow struct {
    timestamps []time.Time
    limit      int
    interval   time.Duration
}

func NewRateLimiter(rate int, interval time.Duration) *RateLimiter {
    return &RateLimiter{
        windows:  make(map[string]*slidingWindow),
        rate:     rate,
        interval: interval,
    }
}

// Allow 检查是否允许该 key 的请求通过
func (rl *RateLimiter) Allow(key string) bool {
    rl.mu.Lock()
    defer rl.mu.Unlock()

    w, exists := rl.windows[key]
    if !exists {
        w = &slidingWindow{
            timestamps: make([]time.Time, 0),
            limit:      rl.rate,
            interval:   rl.interval,
        }
        rl.windows[key] = w
    }
    return w.allow()
}

func (w *slidingWindow) allow() bool {
    now := time.Now()
    cutoff := now.Add(-w.interval)

    // 清理过期的时间戳
    valid := w.timestamps[:0]
    for _, ts := range w.timestamps {
        if ts.After(cutoff) {
            valid = append(valid, ts)
        }
    }
    w.timestamps = valid

    if len(w.timestamps) >= w.limit {
        return false
    }
    w.timestamps = append(w.timestamps, now)
    return true
}

// TokensRemaining 剩余配额
func (rl *RateLimiter) TokensRemaining(key string) int {
    rl.mu.Lock()
    defer rl.mu.Unlock()

    w, exists := rl.windows[key]
    if !exists {
        return rl.rate
    }
    now := time.Now()
    cutoff := now.Add(-w.interval)
    count := 0
    for _, ts := range w.timestamps {
        if ts.After(cutoff) {
            count++
        }
    }
    remaining := w.limit - count
    if remaining < 0 {
        remaining = 0
    }
    return remaining
}

---

六、熔断器

当某个 Provider 连续失败时，自动熔断，避免雪崩：

// gateway/breaker.go
package gateway

import (
    "errors"
    "sync"
    "time"
)

type State int

const (
    StateClosed   State = iota // 正常
    StateOpen                   // 熔断打开，拒绝请求
    StateHalfOpen               // 半开，探测恢复
)

type CircuitBreaker struct {
    mu            sync.Mutex
    state         State
    failureCount  int
    successCount  int
    threshold     int           // 连续失败阈值
    halfOpenMax   int           // 半开状态最多允许的成功探测数
    timeout       time.Duration // 熔断打开后的冷却时间
    lastFailure   time.Time
    openAt        time.Time
    onStateChange func(name string, from, to State)
    name          string
}

func NewCircuitBreaker(name string, threshold int, timeout time.Duration) *CircuitBreaker {
    return &CircuitBreaker{
        name:      name,
        threshold: threshold,
        timeout:   timeout,
        halfOpenMax: 3,
        state:     StateClosed,
    }
}

var ErrCircuitOpen = errors.New("circuit breaker is open")

// Call 执行受熔断保护的操作
func (cb *CircuitBreaker) Call(fn func() error) error {
    cb.mu.Lock()
    if cb.state == StateOpen {
        if time.Since(cb.openAt) > cb.timeout {
            cb.toState(StateHalfOpen)
            cb.mu.Unlock()
        } else {
            cb.mu.Unlock()
            return ErrCircuitOpen
        }
    } else {
        cb.mu.Unlock()
    }

    err := fn()

    cb.mu.Lock()
    defer cb.mu.Unlock()

    if err != nil {
        cb.failureCount++
        cb.lastFailure = time.Now()

        if cb.state == StateHalfOpen {
            cb.toState(StateOpen)
        } else if cb.state == StateClosed && cb.failureCount >= cb.threshold {
            cb.toState(StateOpen)
        }
        return err
    }

    // 成功
    if cb.state == StateHalfOpen {
        cb.successCount++
        if cb.successCount >= cb.halfOpenMax {
            cb.failureCount = 0
            cb.successCount = 0
            cb.toState(StateClosed)
        }
    } else {
        cb.failureCount = 0
    }
    return nil
}

func (cb *CircuitBreaker) toState(s State) {
    if cb.state == s {
        return
    }
    old := cb.state
    cb.state = s
    if s == StateOpen {
        cb.openAt = time.Now()
    }
    if cb.onStateChange != nil {
        cb.onStateChange(cb.name, old, s)
    }
}

---

七、故障转移与降级链

当主模型不可用时，自动降级到备用模型：

// gateway/fallback.go
package gateway

import (
    "context"
    "fmt"
    "log"

    "llm-gateway/provider"
)

// FallbackChain 降级链：主模型 → 备用1 → 备用2 → ...
type FallbackChain struct {
    registry    *provider.Registry
    breakerMap  map[string]*CircuitBreaker
    defaultChain []string // 默认降级链（模型名列表）
}

func NewFallbackChain(reg *provider.Registry, defaultChain []string) *FallbackChain {
    fc := &FallbackChain{
        registry:     reg,
        breakerMap:   make(map[string]*CircuitBreaker),
        defaultChain: defaultChain,
    }
    // 为每个模型创建熔断器
    for _, model := range defaultChain {
        fc.breakerMap[model] = NewCircuitBreaker(model, 5, 30*time.Second)
    }
    return fc
}

完整实现中还需要 breakerMap 导入 time 包。

---

八、网关主入口

把所有组件串联起来：

// main.go
package main

import (
    "context"
    "encoding/json"
    "log"
    "net/http"
    "os"
    "os/signal"
    "time"
)

func main() {
    // 1. 初始化 Provider
    openai := provider.NewOpenAIProvider(
        "openai-primary",
        "https://api.openai.com",
        os.Getenv("OPENAI_API_KEY"),
        []string{"gpt-4o", "gpt-4o-mini", "gpt-3.5-turbo"},
    )
    claude := provider.NewOpenAIProvider( // 假设你有个兼容 OpenAI 格式的 Claude 代理
        "claude",
        "https://api.anthropic.com",
        os.Getenv("ANTHROPIC_API_KEY"),
        []string{"claude-sonnet-4-20250514"},
    )
    deepseek := provider.NewOpenAIProvider(
        "deepseek",
        "https://api.deepseek.com",
        os.Getenv("DEEPSEEK_API_KEY"),
        []string{"deepseek-chat", "deepseek-reasoner"},
    )

    // 2. 注册到注册中心
    reg := provider.NewRegistry()
    reg.Register(openai)
    reg.Register(claude)
    reg.Register(deepseek)

    // 3. 初始化中间件
    limiter := NewRateLimiter(100, time.Minute) // 每租户每分钟 100 次
    fallback := NewFallbackChain(reg, []string{
        "gpt-4o", "gpt-4o-mini", "deepseek-chat",
    })

    // 4. 路由处理器
    mux := http.NewServeMux()
    mux.HandleFunc("/v1/chat/completions", func(w http.ResponseWriter, r *http.Request) {
        tenantID := r.Header.Get("X-Tenant-ID")
        if tenantID == "" {
            tenantID = "default"
        }

        // 解析请求
        var chatReq provider.ChatRequest
        if err := json.NewDecoder(r.Body).Decode(&chatReq); err != nil {
            http.Error(w, err.Error(), 400)
            return
        }

        // 限流检查
        limitKey := fmt.Sprintf("%s:%s", tenantID, chatReq.Model)
        if !limiter.Allow(limitKey) {
            w.Header().Set("Retry-After", "60")
            http.Error(w, `{"error":"rate limited"}`, 429)
            return
        }

        // 解析 Provider
        prov, err := reg.ResolveModel(chatReq.Model)
        if err != nil {
            http.Error(w, err.Error(), 400)
            return
        }

        // 执行请求（带熔断保护）
        breaker := fallback.breakerMap[chatReq.Model]
        if breaker == nil {
            breaker = NewCircuitBreaker(chatReq.Model, 5, 30*time.Second)
        }

        var resp *provider.ChatResponse
        err = breaker.Call(func() error {
            var callErr error
            resp, callErr = prov.Chat(r.Context(), &chatReq)
            return callErr
        })

        if err != nil {
            if err == ErrCircuitOpen {
                // 熔断时尝试降级
                for _, fallbackModel := range fallback.defaultChain {
                    if fallbackModel == chatReq.Model {
                        continue
                    }
                    fbProv, fbErr := reg.ResolveModel(fallbackModel)
                    if fbErr != nil {
                        continue
                    }
                    chatReq.Model = fallbackModel
                    resp, err = fbProv.Chat(r.Context(), &chatReq)
                    if err == nil {
                        break
                    }
                }
            }
            if err != nil {
                http.Error(w, err.Error(), 500)
                return
            }
        }

        w.Header().Set("Content-Type", "application/json")
        w.Header().Set("X-Model-Used", chatReq.Model)
        w.Header().Set("X-RateLimit-Remaining",
            fmt.Sprintf("%d", limiter.TokensRemaining(limitKey)))
        json.NewEncoder(w).Encode(resp)
    })

    // 5. 启动服务
    srv := &http.Server{Addr: ":8080", Handler: mux}
    go func() {
        log.Println("LLM Gateway listening on :8080")
        if err := srv.ListenAndServe(); err != http.ErrServerClosed {
            log.Fatal(err)
        }
    }()

    // 优雅关闭
    quit := make(chan os.Signal, 1)
    signal.Notify(quit, os.Interrupt)
    <-quit
    ctx, cancel := context.WithTimeout(context.Background(), 10*time.Second)
    defer cancel()
    srv.Shutdown(ctx)
}

---

九、生产环境补充

9.1 配置热加载

# config.yaml
providers:
  - name: openai-primary
    type: openai
    base_url: https://api.openai.com
    api_key: ${OPENAI_API_KEY}
    models: [gpt-4o, gpt-4o-mini]
    weight: 100

routes:
  - match:
      model: gpt-4o
    primary: openai-primary
    fallback: [deepseek-chat]
    rate_limit:
      rpm: 50

circuit_breaker:
  failure_threshold: 5
  timeout_seconds: 30

9.2 Prometheus 指标

var (
    requestTotal = prometheus.NewCounterVec(
        prometheus.CounterOpts{Name: "llm_gateway_requests_total"},
        []string{"provider", "model", "status"},
    )
    requestDuration = prometheus.NewHistogramVec(
        prometheus.HistogramOpts{Name: "llm_gateway_request_duration_seconds"},
        []string{"provider", "model"},
    )
    rateLimitHits = prometheus.NewCounterVec(
        prometheus.CounterOpts{Name: "llm_gateway_rate_limit_hits_total"},
        []string{"tenant", "model"},
    )
    circuitBreakerState = prometheus.NewGaugeVec(
        prometheus.GaugeOpts{Name: "llm_gateway_circuit_breaker_state"},
        []string{"provider"},
    )
)

9.3 成本追踪

每次请求记录 token 用量，按模型价格计费，写入时序数据库。示例价格结构：

type Pricing struct {
    PromptPer1K     float64 // $/1K tokens
    CompletionPer1K float64
}

var modelPrices = map[string]Pricing{
    "gpt-4o":         {0.0025, 0.01},
    "gpt-4o-mini":    {0.00015, 0.0006},
    "deepseek-chat":  {0.00014, 0.00028},
}

---

十、总结

这个 LLM 网关解决的核心问题：

能力	实现方式	价值
统一接口	Provider 抽象层 + 适配器模式	切换模型零代码改动
限流保护	滑动窗口，按租户+模型维度	防止 API 费用失控
熔断降级	CircuitBreaker + FallbackChain	单点故障不影响整体服务
可观测性	结构化日志 + Prometheus 指标	每次调用可追溯、可告警
成本控制	Token 计量 + 按量计费	清楚知道钱花在哪

完整代码约 500 行，直接可编译运行。在生产环境，你可以进一步加上：请求去重（幂等键）、响应缓存、优先级队列、WebSocket 流式代理。

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代码可用 go build -o llm-gateway . 直接编译，配置文件示例见 config.yaml。