M0+M1: 基建 + 用户/密钥/核心代理

后端 (Go/Gin/GORM): - 配置(viper+env)、SQLite/Postgres 迁移、argon2id、AES-GCM 渠道密钥、JWT+refresh cookie - 用户注册/登录/刷新/登出、API Key CRUD(仅存哈希、明文一次展示) - 代理网关: /v1/chat/completions、/v1/responses、/v1/models 直通 OpenAI 渠道非流式+流式(SSE 零缓冲转发), 用量捕获(chat 末块/responses completed 嵌套), OpenAI 错误格式(401/402/404/502), 余额检查 - 异步批量记账 + 余额流水 + 日聚合, admin 用户/余额/配置 API - 单测: crypto/jwt/apikey/流式 usage 提取前端 (Vue3+TS+Vite+Tailwind v4): - taste-skill 设计 tokens: 深色仪表盘, 石墨+信号铜色, Outfit+JetBrains Mono - Landing/登录/注册, 控制台(仪表盘图表/密钥管理/用量明细) - 基础组件 Button/Input/Badge/Modal, ECharts 用量图部署: docker-compose(nginx+api+postgres), 双 Dockerfile, nginx SSE 反代联调: scripts/mockupstream 本地 mock 上游, 端到端验证通过
2026-08-15 13:10:47 +08:00
commit 360c6b33a6
75 changed files with 7044 additions and 0 deletions
@@ -0,0 +1,3 @@
+module mockupstream
+
+go 1.26.5
@@ -0,0 +1,140 @@
+// mockupstream 本地 mock OpenAI 上游服务（联调代理链路，无需真实 key）。
+// 支持 /v1/chat/completions 与 /v1/responses，含流式与非流式。
+package main
+
+import (
+	"encoding/json"
+	"flag"
+	"fmt"
+	"io"
+	"log"
+	"net/http"
+	"time"
+)
+
+func main() {
+	addr := flag.String("addr", ":9000", "listen address")
+	flag.Parse()
+
+	http.HandleFunc("/v1/chat/completions", func(w http.ResponseWriter, r *http.Request) {
+		body, _ := io.ReadAll(r.Body)
+		var req struct {
+			Model  string `json:"model"`
+			Stream bool   `json:"stream"`
+		}
+		_ = json.Unmarshal(body, &req)
+		if req.Stream {
+			streamChat(w, req.Model)
+			return
+		}
+		replyChat(w, req.Model)
+	})
+
+	http.HandleFunc("/v1/responses", func(w http.ResponseWriter, r *http.Request) {
+		body, _ := io.ReadAll(r.Body)
+		var req struct {
+			Model  string `json:"model"`
+			Stream bool   `json:"stream"`
+		}
+		_ = json.Unmarshal(body, &req)
+		if req.Stream {
+			streamResponses(w, req.Model)
+			return
+		}
+		replyResponses(w, req.Model)
+	})
+
+	http.HandleFunc("/v1/models", func(w http.ResponseWriter, r *http.Request) {
+		w.Header().Set("Content-Type", "application/json")
+		fmt.Fprint(w, `{"object":"list","data":[{"id":"gpt-4o-mini","object":"model"},{"id":"gpt-4o","object":"model"}]}`)
+	})
+
+	log.Printf("mock upstream listening on %s", *addr)
+	log.Fatal(http.ListenAndServe(*addr, nil))
+}
+
+func replyChat(w http.ResponseWriter, model string) {
+	w.Header().Set("Content-Type", "application/json")
+	resp := map[string]any{
+		"id":      "chatcmpl-mock123",
+		"object":  "chat.completion",
+		"model":   model,
+		"choices": []any{map[string]any{
+			"index": 0,
+			"message": map[string]any{"role": "assistant", "content": "你好，这是 mock 上游的回复。"},
+			"finish_reason": "stop",
+		}},
+		"usage": map[string]any{"prompt_tokens": 12, "completion_tokens": 9, "total_tokens": 21},
+	}
+	_ = json.NewEncoder(w).Encode(resp)
+}
+
+func streamChat(w http.ResponseWriter, model string) {
+	w.Header().Set("Content-Type", "text/event-stream")
+	w.Header().Set("Cache-Control", "no-cache")
+	fl, _ := w.(http.Flusher)
+	chunks := []string{"你好", "，这是", " mock ", "流式回复。"}
+	for i, c := range chunks {
+		chunk := map[string]any{
+			"id": "chatcmpl-mock123", "object": "chat.completion.chunk", "model": model,
+			"choices": []any{map[string]any{
+				"index": 0,
+				"delta": map[string]any{"content": c},
+				"finish_reason": nil,
+			}},
+		}
+		if i == len(chunks)-1 {
+			chunk["choices"] = []any{map[string]any{
+				"index": 0, "delta": map[string]any{}, "finish_reason": "stop",
+			}}
+		}
+		b, _ := json.Marshal(chunk)
+		fmt.Fprintf(w, "data: %s\n\n", b)
+		fl.Flush()
+		time.Sleep(50 * time.Millisecond)
+	}
+	// usage 末块（include_usage 时返回）
+	usage := map[string]any{
+		"id": "chatcmpl-mock123", "object": "chat.completion.chunk", "model": model,
+		"choices": []any{}, "usage": map[string]any{"prompt_tokens": 12, "completion_tokens": 9, "total_tokens": 21},
+	}
+	b, _ := json.Marshal(usage)
+	fmt.Fprintf(w, "data: %s\n\n", b)
+	fmt.Fprint(w, "data: [DONE]\n\n")
+	fl.Flush()
+}
+
+func replyResponses(w http.ResponseWriter, model string) {
+	w.Header().Set("Content-Type", "application/json")
+	resp := map[string]any{
+		"id":      "resp_mock456",
+		"object":  "response",
+		"model":   model,
+		"status":  "completed",
+		"output":  []any{map[string]any{
+			"type": "message", "role": "assistant",
+			"content": []any{map[string]any{"type": "output_text", "text": "这是 Responses API 的 mock 回复。"}},
+		}},
+		"usage": map[string]any{"input_tokens": 15, "output_tokens": 11, "total_tokens": 26},
+	}
+	_ = json.NewEncoder(w).Encode(resp)
+}
+
+func streamResponses(w http.ResponseWriter, model string) {
+	w.Header().Set("Content-Type", "text/event-stream")
+	fl, _ := w.(http.Flusher)
+	events := []map[string]any{
+		{"type": "response.created", "response": map[string]any{"id": "resp_mock456", "model": model, "object": "response", "status": "in_progress"}},
+		{"type": "response.output_text.delta", "delta": "流式 Responses 内容", "item_id": "msg_1", "output_index": 0, "content_index": 0},
+		{"type": "response.completed", "response": map[string]any{
+			"id": "resp_mock456", "object": "response", "model": model, "status": "completed",
+			"usage": map[string]any{"input_tokens": 15, "output_tokens": 11, "total_tokens": 26},
+		}},
+	}
+	for _, e := range events {
+		b, _ := json.Marshal(e)
+		fmt.Fprintf(w, "event: %s\ndata: %s\n\n", e["type"], b)
+		fl.Flush()
+		time.Sleep(50 * time.Millisecond)
+	}
+}