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refactor: move backend files to backend/ directory

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Reorganize project structure:
- backend/cmd/openteam/ — entry point
- backend/internal/ — core packages
- backend/middleware/ — HTTP middleware
- backend/router/ — route setup
- backend/wire/ — dependency injection
- backend/pkg/ — shared utilities
- backend/go.mod, go.sum — Go module files

Updated Makefile to work from backend/ directory.
Removed old lowercase makefile.
This commit is contained in:
Sakurasan
2026-08-30 12:02:52 +08:00
parent ef3025dd80
commit 902ecaeacc
64 changed files with 12 additions and 107 deletions
Download Patch File Download Diff File Expand all files Collapse all files
backend/pkg/config/config.go
+245
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package config
import (
"fmt"
"os"
"strconv"
"strings"
"time"
_ "github.com/joho/godotenv/autoload"
)
var Cfg *Config
// Config 结构体存储应用配置
type Config struct {
// 服务器配置
Port int
ReadTimeout time.Duration
WriteTimeout time.Duration
// PassKey配置
AppName string // 依赖方(Relying Party)显示名称
RPID string // 依赖方ID(通常为域名)
RPOrigins []string // 依赖方源(URL)
WebAuthnTimeout time.Duration
ChallengeExpiration time.Duration
// 数据库配置
DB_Type string
DSN string
DBMaxOpenConns int
DBMaxIdleConns int
// DBHost string
// DBPort int
// DBUser string
// DBPassword string
// DBName string
// 缓存配置
RedisHost string
RedisPort int
RedisPassword string
RedisDB int
// 日志配置
LogLevel string
LogPath string
// 其他应用特定配置
AllowRegister bool
UnlimitedQuota bool
DefaultActive bool
UsageWorker int
UsageChanSize int
TaskTimeInterval int
}
func init() {
// 加载配置
cfg, err := LoadConfig()
if err != nil {
panic(fmt.Sprintf("加载配置失败: %v", err))
}
Cfg = cfg
}
// LoadConfig 从环境变量加载配置
func LoadConfig() (*Config, error) {
cfg := &Config{
AppName: "OpenTeam",
RPID: "localhost", // 域名
RPOrigins: []string{"https://localhost:5173"},
// 默认值设置
Port: 80,
ReadTimeout: 10 * time.Second,
WriteTimeout: 10 * time.Second,
LogLevel: "info",
LogPath: "./logs/",
DB_Type: "sqlite",
DSN: "",
DBMaxOpenConns: 10,
DBMaxIdleConns: 5,
RedisDB: 0,
// 系统设置
AllowRegister: false,
UnlimitedQuota: true,
DefaultActive: true,
UsageWorker: 1,
UsageChanSize: 1000,
TaskTimeInterval: 60,
}
// PassKey配置
if appName := os.Getenv("APP_NAME"); appName != "" {
cfg.AppName = appName
}
if domain := os.Getenv("RPID"); domain != "" {
cfg.RPID = domain
}
if origin := os.Getenv("RPORIGINS"); origin != "" {
var rpos []string
list := strings.Split(origin, ",")
for _, l := range list {
trimmedl := strings.TrimSpace(l)
if trimmedl != "" {
rpos = append(rpos, trimmedl)
}
}
cfg.RPOrigins = rpos
}
// 服务器配置
if port := os.Getenv("PORT"); port != "" {
if p, err := strconv.Atoi(port); err == nil {
cfg.Port = p
} else {
return nil, fmt.Errorf("PORT: %s", port)
}
}
if timeout := os.Getenv("READ_TIMEOUT"); timeout != "" {
if t, err := strconv.Atoi(timeout); err == nil {
cfg.ReadTimeout = time.Duration(t) * time.Second
} else {
return nil, fmt.Errorf("无效的READ_TIMEOUT: %s", timeout)
}
}
if timeout := os.Getenv("WRITE_TIMEOUT"); timeout != "" {
if t, err := strconv.Atoi(timeout); err == nil {
cfg.WriteTimeout = time.Duration(t) * time.Second
} else {
return nil, fmt.Errorf("无效的WRITE_TIMEOUT: %s", timeout)
}
}
// 数据库配置
if dbType := os.Getenv("DB_TYPE"); dbType != "" {
cfg.DB_Type = dbType
} else {
cfg.DB_Type = "sqlite"
}
if dsn := os.Getenv("DB_DSN"); dsn != "" {
cfg.DSN = dsn
}
if conns := os.Getenv("DB_MAX_OPEN_CONNS"); conns != "" {
if c, err := strconv.Atoi(conns); err == nil {
cfg.DBMaxOpenConns = c
} else {
return nil, fmt.Errorf("无效的DB_MAX_OPEN_CONNS: %s", conns)
}
}
if conns := os.Getenv("DB_MAX_IDLE_CONNS"); conns != "" {
if c, err := strconv.Atoi(conns); err == nil {
cfg.DBMaxIdleConns = c
} else {
return nil, fmt.Errorf("无效的DB_MAX_IDLE_CONNS: %s", conns)
}
}
// Redis配置
if host := os.Getenv("REDIS_HOST"); host != "" {
cfg.RedisHost = host
}
if port := os.Getenv("REDIS_PORT"); port != "" {
if p, err := strconv.Atoi(port); err == nil {
cfg.RedisPort = p
} else {
return nil, fmt.Errorf("无效的REDIS_PORT: %s", port)
}
}
if password := os.Getenv("REDIS_PASSWORD"); password != "" {
cfg.RedisPassword = password
}
if db := os.Getenv("REDIS_DB"); db != "" {
if d, err := strconv.Atoi(db); err == nil {
cfg.RedisDB = d
} else {
return nil, fmt.Errorf("无效的REDIS_DB: %s", db)
}
}
// 日志配置
if level := os.Getenv("LOG_LEVEL"); level != "" {
cfg.LogLevel = level
}
if path := os.Getenv("LOG_PATH"); path != "" {
cfg.LogPath = path
}
// 功能标志
if allowRegister := os.Getenv("ALLOW_REGISTER"); allowRegister != "" {
if b, err := strconv.ParseBool(allowRegister); err == nil {
cfg.AllowRegister = b
}
}
if unlimitedQuota := os.Getenv("UNLIMITED_QUOTA"); unlimitedQuota != "" {
if b, err := strconv.ParseBool(unlimitedQuota); err == nil {
cfg.UnlimitedQuota = b
}
}
if defaultActive := os.Getenv("DEFAULT_ACTIVE"); defaultActive != "" {
if b, err := strconv.ParseBool(defaultActive); err == nil {
cfg.DefaultActive = b
}
}
if worker := os.Getenv("USAGE_WORKER"); worker != "" {
if w, err := strconv.Atoi(worker); err == nil {
cfg.UsageWorker = w
}
}
if size := os.Getenv("USAGE_CHAN_SIZE"); size != "" {
if s, err := strconv.Atoi(size); err == nil {
cfg.UsageChanSize = s
}
}
if interval := os.Getenv("TASK_TIME_INTERVAL"); interval != "" {
if i, err := strconv.Atoi(interval); err == nil {
cfg.TaskTimeInterval = i
}
}
return cfg, nil
}
backend/pkg/tokenizer/tokenizer.go
+220
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@@ -0,0 +1,220 @@
package tokenizer
import (
"fmt"
"log"
"strings"
"github.com/pkoukk/tiktoken-go"
"github.com/sashabaranov/go-openai"
)
func NumTokensFromMessages(messages []openai.ChatCompletionMessage, model string) (numTokens int) {
tkm, err := tiktoken.EncodingForModel(model)
if err != nil {
err = fmt.Errorf("EncodingForModel: %v", err)
log.Println(err)
return
}
var tokensPerMessage, tokensPerName int
switch model {
case "gpt-3.5-turbo",
"gpt-3.5-turbo-0613",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-16k-0613",
"gpt-4",
"gpt-4-0314",
"gpt-4-0613",
"gpt-4-32k",
"gpt-4-32k-0314",
"gpt-4-32k-0613":
tokensPerMessage = 3
tokensPerName = 1
case "gpt-3.5-turbo-0301":
tokensPerMessage = 4 // every message follows <|start|>{role/name}\n{content}<|end|>\n
tokensPerName = -1 // if there's a name, the role is omitted
default:
if strings.Contains(model, "gpt-3.5-turbo") {
log.Println("warning: gpt-3.5-turbo may update over time. Returning num tokens assuming gpt-3.5-turbo-0613.")
return NumTokensFromMessages(messages, "gpt-3.5-turbo-0613")
} else if strings.Contains(model, "gpt-4") {
log.Println("warning: gpt-4 may update over time. Returning num tokens assuming gpt-4-0613.")
return NumTokensFromMessages(messages, "gpt-4-0613")
} else {
err = fmt.Errorf("warning: unknown model [%s]. Use default calculation method converted tokens.", model)
log.Println(err)
return NumTokensFromMessages(messages, "gpt-3.5-turbo-0613")
}
}
for _, message := range messages {
numTokens += tokensPerMessage
numTokens += len(tkm.Encode(message.Content, nil, nil))
numTokens += len(tkm.Encode(message.Role, nil, nil))
numTokens += len(tkm.Encode(message.Name, nil, nil))
if message.Name != "" {
numTokens += tokensPerName
}
}
numTokens += 3
return numTokens
}
func NumTokensFromStr(messages string, model string) (num_tokens int) {
tkm, err := tiktoken.EncodingForModel(model)
if err != nil {
fmt.Println(err)
fmt.Println("Unsupport Model,use cl100k_base Encode")
tkm, _ = tiktoken.GetEncoding("cl100k_base")
}
num_tokens += len(tkm.Encode(messages, nil, nil))
return num_tokens
}
// https://openai.com/pricing
func Cost(model string, promptCount, completionCount int) float64 {
var cost, prompt, completion float64
prompt = float64(promptCount)
completion = float64(completionCount)
switch model {
case "gpt-3.5-turbo-0301":
cost = 0.002 * float64((prompt+completion)/1000)
case "gpt-3.5-turbo", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-1106", "gpt-3.5-turbo-0125":
cost = 0.0015*float64((prompt)/1000) + 0.002*float64(completion/1000)
case "gpt-3.5-turbo-16k", "gpt-3.5-turbo-16k-0613":
cost = 0.003*float64((prompt)/1000) + 0.004*float64(completion/1000)
case "gpt-4", "gpt-4-0613", "gpt-4-0314":
cost = 0.03*float64(prompt/1000) + 0.06*float64(completion/1000)
case "gpt-4-32k", "gpt-4-32k-0314", "gpt-4-32k-0613":
cost = 0.06*float64(prompt/1000) + 0.12*float64(completion/1000)
case "gpt-4-1106-preview", "gpt-4-vision-preview", "gpt-4-0125-preview", "gpt-4-turbo-preview":
cost = 0.01*float64(prompt/1000) + 0.03*float64(completion/1000)
case "gpt-4-turbo", "gpt-4-turbo-2024-04-09":
cost = 0.01*float64(prompt/1000) + 0.03*float64(completion/1000)
// omni
case "gpt-4o", "gpt-4o-2024-08-06":
cost = 0.0025*float64(prompt/1000) + 0.01*float64(completion/1000)
case "gpt-4o-2024-05-13":
cost = 0.005*float64(prompt/1000) + 0.015*float64(completion/1000)
case "gpt-4o-mini", "gpt-4o-mini-2024-07-18":
cost = 0.00015*float64(prompt/1000) + 0.0006*float64(completion/1000)
case "chatgpt-4o-latest":
cost = 0.005*float64(prompt/1000) + 0.015*float64(completion/1000)
// o1
case "o1-preview", "o1-preview-2024-09-12":
cost = 0.015*float64(prompt/1000) + 0.06*float64(completion/1000)
case "o1-mini", "o1-mini-2024-09-12":
cost = 0.003*float64(prompt/1000) + 0.012*float64(completion/1000)
case "o3-mini", "o3-mini-2025-01-31":
cost = 0.003*float64(prompt/1000) + 0.012*float64(completion/1000)
// Realtime API
// Audio*
// $0.1 / 1K input tokens
// $0.2 / 1K output tokens
case "gpt-4o-audio-preview", "gpt-4o-audio-preview-2024-12-17":
cost = 0.0025*float64(prompt/1000) + 0.01*float64(completion/1000)
case "gpt-4o-realtime-preview", "gpt-4o-realtime-preview-2024-10-01":
cost = 0.005*float64(prompt/1000) + 0.020*float64(completion/1000)
case "gpt-4o-realtime-preview.audio", "gpt-4o-realtime-preview-2024-10-01.audio":
cost = 0.1*float64(prompt/1000) + 0.2*float64(completion/1000)
case "gpt-4o-mini-audio-preview", "gpt-4o-mini-audio-preview-2024-12-17":
cost = 0.00015*float64(prompt/1000) + 0.0006*float64(completion/1000)
case "gpt-4o-mini-realtime-preview", "gpt-4o-mini-realtime-preview-2024-12-17":
cost = 0.0006*float64(prompt/1000) + 0.0024*float64(completion/1000)
case "whisper-1":
// 0.006$/min
cost = 0.006 * float64(prompt+completion) / 60
case "tts-1":
cost = 0.015 * float64(prompt+completion)
case "tts-1-hd":
cost = 0.03 * float64(prompt+completion)
case "dall-e-2.256x256":
cost = float64(0.016 * completion)
case "dall-e-2.512x512":
cost = float64(0.018 * completion)
case "dall-e-2.1024x1024":
cost = float64(0.02 * completion)
case "dall-e-3.256x256":
cost = float64(0.04 * completion)
case "dall-e-3.512x512":
cost = float64(0.04 * completion)
case "dall-e-3.1024x1024":
cost = float64(0.04 * completion)
case "dall-e-3.1024x1792", "dall-e-3.1792x1024":
cost = float64(0.08 * completion)
case "dall-e-3.256x256.hd":
cost = float64(0.08 * completion)
case "dall-e-3.512x512.hd":
cost = float64(0.08 * completion)
case "dall-e-3.1024x1024.hd":
cost = float64(0.08 * completion)
case "dall-e-3.1024x1792.hd", "dall-e-3.1792x1024.hd":
cost = float64(0.12 * completion)
// claude /million tokens
// https://aws.amazon.com/cn/bedrock/pricing/
case "claude-v1", "claude-v1-100k":
cost = 11.02/1000000*float64(prompt) + (32.68/1000000)*float64(completion)
case "claude-instant-v1", "claude-instant-v1-100k":
cost = (1.63/1000000)*float64(prompt) + (5.51/1000000)*float64(completion)
case "claude-2", "claude-2.1":
cost = (8.0/1000000)*float64(prompt) + (24.0/1000000)*float64(completion)
case "claude-3-haiku":
cost = (0.00025/1000)*float64(prompt) + (0.00125/1000)*float64(completion)
case "claude-3-sonnet":
cost = (0.003/1000)*float64(prompt) + (0.015/1000)*float64(completion)
case "claude-3-opus":
cost = (0.015/1000)*float64(prompt) + (0.075/1000)*float64(completion)
case "claude-3-haiku-20240307":
cost = (0.00025/1000)*float64(prompt) + (0.00125/1000)*float64(completion)
case "claude-3-5-haiku-latest", "claude-3-5-haiku-20241022":
cost = (0.001/1000)*float64(prompt) + (0.005/1000)*float64(completion)
case "claude-3-sonnet-20240229":
cost = (0.003/1000)*float64(prompt) + (0.015/1000)*float64(completion)
case "claude-3-opus-20240229":
cost = (0.015/1000)*float64(prompt) + (0.075/1000)*float64(completion)
case "claude-3-5-sonnet", "claude-3-5-sonnet-latest", "claude-3-5-sonnet-20240620", "claude-3-5-sonnet-20241022":
cost = (0.003/1000)*float64(prompt) + (0.015/1000)*float64(completion)
// google
// https://ai.google.dev/pricing?hl=zh-cn
case "gemini-pro":
cost = (0.0005/1000)*float64(prompt) + (0.0015/1000)*float64(completion)
case "gemini-pro-vision":
cost = (0.0005/1000)*float64(prompt) + (0.0015/1000)*float64(completion)
case "gemini-1.5-pro-latest":
cost = (0.0035/1000)*float64(prompt) + (0.0105/1000)*float64(completion)
case "gemini-1.5-flash-latest":
cost = (0.00035/1000)*float64(prompt) + (0.00053/1000)*float64(completion)
case "gemini-2.0-flash-exp":
cost = (0.00035/1000)*float64(prompt) + (0.00053/1000)*float64(completion)
case "gemini-2.0-flash-thinking-exp-1219", "gemini-2.0-flash-thinking-exp-01-21":
cost = (0.00035/1000)*float64(prompt) + (0.00053/1000)*float64(completion)
case "learnlm-1.5-pro-experimental", " gemini-exp-1114", "gemini-exp-1121", "gemini-exp-1206":
cost = (0.00035/1000)*float64(prompt) + (0.00053/1000)*float64(completion)
// Mistral AI
// https://docs.mistral.ai/platform/pricing/
case "mistral-small-latest":
cost = (0.002/1000)*float64(prompt) + (0.006/1000)*float64(completion)
case "mistral-medium-latest":
cost = (0.0027/1000)*float64(prompt) + (0.0081/1000)*float64(completion)
case "mistral-large-latest":
cost = (0.008/1000)*float64(prompt) + (0.024/1000)*float64(completion)
default:
if strings.Contains(model, "gpt-3.5-turbo") {
cost = 0.003 * float64((prompt+completion)/1000)
} else if strings.Contains(model, "gpt-4") {
cost = 0.06 * float64((prompt+completion)/1000)
} else {
cost = 0.002 * float64((prompt+completion)/1000)
}
}
return cost
}