# ==========================================
# 蜀道安全管理系统 - 配置文件模板
# ==========================================
# 使用说明:
# 1. 复制此文件为 app.conf (cp app.conf.example app.conf)
# 2. 根据部署环境填写对应的配置值
# 3. app.conf 已加入 .gitignore,不会被提交到版本控制
# ==========================================

appname = shudao-chat-go
httpport = 22001
runmode = dev

# ==========================================
# 基础配置 (Base Configuration)
# ==========================================
# 说明: 系统的基础URL,用于生成OSS代理链接等
# 本地环境: http://127.0.0.1:22000 或 http://localhost:22000
# 测试环境: https://aqai.shudaodsj.com:22000
# 生产环境: https://aqai.shudaodsj.com:22000
base_url = "https://aqai.shudaodsj.com:22000"

# ==========================================
# 数据库配置 (MySQL Database)
# ==========================================
# 本地环境: 使用测试环境数据库 172.16.29.101:21000
# 测试环境: 172.16.29.101:21000
# 生产环境: 172.16.35.57:21000
mysql_user = "root"
mysql_pass = "your_password_here"
mysql_urls = "172.16.29.101"
mysql_port = "21000"
mysql_db = "shudao"

# ==========================================
# 认证服务配置 (Authentication Service)
# ==========================================
# 说明: Token验证API地址
# 生产环境: https://aqai.shudaodsj.com:22000/api/auth/verify
# auth_api_url = "http://127.0.0.1:28004/api/auth/verify"

# ==========================================
# 本地登录配置 (Local Login - 仅本地/测试环境)
# ==========================================
# 说明: 本地登录功能开关,仅在本地和测试环境启用
# 生产环境必须设置为 false
enable_local_login = true

# JWT密钥 (用于本地token签名)
# 请修改为随机字符串,建议32位以上
jwt_secret = "shudao-local-jwt-secret-key-please-change-this-in-production"

# ==========================================
# OSS对象存储配置 (Object Storage Service)
# ==========================================
# 说明: MinIO或兼容S3的对象存储服务
# 本地环境: http://localhost:9000
# 测试/生产环境: http://172.16.17.52:8060
oss_endpoint = "http://172.16.17.52:8060"
oss_access_key_id = "your_access_key_here"
oss_access_key_secret = "your_secret_key_here"
oss_bucket = "gdsc-ai-aqzs"
oss_parse_encrypt_key = "your_encrypt_key_here"

# ==========================================
# AI模型服务配置 (AI Model Services)
# ==========================================

# DeepSeek API配置
# 生产环境: https://api.deepseek.com
deepseek_api_key = "sk-your-deepseek-api-key"
deepseek_api_url = "https://api.deepseek.com"

# 阿里通义千问模型配置
# 本地环境: http://localhost:8000
# 测试/生产环境: http://172.16.35.50:8000
qwen3_api_url = "http://172.16.35.50:8000"
qwen3_model = "Qwen3-30B-A3B-Instruct-2507"

# 意图识别模型配置
# 本地环境: http://localhost:8000
# 测试/生产环境: http://172.16.35.50:8000
intent_api_url = "http://172.16.35.50:8000"
intent_model = "Qwen2.5-1.5B-Instruct"

# ==========================================
# YOLO隐患识别服务配置 (YOLO Detection Service)
# ==========================================
# 说明: YOLO模型API服务地址
# 本地环境: http://localhost:18080
# 测试/生产环境: http://172.16.35.50:18080
yolo_base_url = "http://172.16.35.50:18080"

# ==========================================
# 搜索服务配置 (Search Service)
# ==========================================
# 说明: 内部搜索引擎API地址
# 本地环境: http://localhost:24000/api/search
# 测试/生产环境: 根据实际部署调整
search_api_url = "http://localhost:24000/api/search"
heartbeat_api_url = "http://localhost:24000/api/health"

# ==========================================
# 知识库服务配置 (Knowledge Base Service)
# ==========================================
# 说明: 高级搜索API地址
# 本地环境: http://localhost:22000/admin/api/v1/knowledge/files/advanced-search
# 生产环境: https://aqai.shudaodsj.com:22000/admin/api/v1/knowledge/files/advanced-search
knowledge_search_url = "https://aqai.shudaodsj.com:22000/admin/api/v1/knowledge/files/advanced-search"

# ==========================================
# Dify工作流配置 (Dify Workflow Service)
# ==========================================
# 说明: Dify工作流运行API地址
# 本地环境: http://localhost:8000/v1/workflows/run
# 测试/生产环境: http://172.16.35.50:8000/v1/workflows/run
dify_workflow_url = "http://172.16.35.50:8000/v1/workflows/run"

# Chroma向量数据库配置 (已弃用)
# ==========================================
# 注意: 此配置已被知识库服务替代,保留仅供参考
# 本地环境: 使用测试环境 172.16.29.101:23000
# 测试环境: 172.16.29.101:23000
# 生产环境: 172.16.35.57:23000
# chroma_host = "172.16.29.101"
# chroma_port = "23000"
# chroma_collection_name = "my_rag_collection"