110 lines
3.0 KiB
YAML
110 lines
3.0 KiB
YAML
server:
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address: ":3000"
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name: "customer-server"
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jwt:
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secret: "abcdefghijklmnopqrstuvwxyz"
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rate:
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limit: 200
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burst: 300
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# --- 华为云服务器（116.204.74.41:17027，带认证） ---
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#mongo:
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# default:
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# address: "mongodb://root:M0ng0DB%40Pass2026%21@116.204.74.41:17027?authSource=admin"
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# database: "customer_service"
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# logger:
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# level: "all"
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# stdout: true
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# --- 内网服务器（192.168.3.200:27017，无认证） ---
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mongo:
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default:
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address: "mongodb://192.168.3.200:27017/?directConnection=true"
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database: "customer_service"
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logger:
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level: "all"
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stdout: true
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redis:
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default:
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address: 116.204.74.41:6379
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db: 0
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idleTimeout: "60s"
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maxConnLifetime: "90s"
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waitTimeout: "60s"
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dialTimeout: "30s"
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readTimeout: "30s"
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writeTimeout: "30s"
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maxActive: 100
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consul:
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address: 116.204.74.41:8500
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rabbitmq:
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host: 116.204.74.41
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port: 5672
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username: root
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password: root
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# 响应队列配置（从message迁移）
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responseExchange: "ragflow.response"
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responseQueue: "ragflow.response.queue"
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responseRoutingKey: "#" # 匹配所有routing key
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# 不配置instanceName，直接使用os.Hostname()获取容器名/主机名作为实例ID
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jaeger:
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addr: 116.204.74.41:4318
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# RAGFlow配置（customerservice只需要base_url和api_key用于更新prompt接口）
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ragflow:
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base_url: "http://116.204.74.41"
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api_key: "ragflow-tg4BrmCIDXbZDB80JGyq1cDNFyr2_kfAEd053YuDV58"
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default_model: "qwen3-235b-a22b-instruct-2507" # 默认LLM模型，可通过Consul动态覆盖
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embedding_model: "text-embedding-v4@Tongyi-Qianwen" # embedding模型，创建知识库时使用（格式：model@factory）
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followUp:
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enable: true
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queue: "followup.queue"
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exchange: "followup.delayed"
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routingKey: "followup"
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delays: [30, 60, 180] # 三次追问延时（秒）：第一次30s，第二次60s，第三次180s
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contents:
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- "还有其他问题吗？"
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- "如果需要帮助，随时告诉我～"
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- "我一直在线，有问题随时找我～"
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archive:
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enable: true
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queue: "archive.queue"
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exchange: "archive.delayed"
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routingKey: "archive"
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delay: 3600 # 归档延时（秒），默认1小时
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# 月度归档配置
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enabled: true # 是否启用月度归档
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cron: "0 0 0 1 * *" # 每月1号0点执行（归档上个月整月数据）
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mongoBatchSize: 1000 # 从原表复制到临时表的批量大小
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esBatchSize: 500 # 从临时表写入 ES 的批量大小
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testMode: true # 测试模式：true=归档最近7天，false=归档上个月（生产环境设为false）
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# 卡片触发配置
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card:
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triggerCount: 5 # 触发发送卡片的对话轮数（对话>=此值时触发）
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# 历史上下文配置
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history:
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contextLimit: 5 # 读取历史对话轮数（用于新Session上下文注入）
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# Elasticsearch 配置
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elasticsearch:
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addresses:
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- "http://116.204.74.41:9200"
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username: ""
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password: ""
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database:
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logger:
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level: "none" # 关闭数据库日志
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stdout: false
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