55 lines
1.4 KiB
YAML
55 lines
1.4 KiB
YAML
server:
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ip: 0.0.0.0
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port: 50055
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accessToken: "me256487ang1chubdpdialoud22sev1ozhoguumyqca"
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log:
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level: "info"
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logPath: "runtime/logs/app.log"
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chat:
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api_key: "__SET_FROM_ENV__"
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base_url: "https://api.moonshot.cn/v1"
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model: "kimi-k2-turbo-preview" # kimi-k2.5
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max_tokens: 4096
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temperature: 1
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top_p: 0.95
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presence_penalty: 0
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frequency_penalty: 0
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bot_desc: "你是一个AI助手，我需要你模拟一名资深的软件工程师来回答我的问题"
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min_response_tokens: 600
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context_ttl: 1800
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context_len: 4
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redis:
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host: "host.docker.internal"
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port: 8888
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pwd: "123456"
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mysql:
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dsn: "root:root@tcp(mysql:3306)/ai_chat?collation=utf8mb4_unicode_ci&charset=utf8mb4"
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maxLifeTime: 3600
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maxOpenConn: 10
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maxIdleConn: 10
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dependOn:
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sensitive:
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address: "sensitive-filter:50053"
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accessToken: "ang1chubdev1ozhome256487d22sapguuv1ozhom"
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keywords:
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address: "keywords-filter:50054"
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accessToken: "ang1chubdev1ozhome256487d22sapguuv1ozhom"
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tokenizer:
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address: "http://tokenizer:3002"
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vector:
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provider: "pgvector"
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threshold: 0.99
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pgvector:
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dsn: "postgres://postgres:postgres@pgvector:5432/ai_chat?sslmode=disable"
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table: "chat_record_vectors"
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dimensions: 1024
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maxLifeTime: 3600
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maxOpenConn: 10
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maxIdleConn: 10
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embedding:
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provider: "openai-compatible"
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base_url: "https://open.bigmodel.cn/api/paas/v4"
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api_key: "__SET_FROM_ENV__"
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model: "embedding-2"
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timeout: 10
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