server:
  port: 8080

spring:
  servlet:
    multipart:
      max-file-size: 100MB
      max-request-size: 100MB
  ai:
    openai:
      api-key: ollama
      base-url: http://localhost:11434
      chat:
        api-key: ollama
        base-url: http://localhost:11434
        options:
          model: gpt-oss:120b-cloud
#          model: kimi-k2.5:cloud
#          model: gemma4:e2b
#          max-tokens: 10000
          temperature: 0.7
      embedding:
        api-key: key
        base-url: https://api.siliconflow.cn
        options:
          model: BAAI/bge-m3
          dimensions: 1024
        enable: true
    vectorstore:
      milvus:
        client:
          host: "192.168.50.103"
          port: 19530
        databaseName: "doris_docs"
        collectionName: "vector_store"
        embeddingDimension: 1024
        indexType: IVF_FLAT
        metricType: COSINE
        #        增加这个配置，可以让springai帮我们创建vector_store
        initialize-schema: true

document:
  data-path: data
  chunk-size: 400
  min-chunk-size: 200
  max-num-chunk: 10000

# CORS 配置
cors:
  allowed-origins: ${CORS_ORIGINS:http://localhost:8081,http://localhost:5173}
  allowed-methods: GET,POST,PUT,DELETE,OPTIONS
  allowed-headers: "*"
  allow-credentials: true