nl2sql/docker-compose.yml at main · Tele-AI/nl2sql · GitHub

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services:
  elasticsearch:
    image: docker.elastic.co/elasticsearch/elasticsearch:8.8.0
    container_name: nl2sql-elasticsearch
    environment:
      - discovery.type=single-node
      # - xpack.security.enabled=false
      - xpack.security.enrollment.enabled=false
      - xpack.security.http.ssl.enabled=false
      - xpack.security.transport.ssl.enabled=false
      - ES_JAVA_OPTS=-Xms512m -Xmx512m
      - ELASTIC_PASSWORD=pleaseChangeMe
    volumes:
      - elasticsearch-data:/usr/share/elasticsearch/data
    healthcheck:
      test: ["CMD-SHELL", "curl -u elastic:pleaseChangeMe -fsS http://localhost:9200/_cluster/health?wait_for_status=yellow || exit 1"]
      interval: 10s
      timeout: 10s
      retries: 5
    networks:
      - nl2sql-network
    ports:
      - "9200:9200"
      - "9300:9300"

  nl2sql:
    image: nl2sql:0.0.1
    build:
      context: .
      dockerfile: Dockerfile
    container_name: nl2sql-backend
    environment:
      # Elasticsearch settings
      - ELASTICSEARCH_URL=http://elasticsearch:9200
      - ELASTICSEARCH_USERNAME=elastic
      - ELASTICSEARCH_PASSWORD=pleaseChangeMe
      - ELASTICSEARCH_ENV=dev
      # NL2SQL settings
      - NL2SQL_THRESHOLD=0.2
      # 词向量服务配置
      # e.g. 硅基流动推理服务
      - EMBEDDING_PROVIDER=
      # 词向量服务URL
      - EMBEDDING_URL=
      # 词向量维度配置
      - VECTOR_DIMENSION=
      # token
      - EMBEDDING_SILICONFLOW_TOKEN=
      # 目前支持1024长度的词向量模型，如BGE等
      - EMBEDDING_SILICONFLOW_MODEL=
      # 大模型推理服务配置，支持OpenAI接口的推理服务
      - LLM_URL=
      # LLM Key
      - LLM_KEY=
      # Model-name, 支持Qwen系列非think模型
      - LLM_MODEL=
    depends_on:
      elasticsearch:
        condition: service_healthy
    networks:
      - nl2sql-network
    ports:
      - "8001:80"

volumes:
  elasticsearch-data:
    driver: local

networks:
  nl2sql-network:
    driver: bridge