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Service

  • wren-engine: the engine service. check out example here: wren-engine /example
  • wren-ai-service: the AI service. check out example here: wren-ai-service docker-compose example
  • qdrant: the vector store ai service is using.
  • wren-ui: the UI service.
  • bootstrap: put required files to volume for engine service.

Volume

Shared data using data volume.

Path structure as following:

  • /mdl
    • *.json (will put sample.json during bootstrap)
  • accounts
  • config.properties

Network

How to start with OpenAI

  1. copy .env.example to .env.local and modify the OpenAI API key.
  2. start all services: docker-compose --env-file .env.local up -d.
  3. stop all services: docker-compose --env-file .env.local down.

How to start with custom LLM

  1. copy .env.example to .env.local and modify the OpenAI API key.
  2. copy .env.ai.example to .env.ai and fill in necessary information if you would like to use custom LLM.
  3. start all services(with custom LLM): docker-compose -f docker-compose.yaml -f docker-compose.llm.yaml --env-file .env.local --env-file .env.ai up -d.
  4. stop all services(with custom LLM): docker-compose -f docker-compose.yaml -f docker-compose.llm.yaml --env-file .env.local --env-file .env.ai down.

Note: If your port 3000 is occupied, you can modify the HOST_PORT in .env.local.