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WrenAI/docker/.env.example
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2025-03-20 16:39:32 +08:00

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COMPOSE_PROJECT_NAME=wrenai
PLATFORM=linux/amd64
PROJECT_DIR=.
# service port
WREN_ENGINE_PORT=8080
WREN_ENGINE_SQL_PORT=7432
WREN_AI_SERVICE_PORT=5555
WREN_UI_PORT=3000
IBIS_SERVER_PORT=8000
WREN_UI_ENDPOINT=http://wren-ui:${WREN_UI_PORT}
# ai service settings
QDRANT_HOST=qdrant
SHOULD_FORCE_DEPLOY=1
# vendor keys
OPENAI_API_KEY=
# version
# CHANGE THIS TO THE LATEST VERSION
WREN_PRODUCT_VERSION=0.17.0-rc.2
WREN_ENGINE_VERSION=0.14.7
WREN_AI_SERVICE_VERSION=0.17.1
IBIS_SERVER_VERSION=0.14.7
WREN_UI_VERSION=0.22.0
WREN_BOOTSTRAP_VERSION=0.1.5
# user id (uuid v4)
USER_UUID=
# for other services
POSTHOG_API_KEY=phc_nhF32aj4xHXOZb0oqr2cn4Oy9uiWzz6CCP4KZmRq9aE
POSTHOG_HOST=https://app.posthog.com
TELEMETRY_ENABLED=true
# this is for telemetry to know the model, i think ai-service might be able to provide a endpoint to get the information
GENERATION_MODEL=gpt-4o-mini
LANGFUSE_SECRET_KEY=
LANGFUSE_PUBLIC_KEY=
# the port exposes to the host
# OPTIONAL: change the port if you have a conflict
HOST_PORT=3000
AI_SERVICE_FORWARD_PORT=5555
# Wren UI
EXPERIMENTAL_ENGINE_RUST_VERSION=false