# The type of doc engine to use.
# Available options:
# - `elasticsearch` (default)
# - `infinity` (https://github.com/infiniflow/infinity)
# - `opensearch` (https://github.com/opensearch-project/OpenSearch)
DOC_ENGINE=${DOC_ENGINE:-elasticsearch}

# ------------------------------
# docker env var for specifying vector db type at startup
# (based on the vector db type, the corresponding docker
# compose profile will be used)
# ------------------------------
COMPOSE_PROFILES=${DOC_ENGINE}

# The version of Elasticsearch.
STACK_VERSION=8.11.3

# The hostname where the Elasticsearch service is exposed
ES_HOST=es01

# The port used to expose the Elasticsearch service to the host machine,
# allowing EXTERNAL access to the service running inside the Docker container.
ES_PORT=1200

# The password for Elasticsearch.
ELASTIC_PASSWORD=infini_rag_flow

# the hostname where OpenSearch service is exposed, set it not the same as elasticsearch
OS_PORT=1201

# The hostname where the OpenSearch service is exposed
OS_HOST=opensearch01

# The password for OpenSearch.
# At least one uppercase letter, one lowercase letter, one digit, and one special character
OPENSEARCH_PASSWORD=infini_rag_flow_OS_01

# The port used to expose the Kibana service to the host machine,
# allowing EXTERNAL access to the service running inside the Docker container.
KIBANA_PORT=6601
KIBANA_USER=rag_flow
KIBANA_PASSWORD=infini_rag_flow

# The maximum amount of the memory, in bytes, that a specific Docker container can use while running.
# Update it according to the available memory in the host machine.
MEM_LIMIT=8073741824

# The hostname where the Infinity service is exposed
INFINITY_HOST=infinity

# Port to expose Infinity API to the host
INFINITY_THRIFT_PORT=23817
INFINITY_HTTP_PORT=23820
INFINITY_PSQL_PORT=5432

# The password for MySQL.
MYSQL_PASSWORD=infini_rag_flow
# The hostname where the MySQL service is exposed
MYSQL_HOST=mysql
# The database of the MySQL service to use
MYSQL_DBNAME=rag_flow
# The port used to expose the MySQL service to the host machine,
# allowing EXTERNAL access to the MySQL database running inside the Docker container.
MYSQL_PORT=5455

# The hostname where the MinIO service is exposed
MINIO_HOST=minio
# The port used to expose the MinIO console interface to the host machine,
# allowing EXTERNAL access to the web-based console running inside the Docker container.
MINIO_CONSOLE_PORT=9001
# The port used to expose the MinIO API service to the host machine,
# allowing EXTERNAL access to the MinIO object storage service running inside the Docker container.
MINIO_PORT=9000
# The username for MinIO.
# When updated, you must revise the `minio.user` entry in service_conf.yaml accordingly.
MINIO_USER=rag_flow
# The password for MinIO.
# When updated, you must revise the `minio.password` entry in service_conf.yaml accordingly.
MINIO_PASSWORD=infini_rag_flow

# The hostname where the Redis service is exposed
REDIS_HOST=redis
# The port used to expose the Redis service to the host machine,
# allowing EXTERNAL access to the Redis service running inside the Docker container.
REDIS_PORT=6379
# The password for Redis.
REDIS_PASSWORD=infini_rag_flow

# The port used to expose RAGFlow's HTTP API service to the host machine,
# allowing EXTERNAL access to the service running inside the Docker container.
SVR_HTTP_PORT=9380

# The RAGFlow Docker image to download.
# Defaults to the v0.19.1-slim edition, which is the RAGFlow Docker image without embedding models.
RAGFLOW_IMAGE=infiniflow/ragflow:v0.19.1-slim
#
# To download the RAGFlow Docker image with embedding models, uncomment the following line instead:
# RAGFLOW_IMAGE=infiniflow/ragflow:v0.19.1
#
# The Docker image of the v0.19.1 edition includes built-in embedding models:
#   - BAAI/bge-large-zh-v1.5
#   - maidalun1020/bce-embedding-base_v1
#

# If you cannot download the RAGFlow Docker image:
#
# - For the `nightly-slim` edition, uncomment either of the following:
# RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:nightly-slim
# RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:nightly-slim
#
# - For the `nightly` edition, uncomment either of the following:
# RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:nightly
# RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:nightly

# The local time zone.
TIMEZONE='Asia/Shanghai'

# Uncomment the following line if you have limited access to huggingface.co:
# HF_ENDPOINT=https://hf-mirror.com

# Optimizations for MacOS
# Uncomment the following line if your operating system is MacOS:
# MACOS=1

# The maximum file size limit (in bytes) for each upload to your knowledge base or File Management.
# To change the 1GB file size limit, uncomment the line below and update as needed.
# MAX_CONTENT_LENGTH=1073741824
# After updating, ensure `client_max_body_size` in nginx/nginx.conf is updated accordingly.
# Note that neither `MAX_CONTENT_LENGTH` nor `client_max_body_size` sets the maximum size for files uploaded to an agent.
# See https://ragflow.io/docs/dev/begin_component for details.

# Controls how many documents are processed in a single batch.
# Defaults to 4 if DOC_BULK_SIZE is not explicitly set.
DOC_BULK_SIZE=${DOC_BULK_SIZE:-4}

# Defines the number of items to process per batch when generating embeddings.
# Defaults to 16 if EMBEDDING_BATCH_SIZE is not set in the environment.
EMBEDDING_BATCH_SIZE=${EMBEDDING_BATCH_SIZE:-16}

# Log level for the RAGFlow's own and imported packages.
# Available levels:
# - `DEBUG`
# - `INFO` (default)
# - `WARNING`
# - `ERROR`
# For example, the following line changes the log level of `ragflow.es_conn` to `DEBUG`:
# LOG_LEVELS=ragflow.es_conn=DEBUG

# aliyun OSS configuration
# STORAGE_IMPL=OSS
# ACCESS_KEY=xxx
# SECRET_KEY=eee
# ENDPOINT=http://oss-cn-hangzhou.aliyuncs.com
# REGION=cn-hangzhou
# BUCKET=ragflow65536

# A user registration switch:
# - Enable registration: 1
# - Disable registration: 0
REGISTER_ENABLED=1

# Sandbox settings
# Important: To enable sandbox, you must re-declare the compose profiles. See hints at the end of file.
# Double check if you add `sandbox-executor-manager` to your `/etc/hosts`
# Pull the required base images before running:
#   docker pull infiniflow/sandbox-base-nodejs:latest
#   docker pull infiniflow/sandbox-base-python:latest
# Our default sandbox environments include:
#   - Node.js base image: includes axios
#   - Python base image: includes requests, numpy, and pandas
# Specify custom executor images below if you're using non-default environments.
# SANDBOX_ENABLED=1
# SANDBOX_HOST=sandbox-executor-manager
# SANDBOX_EXECUTOR_MANAGER_IMAGE=infiniflow/sandbox-executor-manager:latest
# SANDBOX_EXECUTOR_MANAGER_POOL_SIZE=3
# SANDBOX_BASE_PYTHON_IMAGE=infiniflow/sandbox-base-python:latest
# SANDBOX_BASE_NODEJS_IMAGE=infiniflow/sandbox-base-nodejs:latest
# SANDBOX_EXECUTOR_MANAGER_PORT=9385
# SANDBOX_ENABLE_SECCOMP=false
# SANDBOX_MAX_MEMORY=256m # b, k, m, g
# SANDBOX_TIMEOUT=10s # s, m, 1m30s

# Important: To enable sandbox, you must re-declare the compose profiles.
# 1. Comment out the COMPOSE_PROFILES line above.
# 2. Uncomment one of the following based on your chosen document engine:
#    - For Elasticsearch:
# COMPOSE_PROFILES=elasticsearch,sandbox
#    - For Infinity:
# COMPOSE_PROFILES=infinity,sandbox
#    - For OpenSearch:
# COMPOSE_PROFILES=opensearch,sandbox