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# Server
export LISTEN_ADDR=":8888"
export LOG_LEVEL="debug"
export MAX_REQUEST_BODY_SIZE=1073741824
export SERVER_HOST="localhost${LISTEN_ADDR}"
export MINIO_PROXY_ENDPOINT=":8889"
export USE_SSL="0"
export SSL_CERT_FILE=""
export SSL_KEY_FILE=""
# MySQL
export MYSQL_ROOT_PASSWORD=root
export MYSQL_DATABASE=opencoze
export MYSQL_USER=coze
export MYSQL_PASSWORD=coze123
export MYSQL_HOST=127.0.0.1
export MYSQL_PORT=3306
export MYSQL_DSN="${MYSQL_USER}:${MYSQL_PASSWORD}@tcp(${MYSQL_HOST}:${MYSQL_PORT})/${MYSQL_DATABASE}?charset=utf8mb4&parseTime=True"
export ATLAS_URL="mysql://${MYSQL_USER}:${MYSQL_PASSWORD}@${MYSQL_HOST}:${MYSQL_PORT}/${MYSQL_DATABASE}?charset=utf8mb4&parseTime=True"
# Redis
export REDIS_AOF_ENABLED=no
export REDIS_IO_THREADS=4
export ALLOW_EMPTY_PASSWORD=yes
export REDIS_ADDR="127.0.0.1:6379"
export REDIS_PASSWORD=""
# This Upload component used in Agent / workflow File/Image With LLM , support the component of imagex / storage
# default: storage, use the settings of storage component
# if imagex, you must finish the configuration of <VolcEngine ImageX>
export FILE_UPLOAD_COMPONENT_TYPE="storage"
# VolcEngine ImageX
export VE_IMAGEX_AK=""
export VE_IMAGEX_SK=""
export VE_IMAGEX_SERVER_ID=""
export VE_IMAGEX_DOMAIN=""
export VE_IMAGEX_TEMPLATE=""
export VE_IMAGEX_UPLOAD_HOST="https://imagex.volcengineapi.com"
# Storage component
export STORAGE_TYPE="minio" # minio / tos / s3
export STORAGE_BUCKET="opencoze"
# MiniIO
export MINIO_ROOT_USER=minioadmin
export MINIO_ROOT_PASSWORD=minioadmin123
export MINIO_DEFAULT_BUCKETS=milvus
export MINIO_AK=$MINIO_ROOT_USER
export MINIO_SK=$MINIO_ROOT_PASSWORD
export MINIO_ENDPOINT="127.0.0.1:9000"
export MINIO_API_HOST="http://${MINIO_ENDPOINT}"
# TOS
export TOS_ACCESS_KEY=
export TOS_SECRET_KEY=
export TOS_ENDPOINT=https://tos-cn-beijing.volces.com
export TOS_BUCKET_ENDPOINT=https://opencoze.tos-cn-beijing.volces.com
export TOS_REGION=cn-beijing
# S3
export S3_ACCESS_KEY=
export S3_SECRET_KEY=
export S3_ENDPOINT=
export S3_BUCKET_ENDPOINT=
export S3_REGION=
# Elasticsearch
export ES_ADDR="http://127.0.0.1:9200"
export ES_VERSION="v8"
export ES_USERNAME=""
export ES_PASSWORD=""
export COZE_MQ_TYPE="nsq" # nsq / kafka / rmq
export MQ_NAME_SERVER="127.0.0.1:4150"
# RocketMQ
export RMQ_ACCESS_KEY=""
export RMQ_SECRET_KEY=""
# Settings for VectorStore
# VectorStore type: milvus / vikingdb
# If you want to use vikingdb, you need to set up the vikingdb configuration.
export VECTOR_STORE_TYPE="milvus"
# milvus vector store
export MILVUS_ADDR="127.0.0.1:19530"
# vikingdb vector store for Volcengine
export VIKING_DB_HOST=""
export VIKING_DB_REGION=""
export VIKING_DB_AK=""
export VIKING_DB_SK=""
export VIKING_DB_SCHEME=""
export VIKING_DB_MODEL_NAME="" # if vikingdb model name is not set, you need to set Embedding settings
# Settings for Embedding
# The Embedding model relied on by knowledge base vectorization does not need to be configured
# if the vector database comes with built-in Embedding functionality (such as VikingDB). Currently,
# Coze Studio supports three access methods: openai, ark, ollama, and custom http. Users can simply choose one of them when using
# embedding type: openai / ark / ollama / http
export EMBEDDING_TYPE="ark"
export EMBEDDING_MAX_BATCH_SIZE=100
# openai embedding
export OPENAI_EMBEDDING_BASE_URL="" # (string) OpenAI base_url
export OPENAI_EMBEDDING_MODEL="" # (string) OpenAI embedding model
export OPENAI_EMBEDDING_API_KEY="" # (string) OpenAI api_key
export OPENAI_EMBEDDING_BY_AZURE=false # (bool) OpenAI by_azure
export OPENAI_EMBEDDING_API_VERSION="" # OpenAI azure api version
export OPENAI_EMBEDDING_DIMS=1024 # (int) 向量维度
export OPENAI_EMBEDDING_REQUEST_DIMS=1024
# ark embedding
export ARK_EMBEDDING_MODEL=""
export ARK_EMBEDDING_AK=""
export ARK_EMBEDDING_DIMS="2048"
export ARK_EMBEDDING_BASE_URL=""
# ollama embedding
export OLLAMA_EMBEDDING_BASE_URL=""
export OLLAMA_EMBEDDING_MODEL=""
export OLLAMA_EMBEDDING_DIMS=""
# http embedding
export HTTP_EMBEDDING_ADDR=""
export HTTP_EMBEDDING_DIMS=1024
# Settings for OCR
# If you want to use the OCR-related functions in the knowledge base feature，
# Currently, Coze Studio has built-in Volcano OCR.
# ocr_type: default type `ve`
export OCR_TYPE="ve"
# ve ocr
export VE_OCR_AK=""
export VE_OCR_SK=""
# Settings for Model
# Model for agent & workflow
# add suffix number to add different models
export MODEL_PROTOCOL_0="ark" # protocol
export MODEL_OPENCOZE_ID_0="100001" # id for record
export MODEL_NAME_0="" # model name for show
export MODEL_ID_0="" # model name for connection
export MODEL_API_KEY_0="" # model api key
export MODEL_BASE_URL_0="" # model base url
# Model for knowledge nl2sql, messages2query (rewrite), image annotation, workflow knowledge recall
# add prefix to assign specific model, downgrade to default config when prefix is not configured:
# 1. nl2sql: NL2SQL_ (e.g. NL2SQL_BUILTIN_CM_TYPE)
# 2. messages2query: M2Q_ (e.g. M2Q_BUILTIN_CM_TYPE)
# 3. image annotation: IA_ (e.g. IA_BUILTIN_CM_TYPE)
# 4. workflow knowledge recall: WKR_ (e.g. WKR_BUILTIN_CM_TYPE)
# supported chat model type: openai / ark / deepseek / ollama / qwen / gemini
export BUILTIN_CM_TYPE="ark"
# type openai
export BUILTIN_CM_OPENAI_BASE_URL=""
export BUILTIN_CM_OPENAI_API_KEY=""
export BUILTIN_CM_OPENAI_BY_AZURE=false
export BUILTIN_CM_OPENAI_MODEL=""
# type ark
export BUILTIN_CM_ARK_API_KEY=""
export BUILTIN_CM_ARK_MODEL=""
export BUILTIN_CM_ARK_BASE_URL=""
# type deepseek
export BUILTIN_CM_DEEPSEEK_BASE_URL=""
export BUILTIN_CM_DEEPSEEK_API_KEY=""
export BUILTIN_CM_DEEPSEEK_MODEL=""
# type ollama
export BUILTIN_CM_OLLAMA_BASE_URL=""
export BUILTIN_CM_OLLAMA_MODEL=""
# type qwen
export BUILTIN_CM_QWEN_BASE_URL=""
export BUILTIN_CM_QWEN_API_KEY=""
export BUILTIN_CM_QWEN_MODEL=""
# type gemini
export BUILTIN_CM_GEMINI_BACKEND=""
export BUILTIN_CM_GEMINI_API_KEY=""
export BUILTIN_CM_GEMINI_PROJECT=""
export BUILTIN_CM_GEMINI_LOCATION=""
export BUILTIN_CM_GEMINI_BASE_URL=""
export BUILTIN_CM_GEMINI_MODEL=""
# Workflow Code Runner Configuration
# Supported code runner types: sandbox / local
# Default using local
# - sandbox: execute python code in a sandboxed env with deno + pyodide
# - local: using venv, no env isolation
export CODE_RUNNER_TYPE="local"
# Sandbox sub configuration
# Access restricted to specific environment variables, split with comma, e.g. "PATH,USERNAME"
export CODE_RUNNER_ALLOW_ENV=""
# Read access restricted to specific paths, split with comma, e.g. "/tmp,./data"
export CODE_RUNNER_ALLOW_READ=""
# Write access restricted to specific paths, split with comma, e.g. "/tmp,./data"
export CODE_RUNNER_ALLOW_WRITE=""
# Subprocess execution restricted to specific commands, split with comma, e.g. "python,git"
export CODE_RUNNER_ALLOW_RUN=""
# Network access restricted to specific domains/IPs, split with comma, e.g. "api.test.com,api.test.org:8080"
# The following CDN supports downloading the packages required for pyodide to run Python code. Sandbox may not work properly if removed.
export CODE_RUNNER_ALLOW_NET="cdn.jsdelivr.net"
# Foreign Function Interface access to specific libraries, split with comma, e.g. "/usr/lib/libm.so"
export CODE_RUNNER_ALLOW_FFI=""
# Directory for deno modules, default using pwd. e.g. "/tmp/path/node_modules"
export CODE_RUNNER_NODE_MODULES_DIR=""
# Code execution timeout, default 60 seconds. e.g. "2.56"
export CODE_RUNNER_TIMEOUT_SECONDS=""
# Code execution memory limit, default 100MB. e.g. "256"
export CODE_RUNNER_MEMORY_LIMIT_MB=""
# The function of registration controller
# If you want to disable the registration feature, set DISABLE_USER_REGISTRATION to true. You can then control allowed registrations via a whitelist with ALLOW_REGISTRATION_EMAIL.
export DISABLE_USER_REGISTRATION="" # default "", if you want to disable, set to true
export ALLOW_REGISTRATION_EMAIL="" # is a list of email addresses, separated by ",". Example: "11@example.com,22@example.com"
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