218 lines
8.0 KiB
Plaintext
218 lines
8.0 KiB
Plaintext
# Server
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export LISTEN_ADDR=":8888"
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export LOG_LEVEL="debug"
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export MAX_REQUEST_BODY_SIZE=1073741824
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export SERVER_HOST="localhost${LISTEN_ADDR}"
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export MINIO_PROXY_ENDPOINT=":8889"
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export USE_SSL="0"
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export SSL_CERT_FILE=""
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export SSL_KEY_FILE=""
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# MySQL
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export MYSQL_ROOT_PASSWORD=root
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export MYSQL_DATABASE=opencoze
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export MYSQL_USER=coze
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export MYSQL_PASSWORD=coze123
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export MYSQL_HOST=localhost
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export MYSQL_PORT=3306
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export MYSQL_DSN="${MYSQL_USER}:${MYSQL_PASSWORD}@tcp(${MYSQL_HOST}:${MYSQL_PORT})/${MYSQL_DATABASE}?charset=utf8mb4&parseTime=True"
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export ATLAS_URL="mysql://${MYSQL_USER}:${MYSQL_PASSWORD}@${MYSQL_HOST}:${MYSQL_PORT}/${MYSQL_DATABASE}?charset=utf8mb4&parseTime=True"
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# Redis
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export REDIS_AOF_ENABLED=no
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export REDIS_IO_THREADS=4
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export ALLOW_EMPTY_PASSWORD=yes
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export REDIS_ADDR="localhost:6379"
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export REDIS_PASSWORD=""
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# This Upload component used in Agent / workflow File/Image With LLM , support the component of imagex / storage
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# default: storage, use the settings of storage component
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# if imagex, you must finish the configuration of <VolcEngine ImageX>
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export FILE_UPLOAD_COMPONENT_TYPE="storage"
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# VolcEngine ImageX
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export VE_IMAGEX_AK=""
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export VE_IMAGEX_SK=""
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export VE_IMAGEX_SERVER_ID=""
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export VE_IMAGEX_DOMAIN=""
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export VE_IMAGEX_TEMPLATE=""
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export VE_IMAGEX_UPLOAD_HOST="https://imagex.volcengineapi.com"
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# Storage component
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export STORAGE_TYPE="minio" # minio / tos / s3
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export STORAGE_BUCKET="opencoze"
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# MiniIO
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export MINIO_ROOT_USER=minioadmin
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export MINIO_ROOT_PASSWORD=minioadmin123
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export MINIO_DEFAULT_BUCKETS=milvus
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export MINIO_AK=$MINIO_ROOT_USER
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export MINIO_SK=$MINIO_ROOT_PASSWORD
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export MINIO_ENDPOINT="localhost:9000"
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export MINIO_API_HOST="http://${MINIO_ENDPOINT}"
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# TOS
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export TOS_ACCESS_KEY=
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export TOS_SECRET_KEY=
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export TOS_ENDPOINT=https://tos-cn-beijing.volces.com
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export TOS_BUCKET_ENDPOINT=https://opencoze.tos-cn-beijing.volces.com
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export TOS_REGION=cn-beijing
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# S3
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export S3_ACCESS_KEY=
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export S3_SECRET_KEY=
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export S3_ENDPOINT=
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export S3_BUCKET_ENDPOINT=
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export S3_REGION=
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# Elasticsearch
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export ES_ADDR="http://localhost:9200"
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export ES_VERSION="v8"
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export ES_USERNAME=""
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export ES_PASSWORD=""
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export COZE_MQ_TYPE="nsq" # nsq / kafka / rmq
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export MQ_NAME_SERVER="127.0.0.1:4150"
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# RocketMQ
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export RMQ_ACCESS_KEY=""
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export RMQ_SECRET_KEY=""
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# Settings for VectorStore
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# VectorStore type: milvus / vikingdb
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# If you want to use vikingdb, you need to set up the vikingdb configuration.
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export VECTOR_STORE_TYPE="milvus"
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# milvus vector store
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export MILVUS_ADDR="localhost:19530"
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# vikingdb vector store for Volcengine
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export VIKING_DB_HOST=""
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export VIKING_DB_REGION=""
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export VIKING_DB_AK=""
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export VIKING_DB_SK=""
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export VIKING_DB_SCHEME=""
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export VIKING_DB_MODEL_NAME="" # if vikingdb model name is not set, you need to set Embedding settings
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# Settings for Embedding
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# The Embedding model relied on by knowledge base vectorization does not need to be configured
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# if the vector database comes with built-in Embedding functionality (such as VikingDB). Currently,
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# Coze Studio supports three access methods: openai, ark, ollama, and custom http. Users can simply choose one of them when using
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# embedding type: openai / ark / ollama / http
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export EMBEDDING_TYPE="ark"
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export EMBEDDING_MAX_BATCH_SIZE=100
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# openai embedding
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export OPENAI_EMBEDDING_BASE_URL="" # (string) OpenAI base_url
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export OPENAI_EMBEDDING_MODEL="" # (string) OpenAI embedding model
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export OPENAI_EMBEDDING_API_KEY="" # (string) OpenAI api_key
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export OPENAI_EMBEDDING_BY_AZURE=false # (bool) OpenAI by_azure
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export OPENAI_EMBEDDING_API_VERSION="" # OpenAI azure api version
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export OPENAI_EMBEDDING_DIMS=1024 # (int) 向量维度
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export OPENAI_EMBEDDING_REQUEST_DIMS=1024
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# ark embedding
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export ARK_EMBEDDING_MODEL=""
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export ARK_EMBEDDING_AK=""
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export ARK_EMBEDDING_DIMS="2048"
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export ARK_EMBEDDING_BASE_URL=""
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# ollama embedding
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export OLLAMA_EMBEDDING_BASE_URL=""
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export OLLAMA_EMBEDDING_MODEL=""
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export OLLAMA_EMBEDDING_DIMS=""
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# http embedding
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export HTTP_EMBEDDING_ADDR="http://127.0.0.1:6543"
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export HTTP_EMBEDDING_DIMS=1024
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# Settings for OCR
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# If you want to use the OCR-related functions in the knowledge base feature，You need to set up the OCR configuration.
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# Currently, Coze Studio has built-in Volcano OCR.
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# ocr_type: default type `ve`
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export OCR_TYPE="ve"
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# ve ocr
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export VE_OCR_AK=""
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export VE_OCR_SK=""
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# Settings for Model
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# Model for agent & workflow
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# add suffix number to add different models
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export MODEL_PROTOCOL_0="ark" # protocol
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export MODEL_OPENCOZE_ID_0="100001" # id for record
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export MODEL_NAME_0="" # model name for show
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export MODEL_ID_0="" # model name for connection
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export MODEL_API_KEY_0="" # model api key
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export MODEL_BASE_URL_0="" # model base url
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# Model for knowledge nl2sql, messages2query (rewrite), image annotation, workflow knowledge recall
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# add prefix to assign specific model, downgrade to default config when prefix is not configured:
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# 1. nl2sql: NL2SQL_ (e.g. NL2SQL_BUILTIN_CM_TYPE)
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# 2. messages2query: M2Q_ (e.g. M2Q_BUILTIN_CM_TYPE)
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# 3. image annotation: IA_ (e.g. IA_BUILTIN_CM_TYPE)
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# 4. workflow knowledge recall: WKR_ (e.g. WKR_BUILTIN_CM_TYPE)
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# supported chat model type: openai / ark / deepseek / ollama / qwen / gemini
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export BUILTIN_CM_TYPE="ark"
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# type openai
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export BUILTIN_CM_OPENAI_BASE_URL=""
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export BUILTIN_CM_OPENAI_API_KEY=""
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export BUILTIN_CM_OPENAI_BY_AZURE=false
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export BUILTIN_CM_OPENAI_MODEL=""
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# type ark
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export BUILTIN_CM_ARK_API_KEY=""
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export BUILTIN_CM_ARK_MODEL=""
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export BUILTIN_CM_ARK_BASE_URL=""
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# type deepseek
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export BUILTIN_CM_DEEPSEEK_BASE_URL=""
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export BUILTIN_CM_DEEPSEEK_API_KEY=""
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export BUILTIN_CM_DEEPSEEK_MODEL=""
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# type ollama
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export BUILTIN_CM_OLLAMA_BASE_URL=""
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export BUILTIN_CM_OLLAMA_MODEL=""
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# type qwen
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export BUILTIN_CM_QWEN_BASE_URL=""
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export BUILTIN_CM_QWEN_API_KEY=""
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export BUILTIN_CM_QWEN_MODEL=""
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# type gemini
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export BUILTIN_CM_GEMINI_BACKEND=""
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export BUILTIN_CM_GEMINI_API_KEY=""
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export BUILTIN_CM_GEMINI_PROJECT=""
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export BUILTIN_CM_GEMINI_LOCATION=""
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export BUILTIN_CM_GEMINI_BASE_URL=""
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export BUILTIN_CM_GEMINI_MODEL=""
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# Workflow Code Runner Configuration
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# Supported code runner types: sandbox / local
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# Default using local
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# - sandbox: execute python code in a sandboxed env with deno + pyodide
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# - local: using venv, no env isolation
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export CODE_RUNNER_TYPE="local"
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# Sandbox sub configuration
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# Access restricted to specific environment variables, split with comma, e.g. "PATH,USERNAME"
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export CODE_RUNNER_ALLOW_ENV=""
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# Read access restricted to specific paths, split with comma, e.g. "/tmp,./data"
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export CODE_RUNNER_ALLOW_READ=""
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# Write access restricted to specific paths, split with comma, e.g. "/tmp,./data"
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export CODE_RUNNER_ALLOW_WRITE=""
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# Subprocess execution restricted to specific commands, split with comma, e.g. "python,git"
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export CODE_RUNNER_ALLOW_RUN=""
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# Network access restricted to specific domains/IPs, split with comma, e.g. "api.test.com,api.test.org:8080"
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# The following CDN supports downloading the packages required for pyodide to run Python code. Sandbox may not work properly if removed.
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export CODE_RUNNER_ALLOW_NET="cdn.jsdelivr.net"
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# Foreign Function Interface access to specific libraries, split with comma, e.g. "/usr/lib/libm.so"
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export CODE_RUNNER_ALLOW_FFI=""
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# Directory for deno modules, default using pwd. e.g. "/tmp/path/node_modules"
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export CODE_RUNNER_NODE_MODULES_DIR=""
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# Code execution timeout, default 60 seconds. e.g. "2.56"
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export CODE_RUNNER_TIMEOUT_SECONDS=""
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# Code execution memory limit, default 100MB. e.g. "256"
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export CODE_RUNNER_MEMORY_LIMIT_MB=""
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# The function of registration controller
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# 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.
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export DISABLE_USER_REGISTRATION="" # default "", if you want to disable, set to true
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export ALLOW_REGISTRATION_EMAIL="" # is a list of email addresses, separated by ",". Example: "11@example.com,22@example.com"
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