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nginx | 1 jaar geleden | |
.env | 10 maanden geleden | |
README.md | 10 maanden geleden | |
docker-compose-CN-oc9.yml | 10 maanden geleden | |
docker-compose-base.yml | 10 maanden geleden | |
docker-compose-gpu-CN-oc9.yml | 10 maanden geleden | |
docker-compose-gpu.yml | 10 maanden geleden | |
docker-compose.yml | 11 maanden geleden | |
entrypoint.sh | 11 maanden geleden | |
infinity_conf.toml | 11 maanden geleden | |
init-kibana.sh | 1 jaar geleden | |
init.sql | 1 jaar geleden | |
launch_backend_service.sh | 11 maanden geleden | |
service_conf.yaml.template | 11 maanden geleden |
[!CAUTION] We do not actively maintain docker-compose-CN-oc9.yml, docker-compose-gpu-CN-oc9.yml, or docker-compose-gpu.yml, so use them at your own risk. However, you are welcome to file a pull request to improve any of them.
The .env file contains important environment variables for Docker.
STACK_VERSION
8.11.3
ES_PORT
1200
.ELASTIC_PASSWORD
KIBANA_PORT
6601
.KIBANA_USER
rag_flow
.KIBANA_PASSWORD
infini_rag_flow
.MEM_LIMIT
8073741824
.MYSQL_PASSWORD
MYSQL_PORT
5455
.MINIO_CONSOLE_PORT
9001
MINIO_PORT
9000
.MINIO_USER
MINIO_PASSWORD
REDIS_PORT
6379
.REDIS_PASSWORD
SVR_HTTP_PORT
9380
.RAGFLOW-IMAGE
The Docker image edition. Available editions:
infiniflow/ragflow:v0.15.0-slim
(default): The RAGFlow Docker image without embedding models.infiniflow/ragflow:v0.15.0
: The RAGFlow Docker image with embedding models including:BAAI/bge-large-zh-v1.5
BAAI/bge-reranker-v2-m3
maidalun1020/bce-embedding-base_v1
maidalun1020/bce-reranker-base_v1
BAAI/bge-base-en-v1.5
BAAI/bge-large-en-v1.5
BAAI/bge-small-en-v1.5
BAAI/bge-small-zh-v1.5
jinaai/jina-embeddings-v2-base-en
jinaai/jina-embeddings-v2-small-en
nomic-ai/nomic-embed-text-v1.5
sentence-transformers/all-MiniLM-L6-v2
[!TIP]
If you cannot download the RAGFlow Docker image, try the following mirrors.
- For the
nightly-slim
edition:
RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:nightly-slim
or,RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:nightly-slim
.- For the
nightly
edition:
RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:nightly
or,RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:nightly
.
TIMEZONE
'Asia/Shanghai'
.HF_ENDPOINT
MACOS
MAX_CONTENT_LENGTH
client_max_body_size
in nginx/nginx.conf correspondingly.service_conf.yaml specifies the system-level configuration for RAGFlow and is used by its API server and task executor. In a dockerized setup, this file is automatically created based on the service_conf.yaml.template file (replacing all environment variables by their values).
ragflow
host
: The API server’s IP address inside the Docker container. Defaults to 0.0.0.0
.port
: The API server’s serving port inside the Docker container. Defaults to 9380
.mysql
name
: The MySQL database name. Defaults to rag_flow
.user
: The username for MySQL.password
: The password for MySQL.port
: The MySQL serving port inside the Docker container. Defaults to 3306
.max_connections
: The maximum number of concurrent connections to the MySQL database. Defaults to 100
.stale_timeout
: Timeout in seconds.minio
user
: The username for MinIO.password
: The password for MinIO.host
: The MinIO serving IP and port inside the Docker container. Defaults to minio:9000
.oauth
The OAuth configuration for signing up or signing in to RAGFlow using a third-party account. It is disabled by default. To enable this feature, uncomment the corresponding lines in service_conf.yaml.template.
github
: The GitHub authentication settings for your application. Visit the Github Developer Settings page to obtain your client_id and secret_key.user_default_llm
The default LLM to use for a new RAGFlow user. It is disabled by default. To enable this feature, uncomment the corresponding lines in service_conf.yaml.template.
factory
: The LLM supplier. Available options:"OpenAI"
"DeepSeek"
"Moonshot"
"Tongyi-Qianwen"
"VolcEngine"
"ZHIPU-AI"
api_key
: The API key for the specified LLM. You will need to apply for your model API key online.[!TIP]
If you do not set the default LLM here, configure the default LLM on the Settings page in the RAGFlow UI.