ragflow/helm/values.yaml

# Based on docker compose .env file
env:
  # The type of doc engine to use.
  # Available options:
  # - `elasticsearch` (default)
  # - `infinity` (https://github.com/infiniflow/infinity)
  # DOC_ENGINE: elasticsearch
  DOC_ENGINE: infinity

  # The version of Elasticsearch.
  STACK_VERSION: "8.11.3"

  # The password for Elasticsearch
  ELASTIC_PASSWORD: infini_rag_flow_helm

  # The password for MySQL
  MYSQL_PASSWORD: infini_rag_flow_helm
  # The database of the MySQL service to use
  MYSQL_DBNAME: rag_flow

  # The username for MinIO.
  MINIO_ROOT_USER: rag_flow
  # The password for MinIO
  MINIO_PASSWORD: infini_rag_flow_helm

  # The password for Redis
  REDIS_PASSWORD: infini_rag_flow_helm

  # 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
  #   - BAAI/bge-reranker-v2-m3
  #   - maidalun1020/bce-embedding-base_v1
  #   - maidalun1020/bce-reranker-base_v1
  # - Embedding models that will be downloaded once you select them in the RAGFlow UI:
  #   - 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
  #
  #

  # 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

  # The maximum file size for each uploaded file, in bytes.
  # You can uncomment this line and update the value if you wish to change 128M file size limit
  # MAX_CONTENT_LENGTH: "134217728"
  # After making the change, ensure you update `client_max_body_size` in nginx/nginx.conf correspondingly.

  # The number of document chunks processed in a single batch during document parsing.
  DOC_BULK_SIZE: 4

  # The number of text chunks processed in a single batch during embedding vectorization.
  EMBEDDING_BATCH_SIZE: 16

ragflow:
  deployment:
    strategy:
    resources:
  service:
    # Use LoadBalancer to expose the web interface externally
    type: ClusterIP
  api:
    service:
      enabled: true
      type: ClusterIP

infinity:
  image:
    repository: infiniflow/infinity
    tag: v0.6.0-dev3
  storage:
    className:
    capacity: 5Gi
  deployment:
    strategy:
    resources:
  service:
    type: ClusterIP

elasticsearch:
  storage:
    className:
    capacity: 20Gi
  deployment:
    strategy:
    resources:
      requests:
        cpu: "4"
        memory: "16Gi"
  service:
    type: ClusterIP

minio:
  image:
    repository: quay.io/minio/minio
    tag: RELEASE.2023-12-20T01-00-02Z
  storage:
    className:
    capacity: 5Gi
  deployment:
    strategy:
    resources:
  service:
    type: ClusterIP

mysql:
  image:
    repository: mysql
    tag: 8.0.39
  storage:
    className:
    capacity: 5Gi
  deployment:
    strategy:
    resources:
  service:
    type: ClusterIP

redis:
  image:
    repository: valkey/valkey
    tag: 8
  storage:
    className:
    capacity: 5Gi
  persistence:
    enabled: true
  deployment:
    strategy:
    resources:
  service:
    type: ClusterIP


# This block is for setting up web service ingress. For more information, see:
# https://kubernetes.io/docs/concepts/services-networking/ingress/
ingress:
  enabled: false
  className: ""
  annotations: {}
    # kubernetes.io/ingress.class: nginx
    # kubernetes.io/tls-acme: "true"
  hosts:
    - host: chart-example.local
      paths:
        - path: /
          pathType: ImplementationSpecific
  tls: []
  #  - secretName: chart-example-tls
  #    hosts:
  #      - chart-example.local