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### What problem does this PR solve? Adds configuration options to the RAGFlow Helm chart to set the Redis data retention policies. By default this feature is disabled to maintain support with older Kubernetes versions. https://kubernetes.io/docs/concepts/workloads/controllers/statefulset/#persistentvolumeclaim-retention ### Type of change - [X] New Feature (non-breaking change which adds functionality)
219 lines
5.4 KiB
YAML
219 lines
5.4 KiB
YAML
# Based on docker compose .env file
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env:
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# The type of doc engine to use.
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# Available options:
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# - `elasticsearch` (default)
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# - `infinity` (https://github.com/infiniflow/infinity)
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# - `opensearch` (https://github.com/opensearch-project/OpenSearch)
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# DOC_ENGINE: elasticsearch
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DOC_ENGINE: infinity
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# DOC_ENGINE: opensearch
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# The version of Elasticsearch.
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STACK_VERSION: "8.11.3"
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# The password for Elasticsearch
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ELASTIC_PASSWORD: infini_rag_flow_helm
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# The password for OpenSearch.
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# At least one uppercase letter, one lowercase letter, one digit, and one special character
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OPENSEARCH_PASSWORD: infini_rag_flow_OS_01
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# The password for MySQL
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MYSQL_PASSWORD: infini_rag_flow_helm
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# The database of the MySQL service to use
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MYSQL_DBNAME: rag_flow
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# The username for MinIO.
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MINIO_ROOT_USER: rag_flow
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# The password for MinIO
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MINIO_PASSWORD: infini_rag_flow_helm
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# The password for Redis
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REDIS_PASSWORD: infini_rag_flow_helm
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# The RAGFlow Docker image to download.
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# Defaults to the v0.19.1-slim edition, which is the RAGFlow Docker image without embedding models.
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RAGFLOW_IMAGE: infiniflow/ragflow:v0.19.1-slim
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#
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# To download the RAGFlow Docker image with embedding models, uncomment the following line instead:
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# RAGFLOW_IMAGE: infiniflow/ragflow:v0.19.1
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#
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# The Docker image of the v0.19.1 edition includes:
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# - Built-in embedding models:
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# - BAAI/bge-large-zh-v1.5
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# - BAAI/bge-reranker-v2-m3
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# - maidalun1020/bce-embedding-base_v1
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# - maidalun1020/bce-reranker-base_v1
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# - Embedding models that will be downloaded once you select them in the RAGFlow UI:
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# - BAAI/bge-base-en-v1.5
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# - BAAI/bge-large-en-v1.5
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# - BAAI/bge-small-en-v1.5
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# - BAAI/bge-small-zh-v1.5
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# - jinaai/jina-embeddings-v2-base-en
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# - jinaai/jina-embeddings-v2-small-en
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# - nomic-ai/nomic-embed-text-v1.5
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# - sentence-transformers/all-MiniLM-L6-v2
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#
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#
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# The local time zone.
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TIMEZONE: "Asia/Shanghai"
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# Uncomment the following line if you have limited access to huggingface.co:
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# HF_ENDPOINT: https://hf-mirror.com
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# The maximum file size for each uploaded file, in bytes.
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# You can uncomment this line and update the value if you wish to change 128M file size limit
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# MAX_CONTENT_LENGTH: "134217728"
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# After making the change, ensure you update `client_max_body_size` in nginx/nginx.conf correspondingly.
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# The number of document chunks processed in a single batch during document parsing.
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DOC_BULK_SIZE: 4
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# The number of text chunks processed in a single batch during embedding vectorization.
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EMBEDDING_BATCH_SIZE: 16
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ragflow:
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# Optional service configuration overrides
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# to be written to local.service_conf.yaml
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# inside the RAGFlow container
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# https://ragflow.io/docs/dev/configurations#service-configuration
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service_conf:
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# Optional yaml formatted override for the
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# llm_factories.json file inside the RAGFlow
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# container.
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llm_factories:
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# factory_llm_infos:
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# - name: OpenAI-API-Compatible
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# logo: ""
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# tags: "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION"
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# status: "1"
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# llm:
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# - llm_name: my-custom-llm
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# tags: "LLM,CHAT,"
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# max_tokens: 100000
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# model_type: chat
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# is_tools: false
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# Kubernetes configuration
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deployment:
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strategy:
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resources:
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service:
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# Use LoadBalancer to expose the web interface externally
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type: ClusterIP
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api:
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service:
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enabled: true
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type: ClusterIP
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infinity:
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image:
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repository: infiniflow/infinity
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tag: v0.6.0-dev5
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storage:
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className:
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capacity: 5Gi
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deployment:
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strategy:
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resources:
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service:
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type: ClusterIP
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elasticsearch:
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storage:
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className:
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capacity: 20Gi
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deployment:
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strategy:
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resources:
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requests:
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cpu: "4"
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memory: "16Gi"
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service:
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type: ClusterIP
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opensearch:
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image:
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repository: opensearchproject/opensearch
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tag: 2.19.1
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storage:
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className:
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capacity: 20Gi
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deployment:
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strategy:
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resources:
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requests:
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cpu: "4"
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memory: "16Gi"
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service:
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type: ClusterIP
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minio:
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image:
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repository: quay.io/minio/minio
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tag: RELEASE.2023-12-20T01-00-02Z
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storage:
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className:
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capacity: 5Gi
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deployment:
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strategy:
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resources:
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service:
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type: ClusterIP
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mysql:
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image:
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repository: mysql
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tag: 8.0.39
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storage:
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className:
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capacity: 5Gi
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deployment:
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strategy:
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resources:
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service:
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type: ClusterIP
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redis:
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image:
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repository: valkey/valkey
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tag: 8
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storage:
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className:
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capacity: 5Gi
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persistence:
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enabled: true
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# Set's the retention policy for the persistent storage (only available in k8s 1.32 or later)
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# https://kubernetes.io/docs/concepts/workloads/controllers/statefulset/#persistentvolumeclaim-retention
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# retentionPolicy:
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# whenDeleted: Delete
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# whenScaled: Delete
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deployment:
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strategy:
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resources:
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service:
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type: ClusterIP
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# This block is for setting up web service ingress. For more information, see:
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# https://kubernetes.io/docs/concepts/services-networking/ingress/
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ingress:
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enabled: false
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className: ""
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annotations: {}
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# kubernetes.io/ingress.class: nginx
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# kubernetes.io/tls-acme: "true"
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hosts:
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- host: chart-example.local
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paths:
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- path: /
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pathType: ImplementationSpecific
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tls: []
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# - secretName: chart-example-tls
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# hosts:
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# - chart-example.local
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