RAGFlow Helm Chart

This Helm chart deploys RAGFlow, an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding, which is licensed under the Apache License 2.0.

Prerequisites

• Kubernetes 1.19+
• Helm 3.2.0+
• PV provisioner support in the underlying infrastructure (if persistence is enabled)

Installing the Chart

1. Clone this repository

git clone <your-repo-url>
cd <repo-directory>/ragflow

2. Update dependencies

Before installing the chart, you need to update the dependencies:

# Create charts directory if it doesn't exist
mkdir -p charts

# Update dependencies
helm dependency update

This will download the Milvus chart into the charts/ directory.

3. Install the chart

# Install with default configuration
helm install ragflow .

# Or with custom values file
helm install ragflow . -f values.yaml

# Or override specific values
helm install ragflow . --set replicaCount=2 --set persistence.size=20Gi

Configuration

The following table lists the configurable parameters for the RAGFlow chart and their default values.

Parameter	Description	Default
replicaCount	Number of RAGFlow replicas	1
image.repository	RAGFlow image repository	infiniflow/ragflow
image.tag	RAGFlow image tag	latest
image.pullPolicy	Image pull policy	IfNotPresent
persistence.enabled	Enable persistence	true
persistence.size	Size of persistent volume	10Gi
persistence.storageClass	Storage class for PVC	"" (use default)
config.logLevel	Log level	info
config.embeddingModel	Embedding model to use	BAAI/bge-small-en-v1.5
config.maxDocumentSize	Maximum document size in bytes	10485760 (10MB)
llm.provider	LLM provider (openai, azure, local)	openai
llm.model	LLM model to use	gpt-3.5-turbo
llm.apiKey	LLM API key	""
milvus.enabled	Deploy Milvus as dependency	true
resources	CPU/Memory resource requests/limits	See values.yaml
service.type	Kubernetes service type	ClusterIP
service.port	Service port	8000
ingress.enabled	Enable ingress	false

Common Usage Examples

Deploying with External Milvus

helm install ragflow . \
  --set milvus.enabled=false \
  --set externalMilvus.host=my-milvus-service \
  --set externalMilvus.port=19530

Using a Different LLM Provider

helm install ragflow . \
  --set llm.provider=azure \
  --set llm.model=gpt-4 \
  --set-string llm.apiKey=your-api-key

Enabling Ingress

helm install ragflow . \
  --set ingress.enabled=true \
  --set ingress.hosts[0].host=ragflow.example.com \
  --set ingress.hosts[0].paths[0].path=/ \
  --set ingress.hosts[0].paths[0].pathType=Prefix

Upgrading the Chart

helm upgrade ragflow . --set replicaCount=3

Uninstalling the Chart

helm uninstall ragflow

Persistence

This chart mounts a Persistent Volume for storing RAGFlow data. By default, the chart creates a PersistentVolumeClaim with ReadWriteOnce access mode. If persistence is disabled, an emptyDir volume is used.

Troubleshooting

Milvus Dependency Error

If you see an error like:

Error: found in Chart.yaml, but missing in charts/ directory: milvus

Run the following command to update dependencies:

helm dependency update

Checking Logs

# Get pod name
kubectl get pods -l app.kubernetes.io/name=ragflow

# View logs
kubectl logs <pod-name>

Security Notes

• API keys are stored as Kubernetes secrets
• For production use, consider using a secrets management solution like HashiCorp Vault
• Set resource limits appropriate to your workload to prevent resource exhaustion

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Attribution

This Helm chart is provided to deploy RAGFlow. RAGFlow is developed by InfiniFlow and licensed under the Apache License 2.0.

The Helm chart itself is also licensed under the Apache License 2.0.

This is not an official product of InfiniFlow.