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# Self-hosting DocsGPT on Kubernetes
This guide will walk you through deploying DocsGPT on Kubernetes.
## Prerequisites
Ensure you have the following installed before proceeding:
- [kubectl](https://kubernetes.io/docs/tasks/tools/install-kubectl/)
- Access to a Kubernetes cluster
## Folder Structure
The `k8s` folder contains the necessary deployment and service configuration files:
- `deployments/`
- `services/`
- `docsgpt-secrets.yaml`
## Deployment Instructions
1. **Clone the Repository**
```sh
git clone https://github.com/arc53/DocsGPT.git
cd docsgpt/k8s
```
2. **Configure Secrets (optional)**
Ensure that you have all the necessary secrets in `docsgpt-secrets.yaml`. Update it with your secrets before applying if you want. By default we will use qdrant as a vectorstore and public docsgpt llm as llm for inference.
3. **Apply Kubernetes Deployments**
Deploy your DocsGPT resources using the following commands:
```sh
kubectl apply -f deployments/
```
4. **Apply Kubernetes Services**
Set up your services using the following commands:
```sh
kubectl apply -f services/
```
5. **Apply Secrets**
Apply the secret configurations:
```sh
kubectl apply -f docsgpt-secrets.yaml
```
6. **Substitute API URL**
After deploying the services, you need to update the environment variable `VITE_API_HOST` in your deployment file `deployments/docsgpt-deploy.yaml` with the actual endpoint URL created by your `docsgpt-api-service`.
```sh
kubectl get services/docsgpt-api-service -o jsonpath='{.status.loadBalancer.ingress[0].ip}' | xargs -I {} sed -i "s|<your-api-endpoint>|{}|g" deployments/docsgpt-deploy.yaml
```
7. **Rerun Deployment**
After making the changes, reapply the deployment configuration to update the environment variables:
```sh
kubectl apply -f deployments/
```
## Verifying the Deployment
To verify if everything is set up correctly, you can run the following:
```sh
kubectl get pods
kubectl get services
```
Ensure that the pods are running and the services are available.
## Accessing DocsGPT
To access DocsGPT, you need to find the external IP address of the frontend service. You can do this by running:
```sh
kubectl get services/docsgpt-frontend-service | awk 'NR>1 {print "http://" $4}'
```
## Troubleshooting
If you encounter any issues, you can check the logs of the pods for more details:
```sh
kubectl logs <pod-name>
```
Replace `<pod-name>` with the actual name of your DocsGPT pod.

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"Railway-Deploying": {
"title": "🚂Deploying on Railway",
"href": "/Deploying/Railway-Deploying"
},
"Kubernetes-Deploying": {
"title": "🚀Deploying on Kubernetes",
"href": "/Deploying/Kubernetes-Deploying"
}
}

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apiVersion: apps/v1
kind: Deployment
metadata:
name: docsgpt-api
spec:
replicas: 1
selector:
matchLabels:
app: docsgpt-api
template:
metadata:
labels:
app: docsgpt-api
spec:
containers:
- name: docsgpt-api
image: arc53/docsgpt
ports:
- containerPort: 7091
resources:
limits:
memory: "4Gi"
cpu: "2"
requests:
memory: "2Gi"
cpu: "1"
envFrom:
- secretRef:
name: docsgpt-secrets
env:
- name: FLASK_APP
value: "application/app.py"
- name: DEPLOYMENT_TYPE
value: "cloud"
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: docsgpt-worker
spec:
replicas: 1
selector:
matchLabels:
app: docsgpt-worker
template:
metadata:
labels:
app: docsgpt-worker
spec:
containers:
- name: docsgpt-worker
image: arc53/docsgpt
command: ["celery", "-A", "application.app.celery", "worker", "-l", "INFO", "-n", "worker.%h"]
resources:
limits:
memory: "4Gi"
cpu: "2"
requests:
memory: "2Gi"
cpu: "1"
envFrom:
- secretRef:
name: docsgpt-secrets
env:
- name: API_URL
value: "http://<your-api-endpoint>"
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: docsgpt-frontend
spec:
replicas: 1
selector:
matchLabels:
app: docsgpt-frontend
template:
metadata:
labels:
app: docsgpt-frontend
spec:
containers:
- name: docsgpt-frontend
image: arc53/docsgpt-fe
ports:
- containerPort: 5173
resources:
limits:
memory: "1Gi"
cpu: "1"
requests:
memory: "256Mi"
cpu: "100m"
env:
- name: VITE_API_HOST
value: "http://<your-api-endpoint>"
- name: VITE_API_STREAMING
value: "true"

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apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: mongodb-pvc
spec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 10Gi # Adjust size as needed
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: mongodb
spec:
replicas: 1
selector:
matchLabels:
app: mongodb
template:
metadata:
labels:
app: mongodb
spec:
containers:
- name: mongodb
image: mongo:latest
ports:
- containerPort: 27017
resources:
limits:
memory: "1Gi"
cpu: "0.5"
requests:
memory: "512Mi"
cpu: "250m"
volumeMounts:
- name: mongodb-data
mountPath: /data/db
volumes:
- name: mongodb-data
persistentVolumeClaim:
claimName: mongodb-pvc

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apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: qdrant-pvc
spec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 10Gi
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: qdrant
spec:
replicas: 1
selector:
matchLabels:
app: qdrant
template:
metadata:
labels:
app: qdrant
spec:
containers:
- name: qdrant
image: qdrant/qdrant:latest
ports:
- containerPort: 6333
resources:
limits:
memory: "2Gi" # Adjust based on your needs
cpu: "1" # Adjust based on your needs
requests:
memory: "1Gi" # Adjust based on your needs
cpu: "500m" # Adjust based on your needs
volumeMounts:
- name: qdrant-data
mountPath: /qdrant/storage
volumes:
- name: qdrant-data
persistentVolumeClaim:
claimName: qdrant-pvc

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apiVersion: apps/v1
kind: Deployment
metadata:
name: redis
spec:
replicas: 1
selector:
matchLabels:
app: redis
template:
metadata:
labels:
app: redis
spec:
containers:
- name: redis
image: redis:latest
ports:
- containerPort: 6379
resources:
limits:
memory: "1Gi"
cpu: "0.5"
requests:
memory: "512Mi"
cpu: "250m"

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apiVersion: v1
kind: Secret
metadata:
name: docsgpt-secrets
type: Opaque
data:
LLM_NAME: ZG9jc2dwdA==
INTERNAL_KEY: aW50ZXJuYWw=
CELERY_BROKER_URL: cmVkaXM6Ly9yZWRpcy1zZXJ2aWNlOjYzNzkvMA==
CELERY_RESULT_BACKEND: cmVkaXM6Ly9yZWRpcy1zZXJ2aWNlOjYzNzkvMA==
QDRANT_URL: cmVkaXM6Ly9yZWRpcy1zZXJ2aWNlOjYzNzkvMA==
QDRANT_PORT: NjM3OQ==
MONGO_URI: bW9uZ29kYjovL21vbmdvZGItc2VydmljZToyNzAxNy9kb2NzZ3B0P3JldHJ5V3JpdGVzPXRydWUmdz1tYWpvcml0eQ==
mongo-user: bW9uZ28tdXNlcg==
mongo-password: bW9uZ28tcGFzc3dvcmQ=

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apiVersion: v1
kind: Service
metadata:
name: docsgpt-api-service
spec:
selector:
app: docsgpt-api
ports:
- protocol: TCP
port: 80
targetPort: 7091
type: LoadBalancer
---
apiVersion: v1
kind: Service
metadata:
name: docsgpt-frontend-service
spec:
selector:
app: docsgpt-frontend
ports:
- protocol: TCP
port: 80
targetPort: 5173
type: LoadBalancer

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apiVersion: v1
kind: Service
metadata:
name: mongodb-service
spec:
selector:
app: mongodb
ports:
- protocol: TCP
port: 27017
targetPort: 27017
type: ClusterIP

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apiVersion: v1
kind: Service
metadata:
name: qdrant
spec:
selector:
app: qdrant
ports:
- protocol: TCP
port: 6333
targetPort: 6333
type: ClusterIP

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apiVersion: v1
kind: Service
metadata:
name: redis-service
spec:
selector:
app: redis
ports:
- protocol: TCP
port: 6379
targetPort: 6379
type: ClusterIP
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