feat: add optional vector database and semantic search to helm chart
Add support for deploying Qdrant vector database and Ollama embedding service as optional helm chart dependencies. Enables semantic search capabilities for Nextcloud content with flexible deployment options. Chart Dependencies: - Add Qdrant v0.9.0 from qdrant/qdrant-helm (conditional) - Add Ollama v1.33.0 from otwld/ollama-helm (conditional) - Both dependencies only deploy when enabled Configuration (values.yaml): - vectorSync: Background sync settings (interval, workers, queue size) - qdrant: Subchart config with persistence, resources, clustering - ollama: Subchart config with model pull, persistence, resources - Support for external Ollama via ollama.url (no subchart deployment) - openai: Alternative embedding provider (OpenAI or compatible API) Environment Variables (deployment.yaml): - VECTOR_SYNC_* variables when vectorSync.enabled - QDRANT_URL, QDRANT_COLLECTION when qdrant.enabled - OLLAMA_BASE_URL, OLLAMA_EMBEDDING_MODEL when ollama enabled or URL set - OPENAI_API_KEY when openai.enabled Documentation: - README: New "Vector Search & Semantic Capabilities" section - README: Example 5 showing three deployment patterns - NOTES.txt: Conditional guidance when vector features enabled - Secret template for OpenAI API key management All features disabled by default for backward compatibility. Tested with helm template and helm lint. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
Chris Coutinho
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charts/
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@@ -0,0 +1,9 @@
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dependencies:
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- name: qdrant
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repository: https://qdrant.github.io/qdrant-helm
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version: 0.9.0
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- name: ollama
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repository: https://otwld.github.io/ollama-helm
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version: 1.33.0
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digest: sha256:c53b7a604d202460f60408a62025ae837cad8d4da970b1e5bb404e2b41289f94
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generated: "2025-11-08T23:44:59.709689907+01:00"
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@@ -21,3 +21,12 @@ home: https://github.com/cbcoutinho/nextcloud-mcp-server
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sources:
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- https://github.com/cbcoutinho/nextcloud-mcp-server
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icon: https://raw.githubusercontent.com/nextcloud/server/master/core/img/logo/logo.svg
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dependencies:
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- name: qdrant
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version: "0.9.0"
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repository: https://qdrant.github.io/qdrant-helm
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condition: qdrant.enabled
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- name: ollama
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version: "1.33.0"
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repository: https://otwld.github.io/ollama-helm
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condition: ollama.enabled
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@@ -202,6 +202,67 @@ The application exposes HTTP health check endpoints:
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| `documentProcessing.unstructured.apiUrl` | Unstructured API URL | `http://unstructured:8000` |
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| `documentProcessing.tesseract.enabled` | Enable Tesseract OCR | `false` |
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#### Vector Search & Semantic Capabilities (Optional)
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Enable semantic search capabilities by deploying a vector database (Qdrant) and embedding service (Ollama or OpenAI).
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**Vector Sync Configuration:**
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| Parameter | Description | Default |
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|-----------|-------------|---------|
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| `vectorSync.enabled` | Enable background vector synchronization | `false` |
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| `vectorSync.scanInterval` | Scan interval in seconds | `3600` |
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| `vectorSync.processorWorkers` | Number of concurrent processor workers | `3` |
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| `vectorSync.queueMaxSize` | Maximum queue size for pending documents | `10000` |
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**Qdrant Vector Database:**
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Qdrant is deployed as a subchart when `qdrant.enabled` is `true`. All configuration values are passed through to the [qdrant/qdrant](https://github.com/qdrant/qdrant-helm) chart.
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| Parameter | Description | Default |
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|-----------|-------------|---------|
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| `qdrant.enabled` | Deploy Qdrant as a subchart | `false` |
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| `qdrant.replicaCount` | Number of Qdrant replicas | `1` |
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| `qdrant.image.tag` | Qdrant version | `v1.12.5` |
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| `qdrant.apiKey` | Optional API key for authentication | `""` |
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| `qdrant.persistence.size` | Storage size for vector data | `10Gi` |
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| `qdrant.persistence.storageClass` | Storage class | `""` |
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| `qdrant.resources.requests.cpu` | CPU request | `200m` |
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| `qdrant.resources.requests.memory` | Memory request | `512Mi` |
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| `qdrant.resources.limits.cpu` | CPU limit | `1000m` |
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| `qdrant.resources.limits.memory` | Memory limit | `2Gi` |
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**Ollama Embedding Service:**
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Ollama is deployed as a subchart when `ollama.enabled` is `true`. All configuration values are passed through to the [ollama/ollama](https://github.com/otwld/ollama-helm) chart. Alternatively, set `ollama.url` to use an external Ollama instance.
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| Parameter | Description | Default |
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|-----------|-------------|---------|
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| `ollama.enabled` | Deploy Ollama as a subchart | `false` |
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| `ollama.url` | External Ollama URL (use with `enabled: false`) | `""` |
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| `ollama.embeddingModel` | Embedding model to use | `nomic-embed-text` |
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| `ollama.verifySsl` | Verify SSL certificates | `true` |
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| `ollama.replicaCount` | Number of Ollama replicas | `1` |
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| `ollama.ollama.models.pull` | Models to pull on startup | `["nomic-embed-text"]` |
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| `ollama.persistentVolume.enabled` | Enable persistent storage | `true` |
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| `ollama.persistentVolume.size` | Storage size for models | `20Gi` |
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| `ollama.resources.requests.cpu` | CPU request | `500m` |
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| `ollama.resources.requests.memory` | Memory request | `1Gi` |
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| `ollama.resources.limits.cpu` | CPU limit | `2000m` |
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| `ollama.resources.limits.memory` | Memory limit | `4Gi` |
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**OpenAI Embedding Provider (Alternative):**
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Use OpenAI or any OpenAI-compatible API instead of Ollama.
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| Parameter | Description | Default |
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|-----------|-------------|---------|
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| `openai.enabled` | Enable OpenAI embedding provider | `false` |
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| `openai.apiKey` | OpenAI API key | `""` |
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| `openai.existingSecret` | Use existing secret for API key | `""` |
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| `openai.secretKey` | Key in secret containing API key | `api-key` |
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| `openai.baseUrl` | Custom API endpoint (optional) | `""` |
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## Examples
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### Example 1: Basic Auth with Ingress
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@@ -379,6 +440,90 @@ affinity:
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topologyKey: kubernetes.io/hostname
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```
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### Example 5: Semantic Search with Qdrant and Ollama
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Deploy with vector search capabilities using embedded Qdrant and Ollama:
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```yaml
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nextcloud:
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host: https://cloud.example.com
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auth:
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mode: basic
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basic:
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username: admin
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password: secure-password
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# Enable vector sync
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vectorSync:
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enabled: true
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scanInterval: 1800 # Scan every 30 minutes
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processorWorkers: 5
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# Deploy Qdrant as a subchart
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qdrant:
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enabled: true
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persistence:
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size: 20Gi
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storageClass: fast-ssd
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resources:
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requests:
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cpu: 500m
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memory: 1Gi
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limits:
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cpu: 2000m
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memory: 4Gi
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# Deploy Ollama as a subchart
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ollama:
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enabled: true
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embeddingModel: nomic-embed-text
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persistentVolume:
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size: 30Gi
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storageClass: standard
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resources:
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requests:
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cpu: 1000m
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memory: 2Gi
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limits:
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cpu: 4000m
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memory: 8Gi
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```
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Or use an external Ollama instance:
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```yaml
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vectorSync:
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enabled: true
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qdrant:
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enabled: true
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# Use external Ollama instead of deploying subchart
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ollama:
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enabled: false
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url: "http://ollama.ai-services.svc.cluster.local:11434"
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embeddingModel: nomic-embed-text
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```
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Or use OpenAI for embeddings:
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```yaml
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vectorSync:
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enabled: true
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qdrant:
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enabled: true
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# Use OpenAI instead of Ollama
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openai:
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enabled: true
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apiKey: "sk-..."
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# Or use existing secret:
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# existingSecret: openai-api-key
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# secretKey: api-key
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```
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## Upgrading
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### To upgrade an existing deployment:
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@@ -69,6 +69,33 @@ Your Nextcloud MCP Server has been deployed in {{ .Values.auth.mode }} authentic
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{{- end }}
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{{- end }}
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{{- if .Values.vectorSync.enabled }}
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5. Vector Search & Semantic Capabilities:
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- Vector Sync: Enabled
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- Scan Interval: {{ .Values.vectorSync.scanInterval }}s
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- Processor Workers: {{ .Values.vectorSync.processorWorkers }}
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{{- if .Values.qdrant.enabled }}
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- Qdrant: Deployed as subchart ({{ .Release.Name }}-qdrant:6333)
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{{- else }}
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- Qdrant: Not deployed (configure external instance)
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{{- end }}
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{{- if .Values.ollama.enabled }}
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- Ollama: Deployed as subchart ({{ .Release.Name }}-ollama:11434)
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- Embedding Model: {{ .Values.ollama.embeddingModel }}
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{{- else if .Values.ollama.url }}
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- Ollama: Using external instance at {{ .Values.ollama.url }}
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- Embedding Model: {{ .Values.ollama.embeddingModel }}
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{{- else if .Values.openai.enabled }}
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- OpenAI: Enabled for embeddings
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{{- else }}
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- WARNING: No embedding provider configured (Ollama or OpenAI required)
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{{- end }}
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Check vector sync status:
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kubectl --namespace {{ .Release.Namespace }} exec -it deploy/{{ include "nextcloud-mcp-server.fullname" . }} -- curl -s http://localhost:{{ include "nextcloud-mcp-server.port" . }}/user/page | grep "Vector Sync"
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{{- end }}
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For more information and documentation:
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- GitHub: https://github.com/cbcoutinho/nextcloud-mcp-server
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- Documentation: https://github.com/cbcoutinho/nextcloud-mcp-server#readme
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@@ -140,6 +140,52 @@ spec:
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value: {{ .Values.documentProcessing.custom.types | quote }}
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{{- end }}
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{{- end }}
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# Vector Sync
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- name: VECTOR_SYNC_ENABLED
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value: {{ .Values.vectorSync.enabled | quote }}
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{{- if .Values.vectorSync.enabled }}
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- name: VECTOR_SYNC_SCAN_INTERVAL
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value: {{ .Values.vectorSync.scanInterval | quote }}
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- name: VECTOR_SYNC_PROCESSOR_WORKERS
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value: {{ .Values.vectorSync.processorWorkers | quote }}
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- name: VECTOR_SYNC_QUEUE_MAX_SIZE
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value: {{ .Values.vectorSync.queueMaxSize | quote }}
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{{- end }}
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# Qdrant Vector Database
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{{- if .Values.qdrant.enabled }}
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- name: QDRANT_URL
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value: "http://{{ .Release.Name }}-qdrant:6333"
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- name: QDRANT_COLLECTION
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value: "nextcloud_content"
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{{- if .Values.qdrant.apiKey }}
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- name: QDRANT_API_KEY
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valueFrom:
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secretKeyRef:
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name: {{ .Release.Name }}-qdrant
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key: api-key
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{{- end }}
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{{- end }}
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# Ollama Embedding Service
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{{- if or .Values.ollama.enabled .Values.ollama.url }}
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- name: OLLAMA_BASE_URL
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value: {{ .Values.ollama.url | default (printf "http://%s-ollama:11434" .Release.Name) | quote }}
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- name: OLLAMA_EMBEDDING_MODEL
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value: {{ .Values.ollama.embeddingModel | quote }}
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- name: OLLAMA_VERIFY_SSL
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value: {{ .Values.ollama.verifySsl | quote }}
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{{- end }}
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# OpenAI Embedding Provider (alternative to Ollama)
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{{- if .Values.openai.enabled }}
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- name: OPENAI_API_KEY
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valueFrom:
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secretKeyRef:
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name: {{ .Values.openai.existingSecret | default (printf "%s-openai" (include "nextcloud-mcp-server.fullname" .)) }}
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key: {{ .Values.openai.secretKey }}
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{{- if .Values.openai.baseUrl }}
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- name: OPENAI_BASE_URL
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value: {{ .Values.openai.baseUrl | quote }}
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{{- end }}
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{{- end }}
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{{- with .Values.extraEnv }}
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{{- toYaml . | nindent 12 }}
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{{- end }}
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@@ -0,0 +1,11 @@
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{{- if and .Values.openai.enabled (not .Values.openai.existingSecret) }}
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apiVersion: v1
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kind: Secret
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metadata:
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name: {{ include "nextcloud-mcp-server.fullname" . }}-openai
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labels:
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{{- include "nextcloud-mcp-server.labels" . | nindent 4 }}
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type: Opaque
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data:
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{{ .Values.openai.secretKey }}: {{ .Values.openai.apiKey | b64enc | quote }}
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{{- end }}
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@@ -264,3 +264,98 @@ extraEnvFrom: []
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# name: my-configmap
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# - secretRef:
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# name: my-secret
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# Vector Sync Configuration
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# Background synchronization of Nextcloud content into vector database for semantic search
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vectorSync:
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# Enable background vector synchronization
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enabled: false
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# Scan interval in seconds (how often to check for changes)
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scanInterval: 3600
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# Number of concurrent processor workers
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processorWorkers: 3
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# Maximum queue size for documents pending indexing
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queueMaxSize: 10000
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# Qdrant Vector Database
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# Deployed as a subchart when enabled. All values are passed through to the qdrant/qdrant chart.
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# See https://github.com/qdrant/qdrant-helm for full configuration options.
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qdrant:
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# Enable Qdrant subchart deployment
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enabled: false
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# Number of Qdrant replicas
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replicaCount: 1
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image:
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# Qdrant version
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tag: v1.12.5
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# Optional API key for Qdrant authentication
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apiKey: ""
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config:
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cluster:
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# Enable distributed cluster mode
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enabled: false
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# Persistent storage for vector data
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persistence:
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size: 10Gi
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storageClass: ""
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accessModes:
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- ReadWriteOnce
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# Resource limits and requests
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resources:
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requests:
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cpu: 200m
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memory: 512Mi
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limits:
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cpu: 1000m
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memory: 2Gi
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# Ollama Embedding Service
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# Deployed as a subchart when enabled. All values are passed through to the ollama/ollama chart.
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# See https://github.com/otwld/ollama-helm for full configuration options.
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ollama:
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# Enable Ollama subchart deployment
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# Set to true to deploy Ollama as a subchart, or false to use an external Ollama instance
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enabled: false
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# External Ollama URL (use this if you have Ollama deployed elsewhere)
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# When set, use enabled: false to prevent deploying the subchart
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# Example: "http://ollama.default.svc.cluster.local:11434"
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url: ""
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# Embedding model to use
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embeddingModel: "nomic-embed-text"
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# Verify SSL certificates when connecting to Ollama
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verifySsl: true
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# Number of Ollama replicas (only used when subchart is deployed)
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replicaCount: 1
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# Ollama configuration (only used when subchart is deployed)
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ollama:
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# Models to automatically pull on startup
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models:
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pull:
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- nomic-embed-text
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# Persistent storage for models (only used when subchart is deployed)
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persistentVolume:
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enabled: true
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size: 20Gi
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storageClass: ""
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# Resource limits and requests (only used when subchart is deployed)
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resources:
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requests:
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cpu: 500m
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memory: 1Gi
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limits:
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cpu: 2000m
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memory: 4Gi
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# OpenAI-compatible Embedding Provider
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# Alternative to Ollama for embedding generation. Can be used with OpenAI or any compatible API.
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openai:
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# Enable OpenAI embedding provider
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enabled: false
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# OpenAI API key (only used if existingSecret is not set)
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apiKey: ""
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# Name of existing secret containing the API key
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existingSecret: ""
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# Key in the secret that contains the API key
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secretKey: "api-key"
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# Optional custom API endpoint (e.g., for Azure OpenAI or local compatible services)
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baseUrl: ""
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Block a user