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>

charts/nextcloud-mcp-server/values.yaml

@@ -264,3 +264,98 @@ extraEnvFrom: []
 #     name: my-configmap
 # - secretRef:
 #     name: my-secret
+
+# Vector Sync Configuration
+# Background synchronization of Nextcloud content into vector database for semantic search
+vectorSync:
+  # Enable background vector synchronization
+  enabled: false
+  # Scan interval in seconds (how often to check for changes)
+  scanInterval: 3600
+  # Number of concurrent processor workers
+  processorWorkers: 3
+  # Maximum queue size for documents pending indexing
+  queueMaxSize: 10000
+
+# Qdrant Vector Database
+# Deployed as a subchart when enabled. All values are passed through to the qdrant/qdrant chart.
+# See https://github.com/qdrant/qdrant-helm for full configuration options.
+qdrant:
+  # Enable Qdrant subchart deployment
+  enabled: false
+  # Number of Qdrant replicas
+  replicaCount: 1
+  image:
+    # Qdrant version
+    tag: v1.12.5
+  # Optional API key for Qdrant authentication
+  apiKey: ""
+  config:
+    cluster:
+      # Enable distributed cluster mode
+      enabled: false
+  # Persistent storage for vector data
+  persistence:
+    size: 10Gi
+    storageClass: ""
+    accessModes:
+      - ReadWriteOnce
+  # Resource limits and requests
+  resources:
+    requests:
+      cpu: 200m
+      memory: 512Mi
+    limits:
+      cpu: 1000m
+      memory: 2Gi
+
+# Ollama Embedding Service
+# Deployed as a subchart when enabled. All values are passed through to the ollama/ollama chart.
+# See https://github.com/otwld/ollama-helm for full configuration options.
+ollama:
+  # Enable Ollama subchart deployment
+  # Set to true to deploy Ollama as a subchart, or false to use an external Ollama instance
+  enabled: false
+  # External Ollama URL (use this if you have Ollama deployed elsewhere)
+  # When set, use enabled: false to prevent deploying the subchart
+  # Example: "http://ollama.default.svc.cluster.local:11434"
+  url: ""
+  # Embedding model to use
+  embeddingModel: "nomic-embed-text"
+  # Verify SSL certificates when connecting to Ollama
+  verifySsl: true
+  # Number of Ollama replicas (only used when subchart is deployed)
+  replicaCount: 1
+  # Ollama configuration (only used when subchart is deployed)
+  ollama:
+    # Models to automatically pull on startup
+    models:
+      pull:
+        - nomic-embed-text
+  # Persistent storage for models (only used when subchart is deployed)
+  persistentVolume:
+    enabled: true
+    size: 20Gi
+    storageClass: ""
+  # Resource limits and requests (only used when subchart is deployed)
+  resources:
+    requests:
+      cpu: 500m
+      memory: 1Gi
+    limits:
+      cpu: 2000m
+      memory: 4Gi
+
+# OpenAI-compatible Embedding Provider
+# Alternative to Ollama for embedding generation. Can be used with OpenAI or any compatible API.
+openai:
+  # Enable OpenAI embedding provider
+  enabled: false
+  # OpenAI API key (only used if existingSecret is not set)
+  apiKey: ""
+  # Name of existing secret containing the API key
+  existingSecret: ""
+  # Key in the secret that contains the API key
+  secretKey: "api-key"
+  # Optional custom API endpoint (e.g., for Azure OpenAI or local compatible services)
+  baseUrl: ""