Add support for configurable document chunking parameters to Helm chart
to match docker-compose and application capabilities.
Changes:
1. values.yaml:
- Add documentChunking section with chunkSize (512) and chunkOverlap (50)
- Include comprehensive comments explaining chunking strategies
- Positioned between vectorSync and qdrant sections
2. templates/deployment.yaml:
- Add DOCUMENT_CHUNK_SIZE and DOCUMENT_CHUNK_OVERLAP env vars
- Always set (not conditional), used by vector sync processor
- Environment variables follow same pattern as config.py defaults
3. README.md:
- Add documentChunking parameter table in Vector Search section
- Document chunking strategies (small/medium/large chunks)
- Explain overlap recommendations (10-20% of chunk size)
Validation:
- helm lint: Passes
- helm template: Environment variables correctly generated
- Custom values: Work as expected (tested with chunkSize=1024)
- Always present: Not conditional on vectorSync.enabled
This maintains feature parity between Helm and docker-compose deployments,
allowing users to tune chunking for their embedding models and use cases.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Add support for three Qdrant deployment modes in Helm chart:
1. In-memory mode (:memory:) - Default, zero-config, ephemeral storage
2. Persistent local mode (path-based) - File-based storage with PVC
3. Network mode (URL-based) - Dedicated Qdrant service or external instance
Changes:
- Restructured qdrant configuration in values.yaml with mode selector
- Added conditional environment variable logic in deployment.yaml
- Created PVC template for persistent local mode with optional existingClaim
- Added qdrantPvcName helper template in _helpers.tpl
- Updated README.md with Helm registry URL (https://cbcoutinho.github.io/nextcloud-mcp-server)
Breaking change: Default changed from requiring qdrant.enabled to using
in-memory mode (:memory:) when no Qdrant configuration is provided.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
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>
