Chris Coutinho
857d8f2152
Adds flexible Qdrant deployment modes to reduce infrastructure requirements
for local development and smaller deployments:
**Configuration Changes:**
- Add QDRANT_LOCATION environment variable (mutually exclusive with QDRANT_URL)
- Three modes: network (URL), in-memory (:memory:, default), persistent (file path)
- Settings dataclass validation via __post_init__ ensures mutual exclusivity
- API key warning when set in local mode (ignored, only for network mode)
**Client Initialization:**
- Auto-detect mode: network (url + api_key) vs local (:memory: or path=)
- In-memory: AsyncQdrantClient(":memory:") - zero config default
- Persistent: AsyncQdrantClient(path="/app/data/qdrant") - file storage
- Network: AsyncQdrantClient(url, api_key) - production mode
**Docker Compose Updates:**
- Qdrant service moved to optional profile (--profile qdrant)
- MCP service uses QDRANT_LOCATION=:memory: by default
- Added mcp-data volume for persistent storage (/app/data)
- No hard dependency on qdrant service
**Documentation:**
- Comprehensive configuration guide in docs/configuration.md
- All three modes documented with pros/cons
- Docker Compose examples for each mode
- Environment variable reference table
**Tests:**
- 13 new config validation tests (mutual exclusivity, defaults, warnings)
- Persistent mode integration test (create, close, reopen, verify persistence)
- All 82 unit tests + 5 smoke tests pass
**Breaking Change:**
- Default changed from QDRANT_URL=http://qdrant:6333 to QDRANT_LOCATION=:memory:
- Simplifies local development (no external service needed)
- Production deployments: explicitly set QDRANT_URL or QDRANT_LOCATION
Related: ADR-007 background vector sync implementation
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
89 lines
3.1 KiB
Python
89 lines
3.1 KiB
Python
"""Qdrant client wrapper."""
|
|
|
|
import logging
|
|
|
|
from qdrant_client import AsyncQdrantClient
|
|
from qdrant_client.models import Distance, VectorParams
|
|
|
|
from nextcloud_mcp_server.config import get_settings
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
# Singleton instance
|
|
_qdrant_client: AsyncQdrantClient | None = None
|
|
|
|
|
|
async def get_qdrant_client() -> AsyncQdrantClient:
|
|
"""
|
|
Get singleton Qdrant client instance.
|
|
|
|
Automatically creates collection on first use if it doesn't exist.
|
|
|
|
Supports three Qdrant modes:
|
|
- Network mode: QDRANT_URL set (e.g., http://qdrant:6333)
|
|
- In-memory mode: QDRANT_LOCATION=:memory: (default if nothing configured)
|
|
- Persistent local mode: QDRANT_LOCATION=/path/to/data
|
|
|
|
Returns:
|
|
Configured AsyncQdrantClient instance
|
|
|
|
Raises:
|
|
Exception: If Qdrant connection fails or collection creation fails
|
|
"""
|
|
global _qdrant_client
|
|
|
|
if _qdrant_client is None:
|
|
settings = get_settings()
|
|
|
|
# Detect mode and initialize client accordingly
|
|
if settings.qdrant_url:
|
|
# Network mode
|
|
logger.info(f"Using Qdrant network mode: {settings.qdrant_url}")
|
|
_qdrant_client = AsyncQdrantClient(
|
|
url=settings.qdrant_url,
|
|
api_key=settings.qdrant_api_key,
|
|
timeout=30,
|
|
)
|
|
elif settings.qdrant_location:
|
|
# Local mode (either :memory: or persistent path)
|
|
if settings.qdrant_location == ":memory:":
|
|
logger.info("Using Qdrant in-memory mode: :memory:")
|
|
_qdrant_client = AsyncQdrantClient(":memory:")
|
|
else:
|
|
# Persistent local mode - use path parameter
|
|
logger.info(f"Using Qdrant persistent mode: {settings.qdrant_location}")
|
|
_qdrant_client = AsyncQdrantClient(path=settings.qdrant_location)
|
|
else:
|
|
# Should not happen due to __post_init__ validation, but handle gracefully
|
|
logger.warning("No Qdrant mode configured, defaulting to :memory:")
|
|
_qdrant_client = AsyncQdrantClient(":memory:")
|
|
|
|
# Ensure collection exists
|
|
collection_name = settings.qdrant_collection
|
|
|
|
# Import here to avoid circular dependency
|
|
from nextcloud_mcp_server.embedding import get_embedding_service
|
|
|
|
embedding_service = get_embedding_service()
|
|
dimension = embedding_service.get_dimension()
|
|
|
|
try:
|
|
await _qdrant_client.get_collection(collection_name)
|
|
logger.info(f"Using existing Qdrant collection: {collection_name}")
|
|
except Exception:
|
|
# Collection doesn't exist, create it
|
|
await _qdrant_client.create_collection(
|
|
collection_name=collection_name,
|
|
vectors_config=VectorParams(
|
|
size=dimension,
|
|
distance=Distance.COSINE,
|
|
),
|
|
)
|
|
logger.info(
|
|
f"Created Qdrant collection: {collection_name} "
|
|
f"(dimension={dimension}, distance=COSINE)"
|
|
)
|
|
|
|
return _qdrant_client
|