Files
nextcloud-mcp-server/nextcloud_mcp_server/config.py
T
Chris Coutinho fdd82f59e2 feat: implement semantic search tool and fix vector sync issues (ADR-007 Phase 3)
Completes the ADR-007 implementation by adding user-facing semantic search
functionality. Previous phases implemented scanner and processor for background
indexing; this adds the query interface.

Changes:
- Add nc_notes_semantic_search MCP tool for natural language queries
- Fix Qdrant point IDs to use UUIDs instead of strings (was causing 400 errors)
- Reduce scan interval default from 1 hour to 5 minutes for faster updates
- Add SemanticSearchResult and SemanticSearchNotesResponse models
- Implement dual-phase authorization (Qdrant filter + Nextcloud API verification)

The semantic search enables finding notes by meaning rather than exact keywords,
using vector embeddings to understand query intent. Point ID fix resolves
critical bug where all document indexing failed with "invalid point ID" errors.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-08 21:51:12 +01:00

231 lines
7.9 KiB
Python

import logging.config
import os
from dataclasses import dataclass
from typing import Any, Optional
LOGGING_CONFIG = {
"version": 1,
"disable_existing_loggers": False,
"handlers": {
"default": {
"class": "logging.StreamHandler",
"formatter": "http",
},
},
"formatters": {
"http": {
"format": "%(levelname)s [%(asctime)s] %(name)s - %(message)s",
"datefmt": "%Y-%m-%d %H:%M:%S",
},
},
"loggers": {
"": {
"handlers": ["default"],
"level": "INFO",
},
"httpx": {
"handlers": ["default"],
"level": "INFO",
"propagate": False, # Prevent propagation to root logger
},
"httpcore": {
"handlers": ["default"],
"level": "INFO",
"propagate": False, # Prevent propagation to root logger
},
"uvicorn": {
"handlers": ["default"],
"level": "INFO",
"propagate": False,
},
"uvicorn.access": {
"handlers": ["default"],
"level": "INFO",
"propagate": False,
},
"uvicorn.error": {
"handlers": ["default"],
"level": "INFO",
"propagate": False,
},
},
}
def setup_logging():
logging.config.dictConfig(LOGGING_CONFIG)
# Document Processing Configuration
def get_document_processor_config() -> dict[str, Any]:
"""Get document processor configuration from environment.
Returns:
Dict with processor configs:
{
"enabled": bool,
"default_processor": str,
"processors": {
"unstructured": {...},
"tesseract": {...},
"custom": {...},
}
}
"""
config: dict[str, Any] = {
"enabled": os.getenv("ENABLE_DOCUMENT_PROCESSING", "false").lower() == "true",
"default_processor": os.getenv("DOCUMENT_PROCESSOR", "unstructured"),
"processors": {},
}
# Unstructured configuration
if os.getenv("ENABLE_UNSTRUCTURED", "false").lower() == "true":
config["processors"]["unstructured"] = {
"api_url": os.getenv("UNSTRUCTURED_API_URL", "http://unstructured:8000"),
"timeout": int(os.getenv("UNSTRUCTURED_TIMEOUT", "120")),
"strategy": os.getenv("UNSTRUCTURED_STRATEGY", "auto"),
"languages": [
lang.strip()
for lang in os.getenv("UNSTRUCTURED_LANGUAGES", "eng,deu").split(",")
if lang.strip()
],
"progress_interval": int(os.getenv("PROGRESS_INTERVAL", "10")),
}
# Tesseract configuration
if os.getenv("ENABLE_TESSERACT", "false").lower() == "true":
config["processors"]["tesseract"] = {
"tesseract_cmd": os.getenv("TESSERACT_CMD"), # None = auto-detect
"lang": os.getenv("TESSERACT_LANG", "eng"),
}
# Custom processor (via HTTP API)
if os.getenv("ENABLE_CUSTOM_PROCESSOR", "false").lower() == "true":
custom_url = os.getenv("CUSTOM_PROCESSOR_URL")
if custom_url:
supported_types_str = os.getenv("CUSTOM_PROCESSOR_TYPES", "application/pdf")
supported_types = {
t.strip() for t in supported_types_str.split(",") if t.strip()
}
config["processors"]["custom"] = {
"name": os.getenv("CUSTOM_PROCESSOR_NAME", "custom"),
"api_url": custom_url,
"api_key": os.getenv("CUSTOM_PROCESSOR_API_KEY"),
"timeout": int(os.getenv("CUSTOM_PROCESSOR_TIMEOUT", "60")),
"supported_types": supported_types,
}
return config
@dataclass
class Settings:
"""Application settings from environment variables."""
# OAuth/OIDC settings
oidc_discovery_url: Optional[str] = None
oidc_client_id: Optional[str] = None
oidc_client_secret: Optional[str] = None
oidc_issuer: Optional[str] = None
# Nextcloud settings
nextcloud_host: Optional[str] = None
nextcloud_username: Optional[str] = None
nextcloud_password: Optional[str] = None
# ADR-005: Token Audience Validation (required for OAuth mode)
nextcloud_mcp_server_url: Optional[str] = None # MCP server URL (used as audience)
nextcloud_resource_uri: Optional[str] = None # Nextcloud resource identifier
# Token verification endpoints
jwks_uri: Optional[str] = None
introspection_uri: Optional[str] = None
userinfo_uri: Optional[str] = None
# Progressive Consent settings (always enabled - no flag needed)
enable_token_exchange: bool = False
enable_offline_access: bool = False
# Token exchange cache settings
token_exchange_cache_ttl: int = 300 # seconds (5 minutes default)
# Token settings
token_encryption_key: Optional[str] = None
token_storage_db: Optional[str] = None
# Vector sync settings (ADR-007)
vector_sync_enabled: bool = False
vector_sync_scan_interval: int = 300 # seconds (5 minutes)
vector_sync_processor_workers: int = 3
vector_sync_queue_max_size: int = 10000
# Qdrant settings
qdrant_url: str = "http://qdrant:6333"
qdrant_api_key: Optional[str] = None
qdrant_collection: str = "nextcloud_content"
# Ollama settings (for embeddings)
ollama_base_url: Optional[str] = None
ollama_embedding_model: str = "nomic-embed-text"
ollama_verify_ssl: bool = True
def get_settings() -> Settings:
"""Get application settings from environment variables.
Returns:
Settings object with configuration values
"""
return Settings(
# OAuth/OIDC settings
oidc_discovery_url=os.getenv("OIDC_DISCOVERY_URL"),
oidc_client_id=os.getenv("OIDC_CLIENT_ID"),
oidc_client_secret=os.getenv("OIDC_CLIENT_SECRET"),
oidc_issuer=os.getenv("OIDC_ISSUER"),
# Nextcloud settings
nextcloud_host=os.getenv("NEXTCLOUD_HOST"),
nextcloud_username=os.getenv("NEXTCLOUD_USERNAME"),
nextcloud_password=os.getenv("NEXTCLOUD_PASSWORD"),
# ADR-005: Token Audience Validation
nextcloud_mcp_server_url=os.getenv("NEXTCLOUD_MCP_SERVER_URL"),
nextcloud_resource_uri=os.getenv("NEXTCLOUD_RESOURCE_URI"),
# Token verification endpoints
jwks_uri=os.getenv("JWKS_URI"),
introspection_uri=os.getenv("INTROSPECTION_URI"),
userinfo_uri=os.getenv("USERINFO_URI"),
# Progressive Consent settings (always enabled)
enable_token_exchange=(
os.getenv("ENABLE_TOKEN_EXCHANGE", "false").lower() == "true"
),
enable_offline_access=(
os.getenv("ENABLE_OFFLINE_ACCESS", "false").lower() == "true"
),
# Token exchange cache settings
token_exchange_cache_ttl=int(os.getenv("TOKEN_EXCHANGE_CACHE_TTL", "300")),
# Token settings
token_encryption_key=os.getenv("TOKEN_ENCRYPTION_KEY"),
token_storage_db=os.getenv("TOKEN_STORAGE_DB", "/tmp/tokens.db"),
# Vector sync settings (ADR-007)
vector_sync_enabled=(
os.getenv("VECTOR_SYNC_ENABLED", "false").lower() == "true"
),
vector_sync_scan_interval=int(os.getenv("VECTOR_SYNC_SCAN_INTERVAL", "300")),
vector_sync_processor_workers=int(
os.getenv("VECTOR_SYNC_PROCESSOR_WORKERS", "3")
),
vector_sync_queue_max_size=int(
os.getenv("VECTOR_SYNC_QUEUE_MAX_SIZE", "10000")
),
# Qdrant settings
qdrant_url=os.getenv("QDRANT_URL", "http://qdrant:6333"),
qdrant_api_key=os.getenv("QDRANT_API_KEY"),
qdrant_collection=os.getenv("QDRANT_COLLECTION", "nextcloud_content"),
# Ollama settings
ollama_base_url=os.getenv("OLLAMA_BASE_URL"),
ollama_embedding_model=os.getenv("OLLAMA_EMBEDDING_MODEL", "nomic-embed-text"),
ollama_verify_ssl=os.getenv("OLLAMA_VERIFY_SSL", "true").lower() == "true",
)