# ============================================
# OAUTH MULTI-USER QUICK START (Recommended)
# ============================================
# Multi-user deployment with OAuth authentication
# Use for: Multi-user production deployments, enhanced security
# Features: Single-audience tokens, automatic client registration (DCR)
#
# Copy this file to .env and configure
# ===== REQUIRED SETTINGS =====
# Your Nextcloud instance URL (without trailing slash)
NEXTCLOUD_HOST=https://nextcloud.example.com
# ===== REQUIRED: LEAVE USERNAME/PASSWORD EMPTY =====
# OAuth mode activates when these are NOT set
NEXTCLOUD_USERNAME=
NEXTCLOUD_PASSWORD=
# ===== OPTIONAL: EXPLICIT MODE DECLARATION =====
# Recommended for clarity
MCP_DEPLOYMENT_MODE=oauth_single_audience
# ===== OPTIONAL: PRE-REGISTERED OAUTH CLIENT =====
# If you pre-register the OAuth client instead of using DCR:
#NEXTCLOUD_OIDC_CLIENT_ID=your-client-id
#NEXTCLOUD_OIDC_CLIENT_SECRET=your-client-secret
# MCP Server URL (for OAuth redirects)
NEXTCLOUD_MCP_SERVER_URL=http://localhost:8000
# ===== OPTIONAL: SEMANTIC SEARCH (Recommended) =====
# AI-powered semantic search with automatic background operation setup
#
# When you enable semantic search in multi-user mode:
# 1. ENABLE_SEMANTIC_SEARCH automatically enables background operations
# 2. Server requests refresh tokens for offline indexing
# 3. Tokens are stored encrypted in TOKEN_STORAGE_DB
# 4. No need to set ENABLE_BACKGROUND_OPERATIONS separately!
#
ENABLE_SEMANTIC_SEARCH=true
# Vector Database (required for semantic search)
QDRANT_URL=http://qdrant:6333
# OR for in-memory mode:
#QDRANT_LOCATION=:memory:
# Embedding Provider (required for semantic search)
# Option 1: Ollama (recommended for local deployment)
OLLAMA_BASE_URL=http://ollama:11434
OLLAMA_EMBEDDING_MODEL=nomic-embed-text
# Option 2: Amazon Bedrock (for AWS deployments)
#AWS_REGION=us-east-1
#BEDROCK_EMBEDDING_MODEL=amazon.titan-embed-text-v2:0
# Token Storage (required for background operations - auto-enabled by semantic search)
# Generate encryption key: python -c "from cryptography.fernet import Fernet; print(Fernet.generate_key().decode())"
TOKEN_ENCRYPTION_KEY=your-encryption-key-here
TOKEN_STORAGE_DB=/app/data/tokens.db
# ===== OPTIONAL: DOCUMENT PROCESSING =====
# Extract text from PDFs, images, DOCX for semantic search
#ENABLE_DOCUMENT_PROCESSING=true
#ENABLE_UNSTRUCTURED=true
#UNSTRUCTURED_API_URL=http://unstructured:8000
# ===== SUMMARY OF AUTO-ENABLEMENT =====
# With ENABLE_SEMANTIC_SEARCH=true in OAuth mode:
# ✅ Background operations enabled automatically
# ✅ Refresh token storage enabled automatically
# ✅ OAuth credentials required (DCR or pre-registered)
# ✅ Encryption key required for token storage
#
# You only need to set ENABLE_SEMANTIC_SEARCH and provide the required
# infrastructure (Qdrant, Ollama, encryption key). The rest is automatic!
# For more advanced configuration, see env.sample
