# Arke Configuration Example
# Copy this file to .env and update with your values

# ============================================================================
# Server Configuration
# ============================================================================
HOST=0.0.0.0
PORT=8000
DEBUG=false
LOG_LEVEL=info
RELOAD=false

# ============================================================================
# PostgreSQL Database Configuration
# ============================================================================

# Database environment variables (same as above)
DB_HOST=localhost
DB_PORT=5432
DB_NAME=arke
DB_USER=arke
DB_PASSWORD=your_secure_password

# ============================================================================
# Memcached Configuration
# ============================================================================
MEMCACHED_HOST=localhost
MEMCACHED_PORT=11211

# ============================================================================
# Multi-Backend Configuration (Environment Variable Format)
# ============================================================================
# Ansible-friendly configuration using individual environment variables
# No JSON escaping issues, works perfectly with Ansible Vault

# --- NTTh Backend (Token Pool) ---
# NTTh is treated specially as it manages a pool of tokens with session limits
NTTH_BACKEND_ENABLED=true
NTTH_SESSION_LIMIT=90
NTTH_SESSION_TTL=3600
NTTH_TOKEN_CACHE_TTL=82800

# NTTh Tokens (numbered, add as many as needed)
NTTH_TOKEN_1_APP_ID=your_app_id_1
NTTH_TOKEN_1_APP_SECRET=your_secret_1
NTTH_TOKEN_1_NAME=production-primary

NTTH_TOKEN_2_APP_ID=your_app_id_2
NTTH_TOKEN_2_APP_SECRET=your_secret_2
NTTH_TOKEN_2_NAME=production-backup

# Add more tokens as needed:
# NTTH_TOKEN_3_APP_ID=your_app_id_3
# NTTH_TOKEN_3_APP_SECRET=your_secret_3
# NTTH_TOKEN_3_NAME=production-tertiary

# --- Standard Backends (OpenAI-Compatible, etc.) ---
# Backend 1: Nyx (llama-cpp instance)
BACKEND_1_NAME=nyx
BACKEND_1_TYPE=openai-compatible
BACKEND_1_ENABLED=true
BACKEND_1_BASE_URL=http://nyx.helu.ca:8080/v1
BACKEND_1_API_KEY=not-needed
BACKEND_1_MODEL_PREFIX=nyx
BACKEND_1_TIMEOUT=60

# Backend 2: Athena (llama-cpp instance)
BACKEND_2_NAME=athena
BACKEND_2_TYPE=openai-compatible
BACKEND_2_ENABLED=true
BACKEND_2_BASE_URL=http://athena.helu.ca:8080/v1
BACKEND_2_API_KEY=not-needed
BACKEND_2_MODEL_PREFIX=athena
BACKEND_2_TIMEOUT=60

# ============================================================================
# Future Backend Examples (Reference Only - Not Active)
# ============================================================================
# These examples show how to configure other backend types when needed

# --- Anthropic Backend Example ---
# BACKEND_3_NAME=anthropic
# BACKEND_3_TYPE=anthropic
# BACKEND_3_ENABLED=true
# BACKEND_3_BASE_URL=https://api.anthropic.com
# BACKEND_3_API_KEY=sk-ant-api03-xxxxx
# BACKEND_3_MODEL_PREFIX=anthropic
# BACKEND_3_TIMEOUT=60

# --- Azure OpenAI Backend Example ---
# BACKEND_4_NAME=azure-openai
# BACKEND_4_TYPE=azure-openai
# BACKEND_4_ENABLED=true
# BACKEND_4_BASE_URL=https://your-resource.openai.azure.com
# BACKEND_4_API_KEY=your-azure-key
# BACKEND_4_MODEL_PREFIX=azure
# BACKEND_4_DEPLOYMENT_NAME=gpt-4
# BACKEND_4_API_VERSION=2024-02-15-preview
# BACKEND_4_TIMEOUT=60

# --- AWS Bedrock Backend Example ---
# BACKEND_5_NAME=bedrock
# BACKEND_5_TYPE=bedrock
# BACKEND_5_ENABLED=true
# BACKEND_5_AWS_REGION=us-east-1
# BACKEND_5_AWS_ACCESS_KEY_ID=AKIA...
# BACKEND_5_AWS_SECRET_ACCESS_KEY=secret...
# BACKEND_5_MODEL_PREFIX=bedrock
# BACKEND_5_TIMEOUT=60

# --- OpenAI Direct Backend Example ---
# BACKEND_6_NAME=openai
# BACKEND_6_TYPE=openai-compatible
# BACKEND_6_ENABLED=true
# BACKEND_6_BASE_URL=https://api.openai.com/v1
# BACKEND_6_API_KEY=sk-...
# BACKEND_6_MODEL_PREFIX=openai
# BACKEND_6_TIMEOUT=60

# ============================================================================
# Embedding Provider Configuration
# ============================================================================
# Choose your embedding provider: 'ollama' or 'openai'
EMBEDDING_PROVIDER=ollama

# --- Ollama Configuration (when EMBEDDING_PROVIDER=ollama) ---
OLLAMA_HOST=nyx.helu.ca
OLLAMA_PORT=11434
EMBEDDING_MODEL=nomic-embed-text

# --- OpenAI-Compatible Configuration (when EMBEDDING_PROVIDER=openai) ---
# Works with OpenAI API, llama-cpp, LocalAI, and other compatible services
OPENAI_EMBEDDING_BASE_URL=http://localhost:8080
OPENAI_EMBEDDING_API_KEY=
OPENAI_EMBEDDING_MODEL=text-embedding-ada-002

# --- Common Embedding Configuration ---
EMBEDDING_TIMEOUT=30.0

# --- Batch Chunking Configuration (for llama-cpp) ---
# These settings optimize embedding requests for llama-cpp's context limits
EMBEDDING_BATCH_SIZE=512
EMBEDDING_UBATCH_SIZE=512
EMBEDDING_MAX_CONTEXT=8192

# ============================================================================
# Memory System Configuration
# ============================================================================
MEMORY_ENABLED=true
MAX_CONTEXT_TOKENS=8000
SIMILARITY_THRESHOLD=0.7
MIN_IMPORTANCE_SCORE=0.7

# ============================================================================
# Message Size Limits
# ============================================================================
# Maximum tokens allowed for incoming messages (default: 32768)
# This limit prevents excessively large requests that could overwhelm the system
MESSAGE_MAX_TOKENS=32768

# ============================================================================
# Background Task Configuration (Async Embedding Generation)
# ============================================================================
# Enable background task processing for async operations
BACKGROUND_TASKS_ENABLED=true

# Number of worker threads for background tasks
BACKGROUND_TASK_WORKERS=5

# Maximum retry attempts for failed tasks
BACKGROUND_TASK_MAX_RETRIES=3

# Initial retry delay in seconds (uses exponential backoff)
BACKGROUND_TASK_RETRY_DELAY=1.0

# Cleanup interval for old completed/failed tasks (hours)
BACKGROUND_TASK_CLEANUP_HOURS=24

# --- Async Embedding Configuration ---
# Enable async embedding generation (non-blocking)
ASYNC_EMBEDDINGS_ENABLED=true

# Number of messages to batch together for embedding generation
ASYNC_EMBEDDING_BATCH_SIZE=50

# Priority level for embedding tasks: LOW, NORMAL, HIGH, CRITICAL
ASYNC_EMBEDDING_PRIORITY=NORMAL

# --- Async Deduplication Configuration ---
# Enable async document enhancement (non-blocking embedding generation for deduplicated documents)
ASYNC_DEDUPLICATION_ENABLED=true

# Number of documents to batch together for enhancement
DEDUPLICATION_BATCH_SIZE=20

# Priority level for document enhancement tasks: LOW, NORMAL, HIGH, CRITICAL
DEDUPLICATION_ENHANCEMENT_PRIORITY=NORMAL

# Enable HTML content extraction and processing
HTML_CONTENT_EXTRACTION=true

# Minimum token count for document deduplication
MIN_TOKENS_FOR_DEDUP=500

# Semantic similarity threshold for duplicate detection (0.0-1.0)
DEDUPLICATION_THRESHOLD=0.95

# Reference expansion strategy: smart, full, summary, minimal
REFERENCE_EXPANSION_STRATEGY=smart

# ============================================================================
# Monitoring Configuration
# ============================================================================
PROMETHEUS_ENABLED=true
METRICS_PORT=9090

# ============================================================================
# Example Configurations for Different Setups
# ============================================================================

# Example 1: Using Ollama (default)
# EMBEDDING_PROVIDER=ollama
# OLLAMA_HOST=localhost
# OLLAMA_PORT=11434
# EMBEDDING_MODEL=nomic-embed-text

# Example 2: Using llama-cpp with OpenAI-compatible API
# EMBEDDING_PROVIDER=openai
# OPENAI_EMBEDDING_BASE_URL=http://localhost:8080
# OPENAI_EMBEDDING_MODEL=text-embedding-ada-002
# OPENAI_EMBEDDING_API_KEY=  # Optional, leave empty if not required

# Example 3: Using actual OpenAI API
# EMBEDDING_PROVIDER=openai
# OPENAI_EMBEDDING_BASE_URL=https://api.openai.com
# OPENAI_EMBEDDING_MODEL=text-embedding-3-small
# OPENAI_EMBEDDING_API_KEY=sk-your-openai-api-key

# Example 4: Using LocalAI
# EMBEDDING_PROVIDER=openai
# OPENAI_EMBEDDING_BASE_URL=http://localhost:8080
# OPENAI_EMBEDDING_MODEL=bert-embeddings
# OPENAI_EMBEDDING_API_KEY=  # Optional