.env.example

# =============================================================================
# AUTOBOT MASTER CONFIGURATION - SINGLE SOURCE OF TRUTH
# =============================================================================
# AutoBot - AI-Powered Automation Platform
# Copyright (c) 2025 mrveiss
# Author: mrveiss
#
# Version: 1.0.0
# Issue: #599 - SSOT Configuration System Epic
# Issue: #601 - SSOT Phase 1: Foundation
#
# This file defines ALL configuration for AutoBot.
# All other configuration files derive from these values.
#
# USAGE:
#   1. Copy this file to .env: cp .env.example .env
#   2. Adjust values for your environment
#   3. Run: ./scripts/sync-env.sh to generate frontend .env
#
# NAMING CONVENTION: AUTOBOT_{CATEGORY}_{NAME}
# Categories: DEPLOYMENT, VM, PORT, LLM, REDIS, TIMEOUT, FEATURE, SECURITY
# =============================================================================


# =============================================================================
# DEPLOYMENT MODE CONFIGURATION
# =============================================================================
# Deployment mode determines infrastructure layout:
#   - hybrid: Mixed local/distributed (default for development)
#   - distributed: Full 6-VM deployment (production)
#   - local: All services on localhost (simple setup)
AUTOBOT_DEPLOYMENT_MODE=hybrid

# Environment type (development, staging, production)
AUTOBOT_ENVIRONMENT=development

# Debug mode (enables detailed logging)
AUTOBOT_DEBUG=true

# Log level (DEBUG, INFO, WARNING, ERROR)
AUTOBOT_LOG_LEVEL=INFO


# =============================================================================
# NETWORK INFRASTRUCTURE (6-VM Architecture)
# =============================================================================
# IP addresses for the distributed VM infrastructure.
# For local development, use 127.0.0.x addresses.
# For distributed deployment, use actual VM IPs.
#
# Default VM Layout:
#   Main (WSL)  - 172.16.168.20 - Backend API + VNC Desktop
#   VM1 Frontend - 172.16.168.21 - Web interface
#   VM2 NPU Worker - 172.16.168.22 - Hardware AI acceleration
#   VM3 Redis - 172.16.168.23 - Data layer
#   VM4 AI Stack - 172.16.168.24 - AI processing
#   VM5 Browser - 172.16.168.25 - Web automation (Playwright)

# Main Machine (WSL) - Backend API + VNC Desktop
AUTOBOT_BACKEND_HOST=172.16.168.20

# VM1 Frontend - Web interface (SINGLE FRONTEND SERVER)
AUTOBOT_FRONTEND_HOST=172.16.168.21

# VM2 NPU Worker - Hardware AI acceleration
AUTOBOT_NPU_WORKER_HOST=172.16.168.22

# VM3 Redis - Data layer
AUTOBOT_REDIS_HOST=172.16.168.23

# VM4 AI Stack - AI processing (Ollama, etc.)
AUTOBOT_AI_STACK_HOST=172.16.168.24

# VM5 Browser - Web automation (Playwright)
AUTOBOT_BROWSER_SERVICE_HOST=172.16.168.25

# Ollama host (typically localhost or AI Stack VM)
AUTOBOT_OLLAMA_HOST=127.0.0.1


# =============================================================================
# SERVICE PORTS
# =============================================================================
# Standard ports for all AutoBot services.

# Backend API port
AUTOBOT_BACKEND_PORT=8001

# Frontend web interface port
AUTOBOT_FRONTEND_PORT=5173

# Redis port
AUTOBOT_REDIS_PORT=6379

# Ollama LLM API port
AUTOBOT_OLLAMA_PORT=11434

# AI Stack port
AUTOBOT_AI_STACK_PORT=8080

# NPU Worker port
AUTOBOT_NPU_WORKER_PORT=8081

# Browser automation service port
AUTOBOT_BROWSER_SERVICE_PORT=3000

# VNC desktop port
AUTOBOT_VNC_PORT=6080

# Prometheus monitoring port
AUTOBOT_PROMETHEUS_PORT=9090

# Grafana dashboard port
AUTOBOT_GRAFANA_PORT=3000


# =============================================================================
# SERVICE URLs (Computed from hosts and ports)
# =============================================================================
# These are computed by the SSOT loaders, but can be overridden if needed.

AUTOBOT_BACKEND_URL=http://172.16.168.20:8001
AUTOBOT_FRONTEND_URL=http://172.16.168.21:5173
AUTOBOT_REDIS_URL=redis://172.16.168.23:6379
AUTOBOT_OLLAMA_URL=http://127.0.0.1:11434
AUTOBOT_AI_STACK_URL=http://172.16.168.24:8080
AUTOBOT_NPU_WORKER_URL=http://172.16.168.22:8081
AUTOBOT_BROWSER_SERVICE_URL=http://172.16.168.25:3000
AUTOBOT_WS_URL=ws://172.16.168.20:8001/ws


# =============================================================================
# REDIS DATABASE CONFIGURATION
# =============================================================================
# Redis database assignments for different data types.
# Each database is isolated for specific functionality.

AUTOBOT_REDIS_DB_MAIN=0
AUTOBOT_REDIS_DB_KNOWLEDGE=1
AUTOBOT_REDIS_DB_PROMPTS=2
AUTOBOT_REDIS_DB_AGENTS=3
AUTOBOT_REDIS_DB_METRICS=4
AUTOBOT_REDIS_DB_CACHE=5
AUTOBOT_REDIS_DB_SESSIONS=6
AUTOBOT_REDIS_DB_TASKS=7
AUTOBOT_REDIS_DB_LOGS=8
AUTOBOT_REDIS_DB_TEMP=9
AUTOBOT_REDIS_DB_BACKUP=10
AUTOBOT_REDIS_DB_TESTING=15

# Redis authentication (leave empty if no password)
AUTOBOT_REDIS_PASSWORD=


# =============================================================================
# LLM MODEL CONFIGURATION - SINGLE SOURCE OF TRUTH
# =============================================================================
# All model references in the codebase read from these environment variables.
# Change models here - they will be used across the entire application.
#
# Available Ollama models (run: ollama list):
#   - llama3.2:1b (1.3GB)        - Fast, lightweight
#   - qwen3.5:9b (4.4GB) - Balanced quality (RECOMMENDED)
#   - dolphin-llama3:8b (4.7GB)  - High quality
#   - qwen2.5-coder:7b (4.7GB)   - Code generation
#   - nomic-embed-text (274MB)   - Embeddings only

# Default model - used for all tasks unless overridden
AUTOBOT_DEFAULT_LLM_MODEL=qwen3.5:9b

# Specialized models by role (all default to AUTOBOT_DEFAULT_LLM_MODEL if not set)
AUTOBOT_EMBEDDING_MODEL=nomic-embed-text:latest
AUTOBOT_CLASSIFICATION_MODEL=qwen3.5:9b
AUTOBOT_REASONING_MODEL=qwen3.5:9b
AUTOBOT_RAG_MODEL=qwen3.5:9b
AUTOBOT_CODING_MODEL=qwen3.5:9b

# Agent/workflow models
AUTOBOT_ORCHESTRATOR_MODEL=qwen3.5:9b
AUTOBOT_AGENT_MODEL=qwen3.5:9b
AUTOBOT_RESEARCH_MODEL=qwen3.5:9b
AUTOBOT_ANALYSIS_MODEL=qwen3.5:9b
AUTOBOT_PLANNING_MODEL=qwen3.5:9b

# LLM provider (ollama, openai, anthropic)
AUTOBOT_LLM_PROVIDER=ollama

# LLM request timeout in seconds
AUTOBOT_LLM_TIMEOUT=30


# =============================================================================
# TIMEOUT CONFIGURATION
# =============================================================================
# Timeouts in milliseconds (ms) unless otherwise noted.

# API request timeout (ms)
AUTOBOT_API_TIMEOUT=10000

# WebSocket timeout (seconds)
AUTOBOT_WEBSOCKET_TIMEOUT=30

# Health check timeout (seconds)
AUTOBOT_HEALTH_CHECK_TIMEOUT=3

# Maximum concurrent requests
AUTOBOT_MAX_CONCURRENT_REQUESTS=50


# =============================================================================
# FEATURE FLAGS
# =============================================================================
# Enable/disable various features.

# Use unified configuration system
AUTOBOT_USE_UNIFIED_CONFIG=true

# Enable semantic chunking for documents
AUTOBOT_SEMANTIC_CHUNKING=true

# Enable debug mode for detailed logging
AUTOBOT_DEBUG_MODE=true

# Enable hot reload for development
AUTOBOT_HOT_RELOAD=true

# Single user mode (no authentication)
AUTOBOT_SINGLE_USER_MODE=true


# =============================================================================
# VNC CONFIGURATION
# =============================================================================
# VNC desktop and terminal configuration.

AUTOBOT_VNC_PASSWORD=<GENERATE_SECURE_PASSWORD>


# =============================================================================
# SECURITY CONFIGURATION
# =============================================================================
# Security-related settings.

# Service authentication enforcement
SERVICE_AUTH_ENFORCEMENT_MODE=true

# Service identity
SERVICE_ID=main-backend
SERVICE_KEY_FILE=/home/kali/.autobot/service-keys/main-backend.env


# =============================================================================
# TLS / mTLS CONFIGURATION (Issue #725)
# =============================================================================
# Transport Layer Security settings for secure service communication.
#
# TLS Modes:
#   - disabled: No TLS (default, for development)
#   - optional: TLS available but not enforced (migration phase)
#   - required: TLS required for all connections (production)
#
# Migration Path:
#   1. Start with disabled (development)
#   2. Switch to optional + generate certs (test TLS)
#   3. Switch to required + disable plain ports (production mTLS)

# TLS Mode (disabled, optional, required)
AUTOBOT_TLS_MODE=disabled

# Certificate directory (relative to project root or absolute path)
AUTOBOT_TLS_CERT_DIR=certs

# CA Certificate path
AUTOBOT_TLS_CA_CERT=certs/ca/ca-cert.pem

# Remote certificate directory on VMs
AUTOBOT_TLS_REMOTE_CERT_DIR=/etc/autobot/certs

# Redis TLS Settings
AUTOBOT_REDIS_TLS_ENABLED=false
AUTOBOT_REDIS_TLS_PORT=6380
AUTOBOT_REDIS_TLS_AUTH_CLIENTS=optional
AUTOBOT_REDIS_TLS_DISABLE_PLAIN=false

# Certificate Source: 'local' (files on controller) or 'slm-api' (fetch from SLM API)
AUTOBOT_TLS_SOURCE=local

# SLM API for certificate management (when AUTOBOT_TLS_SOURCE=slm-api)
# SLM_API_URL=http://172.16.168.19:8000
# SLM_API_TOKEN=<your-auth-token>
# REDIS_TLS_CREDENTIAL_ID=<credential-id-from-slm>

# Backend TLS (HTTPS for FastAPI)
AUTOBOT_BACKEND_TLS_ENABLED=false
AUTOBOT_BACKEND_TLS_PORT=8443


# =============================================================================
# CELERY CONFIGURATION (Task Queue)
# =============================================================================
# Celery broker and result backend using Redis.
# When AUTOBOT_REDIS_TLS_ENABLED=true, use rediss:// protocol and port 6380

CELERY_BROKER_URL=redis://172.16.168.23:6379/1
CELERY_RESULT_BACKEND=redis://172.16.168.23:6379/2
# For TLS: CELERY_BROKER_URL=rediss://172.16.168.23:6380/1
# For TLS: CELERY_RESULT_BACKEND=rediss://172.16.168.23:6380/2


# =============================================================================
# HARDWARE ACCELERATION
# =============================================================================
# TensorFlow/Keras compatibility settings.

TF_USE_LEGACY_KERAS=1
KERAS_BACKEND=tensorflow


# =============================================================================
# CHROMADB CONFIGURATION
# =============================================================================
# Vector database settings.

ANONYMIZED_TELEMETRY=False


# =============================================================================
# CONTEXTUAL RETRIEVAL (Issue #1498)
# =============================================================================
# Prepends LLM-generated context to each chunk before embedding.
# Reported +35% retrieval improvement. Disabled by default (zero behavior change).

# Enable contextual retrieval enrichment
CONTEXT_ENABLED=false

# LLM model for context generation (lightweight model recommended)
CONTEXT_MODEL=llama3.2:3b

# Days to cache per-document summaries in Redis (key: context:summary:{doc_id})
CONTEXT_SUMMARY_TTL_DAYS=30

# Max tokens for document text sent to summary LLM
CONTEXT_MAX_TOKENS=150


# =============================================================================
# FRONTEND ENVIRONMENT VARIABLES (VITE_*)
# =============================================================================
# These are auto-generated by ./scripts/sync-env.sh
# Do NOT edit directly - update the AUTOBOT_* variables above instead.
#
# Run: ./scripts/sync-env.sh to regenerate autobot-vue/.env

VITE_BACKEND_HOST=172.16.168.20
VITE_BACKEND_PORT=8001
VITE_FRONTEND_HOST=172.16.168.21
VITE_FRONTEND_PORT=5173
VITE_REDIS_HOST=172.16.168.23
VITE_REDIS_PORT=6379
VITE_OLLAMA_HOST=127.0.0.1
VITE_OLLAMA_PORT=11434
VITE_AI_STACK_HOST=172.16.168.24
VITE_AI_STACK_PORT=8080
VITE_NPU_WORKER_HOST=172.16.168.22
VITE_NPU_WORKER_PORT=8081
VITE_BROWSER_HOST=172.16.168.25
VITE_BROWSER_PORT=3000
VITE_HTTP_PROTOCOL=http

# VNC Configuration
VITE_DESKTOP_VNC_HOST=172.16.168.20
VITE_DESKTOP_VNC_PORT=6080
VITE_DESKTOP_VNC_PASSWORD=autobot
VITE_TERMINAL_VNC_HOST=172.16.168.20
VITE_TERMINAL_VNC_PORT=6080
VITE_TERMINAL_VNC_PASSWORD=autobot
VITE_PLAYWRIGHT_VNC_HOST=172.16.168.25
VITE_PLAYWRIGHT_VNC_PORT=6081
VITE_PLAYWRIGHT_VNC_PASSWORD=playwright

# API Configuration
VITE_API_TIMEOUT=60000
VITE_KNOWLEDGE_TIMEOUT=300000
VITE_API_RETRY_ATTEMPTS=3
VITE_API_RETRY_DELAY=1000
VITE_ENABLE_DEBUG=true
VITE_ENABLE_RUM=true
VITE_DISABLE_CACHE=false

# VM Infrastructure IPs (for multi-host deployments)
VITE_VM0_IP=172.16.168.20
VITE_VM1_IP=172.16.168.21
VITE_VM2_IP=172.16.168.22
VITE_VM3_IP=172.16.168.23
VITE_VM4_IP=172.16.168.24
VITE_VM5_IP=172.16.168.25


# =============================================================================
# LEGACY COMPATIBILITY VARIABLES
# =============================================================================
# These are provided for backward compatibility with older code.
# New code should use AUTOBOT_* variables via the SSOT config loaders.

REDIS_HOST=172.16.168.23
REDIS_PORT=6379
OLLAMA_HOST=127.0.0.1
OLLAMA_PORT=11434


# =============================================================================
# OPTIONAL: USER MANAGEMENT & POSTGRESQL (Issue #576)
# =============================================================================
# Uncomment and configure for multi-user deployments.
#
# User management mode:
#   single_user    - No authentication, personal use (default)
#   single_company - Single organization, teams enabled
#   multi_company  - Multiple organizations with isolation
#   provider       - SaaS mode with billing and self-signup
#
# AUTOBOT_USER_MODE=single_user
#
# PostgreSQL Configuration (required for non-single_user modes)
# AUTOBOT_POSTGRES_HOST=172.16.168.23
# AUTOBOT_POSTGRES_PORT=5432
# AUTOBOT_POSTGRES_DB=autobot
# AUTOBOT_POSTGRES_USER=autobot
# AUTOBOT_POSTGRES_PASSWORD=<GENERATE_SECURE_PASSWORD>


# =============================================================================
# OPENTELEMETRY DISTRIBUTED TRACING (Issue #697)
# =============================================================================
# Configure OpenTelemetry for distributed tracing across the 6-VM infrastructure.
# Traces are exported to Jaeger running on the Redis VM.

# Jaeger OTLP endpoint (default: Redis VM port 4317)
AUTOBOT_JAEGER_ENDPOINT=http://172.16.168.23:4317

# Trace sampling rate (0.0-1.0)
# 1.0 = trace everything (development)
# 0.1 = trace 10% of requests (production recommended)
AUTOBOT_TRACE_SAMPLE_RATE=1.0

# Enable console span export for debugging
AUTOBOT_TRACE_CONSOLE=false


# =============================================================================
# OPTIONAL: ALERT NOTIFICATION (Issue #69)
# =============================================================================
# Uncomment and configure for Prometheus AlertManager integration.
#
# Email Notifications (SMTP)
# ALERT_EMAIL_USERNAME=autobot-alerts@example.com
# ALERT_EMAIL_PASSWORD=<YOUR_SMTP_PASSWORD>
# ALERT_EMAIL_TO=ops-team@example.com
#
# Slack Notifications
# ALERT_SLACK_WEBHOOK_URL=https://hooks.slack.com/services/YOUR/WEBHOOK/URL
#
# Alert Thresholds
# ALERT_ERROR_RATE_THRESHOLD=0.05
# ALERT_COOLDOWN_SECONDS=300
# ALERT_CIRCUIT_BREAKER_FAILURE_WARNING=3