agentic-reliability-framework/.env.example at main · petterjuan/agentic-reliability-framework · GitHub

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# =============================================================================
# Agentic Reliability Framework - Environment Configuration
# v3: Added RAG Graph, MCP Server, and Learning Loop features
# =============================================================================

# === Hugging Face API Configuration ===
HF_API_KEY=your_huggingface_api_key_here
HF_API_URL=https://router.huggingface.co/hf-inference/v1/completions

# === System Configuration ===
MAX_EVENTS_STORED=1000
FAISS_BATCH_SIZE=10
FAISS_SAVE_INTERVAL_SECONDS=30
VECTOR_DIM=384

# === Business Metrics ===
BASE_REVENUE_PER_MINUTE=100.0
BASE_USERS=1000

# === Rate Limiting ===
MAX_REQUESTS_PER_MINUTE=60
MAX_REQUESTS_PER_HOUR=500

# === Logging ===
LOG_LEVEL=INFO

# === Thresholds ===
LATENCY_WARNING=150.0
LATENCY_CRITICAL=300.0
LATENCY_EXTREME=500.0

# =============================================================================
# v3 RAG Graph Features (Phase 1: RAG Graph Foundation)
# =============================================================================

# Enable RAG Graph for historical incident retrieval
RAG_ENABLED=false

# RAG Graph configuration
RAG_SIMILARITY_THRESHOLD=0.3
RAG_MAX_INCIDENT_NODES=1000
RAG_MAX_OUTCOME_NODES=5000
RAG_CACHE_SIZE=100

# =============================================================================
# v3 MCP Server Features (Phase 2: Execution Boundary)
# =============================================================================

# MCP Server execution mode: advisory, approval, or autonomous
MCP_MODE=advisory

# Enable MCP Server for execution boundaries
MCP_ENABLED=false

# MCP Server network configuration
MCP_HOST=localhost
MCP_PORT=8000

# =============================================================================
# v3 Learning Loop Features (Phase 3: Continuous Improvement)
# =============================================================================

# Enable learning from historical outcomes
LEARNING_ENABLED=false

# Minimum data points before applying learned patterns
LEARNING_MIN_DATA_POINTS=10

# =============================================================================
# Performance & Demo Configuration
# =============================================================================

# Agent timeout in seconds
AGENT_TIMEOUT_SECONDS=5

# Cache expiry time in minutes
CACHE_EXPIRY_MINUTES=15

# Enable demo mode with pre-configured scenarios
DEMO_MODE=false

# =============================================================================
# Error Rate Thresholds
# =============================================================================
ERROR_RATE_WARNING=0.05
ERROR_RATE_HIGH=0.15
ERROR_RATE_CRITICAL=0.30

# =============================================================================
# Resource Utilization Thresholds
# =============================================================================
CPU_WARNING=0.8
CPU_CRITICAL=0.9
MEMORY_WARNING=0.8
MEMORY_CRITICAL=0.9

# =============================================================================
# Forecasting Constants
# =============================================================================
SLOPE_THRESHOLD_INCREASING=5.0
SLOPE_THRESHOLD_DECREASING=-2.0
FORECAST_MIN_DATA_POINTS=5
FORECAST_LOOKAHEAD_MINUTES=15
HISTORY_WINDOW=50