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c2ea5ed 18efc55 c2ea5ed 7bc750c c2ea5ed 18efc55 c2ea5ed 18efc55 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 | import os
from pathlib import Path
from dotenv import load_dotenv
def load_environment_variables():
"""
Load environment variables with proper priority:
1. System environment variables (highest priority - for production/HF Spaces)
2. .env file (fallback for local development)
"""
# First check if we're in a production environment (HF Spaces, Docker, etc.)
# by looking for common production indicators
is_production = any([
os.getenv("SPACE_ID"), # Hugging Face Spaces
os.getenv("RENDER"), # Render.com
os.getenv("RAILWAY_ENVIRONMENT"), # Railway
os.getenv("VERCEL"), # Vercel
os.getenv("KUBERNETES_SERVICE_HOST"), # Kubernetes
os.getenv("AWS_LAMBDA_FUNCTION_NAME"), # AWS Lambda
])
# Load .env file only if not in production AND file exists
env_path = Path('.') / '.env'
if not is_production and env_path.exists():
print(f"🔧 Loading environment variables from {env_path}")
load_dotenv(dotenv_path=env_path, override=False) # Don't override existing env vars
elif is_production:
print("🚀 Production environment detected, using system environment variables")
else:
print("⚠️ No .env file found and not in production environment")
# Load environment variables using the unified method
load_environment_variables()
# OpenAI Configuration
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
OPENAI_MODEL_NAME = os.getenv("OPENAI_MODEL_NAME", "gpt-5-mini")
AZURE_API_KEY = os.getenv("AZURE_API_KEY")
AZURE_API_BASE = os.getenv("AZURE_API_BASE")
AZURE_API_VERSION = os.getenv("AZURE_API_VERSION")
# Langfuse Configuration
LANGFUSE_PUBLIC_KEY = os.getenv("LANGFUSE_PUBLIC_KEY")
LANGFUSE_SECRET_KEY = os.getenv("LANGFUSE_SECRET_KEY")
LANGFUSE_HOST = os.getenv("LANGFUSE_HOST", "https://cloud.langfuse.com")
LANGFUSE_AUTH = ""
if LANGFUSE_PUBLIC_KEY and LANGFUSE_SECRET_KEY:
import base64
LANGFUSE_AUTH = base64.b64encode(f"{LANGFUSE_PUBLIC_KEY}:{LANGFUSE_SECRET_KEY}".encode()).decode()
# Other API Keys
ANTHROPIC_API_KEY = os.getenv("ANTHROPIC_API_KEY")
# Database Configuration
DB_URI = os.getenv("DB_URI", "sqlite:///agent_monitoring.db")
# Function to validate configuration
def validate_config():
"""Validates that all required environment variables are set"""
required_vars = [
("OPENAI_API_KEY", OPENAI_API_KEY),
]
missing_vars = [var_name for var_name, var_value in required_vars if not var_value]
if missing_vars:
missing_vars_str = ", ".join(missing_vars)
print(f"❌ Missing required environment variables: {missing_vars_str}")
print(f"📝 Please set them in the .env file or as environment variables")
return False
return True
def debug_config():
"""Debug function to show current configuration state"""
print("🔍 AgentGraph Configuration Debug:")
print("=" * 50)
# Show environment loading method
env_path = Path('.') / '.env'
is_production = any([
os.getenv("SPACE_ID"),
os.getenv("RENDER"),
os.getenv("RAILWAY_ENVIRONMENT"),
os.getenv("VERCEL"),
os.getenv("KUBERNETES_SERVICE_HOST"),
os.getenv("AWS_LAMBDA_FUNCTION_NAME"),
])
print(f"🏗️ Environment: {'Production' if is_production else 'Development'}")
print(f"📁 .env file exists: {env_path.exists()}")
print(f"📍 Working directory: {Path.cwd()}")
print()
# Show key configuration values (masked)
configs = [
("OPENAI_API_KEY", OPENAI_API_KEY),
("OPENAI_MODEL_NAME", OPENAI_MODEL_NAME),
("LANGFUSE_PUBLIC_KEY", LANGFUSE_PUBLIC_KEY),
("LANGFUSE_SECRET_KEY", LANGFUSE_SECRET_KEY),
("LANGFUSE_HOST", LANGFUSE_HOST),
("DB_URI", DB_URI),
]
for name, value in configs:
if value:
if "KEY" in name or "SECRET" in name:
masked = f"{value[:8]}..." if len(value) > 8 else "***"
print(f"✅ {name}: {masked}")
else:
print(f"✅ {name}: {value}")
else:
print(f"❌ {name}: Not set")
print("=" * 50)
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