File size: 3,255 Bytes
461adca 71df805 461adca | 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 | import os
from enum import Enum
from pathlib import Path
from dotenv import load_dotenv
# Load environment variables
load_dotenv()
# API Keys
AWS_ACCESS_KEY_ID = os.getenv("AWS_ACCESS_KEY_ID")
AWS_SECRET_ACCESS_KEY = os.getenv("AWS_SECRET_ACCESS_KEY")
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
ANTHROPIC_API_KEY = os.getenv("ANTHROPIC_API_KEY")
DEEPSEEK_API_KEY = os.getenv("DEEPSEEK_API_KEY")
# Debug: Print key status (masked)
print("="*30)
print("🔧 CONFIGURATION DEBUG")
print(f"OPENAI_API_KEY: {'✅ Found' if OPENAI_API_KEY else '❌ Missing'}")
if OPENAI_API_KEY:
print(f" Length: {len(OPENAI_API_KEY)}")
print(f" Prefix: {OPENAI_API_KEY[:5]}...")
print(f"ANTHROPIC_API_KEY: {'✅ Found' if ANTHROPIC_API_KEY else '❌ Missing'}")
print(f"DEEPSEEK_API_KEY: {'✅ Found' if DEEPSEEK_API_KEY else '❌ Missing'}")
print(f"GEMINI_API_KEY: {'✅ Found' if os.getenv('GEMINI_API_KEY') else '❌ Missing'}")
print("="*30)
# Конфігурація Gemini
GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
if GEMINI_API_KEY:
from google import genai
# New google.genai package - client-based approach
genai_client = genai.Client(api_key=GEMINI_API_KEY)
class ModelProvider(str, Enum):
OPENAI = "openai"
ANTHROPIC = "anthropic"
GEMINI = "gemini"
DEEPSEEK = "deepseek"
# NOTE: All configuration values (AWS, LlamaIndex, Schemas, Models, etc.) are now
# defined in config/environments/default.yaml to avoid duplication.
# This file only contains:
# 1. API key loading from environment variables
# 2. ModelProvider enum (Python-specific type)
# 3. Gemini client initialization
# 4. Environment validation function
#
# To access configuration: from config import get_settings
# To access models: from config import GenerationModelName, AnalysisModelName, DEFAULT_GENERATION_MODEL
# For backward compatibility, you can still: from config import BUCKET_NAME, LOCAL_DIR, etc.
# Check if required environment variables are set
def validate_environment(require_ai_provider: bool = True, require_aws: bool = False):
"""
Validate environment variables.
Args:
require_ai_provider: If True, requires at least one AI provider API key
require_aws: If True, requires AWS credentials
Returns:
dict: Status of each provider (available/missing)
"""
status = {
"openai": bool(os.getenv("OPENAI_API_KEY")),
"anthropic": bool(os.getenv("ANTHROPIC_API_KEY")),
"gemini": bool(os.getenv("GEMINI_API_KEY")),
"deepseek": bool(os.getenv("DEEPSEEK_API_KEY")),
"aws": bool(os.getenv("AWS_ACCESS_KEY_ID") and os.getenv("AWS_SECRET_ACCESS_KEY"))
}
# Check if at least one AI provider is available
if require_ai_provider:
if not any([status["openai"], status["anthropic"], status["gemini"], status["deepseek"]]):
raise ValueError(
"At least one AI provider API key is required. Please set one of: "
"OPENAI_API_KEY, ANTHROPIC_API_KEY, GEMINI_API_KEY, DEEPSEEK_API_KEY"
)
# Check if AWS is required
if require_aws and not status["aws"]:
raise ValueError("AWS credentials (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY) are required")
return status |