Azure AI Search MCP Server

"""Configuration management for Azure AI Search MCP Server.""" import os from dotenv import load_dotenv from pydantic import BaseModel, Field # Load environment variables from .env file load_dotenv() class AzureSearchConfig(BaseModel): """Configuration for Azure AI Search.""" endpoint: str = Field( default_factory=lambda: os.getenv("AZURE_SEARCH_ENDPOINT", "") ) api_key: str = Field(default_factory=lambda: os.getenv("AZURE_SEARCH_API_KEY", "")) index_name: str = Field( default_factory=lambda: os.getenv("AZURE_SEARCH_INDEX_NAME", "") ) class MCPServerConfig(BaseModel): """Configuration for MCP Server.""" name: str = Field( default_factory=lambda: os.getenv("MCP_SERVER_NAME", "azure-search-mcp") ) version: str = Field( default_factory=lambda: os.getenv("MCP_SERVER_VERSION", "0.1.0") ) log_level: str = Field(default_factory=lambda: os.getenv("LOG_LEVEL", "INFO")) class LangSmithConfig(BaseModel): """Configuration for LangSmith tracing.""" tracing_enabled: bool = Field( default_factory=lambda: os.getenv("LANGCHAIN_TRACING_V2", "false").lower() == "true" ) endpoint: str = Field( default_factory=lambda: os.getenv( "LANGCHAIN_ENDPOINT", "https://api.smith.langchain.com" ) ) api_key: str = Field(default_factory=lambda: os.getenv("LANGCHAIN_API_KEY", "")) project: str = Field( default_factory=lambda: os.getenv("LANGCHAIN_PROJECT", "azure-search-mcp") ) class GeminiConfig(BaseModel): """Configuration for Google Gemini.""" api_key: str = Field(default_factory=lambda: os.getenv("GOOGLE_API_KEY", "")) model_name: str = Field( default_factory=lambda: os.getenv("GEMINI_MODEL", "gemini-1.5-flash") ) temperature: float = Field( default_factory=lambda: float(os.getenv("GEMINI_TEMPERATURE", "0.1")) ) class Config: """Main configuration class.""" def __init__(self): self.azure_search = AzureSearchConfig() self.mcp_server = MCPServerConfig() self.langsmith = LangSmithConfig() self.gemini = GeminiConfig() @classmethod def from_env(cls) -> "Config": """Create configuration from environment variables.""" return cls() # Global configuration instance config = Config.from_env()