Nextcloud MCP Server

"""LLM provider abstraction for RAG evaluation. DEPRECATED: This module is maintained for backward compatibility with RAG evaluation tests. New code should use nextcloud_mcp_server.providers directly. Supports Ollama (local), Anthropic (cloud), Bedrock (AWS), and OpenAI (cloud) providers for both ground truth generation and evaluation. """ import os from nextcloud_mcp_server.providers import ( AnthropicProvider, BedrockProvider, OllamaProvider, OpenAIProvider, Provider, ) def create_llm_provider( provider: str | None = None, ollama_base_url: str | None = None, ollama_model: str | None = None, anthropic_api_key: str | None = None, anthropic_model: str | None = None, bedrock_region: str | None = None, bedrock_model: str | None = None, openai_api_key: str | None = None, openai_base_url: str | None = None, openai_model: str | None = None, ) -> Provider: """Create an LLM provider from environment variables or arguments. Args: provider: Provider type ('ollama', 'anthropic', 'bedrock', or 'openai'). Defaults to RAG_EVAL_PROVIDER env var or 'ollama' ollama_base_url: Ollama base URL. Defaults to RAG_EVAL_OLLAMA_BASE_URL or 'http://localhost:11434' ollama_model: Ollama model. Defaults to RAG_EVAL_OLLAMA_MODEL or 'llama3.2:1b' anthropic_api_key: Anthropic API key. Defaults to RAG_EVAL_ANTHROPIC_API_KEY env var anthropic_model: Anthropic model. Defaults to RAG_EVAL_ANTHROPIC_MODEL or 'claude-3-5-sonnet-20241022' bedrock_region: AWS region. Defaults to RAG_EVAL_BEDROCK_REGION or AWS_REGION env var bedrock_model: Bedrock model ID. Defaults to RAG_EVAL_BEDROCK_MODEL or 'anthropic.claude-3-sonnet-20240229-v1:0' openai_api_key: OpenAI API key. Defaults to OPENAI_API_KEY env var openai_base_url: OpenAI base URL. Defaults to OPENAI_BASE_URL (for GitHub Models API) openai_model: OpenAI model. Defaults to OPENAI_GENERATION_MODEL or 'gpt-4o-mini' Returns: Provider instance Raises: ValueError: If provider is invalid or required credentials are missing """ # Get provider from args or env provider = provider or os.environ.get("RAG_EVAL_PROVIDER", "ollama") if provider == "ollama": # Try RAG_EVAL_OLLAMA_BASE_URL, then OLLAMA_HOST, then default base_url = ( ollama_base_url or os.environ.get("RAG_EVAL_OLLAMA_BASE_URL") or os.environ.get("OLLAMA_HOST") or "http://localhost:11434" ) model = ollama_model or os.environ.get("RAG_EVAL_OLLAMA_MODEL", "llama3.2:1b") return OllamaProvider( base_url=base_url, embedding_model=None, generation_model=model ) elif provider == "anthropic": api_key = anthropic_api_key or os.environ.get("RAG_EVAL_ANTHROPIC_API_KEY") if not api_key: raise ValueError( "Anthropic API key required. Set RAG_EVAL_ANTHROPIC_API_KEY environment variable." ) model = anthropic_model or os.environ.get( "RAG_EVAL_ANTHROPIC_MODEL", "claude-3-5-sonnet-20241022" ) return AnthropicProvider(api_key=api_key, model=model) elif provider == "bedrock": region = bedrock_region or os.environ.get( "RAG_EVAL_BEDROCK_REGION", os.environ.get("AWS_REGION", "us-east-1") ) model = bedrock_model or os.environ.get( "RAG_EVAL_BEDROCK_MODEL", "anthropic.claude-3-sonnet-20240229-v1:0" ) return BedrockProvider( region_name=region, embedding_model=None, generation_model=model ) elif provider == "openai": api_key = openai_api_key or os.environ.get("OPENAI_API_KEY") if not api_key: raise ValueError( "OpenAI API key required. Set OPENAI_API_KEY environment variable." ) base_url = openai_base_url or os.environ.get("OPENAI_BASE_URL") model = openai_model or os.environ.get("OPENAI_GENERATION_MODEL", "gpt-4o-mini") return OpenAIProvider( api_key=api_key, base_url=base_url, embedding_model=None, generation_model=model, ) else: raise ValueError( f"Invalid provider: {provider}. Must be 'ollama', 'anthropic', 'bedrock', or 'openai'." )