Nextcloud MCP Server

"""Provider registry and factory for auto-detection and instantiation.""" import logging import os from .base import Provider from .bedrock import BedrockProvider from .ollama import OllamaProvider from .openai import OpenAIProvider from .simple import SimpleProvider logger = logging.getLogger(__name__) class ProviderRegistry: """ Registry for provider auto-detection and instantiation. Checks environment variables in priority order and creates appropriate provider: 1. Bedrock (AWS_REGION + BEDROCK_*_MODEL) 2. OpenAI (OPENAI_API_KEY) 3. Ollama (OLLAMA_BASE_URL) 4. Simple (fallback for testing/development) """ @staticmethod def create_provider() -> Provider: """ Auto-detect and create provider based on environment variables. Priority order: 1. Bedrock - if AWS_REGION or BEDROCK_EMBEDDING_MODEL is set 2. OpenAI - if OPENAI_API_KEY is set 3. Ollama - if OLLAMA_BASE_URL is set 4. Simple - fallback for testing/development Returns: Provider instance Environment Variables: Bedrock: - AWS_REGION: AWS region (e.g., "us-east-1") - AWS_ACCESS_KEY_ID: AWS access key (optional, uses credential chain) - AWS_SECRET_ACCESS_KEY: AWS secret key (optional) - BEDROCK_EMBEDDING_MODEL: Model ID for embeddings (e.g., "amazon.titan-embed-text-v2:0") - BEDROCK_GENERATION_MODEL: Model ID for text generation (e.g., "anthropic.claude-3-sonnet-20240229-v1:0") OpenAI: - OPENAI_API_KEY: OpenAI API key (or GITHUB_TOKEN for GitHub Models) - OPENAI_BASE_URL: Base URL override (e.g., "https://models.github.ai/inference") - OPENAI_EMBEDDING_MODEL: Model for embeddings (default: "text-embedding-3-small") - OPENAI_GENERATION_MODEL: Model for text generation (e.g., "gpt-4o-mini") Ollama: - OLLAMA_BASE_URL: Ollama API base URL (e.g., "http://localhost:11434") - OLLAMA_EMBEDDING_MODEL: Model for embeddings (default: "nomic-embed-text") - OLLAMA_GENERATION_MODEL: Model for text generation (e.g., "llama3.2:1b") - OLLAMA_VERIFY_SSL: Verify SSL certificates (default: "true") Simple (no configuration needed, fallback): - SIMPLE_EMBEDDING_DIMENSION: Embedding dimension (default: 384) """ # 1. Check for Bedrock aws_region = os.getenv("AWS_REGION") bedrock_embedding_model = os.getenv("BEDROCK_EMBEDDING_MODEL") bedrock_generation_model = os.getenv("BEDROCK_GENERATION_MODEL") if aws_region or bedrock_embedding_model or bedrock_generation_model: logger.info( f"Using Bedrock provider: region={aws_region}, " f"embedding_model={bedrock_embedding_model}, " f"generation_model={bedrock_generation_model}" ) return BedrockProvider( region_name=aws_region, embedding_model=bedrock_embedding_model, generation_model=bedrock_generation_model, aws_access_key_id=os.getenv("AWS_ACCESS_KEY_ID"), aws_secret_access_key=os.getenv("AWS_SECRET_ACCESS_KEY"), ) # 2. Check for OpenAI openai_api_key = os.getenv("OPENAI_API_KEY") if openai_api_key: base_url = os.getenv("OPENAI_BASE_URL") embedding_model = os.getenv( "OPENAI_EMBEDDING_MODEL", "text-embedding-3-small" ) generation_model = os.getenv("OPENAI_GENERATION_MODEL") logger.info( f"Using OpenAI provider: base_url={base_url or 'default'}, " f"embedding_model={embedding_model}, " f"generation_model={generation_model}" ) return OpenAIProvider( api_key=openai_api_key, base_url=base_url, embedding_model=embedding_model, generation_model=generation_model, ) # 3. Check for Ollama (local LLM) ollama_url = os.getenv("OLLAMA_BASE_URL") if ollama_url: embedding_model = os.getenv("OLLAMA_EMBEDDING_MODEL", "nomic-embed-text") generation_model = os.getenv("OLLAMA_GENERATION_MODEL") verify_ssl = os.getenv("OLLAMA_VERIFY_SSL", "true").lower() == "true" logger.info( f"Using Ollama provider: {ollama_url}, " f"embedding_model={embedding_model}, " f"generation_model={generation_model}" ) return OllamaProvider( base_url=ollama_url, embedding_model=embedding_model, generation_model=generation_model, verify_ssl=verify_ssl, ) # 4. Fallback to Simple provider for development/testing dimension = int(os.getenv("SIMPLE_EMBEDDING_DIMENSION", "384")) logger.warning( "No provider configured (AWS_REGION, OPENAI_API_KEY, OLLAMA_BASE_URL not set). " "Using SimpleProvider for testing/development. " "For production, configure Bedrock, OpenAI, or Ollama." ) return SimpleProvider(dimension=dimension) # Singleton instance _provider: Provider | None = None def get_provider() -> Provider: """ Get singleton provider instance. Returns: Global Provider instance (auto-detected on first call) """ global _provider if _provider is None: _provider = ProviderRegistry.create_provider() return _provider def reset_provider(): """ Reset singleton provider instance. Useful for testing or reconfiguration. """ global _provider _provider = None