Nextcloud MCP Server

"""Provider fixtures for integration tests. This module provides pytest fixtures that configure LLM providers based on an explicit --provider flag. Supports OpenAI, Ollama, Anthropic, and Bedrock. Usage: pytest tests/integration/test_rag.py --provider=openai pytest tests/integration/test_rag.py --provider=ollama pytest tests/integration/test_rag.py --provider=anthropic pytest tests/integration/test_rag.py --provider=bedrock Environment Variables by Provider: OpenAI: OPENAI_API_KEY: API key (required) OPENAI_BASE_URL: Base URL override (e.g., "https://models.github.ai/inference") OPENAI_EMBEDDING_MODEL: Embedding model (default: "text-embedding-3-small") OPENAI_GENERATION_MODEL: Generation model (default: "gpt-4o-mini") Ollama: OLLAMA_BASE_URL: API URL (required, e.g., "http://localhost:11434") OLLAMA_EMBEDDING_MODEL: Embedding model (default: "nomic-embed-text") OLLAMA_GENERATION_MODEL: Generation model (default: "llama3.2:1b") Anthropic: ANTHROPIC_API_KEY: API key (required) ANTHROPIC_GENERATION_MODEL: Model (default: "claude-3-haiku-20240307") Bedrock: AWS_REGION: AWS region (required) BEDROCK_EMBEDDING_MODEL: Embedding model ID BEDROCK_GENERATION_MODEL: Generation model ID """ import logging import os from typing import AsyncGenerator import pytest from nextcloud_mcp_server.providers.base import Provider logger = logging.getLogger(__name__) # Valid provider names (must match conftest.py) VALID_PROVIDERS = ["openai", "ollama", "anthropic", "bedrock"] async def create_generation_provider(provider_name: str) -> Provider: """Create a provider configured for text generation. Args: provider_name: One of "openai", "ollama", "anthropic", "bedrock" Returns: Provider instance configured for generation Raises: ValueError: If provider_name is invalid or required env vars missing """ if provider_name == "openai": from nextcloud_mcp_server.providers.openai import OpenAIProvider api_key = os.getenv("OPENAI_API_KEY") if not api_key: raise ValueError("OPENAI_API_KEY environment variable required") base_url = os.getenv("OPENAI_BASE_URL") generation_model = os.getenv("OPENAI_GENERATION_MODEL", "gpt-4o-mini") # GitHub Models API requires model name prefix if base_url and "models.github.ai" in base_url: if not generation_model.startswith("openai/"): generation_model = f"openai/{generation_model}" provider = OpenAIProvider( api_key=api_key, base_url=base_url, embedding_model=None, # Generation only generation_model=generation_model, ) logger.info(f"Created OpenAI generation provider: model={generation_model}") return provider elif provider_name == "ollama": from nextcloud_mcp_server.providers.ollama import OllamaProvider base_url = os.getenv("OLLAMA_BASE_URL") if not base_url: raise ValueError("OLLAMA_BASE_URL environment variable required") generation_model = os.getenv("OLLAMA_GENERATION_MODEL", "llama3.2:1b") provider = OllamaProvider( base_url=base_url, embedding_model=None, # Generation only generation_model=generation_model, ) logger.info(f"Created Ollama generation provider: model={generation_model}") return provider elif provider_name == "anthropic": from nextcloud_mcp_server.providers.anthropic import AnthropicProvider api_key = os.getenv("ANTHROPIC_API_KEY") if not api_key: raise ValueError("ANTHROPIC_API_KEY environment variable required") generation_model = os.getenv( "ANTHROPIC_GENERATION_MODEL", "claude-3-haiku-20240307" ) provider = AnthropicProvider( api_key=api_key, generation_model=generation_model, ) logger.info(f"Created Anthropic generation provider: model={generation_model}") return provider elif provider_name == "bedrock": from nextcloud_mcp_server.providers.bedrock import BedrockProvider region = os.getenv("AWS_REGION") if not region: raise ValueError("AWS_REGION environment variable required") generation_model = os.getenv("BEDROCK_GENERATION_MODEL") if not generation_model: raise ValueError("BEDROCK_GENERATION_MODEL environment variable required") provider = BedrockProvider( region=region, embedding_model=None, # Generation only generation_model=generation_model, ) logger.info(f"Created Bedrock generation provider: model={generation_model}") return provider else: raise ValueError(f"Unknown provider: {provider_name}. Valid: {VALID_PROVIDERS}") async def create_embedding_provider(provider_name: str) -> Provider: """Create a provider configured for embeddings. Args: provider_name: One of "openai", "ollama", "bedrock" (Anthropic does not support embeddings) Returns: Provider instance configured for embeddings Raises: ValueError: If provider_name is invalid, doesn't support embeddings, or required env vars missing """ if provider_name == "anthropic": raise ValueError("Anthropic does not support embeddings") if provider_name == "openai": from nextcloud_mcp_server.providers.openai import OpenAIProvider api_key = os.getenv("OPENAI_API_KEY") if not api_key: raise ValueError("OPENAI_API_KEY environment variable required") base_url = os.getenv("OPENAI_BASE_URL") embedding_model = os.getenv("OPENAI_EMBEDDING_MODEL", "text-embedding-3-small") # GitHub Models API requires model name prefix if base_url and "models.github.ai" in base_url: if not embedding_model.startswith("openai/"): embedding_model = f"openai/{embedding_model}" provider = OpenAIProvider( api_key=api_key, base_url=base_url, embedding_model=embedding_model, generation_model=None, # Embeddings only ) logger.info(f"Created OpenAI embedding provider: model={embedding_model}") return provider elif provider_name == "ollama": from nextcloud_mcp_server.providers.ollama import OllamaProvider base_url = os.getenv("OLLAMA_BASE_URL") if not base_url: raise ValueError("OLLAMA_BASE_URL environment variable required") embedding_model = os.getenv("OLLAMA_EMBEDDING_MODEL", "nomic-embed-text") provider = OllamaProvider( base_url=base_url, embedding_model=embedding_model, generation_model=None, # Embeddings only ) logger.info(f"Created Ollama embedding provider: model={embedding_model}") return provider elif provider_name == "bedrock": from nextcloud_mcp_server.providers.bedrock import BedrockProvider region = os.getenv("AWS_REGION") if not region: raise ValueError("AWS_REGION environment variable required") embedding_model = os.getenv("BEDROCK_EMBEDDING_MODEL") if not embedding_model: raise ValueError("BEDROCK_EMBEDDING_MODEL environment variable required") provider = BedrockProvider( region=region, embedding_model=embedding_model, generation_model=None, # Embeddings only ) logger.info(f"Created Bedrock embedding provider: model={embedding_model}") return provider else: raise ValueError(f"Unknown provider: {provider_name}. Valid: {VALID_PROVIDERS}") # ============================================================================= # Pytest Fixtures # ============================================================================= @pytest.fixture(scope="module") def provider_name(request) -> str: """Get the provider name from --provider flag. Raises pytest.skip if --provider not specified. """ name = request.config.getoption("--provider") if not name: pytest.skip("--provider flag required (openai, ollama, anthropic, bedrock)") return name @pytest.fixture(scope="module") async def generation_provider(provider_name: str) -> AsyncGenerator[Provider, None]: """Fixture providing a generation-capable provider. Requires --provider flag to be set. """ provider = await create_generation_provider(provider_name) yield provider await provider.close() @pytest.fixture(scope="module") async def embedding_provider(provider_name: str) -> AsyncGenerator[Provider, None]: """Fixture providing an embedding-capable provider. Requires --provider flag to be set. Note: Anthropic does not support embeddings - test will fail if used. """ if provider_name == "anthropic": pytest.skip("Anthropic does not support embeddings") provider = await create_embedding_provider(provider_name) yield provider await provider.close()