Nextcloud MCP Server

"""Unified provider interface for embeddings and text generation.""" from abc import ABC, abstractmethod class Provider(ABC): """ Unified base class for LLM providers. Providers can support embeddings, text generation, or both. Use capability properties to determine what features are available. """ @property @abstractmethod def supports_embeddings(self) -> bool: """Whether this provider supports embedding generation.""" pass @property @abstractmethod def supports_generation(self) -> bool: """Whether this provider supports text generation.""" pass @abstractmethod async def embed(self, text: str) -> list[float]: """ Generate embedding vector for text. Args: text: Input text to embed Returns: Vector embedding as list of floats Raises: NotImplementedError: If provider doesn't support embeddings """ pass @abstractmethod async def embed_batch(self, texts: list[str]) -> list[list[float]]: """ Generate embeddings for multiple texts (optimized). Args: texts: List of texts to embed Returns: List of vector embeddings Raises: NotImplementedError: If provider doesn't support embeddings """ pass @abstractmethod def get_dimension(self) -> int: """ Get embedding dimension for this provider. Returns: Vector dimension (e.g., 768 for nomic-embed-text) Raises: NotImplementedError: If provider doesn't support embeddings """ pass @abstractmethod async def generate(self, prompt: str, max_tokens: int = 500) -> str: """ Generate text from a prompt. Args: prompt: The prompt to generate from max_tokens: Maximum tokens to generate Returns: Generated text Raises: NotImplementedError: If provider doesn't support generation """ pass @abstractmethod async def close(self) -> None: """Close the provider and release resources.""" pass