LLM Providers

pip install remina-memory[openai]

"llm": {
    "provider": "openai",
    "config": {
        "api_key": None,  # Uses OPENAI_API_KEY env
        "model": "gpt-4o-mini",
        "temperature": 0.1,
        "max_tokens": 2000,
        "base_url": None,
    }
}

pip install remina-memory[gemini]

"llm": {
    "provider": "gemini",
    "config": {
        "api_key": None,  # Uses GOOGLE_API_KEY env
        "model": "gemini-2.0-flash",
        "temperature": 0.1,
        "max_tokens": 2000,
    }
}

pip install remina-memory[anthropic]

"llm": {
    "provider": "anthropic",
    "config": {
        "api_key": None,  # Uses ANTHROPIC_API_KEY env
        "model": "claude-3-5-sonnet-20240620",
        "temperature": 0.1,
        "max_tokens": 2000,
    }
}

pip install remina-memory[ollama]

"llm": {
    "provider": "ollama",
    "config": {
        "base_url": "http://localhost:11434",
        "model": "llama3.2",
        "temperature": 0.1,
    }
}

curl -fsSL https://ollama.com/install.sh | sh
ollama pull llama3.2

class LLMBase(ABC):
    def generate_response(
        self,
        messages: List[Dict[str, str]],
        tools: Optional[List[Dict]] = None,
        tool_choice: str = "auto",
        **kwargs,
    ) -> Dict[str, Any]
    
    @property
    def model_name(self) -> str

"llm": {
    "provider": "openai",
    "config": {
        "model": "gpt-4o-mini",
        "temperature": 0.1,
    }
}