from selfmemory.configs.llms.base import BaseLlmConfig
class AnthropicConfig(BaseLlmConfig):
"""
Configuration class for Anthropic-specific parameters.
Inherits from BaseLlmConfig and adds Anthropic-specific settings.
"""
def __init__(
self,
# Base parameters
model: str | None = None,
temperature: float = 0.1,
api_key: str | None = None,
max_tokens: int = 2000,
top_p: float = 0.1,
top_k: int = 1,
enable_vision: bool = False,
vision_details: str | None = "auto",
http_client_proxies: dict | None = None,
# Anthropic-specific parameters
anthropic_base_url: str | None = None,
):
"""
Initialize Anthropic configuration.
Args:
model: Anthropic model to use, defaults to None
temperature: Controls randomness, defaults to 0.1
api_key: Anthropic API key, defaults to None
max_tokens: Maximum tokens to generate, defaults to 2000
top_p: Nucleus sampling parameter, defaults to 0.1
top_k: Top-k sampling parameter, defaults to 1
enable_vision: Enable vision capabilities, defaults to False
vision_details: Vision detail level, defaults to "auto"
http_client_proxies: HTTP client proxy settings, defaults to None
anthropic_base_url: Anthropic API base URL, defaults to None
"""
# Initialize base parameters
super().__init__(
model=model,
temperature=temperature,
api_key=api_key,
max_tokens=max_tokens,
top_p=top_p,
top_k=top_k,
enable_vision=enable_vision,
vision_details=vision_details,
http_client_proxies=http_client_proxies,
)
# Anthropic-specific parameters
self.anthropic_base_url = anthropic_base_url
