from typing import Any
from selfmemory.configs.llms.base import BaseLlmConfig
class LMStudioConfig(BaseLlmConfig):
"""
Configuration class for LM Studio-specific parameters.
Inherits from BaseLlmConfig and adds LM Studio-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,
# LM Studio-specific parameters
lmstudio_base_url: str | None = None,
lmstudio_response_format: dict[str, Any] | None = None,
):
"""
Initialize LM Studio configuration.
Args:
model: LM Studio model to use, defaults to None
temperature: Controls randomness, defaults to 0.1
api_key: LM Studio 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
lmstudio_base_url: LM Studio base URL, defaults to None
lmstudio_response_format: LM Studio response format, 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,
)
# LM Studio-specific parameters
self.lmstudio_base_url = lmstudio_base_url or "http://localhost:1234/v1"
self.lmstudio_response_format = lmstudio_response_format
