File size: 2,253 Bytes
dc893fb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 | """Base class for LLM clients."""
from abc import ABC, abstractmethod
from typing import Any
from ..retry import RetryConfig
from ..schema import LLMResponse, Message
class LLMClientBase(ABC):
"""Abstract base class for LLM clients.
This class defines the interface that all LLM clients must implement,
regardless of the underlying API protocol (Anthropic, OpenAI, etc.).
"""
def __init__(
self,
api_key: str,
api_base: str,
model: str,
retry_config: RetryConfig | None = None,
):
"""Initialize the LLM client.
Args:
api_key: API key for authentication
api_base: Base URL for the API
model: Model name to use
retry_config: Optional retry configuration
"""
self.api_key = api_key
self.api_base = api_base
self.model = model
self.retry_config = retry_config or RetryConfig()
# Callback for tracking retry count
self.retry_callback = None
@abstractmethod
async def generate(
self,
messages: list[Message],
tools: list[Any] | None = None,
) -> LLMResponse:
"""Generate response from LLM.
Args:
messages: List of conversation messages
tools: Optional list of Tool objects or dicts
Returns:
LLMResponse containing the generated content, thinking, and tool calls
"""
pass
@abstractmethod
def _prepare_request(
self,
messages: list[Message],
tools: list[Any] | None = None,
) -> dict[str, Any]:
"""Prepare the request payload for the API.
Args:
messages: List of conversation messages
tools: Optional list of available tools
Returns:
Dictionary containing the request payload
"""
pass
@abstractmethod
def _convert_messages(self, messages: list[Message]) -> tuple[str | None, list[dict[str, Any]]]:
"""Convert internal message format to API-specific format.
Args:
messages: List of internal Message objects
Returns:
Tuple of (system_message, api_messages)
"""
pass
|