"""Beaver provider 子系统的统一契约。""" from __future__ import annotations from abc import ABC, abstractmethod from dataclasses import dataclass, field from typing import Any @dataclass(slots=True) class ToolCallRequest: """模型返回的一次工具调用请求。""" id: str name: str arguments: dict[str, Any] @dataclass(slots=True) class LLMResponse: """统一的模型响应结构。""" content: str | None tool_calls: list[ToolCallRequest] = field(default_factory=list) finish_reason: str = "stop" usage: dict[str, Any] = field(default_factory=dict) reasoning_content: str | None = None provider_name: str | None = None model: str | None = None @property def has_tool_calls(self) -> bool: return bool(self.tool_calls) class LLMProvider(ABC): """所有 provider 实现必须遵守的统一接口。""" def __init__( self, api_key: str | None = None, api_base: str | None = None, request_timeout_seconds: float | None = None, ) -> None: self.api_key = api_key self.api_base = api_base self.request_timeout_seconds = ( max(1.0, float(request_timeout_seconds)) if request_timeout_seconds is not None else None ) @staticmethod def sanitize_empty_content(messages: list[dict[str, Any]]) -> list[dict[str, Any]]: """清理 provider 普遍不接受的空 content。""" result: list[dict[str, Any]] = [] for message in messages: content = message.get("content") if isinstance(content, str) and content == "": clean = dict(message) clean["content"] = None if (message.get("role") == "assistant" and message.get("tool_calls")) else "(empty)" result.append(clean) continue if isinstance(content, list): filtered = [ item for item in content if not ( isinstance(item, dict) and item.get("type") in ("text", "input_text", "output_text") and not item.get("text") ) ] if len(filtered) != len(content): clean = dict(message) clean["content"] = filtered or "(empty)" if message.get("role") == "assistant" and message.get("tool_calls") and not filtered: clean["content"] = None result.append(clean) continue result.append(message) return result @abstractmethod async def chat( self, messages: list[dict[str, Any]], tools: list[dict[str, Any]] | None = None, model: str | None = None, max_tokens: int | None = None, temperature: float = 0.7, thinking_enabled: bool | None = None, ) -> LLMResponse: """统一聊天接口。""" @abstractmethod def get_default_model(self) -> str: """返回 provider 的默认模型名。"""