修改了nanobot，往Hermes agent的风格走，进度1/3

app-instance/backend/beaver/engine/providers/base.py

@@ -0,0 +1,98 @@
+"""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 = 4096,
+        temperature: float = 0.7,
+    ) -> LLMResponse:
+        """统一聊天接口。"""
+
+    @abstractmethod
+    def get_default_model(self) -> str:
+        """返回 provider 的默认模型名。"""