feat(engine): 添加MCP连接管理和工具集成功能
- 集成MCP连接管理器，支持MCP服务器连接 - 添加多种内置工具：ClarifyTool、CronTool、DelegateTool、ExecuteCodeTool、 PatchFileTool、ProcessTool、SendMessageTool、SpawnTool、TerminalTool、 TodoTool、WebFetchTool、WebSearchTool、WriteFileTool等 - 实现工具注册和装配功能 - 添加技能选择上下文参数 - 支持思考模式控制参数thinking_enabled feat(coordinator): 重构任务执行计划器参数命名 - 将learning_candidate_enabled重命名为allow_candidate_generation - 更新TeamGraphScheduler中的参数传递 - 修改LocalAgentRunner中的相关参数处理 - 更新README文档中的相应描述 refactor(context): 标准化工具调用参数格式 - 添加_json导入用于参数序列化 - 实现_provider_tool_calls方法标准化OpenAI兼容的工具调用载荷 - 修复工具调用中参数非字符串类型的序列化问题 refactor(session): 优化消息历史记录过滤逻辑 - 修改get_messages_as_conversation为基于运行状态过滤消息 - 排除未完成、失败或错误结束的运行记录 - 改进对话历史的可见性控制机制 fix(store): 修复FTS索引重建逻辑 - 添加异常处理防止FTS索引创建失败 - 实现_rebuild_fts_index方法重新构建全文搜索索引 - 优化索引触发器和表的维护流程
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@ -1,40 +1,144 @@
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"""Main Agent routing between simple chat and internal Task mode."""
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"""LLM-based routing between simple chat and internal Task mode."""
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from __future__ import annotations
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import re
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import asyncio
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import json
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from typing import Any
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from .models import MainAgentDecision, TaskRecord
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class MainAgentRouter:
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"""Small deterministic classifier used before the main AgentLoop.
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"""Semantic router for deciding whether a message belongs to a Task."""
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The first version intentionally avoids a mandatory model call so the router
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stays reliable during provider outages. The rule set is conservative:
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anything that implies execution, files, tools, iteration, or validation
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becomes Task mode.
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"""
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async def classify(
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self,
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message: str,
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*,
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active_task: TaskRecord | None = None,
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provider: Any | None = None,
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model: str | None = None,
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recent_messages: list[dict[str, Any]] | None = None,
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thinking_enabled: bool | None = None,
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timeout_seconds: float = 8.0,
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) -> MainAgentDecision:
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if provider is None:
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return self._fallback(active_task=active_task, reason="router_provider_unavailable")
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try:
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chat_kwargs: dict[str, Any] = {
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"messages": [
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{
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"role": "system",
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"content": (
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"You route user messages for Beaver's internal Task mode. "
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"Return only compact JSON. Do not explain."
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),
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},
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{
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"role": "user",
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"content": self._prompt(
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message=message,
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active_task=active_task,
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recent_messages=recent_messages or [],
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),
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},
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],
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"tools": None,
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"model": model,
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"max_tokens": 256,
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"temperature": 0.0,
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}
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if thinking_enabled is not None:
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chat_kwargs["thinking_enabled"] = thinking_enabled
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response = await asyncio.wait_for(provider.chat(**chat_kwargs), timeout=timeout_seconds)
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return self.from_json(response.content or "", active_task=active_task)
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except Exception as exc:
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return self._fallback(active_task=active_task, reason=f"router_failed: {exc}")
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_TASK_PATTERNS = [
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r"\b(implement|fix|debug|refactor|migrate|build|create|write|edit|update|test|validate|deploy)\b",
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r"\b(file|repo|code|project|backend|frontend|api|database|migration|pull request|ci|bug)\b",
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r"\b(step|multi-step|workflow|plan and|then)\b",
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r"(实现|修复|调试|重构|迁移|构建|创建|编写|修改|更新|测试|验证|部署|文件|代码|项目|前端|后端|接口|数据库|多步|任务)",
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]
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_NEW_TASK_PATTERNS = [
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r"\b(new task|another task|different task|start over)\b",
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r"(新任务|另一个任务|换个任务|重新开始)",
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]
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def from_json(self, text: str, *, active_task: TaskRecord | None = None) -> MainAgentDecision:
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payload = self._parse_json_object(text)
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raw_action = str(payload.get("action") or payload.get("mode") or "").strip().lower()
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reason = str(payload.get("reason") or raw_action or "llm_router")
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short_title = _clean_short_title(payload.get("short_title") or payload.get("title"))
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def classify(self, message: str, *, active_task: TaskRecord | None = None) -> MainAgentDecision:
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text = message.strip()
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lowered = text.lower()
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starts_new = any(re.search(pattern, lowered, re.IGNORECASE) for pattern in self._NEW_TASK_PATTERNS)
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if active_task is not None and active_task.status in {"awaiting_feedback", "needs_revision"} and not starts_new:
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return MainAgentDecision(mode="task", reason="continuing_open_task", starts_new_task=False)
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if any(re.search(pattern, lowered, re.IGNORECASE) for pattern in self._TASK_PATTERNS):
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return MainAgentDecision(mode="task", reason="task_pattern_matched", starts_new_task=starts_new)
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if len(text) > 240:
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return MainAgentDecision(mode="task", reason="long_request", starts_new_task=starts_new)
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return MainAgentDecision(mode="simple", reason="simple_question", starts_new_task=False)
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if raw_action in {"continue_task", "continue", "task"}:
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return MainAgentDecision(mode="task", reason=reason, short_title=short_title)
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if raw_action in {"new_task", "new"}:
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return MainAgentDecision(mode="task", reason=reason, starts_new_task=True, short_title=short_title)
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if raw_action in {"close_task", "close", "done", "finish"}:
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return MainAgentDecision(mode="simple", reason=reason, closes_task=active_task is not None, short_title=short_title)
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if raw_action in {"abandon_task", "abandon", "cancel_task"}:
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return MainAgentDecision(mode="simple", reason=reason, abandons_task=active_task is not None, short_title=short_title)
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return MainAgentDecision(mode="simple", reason=reason or "simple_chat", short_title=short_title)
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def _fallback(self, *, active_task: TaskRecord | None, reason: str) -> MainAgentDecision:
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if active_task is not None:
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return MainAgentDecision(mode="task", reason=reason)
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return MainAgentDecision(mode="simple", reason=reason)
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@staticmethod
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def _prompt(
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*,
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message: str,
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active_task: TaskRecord | None,
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recent_messages: list[dict[str, Any]],
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) -> str:
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active_task_payload = None
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if active_task is not None:
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active_task_payload = {
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"task_id": active_task.task_id,
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"description": active_task.description,
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"goal": active_task.goal,
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"status": active_task.status,
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"short_title": active_task.metadata.get("short_title"),
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}
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recent = [
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{"role": item.get("role"), "content": str(item.get("content") or "")[:500]}
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for item in recent_messages[-8:]
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if item.get("role") in {"user", "assistant"}
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]
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return (
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"Decide how to route the current user message.\n\n"
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"Actions:\n"
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"- simple_chat: no Task should be created or continued.\n"
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"- continue_task: keep the user in the active Task.\n"
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"- new_task: start a separate new Task.\n"
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"- close_task: user explicitly says the active Task is done/satisfactory/finished.\n"
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"- abandon_task: user explicitly says to stop, cancel, abandon, or no longer do the active Task.\n\n"
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"Critical policy:\n"
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"- If there is an active Task, choose continue_task unless the user's topic is completely unrelated "
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"to that Task or the user explicitly closes/abandons it.\n"
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"- Follow-up questions, corrections, partial changes, extra constraints, and result discussion stay in continue_task.\n"
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"- Use new_task only when the user clearly asks to start a different task.\n"
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"- If there is no active Task, choose new_task only for work that requires execution, iteration, tools, files, "
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"implementation, validation, or multi-step completion. Otherwise choose simple_chat.\n"
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"- short_title must be 5-15 Chinese characters or a similarly short English phrase when a Task is involved.\n\n"
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"Return JSON only with keys: action, reason, short_title.\n\n"
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f"Active task:\n{json.dumps(active_task_payload, ensure_ascii=False)}\n\n"
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f"Recent conversation:\n{json.dumps(recent, ensure_ascii=False)}\n\n"
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f"Current user message:\n{message}"
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)
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@staticmethod
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def _parse_json_object(text: str) -> dict[str, Any]:
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cleaned = text.strip()
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if cleaned.startswith("```"):
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cleaned = cleaned.strip("`")
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if cleaned.lower().startswith("json"):
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cleaned = cleaned[4:].strip()
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start = cleaned.find("{")
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end = cleaned.rfind("}")
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if start >= 0 and end >= start:
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cleaned = cleaned[start : end + 1]
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payload = json.loads(cleaned)
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if not isinstance(payload, dict):
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raise ValueError("router response must be a JSON object")
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return payload
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def _clean_short_title(value: Any) -> str | None:
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if value in (None, ""):
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return None
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title = " ".join(str(value).strip().split())
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return title[:40] or None
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