ref：分离know模块和cli模块
This commit is contained in:
SengokuCola
3
src/cli/__init__.py
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3
src/cli/__init__.py
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@@ -0,0 +1,3 @@
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"""
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CLI startup and interaction package.
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"""
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17
src/cli/console.py
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17
src/cli/console.py
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@@ -0,0 +1,17 @@
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"""MaiSaka terminal console helpers."""
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from rich.console import Console
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from rich.theme import Theme
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custom_theme = Theme(
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{
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"info": "cyan",
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"success": "green",
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"warning": "yellow",
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"error": "bold red",
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"muted": "dim",
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"accent": "bold magenta",
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}
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)
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console = Console(theme=custom_theme)
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56
src/cli/input_reader.py
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56
src/cli/input_reader.py
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@@ -0,0 +1,56 @@
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"""
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MaiSaka asynchronous stdin reader for CLI interaction.
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"""
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from typing import Optional
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import asyncio
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import sys
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import threading
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class InputReader:
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"""后台读取标准输入，并通过 asyncio.Queue 向主循环投递结果。"""
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def __init__(self) -> None:
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self._loop: Optional[asyncio.AbstractEventLoop] = None
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self._queue: asyncio.Queue[Optional[str]] = asyncio.Queue()
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self._thread: Optional[threading.Thread] = None
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self._stop_event = threading.Event()
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def start(self, loop: asyncio.AbstractEventLoop) -> None:
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"""启动后台输入线程。重复调用时忽略。"""
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if self._thread and self._thread.is_alive():
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return
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self._loop = loop
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self._stop_event.clear()
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self._thread = threading.Thread(target=self._read_loop, name="maisaka-input-reader", daemon=True)
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self._thread.start()
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def _read_loop(self) -> None:
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"""在后台线程中阻塞读取 stdin。"""
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while not self._stop_event.is_set():
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line = sys.stdin.readline()
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if self._loop is None:
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return
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if line == "":
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self._loop.call_soon_threadsafe(self._queue.put_nowait, None)
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return
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self._loop.call_soon_threadsafe(self._queue.put_nowait, line.rstrip("\r\n"))
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async def get_line(self, timeout: Optional[int] = None) -> Optional[str]:
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"""异步获取一行输入；设置 timeout 时支持超时返回。"""
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if timeout is None:
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return await self._queue.get()
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try:
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return await asyncio.wait_for(self._queue.get(), timeout=timeout)
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except asyncio.TimeoutError:
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return None
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def close(self) -> None:
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"""请求后台线程停止。"""
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self._stop_event.set()
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397
src/cli/maisaka_cli.py
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397
src/cli/maisaka_cli.py
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@@ -0,0 +1,397 @@
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"""
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MaiSaka CLI and conversation loop.
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"""
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from datetime import datetime
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from pathlib import Path
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from typing import Optional
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import asyncio
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import os
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import time
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from rich import box
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from rich.markdown import Markdown
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from rich.panel import Panel
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from rich.text import Text
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from src.know_u.knowledge import KnowledgeLearner, retrieve_relevant_knowledge
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from src.know_u.knowledge_store import get_knowledge_store
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from src.chat.message_receive.message import SessionMessage
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from src.chat.replyer.maisaka_generator import MaisakaReplyGenerator
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from src.config.config import config_manager, global_config
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from src.mcp_module import MCPManager
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from src.maisaka.chat_loop_service import MaisakaChatLoopService
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from src.maisaka.message_adapter import build_message, format_speaker_content, remove_last_perception
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from src.maisaka.tool_handlers import (
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ToolHandlerContext,
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handle_mcp_tool,
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handle_stop,
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handle_unknown_tool,
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handle_wait,
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)
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from .console import console
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from .input_reader import InputReader
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class BufferCLI:
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"""Maisaka 命令行交互入口。"""
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def __init__(self) -> None:
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self._chat_loop_service: Optional[MaisakaChatLoopService] = None
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self._reply_generator = MaisakaReplyGenerator()
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self._reader = InputReader()
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self._chat_history: Optional[list[SessionMessage]] = None
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self._knowledge_store = get_knowledge_store()
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self._knowledge_learner = KnowledgeLearner("maisaka_cli")
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self._knowledge_min_messages_for_extraction = 10
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self._knowledge_min_extraction_interval = 30
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self._last_knowledge_extraction_time = 0.0
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knowledge_stats = self._knowledge_store.get_stats()
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if knowledge_stats["total_items"] > 0:
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console.print(f"[success][OK] Knowledge store: {knowledge_stats['total_items']} item(s)[/success]")
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else:
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console.print("[muted][OK] Knowledge store: initialized with no data[/muted]")
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self._chat_start_time: Optional[datetime] = None
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self._last_user_input_time: Optional[datetime] = None
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self._last_assistant_response_time: Optional[datetime] = None
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self._user_input_times: list[datetime] = []
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self._mcp_manager: Optional[MCPManager] = None
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self._init_llm()
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def _init_llm(self) -> None:
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"""初始化 Maisaka 使用的聊天服务。"""
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thinking_env = os.getenv("ENABLE_THINKING", "").strip().lower()
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enable_thinking: Optional[bool] = True if thinking_env == "true" else False if thinking_env == "false" else None
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_ = enable_thinking
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self._chat_loop_service = MaisakaChatLoopService()
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model_name = self._get_current_model_name()
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console.print(f"[success][OK] LLM service initialized[/success] [muted](model: {model_name})[/muted]")
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@staticmethod
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def _get_current_model_name() -> str:
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"""读取当前 planner 模型名。"""
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try:
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model_task_config = config_manager.get_model_config().model_task_config
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if model_task_config.planner.model_list:
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return model_task_config.planner.model_list[0]
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except Exception:
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pass
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return "unconfigured"
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def _build_tool_context(self) -> ToolHandlerContext:
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"""构建工具处理的共享上下文。"""
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tool_context = ToolHandlerContext(
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reader=self._reader,
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user_input_times=self._user_input_times,
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)
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tool_context.last_user_input_time = self._last_user_input_time
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return tool_context
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def _show_banner(self) -> None:
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"""渲染启动横幅。"""
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banner = Text()
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banner.append("MaiSaka", style="bold cyan")
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banner.append(" v2.0\n", style="muted")
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banner.append("Type to chat | Ctrl+C to exit", style="muted")
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console.print(Panel(banner, box=box.DOUBLE_EDGE, border_style="cyan", padding=(1, 2)))
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console.print()
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async def _start_chat(self, user_text: str) -> None:
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"""追加用户输入并继续内部循环。"""
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if self._chat_loop_service is None:
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console.print("[warning]LLM service is not initialized; skipping chat.[/warning]")
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return
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now = datetime.now()
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self._last_user_input_time = now
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self._user_input_times.append(now)
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if self._chat_history is None:
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self._chat_start_time = now
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self._last_assistant_response_time = None
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self._chat_history = self._chat_loop_service.build_chat_context(user_text)
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self._trigger_knowledge_learning([self._chat_history[-1]])
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else:
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self._chat_history.append(
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build_message(
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role="user",
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content=format_speaker_content(
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global_config.maisaka.user_name.strip() or "User",
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user_text,
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now,
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),
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)
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)
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self._trigger_knowledge_learning([self._chat_history[-1]])
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await self._run_llm_loop(self._chat_history)
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def _trigger_knowledge_learning(self, messages: list[SessionMessage]) -> None:
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"""在 CLI 会话中按批次触发 knowledge 学习。"""
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if not global_config.maisaka.enable_knowledge_module:
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return
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self._knowledge_learner.add_messages(messages)
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elapsed = time.monotonic() - self._last_knowledge_extraction_time
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if elapsed < self._knowledge_min_extraction_interval:
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return
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cache_size = self._knowledge_learner.get_cache_size()
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if cache_size < self._knowledge_min_messages_for_extraction:
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return
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self._last_knowledge_extraction_time = time.monotonic()
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asyncio.create_task(self._run_knowledge_learning())
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async def _run_knowledge_learning(self) -> None:
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"""后台执行 knowledge 学习，避免阻塞主对话。"""
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try:
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added_count = await self._knowledge_learner.learn()
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if added_count > 0 and global_config.maisaka.show_thinking:
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console.print(f"[muted]Knowledge learning added {added_count} item(s).[/muted]")
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except Exception as exc:
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console.print(f"[warning]Knowledge learning failed: {exc}[/warning]")
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async def _run_llm_loop(self, chat_history: list[SessionMessage]) -> None:
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"""
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Main inner loop for the Maisaka planner.
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Each round may produce internal thoughts and optionally call tools:
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- reply(msg_id): generate a visible reply for the current round
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- no_reply(): skip visible output and continue the loop
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- wait(seconds): wait for new user input
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- stop(): stop the current inner loop and return to idle
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"""
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if self._chat_loop_service is None:
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return
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consecutive_errors = 0
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last_had_tool_calls = True
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while True:
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if last_had_tool_calls:
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tasks = []
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status_text_parts = []
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if global_config.maisaka.enable_knowledge_module:
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tasks.append(("knowledge", retrieve_relevant_knowledge(self._chat_loop_service, chat_history)))
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status_text_parts.append("knowledge")
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with console.status(
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f"[info]{' + '.join(status_text_parts)} analyzing...[/info]",
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spinner="dots",
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):
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results = await asyncio.gather(*[task for _, task in tasks], return_exceptions=True)
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knowledge_analysis = ""
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if global_config.maisaka.enable_knowledge_module:
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knowledge_result = results[0] if results else None
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if isinstance(knowledge_result, Exception):
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console.print(f"[warning]Knowledge analysis failed: {knowledge_result}[/warning]")
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elif knowledge_result:
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knowledge_analysis = knowledge_result
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if global_config.maisaka.show_thinking:
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console.print(
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Panel(
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Markdown(knowledge_analysis),
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title="Knowledge",
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border_style="bright_magenta",
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padding=(0, 1),
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style="dim",
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)
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)
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remove_last_perception(chat_history)
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perception_parts = []
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if knowledge_analysis:
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perception_parts.append(f"Knowledge\n{knowledge_analysis}")
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if perception_parts:
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chat_history.append(
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build_message(
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role="assistant",
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content="\n\n".join(perception_parts),
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message_kind="perception",
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source="assistant",
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)
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)
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elif global_config.maisaka.show_thinking:
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console.print("[muted]Skipping module analysis because the last round used no tools.[/muted]")
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with console.status("[info]AI is thinking...[/info]", spinner="dots"):
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try:
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response = await self._chat_loop_service.chat_loop_step(chat_history)
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consecutive_errors = 0
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except Exception as exc:
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consecutive_errors += 1
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console.print(f"[error]LLM call failed: {exc}[/error]")
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if consecutive_errors >= 3:
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console.print("[error]Too many consecutive errors. Exiting chat.[/error]\n")
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break
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continue
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chat_history.append(response.raw_message)
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self._last_assistant_response_time = datetime.now()
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if global_config.maisaka.show_thinking and response.content:
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console.print(
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Panel(
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Markdown(response.content),
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title="Thought",
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border_style="dim",
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padding=(1, 2),
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style="dim",
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)
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)
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if response.content and not response.tool_calls:
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last_had_tool_calls = False
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continue
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if not response.tool_calls:
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last_had_tool_calls = False
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continue
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should_stop = False
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tool_context = self._build_tool_context()
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for tool_call in response.tool_calls:
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if tool_call.func_name == "stop":
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await handle_stop(tool_call, chat_history)
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should_stop = True
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elif tool_call.func_name == "reply":
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reply = await self._generate_visible_reply(chat_history, response.content)
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chat_history.append(
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build_message(
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role="tool",
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content="Visible reply generated and recorded.",
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source="tool",
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tool_call_id=tool_call.call_id,
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)
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)
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chat_history.append(
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build_message(
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role="user",
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content=format_speaker_content(
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global_config.bot.nickname.strip() or "MaiSaka",
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reply,
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datetime.now(),
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),
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source="guided_reply",
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)
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)
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elif tool_call.func_name == "no_reply":
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if global_config.maisaka.show_thinking:
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console.print("[muted]No visible reply this round.[/muted]")
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chat_history.append(
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build_message(
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role="tool",
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content="No visible reply was sent for this round.",
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source="tool",
|
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tool_call_id=tool_call.call_id,
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)
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)
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elif tool_call.func_name == "wait":
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tool_result = await handle_wait(tool_call, chat_history, tool_context)
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if tool_context.last_user_input_time != self._last_user_input_time:
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self._last_user_input_time = tool_context.last_user_input_time
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if tool_result.startswith("[[QUIT]]"):
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should_stop = True
|
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|
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elif self._mcp_manager and self._mcp_manager.is_mcp_tool(tool_call.func_name):
|
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await handle_mcp_tool(tool_call, chat_history, self._mcp_manager)
|
||||
|
||||
else:
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await handle_unknown_tool(tool_call, chat_history)
|
||||
|
||||
if should_stop:
|
||||
console.print("[muted]Conversation paused. Waiting for new input...[/muted]\n")
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break
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|
||||
last_had_tool_calls = True
|
||||
|
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async def _init_mcp(self) -> None:
|
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"""初始化 MCP 服务并注册暴露的工具。"""
|
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config_path = Path(__file__).resolve().parents[2] / "config" / "mcp_config.json"
|
||||
self._mcp_manager = await MCPManager.from_config(str(config_path))
|
||||
|
||||
if self._mcp_manager and self._chat_loop_service:
|
||||
mcp_tools = self._mcp_manager.get_openai_tools()
|
||||
if mcp_tools:
|
||||
self._chat_loop_service.set_extra_tools(mcp_tools)
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summary = self._mcp_manager.get_tool_summary()
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console.print(
|
||||
Panel(
|
||||
f"Loaded {len(mcp_tools)} MCP tool(s):\n{summary}",
|
||||
title="MCP Tools",
|
||||
border_style="green",
|
||||
padding=(0, 1),
|
||||
)
|
||||
)
|
||||
|
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async def _generate_visible_reply(self, chat_history: list[SessionMessage], latest_thought: str) -> str:
|
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"""根据最新思考生成并输出可见回复。"""
|
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if not latest_thought:
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return ""
|
||||
|
||||
with console.status("[info]Generating visible reply...[/info]", spinner="dots"):
|
||||
success, result = await self._reply_generator.generate_reply_with_context(
|
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reply_reason=latest_thought,
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chat_history=chat_history,
|
||||
)
|
||||
if success and result.text_fragments:
|
||||
reply = result.text_fragments[0]
|
||||
else:
|
||||
reply = "..."
|
||||
|
||||
console.print(
|
||||
Panel(
|
||||
Markdown(reply),
|
||||
title="MaiSaka",
|
||||
border_style="magenta",
|
||||
padding=(1, 2),
|
||||
)
|
||||
)
|
||||
|
||||
return reply
|
||||
|
||||
async def run(self) -> None:
|
||||
"""主交互循环。"""
|
||||
if global_config.maisaka.enable_mcp:
|
||||
await self._init_mcp()
|
||||
else:
|
||||
console.print("[muted]MCP is disabled (ENABLE_MCP=false)[/muted]")
|
||||
|
||||
self._reader.start(asyncio.get_event_loop())
|
||||
self._show_banner()
|
||||
|
||||
try:
|
||||
while True:
|
||||
console.print("[bold cyan]> [/bold cyan]", end="")
|
||||
raw_input = await self._reader.get_line()
|
||||
|
||||
if raw_input is None:
|
||||
console.print("\n[muted]Goodbye![/muted]")
|
||||
break
|
||||
|
||||
raw_input = raw_input.strip()
|
||||
if not raw_input:
|
||||
continue
|
||||
|
||||
await self._start_chat(raw_input)
|
||||
finally:
|
||||
if self._mcp_manager:
|
||||
await self._mcp_manager.close()
|
||||
Reference in New Issue
Block a user