feat: 增强编码能力 - 新增代码编辑器、代码搜索、Git集成
- 新增 plugins/code_editor.py: 精准代码编辑（搜索替换、批量编辑、diff对比） - 新增 plugins/code_search.py: 代码搜索与理解（跨文件搜索、符号提取、依赖分析） - 新增 plugins/git_tools.py: Git 版本控制（status/diff/log/commit/branch） - 新增 core/ 模块: 配置管理、引擎管理、对话处理、显示输出、代码沙箱 - 修复 requirements.txt: 使用正确的 pip 包名（Pillow、opencv-python 等） - 更新 unified_tool_manager.py: 兼容 Plugin 和 Liugin 两种类名 - 更新系统提示词: 增强编程工作流指导 本次更新由 mimo 自动化执行，与开发者无关。
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"""
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对话处理模块 - 核心对话循环和工具调用
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"""
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import json
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import re
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import time
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import threading
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import logging
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from colorama import Fore, Style
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logger = logging.getLogger(__name__)
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class ConversationManager:
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"""对话管理器 - 处理用户输入、AI 响应、工具调用循环"""
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def __init__(self, cli):
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self.cli = cli
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self.history = []
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self.max_history = 999999
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def process(self, user_input: str):
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"""处理完整的对话循环"""
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self.history.append({"role": "user", "content": user_input})
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tool_prompts = self._get_tool_prompts()
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loop_count = 0
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current_input = user_input
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max_loops = 20
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while loop_count < max_loops:
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response = self._generate_with_animation(current_input, tool_prompts)
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processed = self._process_thinking(response)
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processed = self._process_code_blocks(processed)
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try:
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text_content, json_data = self._parse_response(processed)
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if json_data:
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if text_content:
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self._add_and_display(text_content)
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if isinstance(json_data, dict):
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result = self._handle_dict(json_data, text_content, processed)
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if result == "break":
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break
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elif result == "continue":
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loop_count += 1
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continue
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elif isinstance(json_data, list):
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result = self._handle_list(json_data, text_content, processed)
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if result == "break":
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break
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elif result == "continue":
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loop_count += 1
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continue
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else:
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display = text_content if text_content else processed
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self._add_and_display(display)
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break
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except json.JSONDecodeError:
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text_content, json_data = self._parse_response(processed)
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if json_data:
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# Re-process with parsed data
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pass
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else:
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self._add_and_display(processed)
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break
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if loop_count >= max_loops:
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self.cli.display.output(f"AI 已达到最大循环次数 ({max_loops})，已停止")
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def _handle_dict(self, data, text_content, processed):
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"""处理 dict 类型的 JSON 数据"""
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if data.get('action') == 'use_tool':
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self.cli._execute_single_tool(data)
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return "break"
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if data.get('action') == 'continue':
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content = data.get('content', '')
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if content:
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self._add_and_display(content)
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return "continue"
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if data.get('continue') or data.get('need_continue') or data.get('think_more'):
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msg = data.get('message', '')
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if msg:
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self.history.append({"role": "assistant", "content": msg})
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self.cli.display.response(msg, is_continue=True)
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return "continue"
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msg = data.get('message', '')
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if msg:
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self._add_and_display(msg)
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return "break"
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if text_content:
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self._add_and_display(text_content)
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else:
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self._add_and_display(processed)
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return "break"
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def _handle_list(self, data_list, text_content, processed):
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"""处理 list 类型的 JSON 数据"""
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tool_calls = [item for item in data_list
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if isinstance(item, dict) and item.get('action') == 'use_tool']
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if tool_calls:
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self.cli._execute_concurrent_tools(tool_calls)
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return "break"
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continue_items = [item for item in data_list
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if isinstance(item, dict) and
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(item.get('continue') or item.get('need_continue') or item.get('think_more'))]
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if continue_items:
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msg = continue_items[0].get('message', '')
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if msg:
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self.history.append({"role": "assistant", "content": msg})
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self.cli.display.response(msg, is_continue=True)
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return "continue"
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if text_content:
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self._add_and_display(text_content)
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else:
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self._add_and_display(processed)
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return "break"
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def _add_and_display(self, content):
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"""添加到历史并显示"""
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self.history.append({"role": "assistant", "content": content})
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self.cli.display.response(content)
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def _generate_with_animation(self, user_input, tool_prompts=None):
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"""生成 AI 响应（带动画）"""
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system_prompt = self._build_system_prompt(tool_prompts)
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if not self.cli.engine_manager.current_engine:
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return "错误: 当前没有可用的AI引擎"
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# TUI 模式：直接生成
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if self.cli.display.tui_callback:
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response = self.cli.engine_manager.generate_response(user_input, system_prompt)
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if response:
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self.history.append({"role": "assistant", "content": response})
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return response
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# CLI 模式：带动画
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stop_event = threading.Event()
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esc_event = threading.Event()
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# 加载等待句子
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sentences = self._load_love_sentences()
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anim_thread = threading.Thread(
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target=self.cli.display.thinking_animation,
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args=(sentences, stop_event, esc_event), daemon=True)
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anim_thread.start()
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try:
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response = self.cli.engine_manager.generate_response(user_input, system_prompt)
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if response:
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self.cli.display.typeprint(response, Fore.CYAN)
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self.history.append({"role": "assistant", "content": response})
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return response
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finally:
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stop_event.set()
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anim_thread.join()
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def _build_system_prompt(self, tool_prompts=None):
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"""构建系统提示词"""
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base = ("你叫小狸，是一个强大的智能编程助手。你具备精准的代码编辑能力、"
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"完整的 Git 工作流支持、以及跨文件代码搜索和理解能力。"
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"你可以帮助用户编写、修改、调试代码，管理版本控制，理解复杂代码库。")
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tool_section = ""
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if tool_prompts:
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tool_section = f"\n\n{tool_prompts}"
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call_format = """
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【工具调用格式】
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当需要执行操作时，在回复中包含 JSON 指令：
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1. 纯 JSON: {"action": "use_tool", "tool": "工具名", "args": "参数"}
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2. 文本+JSON: 好的，我来修改这个文件。{"action": "use_tool", "tool": "code_editor", "args": "edit file.py old_code <<<>>> new_code"}
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【核心工具】
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- code_editor: 精准代码编辑（edit/search/diff/insert/create/write）
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- code_search: 代码搜索与理解（find/regex/symbols/imports/structure）
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- git_tools: Git 操作（status/diff/log/add/commit/branch）
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- cmd_executor: 执行 shell 命令
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- file_manager: 文件管理
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【编码工作流】
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1. 先用 code_search 了解代码结构
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2. 用 code_editor.read_range 查看相关代码
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3. 用 code_editor.edit 精准修改
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4. 用 git_tools 提交变更
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【注意事项】
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- code_editor.edit 的格式: old_text <<<>>> new_text（用 <<<>>> 分隔）
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- args 必须是字符串
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- 可以一次返回多个 JSON 指令顺序执行
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- 使用 continue 补充回答: {"action": "continue", "content": "补充内容"}"""
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return base + tool_section + call_format
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def _process_thinking(self, response):
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"""处理深度思考标记"""
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# <think/> 格式
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if '<think/>' in response:
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parts = response.split('<think/>', 1)
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if len(parts) >= 2:
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thinking = parts[0].strip()
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reply = parts[1].strip()
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if thinking:
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print(f"{Fore.LIGHTBLACK_EX}[思考: {thinking[:200]}...]{Style.RESET_ALL}" if len(thinking) > 200 else f"{Fore.LIGHTBLACK_EX}[思考: {thinking}]{Style.RESET_ALL}")
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return reply if reply else ""
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# <thinking>...</thinking> 格式
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engine = self.cli.engine_manager.current_engine
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if engine:
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start = getattr(engine, 'thinking_start_marker', None)
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end = getattr(engine, 'thinking_end_marker', None)
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if start and end and start in response and end in response:
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parts = response.split(start, 1)
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if len(parts) > 1 and end in parts[1]:
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thinking, reply = parts[1].split(end, 1)
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if thinking.strip():
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print(f"{Fore.LIGHTBLACK_EX}[思考: {thinking.strip()[:200]}]{Style.RESET_ALL}")
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return reply.strip()
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return response
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def _process_code_blocks(self, text):
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"""处理代码块标记"""
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pattern = r'(""".*?""")'
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def replace(m):
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inner = m.group(1)[3:-3]
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return f'{Fore.RED}{inner}{Style.RESET_ALL}'
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return re.sub(pattern, replace, text, flags=re.DOTALL)
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def _parse_response(self, response):
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"""解析混合响应（文本+JSON）"""
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response = response.strip()
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# 直接 JSON
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try:
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parsed = json.loads(response)
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if isinstance(parsed, (dict, list)):
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return "", parsed
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except json.JSONDecodeError:
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pass
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# 代码块中的 JSON
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pattern = r"```(?:json)?\s*({.*?})\s*```"
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matches = re.findall(pattern, response, re.DOTALL)
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if matches:
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try:
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data = json.loads(matches[-1])
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if isinstance(data, (dict, list)):
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text = re.sub(pattern, "", response, flags=re.DOTALL).strip()
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return text, data
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except json.JSONDecodeError:
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pass
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# 内联 JSON
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markers = ['{"action": "use_tool"', '{"action": "continue"',
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'{"action":"use_tool"', '{"action":"continue"']
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for marker in markers:
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idx = response.find(marker)
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if idx != -1:
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brace_count = 0
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for i in range(idx, len(response)):
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if response[i] == '{':
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brace_count += 1
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elif response[i] == '}':
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brace_count -= 1
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if brace_count == 0:
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try:
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data = json.loads(response[idx:i+1])
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if isinstance(data, dict) and data.get('action') in ['use_tool', 'continue']:
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return response[:idx].strip(), data
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except json.JSONDecodeError:
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pass
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break
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return response, None
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def _get_tool_prompts(self):
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"""获取工具提示词"""
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if not self.cli.tool_manager or not self.cli.tool_manager.tools:
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return "当前没有可用的工具"
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lines = ["可用工具列表：\n"]
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for tool in self.cli.tool_manager.tools:
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name = tool.get('name', '')
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desc = tool.get('description', '')
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lines.append(f"- {name}: {desc}")
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return '\n'.join(lines)
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def _load_love_sentences(self):
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"""加载等待动画句子"""
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import os
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path = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "love.txt")
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if os.path.exists(path):
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try:
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with open(path, 'r', encoding='utf-8') as f:
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return [l.strip() for l in f.readlines() if l.strip()]
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except:
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pass
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return ["AI正在思考中...", "请稍等片刻...", "正在处理您的请求..."]
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