Xiaoli Dev
e22652fbbb
- 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。
550 lines
18 KiB
Python
550 lines
18 KiB
Python
"""
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语音识别插件 - 弹窗录音界面
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AI 触发后弹出独立录音窗口
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"""
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import os
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import json
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import subprocess
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import sys
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import time
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from typing import Optional, Dict, Any, List
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# 结果保存路径
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RESULT_FILE = os.path.join(os.path.dirname(os.path.abspath(__file__)), "speech_temp", "last_result.txt")
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TEMP_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), "speech_temp")
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class Liugin:
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"""语音识别插件"""
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def __init__(self):
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self.plugin_dir = os.path.dirname(os.path.abspath(__file__))
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self.temp_dir = TEMP_DIR
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os.makedirs(self.temp_dir, exist_ok=True)
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self.usage = """语音识别插件使用方法：
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speech_recognition <操作> [参数]
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录音识别:
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- record - 弹出录音窗口，录音并识别
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文件识别:
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- file <音频文件路径> - 识别音频文件内容
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其他:
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- status - 查看状态
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- result - 获取上次识别结果
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支持的音频格式: wav, mp3, m4a, flac, ogg
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"""
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self.cli = None
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def set_cli(self, cli):
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self.cli = cli
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def get_tool_info(self):
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return {
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"name": "speech_recognition",
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"description": "语音识别插件，弹出录音窗口进行语音识别，将语音转换为文字",
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"keywords": ["语音", "识别", "录音", "转文字", "speech", "voice", "recognition"],
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"usage": self.usage
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}
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def get_mcp_definition(self):
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return {
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"name": "speech_recognition",
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"description": "语音识别插件，弹出录音窗口进行语音识别",
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"inputSchema": {
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"type": "object",
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"properties": {
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"operation": {
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"type": "string",
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"enum": ["record", "file", "status", "result"],
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"description": "操作类型"
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},
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"file_path": {"type": "string", "description": "音频文件路径"}
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},
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"required": ["operation"]
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}
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}
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def convert_mcp_args(self, arguments: Dict[str, Any]) -> str:
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op = arguments.get("operation", "")
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parts = [op]
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if op == "file":
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parts.append(arguments.get("file_path", ""))
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return " ".join(filter(None, parts))
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def handle(self, args: str) -> str:
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try:
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parts = self._parse_args(args)
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if not parts:
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return "错误：请提供操作类型。\n" + self.usage
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operation = parts[0].lower()
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handlers = {
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"record": self._op_record,
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"file": self._op_file,
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"status": self._op_status,
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"result": self._op_result,
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}
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if operation in handlers:
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return handlers[operation](parts[1:])
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else:
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return f"错误：未知操作 '{operation}'\n可用操作: " + ", ".join(handlers.keys())
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except Exception as e:
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return f"处理请求失败: {e}"
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def _parse_args(self, args: str) -> List[str]:
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parts = []
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current = ""
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in_quotes = False
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quote_char = None
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for char in args:
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if char in ('"', "'") and not in_quotes:
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in_quotes = True
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quote_char = char
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elif char == quote_char and in_quotes:
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in_quotes = False
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quote_char = None
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elif char == ' ' and not in_quotes:
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if current:
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parts.append(current)
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current = ""
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else:
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current += char
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if current:
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parts.append(current)
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return parts
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# ==================== 弹窗录音 ====================
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def _op_record(self, args: List[str]) -> str:
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"""弹出录音窗口"""
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# 创建录音窗口脚本
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recorder_script = os.path.join(self.temp_dir, "recorder_gui.py")
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gui_code = f'''import tkinter as tk
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from tkinter import messagebox
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import os
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import sys
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import threading
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import time
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RESULT_FILE = r"{RESULT_FILE}"
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TEMP_DIR = r"{TEMP_DIR}"
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class VoiceRecorder:
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def __init__(self):
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self.root = tk.Tk()
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self.root.title("语音识别录音")
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self.root.geometry("450x350")
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self.root.resizable(False, False)
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# 居中显示
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self.root.update_idletasks()
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x = (self.root.winfo_screenwidth() - 450) // 2
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y = (self.root.winfo_screenheight() - 350) // 2
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self.root.geometry(f"450x350+{{x}}+{{y}}")
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# 录音状态
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self.is_recording = False
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self.record_file = None
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self.frames = []
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self.start_time = None
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self.p = None
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self.stream = None
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# 创建界面
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self._create_ui()
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# 检查 pyaudio
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self.has_pyaudio = self._check_pyaudio()
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if not self.has_pyaudio:
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self.status_label.config(text="请安装 pyaudio: pip install pyaudio", fg="red")
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def _check_pyaudio(self):
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try:
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import pyaudio
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return True
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except:
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return False
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def _create_ui(self):
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# 标题
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title_label = tk.Label(self.root, text="🎙️ 语音识别录音", font=("Arial", 18, "bold"))
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title_label.pack(pady=15)
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# 状态标签
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self.status_label = tk.Label(self.root, text="点击开始录音", font=("Arial", 11))
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self.status_label.pack(pady=5)
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# 时间标签
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self.time_label = tk.Label(self.root, text="00:00", font=("Arial", 28, "bold"), fg="#2196F3")
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self.time_label.pack(pady=10)
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# 按钮框架
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btn_frame = tk.Frame(self.root)
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btn_frame.pack(pady=15)
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# 开始/停止按钮
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self.record_btn = tk.Button(
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btn_frame, text="🎤 开始录音", font=("Arial", 12),
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width=12, height=2, command=self.toggle_record,
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bg="#4CAF50", fg="white", cursor="hand2"
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)
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self.record_btn.pack(side=tk.LEFT, padx=10)
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# 识别按钮
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self.recognize_btn = tk.Button(
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btn_frame, text="📝 识别", font=("Arial", 12),
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width=12, height=2, command=self.recognize,
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bg="#2196F3", fg="white", cursor="hand2", state=tk.DISABLED
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)
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self.recognize_btn.pack(side=tk.LEFT, padx=10)
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# 结果显示
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result_frame = tk.LabelFrame(self.root, text="识别结果", font=("Arial", 10))
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result_frame.pack(pady=10, padx=15, fill=tk.BOTH, expand=True)
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self.result_text = tk.Text(result_frame, height=5, width=50, font=("Arial", 10))
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self.result_text.pack(pady=5, padx=5, fill=tk.BOTH, expand=True)
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def toggle_record(self):
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if not self.has_pyaudio:
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messagebox.showerror("错误", "请先安装 pyaudio:\npip install pyaudio")
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return
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if self.is_recording:
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self.stop_record()
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else:
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self.start_record()
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def start_record(self):
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import pyaudio
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self.is_recording = True
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self.frames = []
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self.start_time = time.time()
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self.record_btn.config(text="⏹️ 停止录音", bg="#f44336")
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self.status_label.config(text="🔴 正在录音...", fg="red")
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self.recognize_btn.config(state=tk.DISABLED)
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CHUNK = 1024
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FORMAT = pyaudio.paInt16
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CHANNELS = 1
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RATE = 16000
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self.p = pyaudio.PyAudio()
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self.stream = self.p.open(
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format=FORMAT, channels=CHANNELS, rate=RATE,
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input=True, frames_per_buffer=CHUNK
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)
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# 更新时间
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self._update_time()
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# 录音线程
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def record_loop():
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while self.is_recording:
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try:
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data = self.stream.read(CHUNK, exception_on_overflow=False)
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self.frames.append(data)
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except:
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break
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self.record_thread = threading.Thread(target=record_loop, daemon=True)
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self.record_thread.start()
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def stop_record(self):
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self.is_recording = False
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self.record_btn.config(text="🎤 开始录音", bg="#4CAF50")
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self.status_label.config(text="录音完成，可以识别", fg="green")
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self.recognize_btn.config(state=tk.NORMAL)
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# 停止录音
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if self.stream:
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self.stream.stop_stream()
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self.stream.close()
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if self.p:
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self.p.terminate()
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# 保存文件
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import wave
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import pyaudio
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self.record_file = os.path.join(TEMP_DIR, f"record_{{int(time.time())}}.wav")
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wf = wave.open(self.record_file, "wb")
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wf.setnchannels(1)
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wf.setsampwidth(pyaudio.get_sample_size(pyaudio.paInt16))
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wf.setframerate(16000)
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wf.writeframes(b"".join(self.frames))
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wf.close()
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self.result_text.delete(1.0, tk.END)
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self.result_text.insert(tk.END, "✅ 录音已保存\n点击 [识别] 按钮进行语音识别")
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def _update_time(self):
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if self.is_recording:
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elapsed = int(time.time() - self.start_time)
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mins = elapsed // 60
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secs = elapsed % 60
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self.time_label.config(text=f"{{mins:02d}}:{{secs:02d}}")
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self.root.after(100, self._update_time)
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def recognize(self):
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if not self.record_file or not os.path.exists(self.record_file):
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messagebox.showerror("错误", "没有录音文件，请先录音")
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return
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self.status_label.config(text="正在识别...", fg="blue")
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self.result_text.delete(1.0, tk.END)
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self.result_text.insert(tk.END, "🔍 识别中，请稍候...")
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self.root.update()
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# 尝试识别
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result = self._do_recognize()
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self.result_text.delete(1.0, tk.END)
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if result:
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self.result_text.insert(tk.END, result)
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self.status_label.config(text="识别完成", fg="green")
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# 保存结果
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with open(RESULT_FILE, "w", encoding="utf-8") as f:
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f.write(result)
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else:
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self.result_text.insert(tk.END, "❌ 识别失败\n\n请安装识别引擎:\n• pip install openai-whisper\n• pip install SpeechRecognition")
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self.status_label.config(text="识别失败", fg="red")
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def _do_recognize(self):
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# 尝试 Whisper
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try:
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import whisper
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self.status_label.config(text="使用 Whisper 识别...", fg="blue")
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self.root.update()
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model = whisper.load_model("base")
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result = model.transcribe(self.record_file, language="zh")
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text = result.get("text", "").strip()
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if text:
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return f"✅ {{text}}"
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except Exception as e:
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print(f"Whisper error: {{e}}")
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# 尝试 SpeechRecognition
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try:
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import speech_recognition as sr
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self.status_label.config(text="使用 Google 识别...", fg="blue")
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self.root.update()
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r = sr.Recognizer()
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with sr.AudioFile(self.record_file) as source:
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audio = r.record(source)
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text = r.recognize_google(audio, language="zh-CN")
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if text:
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return f"✅ {{text}}"
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except Exception as e:
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print(f"SpeechRecognition error: {{e}}")
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return None
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def run(self):
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self.root.mainloop()
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# 清理
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if self.is_recording:
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self.is_recording = False
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if self.stream:
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self.stream.close()
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if self.p:
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self.p.terminate()
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if __name__ == "__main__":
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app = VoiceRecorder()
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app.run()
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'''
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# 写入脚本
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with open(recorder_script, "w", encoding="utf-8") as f:
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f.write(gui_code)
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# 启动录音窗口
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try:
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subprocess.Popen([sys.executable, recorder_script],
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creationflags=subprocess.CREATE_NEW_CONSOLE)
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return "🎙️ 已弹出录音窗口，请在窗口中进行录音和识别\n\n使用方法：\n1. 点击「开始录音」\n2. 对着麦克风说话\n3. 点击「停止录音」\n4. 点击「识别」获取文字结果"
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except Exception as e:
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return f"❌ 启动录音窗口失败: {e}"
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# ==================== 文件识别 ====================
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def _op_file(self, args: List[str]) -> str:
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"""识别音频文件"""
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if not args:
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return "错误：请提供音频文件路径"
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file_path = args[0]
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if not os.path.exists(file_path):
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return f"❌ 文件不存在: {file_path}"
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return self._recognize_file(file_path)
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def _recognize_file(self, file_path: str) -> str:
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"""识别音频文件内容"""
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# 尝试使用 whisper（本地）
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result = self._try_whisper(file_path)
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if result:
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self._save_result(result)
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return result
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# 尝试使用 speech_recognition 库
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result = self._try_speech_recognition(file_path)
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if result:
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self._save_result(result)
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return result
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return "❌ 语音识别失败：未安装识别引擎\n\n安装方法:\n1. Whisper (推荐): pip install openai-whisper\n2. SpeechRecognition: pip install SpeechRecognition\n3. PyAudio (录音): pip install pyaudio"
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def _save_result(self, result: str):
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"""保存识别结果"""
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try:
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with open(RESULT_FILE, "w", encoding="utf-8") as f:
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f.write(result)
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except:
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pass
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def _try_whisper(self, file_path: str) -> Optional[str]:
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"""使用 Whisper 识别"""
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try:
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import whisper
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print(f"[语音识别] 使用 Whisper 识别中...")
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model = whisper.load_model("base")
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result = model.transcribe(file_path, language="zh")
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text = result.get("text", "").strip()
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if text:
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return f"✅ 识别结果:\n{text}"
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return None
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except ImportError:
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return None
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except Exception as e:
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print(f"[语音识别] Whisper 错误: {e}")
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return None
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def _try_speech_recognition(self, file_path: str) -> Optional[str]:
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"""使用 SpeechRecognition 库识别"""
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wav_file = file_path
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try:
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import speech_recognition as sr
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print(f"[语音识别] 使用 SpeechRecognition 识别中...")
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r = sr.Recognizer()
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# 转换为 wav 格式
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wav_file = self._convert_to_wav(file_path)
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with sr.AudioFile(wav_file) as source:
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audio = r.record(source)
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# 尝试 Google 语音识别
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try:
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text = r.recognize_google(audio, language="zh-CN")
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if text:
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return f"✅ 识别结果:\n{text}"
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except:
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pass
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return None
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|
except ImportError:
|
|
return None
|
|
except Exception as e:
|
|
print(f"[语音识别] SpeechRecognition 错误: {e}")
|
|
return None
|
|
finally:
|
|
# 清理转换的临时文件
|
|
if wav_file != file_path and os.path.exists(wav_file):
|
|
try:
|
|
os.remove(wav_file)
|
|
except:
|
|
pass
|
|
|
|
def _convert_to_wav(self, file_path: str) -> str:
|
|
"""转换音频为 wav 格式"""
|
|
if file_path.lower().endswith('.wav'):
|
|
return file_path
|
|
|
|
try:
|
|
wav_file = os.path.join(self.temp_dir, f"convert_{int(time.time())}.wav")
|
|
|
|
# 使用 ffmpeg 转换
|
|
subprocess.run([
|
|
'ffmpeg', '-y', '-i', file_path,
|
|
'-acodec', 'pcm_s16le',
|
|
'-ar', '16000',
|
|
'-ac', '1',
|
|
wav_file
|
|
], capture_output=True, check=True)
|
|
|
|
return wav_file
|
|
|
|
except Exception as e:
|
|
print(f"[语音识别] 转换错误: {e}")
|
|
return file_path
|
|
|
|
# ==================== 其他 ====================
|
|
|
|
def _op_status(self, args: List[str]) -> str:
|
|
"""查看状态"""
|
|
lines = ["📊 语音识别插件状态"]
|
|
|
|
# 检查可用引擎
|
|
engines = []
|
|
|
|
try:
|
|
import whisper
|
|
engines.append("whisper ✅")
|
|
except:
|
|
engines.append("whisper ❌ (pip install openai-whisper)")
|
|
|
|
try:
|
|
import speech_recognition
|
|
engines.append("speech_recognition ✅")
|
|
except:
|
|
engines.append("speech_recognition ❌ (pip install SpeechRecognition)")
|
|
|
|
try:
|
|
import pyaudio
|
|
engines.append("pyaudio ✅ (录音支持)")
|
|
except:
|
|
engines.append("pyaudio ❌ (pip install pyaudio)")
|
|
|
|
lines.append("\n可用引擎:")
|
|
for e in engines:
|
|
lines.append(f" - {e}")
|
|
|
|
return "\n".join(lines)
|
|
|
|
def _op_result(self, args: List[str]) -> str:
|
|
"""获取上次识别结果"""
|
|
if os.path.exists(RESULT_FILE):
|
|
try:
|
|
with open(RESULT_FILE, "r", encoding="utf-8") as f:
|
|
return f.read()
|
|
except:
|
|
pass
|
|
return "暂无识别结果"
|
|
|
|
|
|
if __name__ == "__main__":
|
|
plugin = Plugin()
|
|
print("语音识别插件")
|
|
print(f"临时目录: {plugin.temp_dir}")
|
|
print("\n" + plugin.usage)
|