0a92355bfb
- Updated .env.example to provide clearer configuration instructions and API key setup. - Removed debug_env.py as it was no longer needed. - Refactored main.py to streamline application initialization and workspace setup. - Introduced a new HistoryManager for managing task execution history. - Enhanced UI components in chat_view.py and task_guide_view.py to improve user interaction and code preview functionality. - Added loading indicators and improved task history display in the UI. - Implemented unit tests for history management and intent classification.
124 lines
3.3 KiB
Python
124 lines
3.3 KiB
Python
"""
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LocalAgent - Windows 本地 AI 执行助手 (MVP)
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========================================
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配置说明
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========================================
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1. 复制 .env.example 为 .env
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2. 在 .env 中填入你的 SiliconFlow API Key:
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LLM_API_KEY=sk-xxxxx
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========================================
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运行方式
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========================================
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方式一：使用 Anaconda
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conda create -n localagent python=3.10
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conda activate localagent
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pip install -r requirements.txt
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python main.py
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方式二：直接运行（需已安装依赖）
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python main.py
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========================================
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测试方法
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========================================
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1. 对话测试：输入 "今天天气怎么样" → 应识别为 chat
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2. 执行测试：
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- 将测试文件放入 workspace/input 目录
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- 输入 "把这些文件复制一份" → 应识别为 execution
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- 确认执行后，检查 workspace/output 目录
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========================================
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"""
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import os
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import sys
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import tkinter as tk
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from tkinter import messagebox
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from pathlib import Path
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from dotenv import load_dotenv
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# 确保项目根目录在 Python 路径中
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PROJECT_ROOT = Path(__file__).parent
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ENV_PATH = PROJECT_ROOT / ".env"
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sys.path.insert(0, str(PROJECT_ROOT))
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# 在导入其他模块之前先加载环境变量
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load_dotenv(ENV_PATH)
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from app.agent import LocalAgentApp
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def check_environment() -> bool:
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"""检查运行环境"""
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api_key = os.getenv("LLM_API_KEY")
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if not api_key or api_key == "your_api_key_here":
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print("=" * 50)
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print("错误: 未配置 LLM API Key")
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print("=" * 50)
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print()
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print("请按以下步骤配置:")
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print("1. 复制 .env.example 为 .env")
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print("2. 在 .env 中设置 LLM_API_KEY=你的API密钥")
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print()
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print("获取 API Key: https://siliconflow.cn")
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print("=" * 50)
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# 显示 GUI 错误提示
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root = tk.Tk()
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root.withdraw()
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messagebox.showerror(
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"配置错误",
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"未配置 LLM API Key\n\n"
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"请按以下步骤配置:\n"
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"1. 复制 .env.example 为 .env\n"
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"2. 在 .env 中设置 LLM_API_KEY=你的API密钥\n\n"
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"获取 API Key: https://siliconflow.cn"
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)
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root.destroy()
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return False
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return True
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def setup_workspace():
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"""创建工作目录"""
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workspace = PROJECT_ROOT / "workspace"
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(workspace / "input").mkdir(parents=True, exist_ok=True)
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(workspace / "output").mkdir(parents=True, exist_ok=True)
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(workspace / "logs").mkdir(parents=True, exist_ok=True)
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(workspace / "codes").mkdir(parents=True, exist_ok=True)
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return workspace
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def main():
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"""主入口"""
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print("=" * 50)
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print("LocalAgent - Windows 本地 AI 执行助手")
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print("=" * 50)
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# 检查环境
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if not check_environment():
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sys.exit(1)
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# 创建工作目录
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workspace = setup_workspace()
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print(f"工作目录: {workspace}")
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print(f"输入目录: {workspace / 'input'}")
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print(f"输出目录: {workspace / 'output'}")
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print(f"日志目录: {workspace / 'logs'}")
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print(f"代码目录: {workspace / 'codes'}")
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print("=" * 50)
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# 启动应用
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app = LocalAgentApp(PROJECT_ROOT)
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app.run()
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if __name__ == "__main__":
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main()
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