feat：增强需求澄清与任务管理功能

更新了 .env.example，新增聊天模型配置，以提升对话处理能力。
增强了 README.md，反映了包括需求澄清、代码复用和自动重试在内的新功能。
重构了 agent.py，以支持多模型交互，并为无法在本地执行的任务新增了引导处理逻辑。
改进了 SandboxRunner，增加了任务执行成功校验，并加入了工作区清理功能。

扩展了 HistoryManager，支持任务摘要生成以及记录的批量删除。
优化了 chat_view.py 和 history_view.py 中的 UI 组件，提升用户体验，包括 Markdown 渲染和任务管理选项。

README.md

@@ -5,11 +5,16 @@ A Windows-based local AI assistant that can understand natural language commands
 ## Features
 
 - **Intent Recognition**: Automatically distinguishes between chat conversations and execution tasks
-- **Code Generation**: Generates Python code based on user requirements
+- **Requirement Clarification**: Interactive Q&A to clarify vague requirements before code generation
+- **Code Generation**: Generates Python code based on structured requirements
 - **Safety Checks**: Multi-layer security with static analysis and LLM review
 - **Sandbox Execution**: Runs generated code in an isolated environment
-- **Task History**: Records all executed tasks for review
+- **Task History**: Records all executed tasks with selective deletion
 - **Streaming Responses**: Real-time display of LLM responses
+- **Settings UI**: Easy configuration of API and models
+- **Code Reuse**: Automatically finds and reuses successful code for similar tasks
+- **Auto Retry**: AI-powered code fixing for failed tasks
+- **Multi-Model Support**: Different models for intent recognition, chat, and code generation
 
 ## Project Structure
 
@@ -32,8 +37,10 @@ LocalAgent/
 │   └── manager.py         # History manager
 ├── ui/                     # User interface
 │   ├── chat_view.py       # Chat interface
+│   ├── clarify_view.py    # Requirement clarification view
 │   ├── task_guide_view.py # Task confirmation view
-│   └── history_view.py    # History view
+│   ├── history_view.py    # History view with Markdown support
+│   └── settings_view.py   # Settings configuration view
 ├── tests/                  # Unit tests
 ├── workspace/              # Working directory (auto-created)
 │   ├── input/             # Input files
@@ -85,7 +92,7 @@ LocalAgent/
 
 ## Configuration
 
-Edit `.env` file with your settings:
+Edit `.env` file with your settings (or use the Settings UI in the app):
 
 ```env
 # SiliconFlow API Configuration
@@ -93,7 +100,13 @@ LLM_API_URL=https://api.siliconflow.cn/v1/chat/completions
 LLM_API_KEY=your_api_key_here
 
 # Model Configuration
+# Intent recognition model (small model recommended for speed)
 INTENT_MODEL_NAME=Qwen/Qwen2.5-7B-Instruct
+
+# Chat model (medium model recommended for conversation)
+CHAT_MODEL_NAME=Qwen/Qwen2.5-32B-Instruct
+
+# Code generation model (large model recommended for quality)
 GENERATION_MODEL_NAME=Qwen/Qwen2.5-72B-Instruct
 ```
 
@@ -113,9 +126,26 @@ Describe file processing tasks:
 ### Workflow
 1. Place input files in `workspace/input/`
 2. Describe your task in the chat
-3. Review the execution plan and generated code
-4. Click "Execute" to run
-5. Find results in `workspace/output/`
+3. **If the requirement is vague**, the system will ask clarifying questions:
+   - Radio buttons for single-choice options (e.g., watermark type)
+   - Checkboxes for multi-choice options (e.g., watermark positions)
+   - Input fields for custom values (e.g., watermark text, opacity)
+4. Review the execution plan and generated code
+5. Click "Execute" to run
+6. Find results in `workspace/output/`
+
+### Requirement Clarification Example
+
+When you input a vague request like "Add watermark to images", the system will:
+
+1. **Check completeness** - Detect missing information
+2. **Ask questions** - Present interactive options:
+   - Watermark type: Text / Image (radio)
+   - Position: Top-left / Top-right / Bottom-left / Bottom-right / Center (checkbox)
+   - Text content: [input field]
+   - Opacity: [input field with default 50%]
+3. **Structure requirement** - Convert answers into a complete specification
+4. **Generate code** - Create code based on the structured requirement
 
 ## Security