Merge branch 'main' of http://jeason.online:3000/zhaojie/iov_data_analysis_agent

README.md

@@ -31,7 +31,9 @@ data_analysis_agent/
 │   ├── fallback_openai_client.py  # 支持故障转移的OpenAI客户端
 │   ├── extract_code.py        # 代码提取工具
 │   ├── format_execution_result.py  # 执行结果格式化
-│   └── create_session_dir.py  # 会话目录管理
+│   ├── create_session_dir.py  # 会话目录管理
+│   ├── data_loader.py         # 数据加载与画像生成
+│   └── script_generator.py    # 可复用脚本生成器
 ├── 📄 data_analysis_agent.py  # 主智能体类
 ├── 📄 prompts.py              # 系统提示词模板
 ├── 📄 main.py                 # 使用示例
@@ -266,12 +268,15 @@ stateDiagram-v2
 ```python
 @dataclass
 class LLMConfig:
-    provider: str = "openai"
+    provider: str = os.environ.get("LLM_PROVIDER", "openai")
     api_key: str = os.environ.get("OPENAI_API_KEY", "")
     base_url: str = os.environ.get("OPENAI_BASE_URL", "https://api.openai.com/v1")
     model: str = os.environ.get("OPENAI_MODEL", "gpt-4")
-    max_tokens: int = 4000
+    temperature: float = 0.5
-    temperature: float = 0.1
+    max_tokens: int = 8192
+    
+    # 支持 gemini 等其他 provider 配置
+    # ...
 ```
 
 ### 执行器配置
@@ -281,7 +286,9 @@ class LLMConfig:
 ALLOWED_IMPORTS = {
     'pandas', 'numpy', 'matplotlib', 'duckdb', 
     'scipy', 'sklearn', 'plotly', 'requests',
-    'os', 'json', 'datetime', 're', 'pathlib'
+    'os', 'json', 'datetime', 're', 'pathlib',
+    'seaborn', 'statsmodels', 'networkx', 'jieba',
+    'wordcloud', 'PIL', 'sqlite3', 'yaml'
 }
 ```
 

config/llm_config.py

@@ -18,11 +18,11 @@ class LLMConfig:
     """LLM配置"""
 
     provider: str = os.environ.get("LLM_PROVIDER", "openai")  # openai, gemini, etc.
-    api_key: str = os.environ.get("OPENAI_API_KEY", "sk-Gce85QLROESeOWf3icd2mQnYHOrmMYojwVPQ0AubMjGQ5ZE2")
+    api_key: str = os.environ.get("OPENAI_API_KEY", "sk-2187174de21548b0b8b0c92129700199")
-    base_url: str = os.environ.get("OPENAI_BASE_URL", "https://gemini.jeason.online/v1")
+    base_url: str = os.environ.get("OPENAI_BASE_URL", "http://127.0.0.1:9999/v1")
-    model: str = os.environ.get("OPENAI_MODEL", "gemini-2.5-pro")
+    model: str = os.environ.get("OPENAI_MODEL", "gemini-3-flash")
     temperature: float = 0.5
-    max_tokens: int = 131072
+    max_tokens: int = 8192  # 降低默认值,避免某些API不支持过大的值
 
     def __post_init__(self):
         """配置初始化后的处理"""
@@ -34,6 +34,8 @@ class LLMConfig:
             # Gemini 的 OpenAI 兼容接口地址
             self.base_url = os.environ.get("GEMINI_BASE_URL", "https://gemini.jeason.online")
             self.model = os.environ.get("GEMINI_MODEL", "gemini-2.5-flash")
+            # Gemini 有更严格的 token 限制
+            self.max_tokens = 8192
 
     def to_dict(self) -> Dict[str, Any]:
         """转换为字典"""

data_analysis_agent.py

@@ -18,6 +18,7 @@ from utils.extract_code import extract_code_from_response
 from utils.data_loader import load_and_profile_data
 from utils.llm_helper import LLMHelper
 from utils.code_executor import CodeExecutor
+from utils.script_generator import generate_reusable_script
 from config.llm_config import LLMConfig
 from prompts import data_analysis_system_prompt, final_report_system_prompt, data_analysis_followup_prompt
 
@@ -61,6 +62,8 @@ class DataAnalysisAgent:
         self.session_output_dir = None
         self.executor = None
         self.data_profile = ""  # 存储数据画像
+        self.data_files = []  # 存储数据文件列表
+        self.user_requirement = ""  # 存储用户需求
 
     def _process_response(self, response: str) -> Dict[str, Any]:
         """
@@ -76,7 +79,7 @@ class DataAnalysisAgent:
             yaml_data = self.llm.parse_yaml_response(response)
             action = yaml_data.get("action", "generate_code")
 
-            print(f"🎯 检测到动作: {action}")
+            print(f"[TARGET] 检测到动作: {action}")
 
             if action == "analysis_complete":
                 return self._handle_analysis_complete(response, yaml_data)
@@ -85,11 +88,11 @@ class DataAnalysisAgent:
             elif action == "generate_code":
                 return self._handle_generate_code(response, yaml_data)
             else:
-                print(f"⚠️ 未知动作类型: {action}，按generate_code处理")
+                print(f"[WARN] 未知动作类型: {action}，按generate_code处理")
                 return self._handle_generate_code(response, yaml_data)
 
         except Exception as e:
-            print(f"⚠️ 解析响应失败: {str(e)}，尝试提取代码并按generate_code处理")
+            print(f"[WARN] 解析响应失败: {str(e)}，尝试提取代码并按generate_code处理")
             # 即使YAML解析失败，也尝试提取代码
             extracted_code = extract_code_from_response(response)
             if extracted_code:
@@ -100,7 +103,7 @@ class DataAnalysisAgent:
         self, response: str, yaml_data: Dict[str, Any]
     ) -> Dict[str, Any]:
         """处理分析完成动作"""
-        print("✅ 分析任务完成")
+        print("[OK] 分析任务完成")
         final_report = yaml_data.get("final_report", "分析完成，无最终报告")
         return {
             "action": "analysis_complete",
@@ -113,7 +116,7 @@ class DataAnalysisAgent:
         self, response: str, yaml_data: Dict[str, Any]
     ) -> Dict[str, Any]:
         """处理图片收集动作"""
-        print("📊 开始收集图片")
+        print("[CHART] 开始收集图片")
         figures_to_collect = yaml_data.get("figures_to_collect", [])
 
         collected_figures = []
@@ -130,10 +133,10 @@ class DataAnalysisAgent:
             description = figure_info.get("description", "")
             analysis = figure_info.get("analysis", "")
 
-            print(f"📈 收集图片 {figure_number}: {filename}")
+            print(f"[GRAPH] 收集图片 {figure_number}: {filename}")
-            print(f"   📂 路径: {file_path}")
+            print(f"   [DIR] 路径: {file_path}")
-            print(f"   📝 描述: {description}")
+            print(f"   [NOTE] 描述: {description}")
-            print(f"   🔍 分析: {analysis}")
+            print(f"   [SEARCH] 分析: {analysis}")
 
 
             # 使用seen_paths集合来去重，防止重复收集
@@ -145,7 +148,7 @@ class DataAnalysisAgent:
                 # 检查是否已经收集过该路径
                 abs_path = os.path.abspath(file_path)
                 if abs_path not in seen_paths:
-                    print(f"   ✅ 文件存在: {file_path}")
+                    print(f"   [OK] 文件存在: {file_path}")
                     # 记录图片信息
                     collected_figures.append(
                         {
@@ -158,12 +161,12 @@ class DataAnalysisAgent:
                     )
                     seen_paths.add(abs_path)
                 else:
-                    print(f"   ⚠️ 跳过重复图片: {file_path}")
+                    print(f"   [WARN] 跳过重复图片: {file_path}")
             else:
                 if file_path:
-                    print(f"   ⚠️ 文件不存在: {file_path}")
+                    print(f"   [WARN] 文件不存在: {file_path}")
                 else:
-                    print(f"   ⚠️ 未提供文件路径")
+                    print(f"   [WARN] 未提供文件路径")
 
         return {
             "action": "collect_figures",
@@ -195,7 +198,7 @@ class DataAnalysisAgent:
                 code = code.strip()
 
         if code:
-            print(f"🔧 执行代码:\n{code}")
+            print(f"[TOOL] 执行代码:\n{code}")
             print("-" * 40)
 
             # 执行代码
@@ -203,7 +206,7 @@ class DataAnalysisAgent:
 
             # 格式化执行结果
             feedback = format_execution_result(result)
-            print(f"📋 执行反馈:\n{feedback}")
+            print(f"[LIST] 执行反馈:\n{feedback}")
 
             return {
                 "action": "generate_code",
@@ -215,7 +218,7 @@ class DataAnalysisAgent:
             }
         else:
             # 如果没有代码，说明LLM响应格式有问题，需要重新生成
-            print("⚠️ 未从响应中提取到可执行代码，要求LLM重新生成")
+            print("[WARN] 未从响应中提取到可执行代码，要求LLM重新生成")
             return {
                 "action": "invalid_response",
                 "error": "响应中缺少可执行代码",
@@ -246,6 +249,8 @@ class DataAnalysisAgent:
             self.conversation_history = []
             self.analysis_results = []
             self.current_round = 0
+            self.data_files = files or []  # 保存数据文件列表
+            self.user_requirement = user_input  # 保存用户需求
             
             # 创建本次分析的专用输出目录
             if session_output_dir:
@@ -264,12 +269,12 @@ class DataAnalysisAgent:
             # 设用工具生成数据画像
             data_profile = ""
             if files:
-                print("🔍 正在生成数据画像...")
+                print("[SEARCH] 正在生成数据画像...")
                 try:
                     data_profile = load_and_profile_data(files)
-                    print("✅ 数据画像生成完毕")
+                    print("[OK] 数据画像生成完毕")
                 except Exception as e:
-                    print(f"⚠️ 数据画像生成失败: {e}")
+                    print(f"[WARN] 数据画像生成失败: {e}")
             
             # 保存到实例变量供最终报告使用
             self.data_profile = data_profile
@@ -282,11 +287,11 @@ class DataAnalysisAgent:
             if data_profile:
                 initial_prompt += f"\n\n{data_profile}\n\n请根据上述【数据画像】中的统计信息（如高频值、缺失率、数据范围）来制定分析策略。如果发现明显的高频问题或异常分布，请优先进行深度分析。"
 
-            print(f"🚀 开始数据分析任务")
+            print(f"[START] 开始数据分析任务")
-            print(f"📝 用户需求: {user_input}")
+            print(f"[NOTE] 用户需求: {user_input}")
             if files:
-                print(f"📁 数据文件: {', '.join(files)}")
+                print(f"[FOLDER] 数据文件: {', '.join(files)}")
-            print(f"📂 输出目录: {self.session_output_dir}")
+            print(f"[DIR] 输出目录: {self.session_output_dir}")
             
             # 添加到对话历史
             self.conversation_history.append({"role": "user", "content": initial_prompt})
@@ -297,8 +302,8 @@ class DataAnalysisAgent:
             if max_rounds is None:
                 current_max_rounds = 10 # 追问通常不需要那么长的思考链，10轮足够
             
-            print(f"\n🚀 继续分析任务 (追问模式)")
+            print(f"\n[START] 继续分析任务 (追问模式)")
-            print(f"📝 后续需求: {user_input}")
+            print(f"[NOTE] 后续需求: {user_input}")
             
             # 重置当前轮数计数器，以便给新任务足够的轮次
             self.current_round = 0 
@@ -308,18 +313,21 @@ class DataAnalysisAgent:
             follow_up_prompt = f"后续需求: {user_input}\n(注意：这是后续追问，请直接针对该问题进行分析，无需从头开始执行完整SOP。)"
             self.conversation_history.append({"role": "user", "content": follow_up_prompt})
 
-        print(f"🔢 本次最大轮数: {current_max_rounds}")
+        print(f"[NUM] 本次最大轮数: {current_max_rounds}")
         if self.force_max_rounds:
-            print(f"⚡ 强制模式: 将运行满 {current_max_rounds} 轮（忽略AI完成信号）")
+            print(f"[FAST] 强制模式: 将运行满 {current_max_rounds} 轮（忽略AI完成信号）")
         print("=" * 60)
         
         # 保存原始 max_rounds 以便恢复（虽然 analyze 结束后不需要恢复，但为了逻辑严谨）
         original_max_rounds = self.max_rounds
         self.max_rounds = current_max_rounds
 
+        # 初始化连续失败计数器
+        consecutive_failures = 0
+
         while self.current_round < self.max_rounds:
             self.current_round += 1
-            print(f"\n🔄 第 {self.current_round} 轮分析")
+            print(f"\n[LOOP] 第 {self.current_round} 轮分析")
             # 调用LLM生成响应
             try:  # 获取当前执行环境的变量信息
                 notebook_variables = self.executor.get_environment_info()
@@ -340,15 +348,15 @@ class DataAnalysisAgent:
                 formatted_system_prompt = base_system_prompt.format(
                     notebook_variables=notebook_variables
                 )
-                print(f"🐛 [DEBUG] System Prompt Head:\n{formatted_system_prompt[:500]}...\n[...]")
+                print(f"[DEBUG] [DEBUG] System Prompt Head:\n{formatted_system_prompt[:500]}...\n[...]")
-                print(f"🐛 [DEBUG] System Prompt Rules Check: 'stop_words' in prompt? {'stop_words' in formatted_system_prompt}")
+                print(f"[DEBUG] [DEBUG] System Prompt Rules Check: 'stop_words' in prompt? {'stop_words' in formatted_system_prompt}")
 
                 response = self.llm.call(
                     prompt=self._build_conversation_prompt(),
                     system_prompt=formatted_system_prompt,
                 )
 
-                print(f"🤖 助手响应:\n{response}")
+                print(f"[AI] 助手响应:\n{response}")
 
                 # 使用统一的响应处理方法
                 process_result = self._process_response(response)
@@ -356,9 +364,9 @@ class DataAnalysisAgent:
                 # 根据处理结果决定是否继续（仅在非强制模式下）
                 if process_result.get("action") == "invalid_response":
                     consecutive_failures += 1
-                    print(f"⚠️ 连续失败次数: {consecutive_failures}/3")
+                    print(f"[WARN] 连续失败次数: {consecutive_failures}/3")
                     if consecutive_failures >= 3:
-                        print(f"❌ 连续3次无法获取有效响应，分析终止。请检查网络或配置。")
+                        print(f"[ERROR] 连续3次无法获取有效响应，分析终止。请检查网络或配置。")
                         break
                 else:
                     consecutive_failures = 0  # 重置计数器
@@ -366,7 +374,7 @@ class DataAnalysisAgent:
                 if not self.force_max_rounds and not process_result.get(
                     "continue", True
                 ):
-                    print(f"\n✅ 分析完成！")
+                    print(f"\n[OK] 分析完成！")
                     break
 
                 # 添加到对话历史
@@ -398,7 +406,7 @@ class DataAnalysisAgent:
                     
                     feedback = f"已收集 {len(collected_figures)} 个有效图片及其分析。"
                     if missing_figures:
-                        feedback += f"\n⚠️ 以下图片未找到，请检查代码是否成功保存了这些图片: {missing_figures}"
+                        feedback += f"\n[WARN] 以下图片未找到，请检查代码是否成功保存了这些图片: {missing_figures}"
 
                     self.conversation_history.append(
                         {
@@ -421,7 +429,7 @@ class DataAnalysisAgent:
 
             except Exception as e:
                 error_msg = f"LLM调用错误: {str(e)}"
-                print(f"❌ {error_msg}")
+                print(f"[ERROR] {error_msg}")
                 self.conversation_history.append(
                     {
                         "role": "user",
@@ -430,7 +438,7 @@ class DataAnalysisAgent:
                 )
         # 生成最终总结
         if self.current_round >= self.max_rounds:
-            print(f"\n⚠️ 已达到最大轮数 ({self.max_rounds})，分析结束")
+            print(f"\n[WARN] 已达到最大轮数 ({self.max_rounds})，分析结束")
 
         return self._generate_final_report()
 
@@ -456,8 +464,8 @@ class DataAnalysisAgent:
             if result.get("action") == "collect_figures":
                 all_figures.extend(result.get("collected_figures", []))
 
-        print(f"\n📊 开始生成最终分析报告...")
+        print(f"\n[CHART] 开始生成最终分析报告...")
-        print(f"📂 输出目录: {self.session_output_dir}")
+        print(f"[DIR] 输出目录: {self.session_output_dir}")
         
         # --- 自动补全/发现图片机制 ---
         # 扫描目录下所有的png文件
@@ -475,7 +483,7 @@ class DataAnalysisAgent:
             for png_path in existing_pngs:
                 abs_png_path = os.path.abspath(png_path)
                 if abs_png_path not in collected_paths:
-                    print(f"🔍 [自动发现] 补充未显式收集的图片: {os.path.basename(png_path)}")
+                    print(f"[SEARCH] [自动发现] 补充未显式收集的图片: {os.path.basename(png_path)}")
                     all_figures.append({
                         "figure_number": "Auto",
                         "filename": os.path.basename(png_path),
@@ -484,11 +492,11 @@ class DataAnalysisAgent:
                         "analysis": "（该图表由系统自动捕获，Agent未提供具体分析文本，请结合图表标题理解）"
                     })
         except Exception as e:
-            print(f"⚠️ 自动发现图片失败: {e}")
+            print(f"[WARN] 自动发现图片失败: {e}")
         # ---------------------------
 
-        print(f"🔢 总轮数: {self.current_round}")
+        print(f"[NUM] 总轮数: {self.current_round}")
-        print(f"📈 收集图片: {len(all_figures)} 个")
+        print(f"[GRAPH] 收集图片: {len(all_figures)} 个")
 
         # 构建用于生成最终报告的提示词
         final_report_prompt = self._build_final_report_prompt(all_figures)
@@ -512,12 +520,12 @@ class DataAnalysisAgent:
                 except:
                     pass # 解析失败则保持原样
 
-            print("✅ 最终报告生成完成")
+            print("[OK] 最终报告生成完成")
 
-            print("✅ 最终报告生成完成")
+            print("[OK] 最终报告生成完成")
 
         except Exception as e:
-            print(f"❌ 生成最终报告时出错: {str(e)}")
+            print(f"[ERROR] 生成最终报告时出错: {str(e)}")
             final_report_content = f"报告生成失败: {str(e)}"
 
         # 保存最终报告到文件
@@ -525,9 +533,21 @@ class DataAnalysisAgent:
         try:
             with open(report_file_path, "w", encoding="utf-8") as f:
                 f.write(final_report_content)
-            print(f"📄 最终报告已保存至: {report_file_path}")
+            print(f"[DOC] 最终报告已保存至: {report_file_path}")
         except Exception as e:
-            print(f"❌ 保存报告文件失败: {str(e)}")
+            print(f"[ERROR] 保存报告文件失败: {str(e)}")
+
+        # 生成可复用脚本
+        script_path = ""
+        try:
+            script_path = generate_reusable_script(
+                analysis_results=self.analysis_results,
+                data_files=self.data_files,
+                session_output_dir=self.session_output_dir,
+                user_requirement=self.user_requirement
+            )
+        except Exception as e:
+            print(f"[WARN] 脚本生成失败: {e}")
 
         # 返回完整的分析结果
         return {
@@ -538,6 +558,7 @@ class DataAnalysisAgent:
             "conversation_history": self.conversation_history,
             "final_report": final_report_content,
             "report_file_path": report_file_path,
+            "reusable_script_path": script_path,
         }
 
     def _build_final_report_prompt(self, all_figures: List[Dict[str, Any]]) -> str:
@@ -584,7 +605,7 @@ class DataAnalysisAgent:
         # 在提示词中明确要求使用相对路径
         prompt += """
 
-📁 **图片路径使用说明**：
+[FOLDER] **图片路径使用说明**：
 报告和图片都在同一目录下，请在报告中使用相对路径引用图片：
 - 格式：![图片描述](./图片文件名.png)
 - 示例：![营业总收入趋势](./营业总收入趋势.png)

data_preprocessing/README.md

@@ -0,0 +1,89 @@
+# 数据预处理模块
+
+独立的数据清洗工具，用于在正式分析前准备数据。
+
+## 功能
+
+- **数据合并**：将多个 Excel/CSV 文件合并为单一 CSV
+- **时间排序**：按时间列对数据进行排序
+- **目录管理**：标准化的原始数据和输出数据目录
+
+## 目录结构
+
+```
+project/
+├── raw_data/           # 原始数据存放目录
+│   ├── remotecontrol/  # 按数据来源分类
+│   └── ...
+├── cleaned_data/       # 清洗后数据输出目录
+│   ├── xxx_merged.csv
+│   └── xxx_sorted.csv
+└── data_preprocessing/ # 本模块
+```
+
+## 使用方法
+
+### 命令行
+
+```bash
+# 初始化目录结构
+python -m data_preprocessing.cli init
+
+# 合并 Excel 文件
+python -m data_preprocessing.cli merge --source raw_data/remotecontrol
+
+# 合并并按时间排序
+python -m data_preprocessing.cli merge --source raw_data/remotecontrol --sort-by SendTime
+
+# 指定输出路径
+python -m data_preprocessing.cli merge -s raw_data/remotecontrol -o cleaned_data/my_output.csv
+
+# 排序已有 CSV
+python -m data_preprocessing.cli sort --input some_file.csv --time-col SendTime
+
+# 原地排序（覆盖原文件）
+python -m data_preprocessing.cli sort --input data.csv --inplace
+```
+
+### Python API
+
+```python
+from data_preprocessing import merge_files, sort_by_time, Config
+
+# 合并文件
+output_path = merge_files(
+    source_dir="raw_data/remotecontrol",
+    output_file="cleaned_data/merged.csv",
+    pattern="*.xlsx",
+    time_column="SendTime"  # 可选：合并后排序
+)
+
+# 排序 CSV
+sorted_path = sort_by_time(
+    input_path="data.csv",
+    output_path="sorted_data.csv",
+    time_column="CreateTime"
+)
+
+# 自定义配置
+config = Config()
+config.raw_data_dir = "/path/to/raw"
+config.cleaned_data_dir = "/path/to/cleaned"
+config.ensure_dirs()
+```
+
+## 配置项
+
+| 配置项 | 默认值 | 说明 |
+|--------|--------|------|
+| `raw_data_dir` | `raw_data/` | 原始数据目录 |
+| `cleaned_data_dir` | `cleaned_data/` | 清洗输出目录 |
+| `default_time_column` | `SendTime` | 默认时间列名 |
+| `csv_encoding` | `utf-8-sig` | CSV 编码格式 |
+
+## 注意事项
+
+1. 本模块与 `DataAnalysisAgent` 完全独立，不会相互调用
+2. 合并时会自动添加 `_source_file` 列标记数据来源（可用 `--no-source-col` 禁用）
+3. Excel 文件会自动合并所有 Sheet
+4. 无效时间值在排序时会被放到最后

data_preprocessing/__init__.py

@@ -0,0 +1,14 @@
+# -*- coding: utf-8 -*-
+"""
+数据预处理模块
+
+提供独立的数据清洗功能：
+- 按时间排序
+- 同类数据合并
+"""
+
+from .sorter import sort_by_time
+from .merger import merge_files
+from .config import Config
+
+__all__ = ["sort_by_time", "merge_files", "Config"]

data_preprocessing/cli.py

@@ -0,0 +1,140 @@
+# -*- coding: utf-8 -*-
+"""
+数据预处理命令行接口
+
+使用示例:
+    # 合并 Excel 文件
+    python -m data_preprocessing.cli merge --source raw_data/remotecontrol --output cleaned_data/merged.csv
+    
+    # 合并并排序
+    python -m data_preprocessing.cli merge --source raw_data/remotecontrol --sort-by SendTime
+    
+    # 排序已有 CSV
+    python -m data_preprocessing.cli sort --input data.csv --output sorted.csv --time-col SendTime
+    
+    # 初始化目录结构
+    python -m data_preprocessing.cli init
+"""
+
+import argparse
+import sys
+from .config import default_config
+from .sorter import sort_by_time
+from .merger import merge_files
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        prog="data_preprocessing",
+        description="数据预处理工具：排序、合并",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog="""
+示例:
+  %(prog)s merge --source raw_data/remotecontrol --sort-by SendTime
+  %(prog)s sort --input data.csv --time-col CreateTime
+  %(prog)s init
+        """
+    )
+    
+    subparsers = parser.add_subparsers(dest="command", help="可用命令")
+    
+    # ========== merge 命令 ==========
+    merge_parser = subparsers.add_parser("merge", help="合并同类文件")
+    merge_parser.add_argument(
+        "--source", "-s",
+        required=True,
+        help="源数据目录路径"
+    )
+    merge_parser.add_argument(
+        "--output", "-o",
+        default=None,
+        help="输出文件路径 (默认: cleaned_data/<目录名>_merged.csv)"
+    )
+    merge_parser.add_argument(
+        "--pattern", "-p",
+        default="*.xlsx",
+        help="文件匹配模式 (默认: *.xlsx)"
+    )
+    merge_parser.add_argument(
+        "--sort-by",
+        default=None,
+        dest="time_column",
+        help="合并后按此时间列排序"
+    )
+    merge_parser.add_argument(
+        "--no-source-col",
+        action="store_true",
+        help="不添加来源文件列"
+    )
+    
+    # ========== sort 命令 ==========
+    sort_parser = subparsers.add_parser("sort", help="按时间排序 CSV")
+    sort_parser.add_argument(
+        "--input", "-i",
+        required=True,
+        help="输入 CSV 文件路径"
+    )
+    sort_parser.add_argument(
+        "--output", "-o",
+        default=None,
+        help="输出文件路径 (默认: cleaned_data/<文件名>_sorted.csv)"
+    )
+    sort_parser.add_argument(
+        "--time-col", "-t",
+        default=None,
+        dest="time_column",
+        help=f"时间列名 (默认: {default_config.default_time_column})"
+    )
+    sort_parser.add_argument(
+        "--inplace",
+        action="store_true",
+        help="原地覆盖输入文件"
+    )
+    
+    # ========== init 命令 ==========
+    init_parser = subparsers.add_parser("init", help="初始化目录结构")
+    
+    # 解析参数
+    args = parser.parse_args()
+    
+    if args.command is None:
+        parser.print_help()
+        sys.exit(0)
+    
+    try:
+        if args.command == "merge":
+            result = merge_files(
+                source_dir=args.source,
+                output_file=args.output,
+                pattern=args.pattern,
+                time_column=args.time_column,
+                add_source_column=not args.no_source_col
+            )
+            print(f"\n✅ 合并成功: {result}")
+            
+        elif args.command == "sort":
+            result = sort_by_time(
+                input_path=args.input,
+                output_path=args.output,
+                time_column=args.time_column,
+                inplace=args.inplace
+            )
+            print(f"\n✅ 排序成功: {result}")
+            
+        elif args.command == "init":
+            default_config.ensure_dirs()
+            print("\n✅ 目录初始化完成")
+            
+    except FileNotFoundError as e:
+        print(f"\n❌ 错误: {e}")
+        sys.exit(1)
+    except KeyError as e:
+        print(f"\n❌ 错误: {e}")
+        sys.exit(1)
+    except Exception as e:
+        print(f"\n❌ 未知错误: {e}")
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()

data_preprocessing/config.py

@@ -0,0 +1,42 @@
+# -*- coding: utf-8 -*-
+"""
+数据预处理模块配置
+"""
+
+import os
+from dataclasses import dataclass
+
+# 获取项目根目录
+PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+
+
+@dataclass
+class Config:
+    """预处理模块配置"""
+    
+    # 原始数据存放目录
+    raw_data_dir: str = os.path.join(PROJECT_ROOT, "raw_data")
+    
+    # 清洗后数据输出目录
+    cleaned_data_dir: str = os.path.join(PROJECT_ROOT, "cleaned_data")
+    
+    # 默认时间列名
+    default_time_column: str = "SendTime"
+    
+    # 支持的文件扩展名
+    supported_extensions: tuple = (".csv", ".xlsx", ".xls")
+    
+    # CSV 编码
+    csv_encoding: str = "utf-8-sig"
+    
+    def ensure_dirs(self):
+        """确保目录存在"""
+        os.makedirs(self.raw_data_dir, exist_ok=True)
+        os.makedirs(self.cleaned_data_dir, exist_ok=True)
+        print(f"[OK] 目录已就绪:")
+        print(f"    原始数据: {self.raw_data_dir}")
+        print(f"    清洗输出: {self.cleaned_data_dir}")
+
+
+# 默认配置实例
+default_config = Config()

data_preprocessing/merge_excel.py

@@ -0,0 +1,83 @@
+
+import pandas as pd
+import glob
+import os
+
+def merge_excel_files(source_dir="remotecontrol", output_file="merged_all_files.csv"):
+    """
+    将指定目录下的所有 Excel 文件 (.xlsx, .xls) 合并为一个 CSV 文件。
+    """
+    print(f"[SEARCH] 正在扫描目录: {source_dir} ...")
+    
+    # 支持 xlsx 和 xls
+    files_xlsx = glob.glob(os.path.join(source_dir, "*.xlsx"))
+    files_xls = glob.glob(os.path.join(source_dir, "*.xls"))
+    files = files_xlsx + files_xls
+    
+    if not files:
+        print("[WARN] 未找到 Excel 文件。")
+        return
+
+    # 按文件名中的数字进行排序 (例如: 1.xlsx, 2.xlsx, ..., 10.xlsx)
+    try:
+        files.sort(key=lambda x: int(os.path.basename(x).split('.')[0]))
+        print("[NUM] 已按文件名数字顺序排序")
+    except ValueError:
+        # 如果文件名不是纯数字，退回到字母排序
+        files.sort()
+        print("[TEXT] 已按文件名包含非数字字符，使用字母顺序排序")
+
+    print(f"[DIR] 找到 {len(files)} 个文件: {files}")
+    
+    all_dfs = []
+    for file in files:
+        try:
+            print(f"[READ] 读取: {file}")
+            # 使用 ExcelFile 读取所有 sheet
+            xls = pd.ExcelFile(file)
+            print(f"   [PAGES] 包含 Sheets: {xls.sheet_names}")
+            
+            file_dfs = []
+            for sheet_name in xls.sheet_names:
+                df = pd.read_excel(xls, sheet_name=sheet_name)
+                if not df.empty:
+                    print(f"   [OK] Sheet '{sheet_name}' 读取成功: {len(df)} 行")
+                    file_dfs.append(df)
+                else:
+                    print(f"   [WARN] Sheet '{sheet_name}' 为空，跳过")
+            
+            if file_dfs:
+                # 合并该文件的所有非空 sheet
+                file_merged_df = pd.concat(file_dfs, ignore_index=True)
+                # 可选：添加一列标记来源文件
+                file_merged_df['Source_File'] = os.path.basename(file)
+                all_dfs.append(file_merged_df)
+            else:
+                 print(f"[WARN] 文件 {file} 所有 Sheet 均为空")
+
+        except Exception as e:
+            print(f"[ERROR] 读取 {file} 失败: {e}")
+
+    if all_dfs:
+        print("[LOOP] 正在合并数据...")
+        merged_df = pd.concat(all_dfs, ignore_index=True)
+        
+        # 按 SendTime 排序
+        if 'SendTime' in merged_df.columns:
+            print("[TIMER] 正在按 SendTime 排序...")
+            merged_df['SendTime'] = pd.to_datetime(merged_df['SendTime'], errors='coerce')
+            merged_df = merged_df.sort_values(by='SendTime')
+        else:
+            print("[WARN] 未找到 SendTime 列，跳过排序")
+
+        print(f"[CACHE] 保存到: {output_file}")
+        merged_df.to_csv(output_file, index=False, encoding="utf-8-sig")
+        
+        print(f"[OK] 合并及排序完成！总行数: {len(merged_df)}")
+        print(f"   输出文件: {os.path.abspath(output_file)}")
+    else:
+        print("[WARN] 没有成功读取到任何数据。")
+
+if __name__ == "__main__":
+    # 如果需要在当前目录运行并合并 remotecontrol 文件夹下的内容
+    merge_excel_files(source_dir="remotecontrol", output_file="remotecontrol_merged.csv")

data_preprocessing/merger.py

@@ -0,0 +1,148 @@
+# -*- coding: utf-8 -*-
+"""
+数据合并模块
+
+合并同类 Excel/CSV 文件
+"""
+
+import os
+import glob
+import pandas as pd
+from typing import Optional, List
+from .config import default_config
+
+
+def merge_files(
+    source_dir: str,
+    output_file: Optional[str] = None,
+    pattern: str = "*.xlsx",
+    time_column: Optional[str] = None,
+    add_source_column: bool = True
+) -> str:
+    """
+    合并目录下的所有同类文件
+    
+    Args:
+        source_dir: 源数据目录
+        output_file: 输出 CSV 文件路径。如果为 None，则输出到 cleaned_data 目录
+        pattern: 文件匹配模式 (e.g., "*.xlsx", "*.csv", "*.xls")
+        time_column: 可选，合并后按此列排序
+        add_source_column: 是否添加来源文件列
+        
+    Returns:
+        输出文件的绝对路径
+        
+    Raises:
+        FileNotFoundError: 目录不存在或未找到匹配文件
+    """
+    if not os.path.isdir(source_dir):
+        raise FileNotFoundError(f"目录不存在: {source_dir}")
+    
+    print(f"[SCAN] 正在扫描目录: {source_dir}")
+    print(f"    匹配模式: {pattern}")
+    
+    # 查找匹配文件
+    files = glob.glob(os.path.join(source_dir, pattern))
+    
+    # 如果是 xlsx，也尝试匹配 xls
+    if pattern == "*.xlsx":
+        files.extend(glob.glob(os.path.join(source_dir, "*.xls")))
+    
+    if not files:
+        raise FileNotFoundError(f"未找到匹配 '{pattern}' 的文件")
+    
+    # 排序文件列表
+    files = _sort_files(files)
+    print(f"[FOUND] 找到 {len(files)} 个文件")
+    
+    # 确定输出路径
+    if output_file is None:
+        default_config.ensure_dirs()
+        dir_name = os.path.basename(os.path.normpath(source_dir))
+        output_file = os.path.join(
+            default_config.cleaned_data_dir,
+            f"{dir_name}_merged.csv"
+        )
+    
+    # 合并数据
+    all_dfs = []
+    for file in files:
+        try:
+            df = _read_file(file)
+            if df is not None and not df.empty:
+                if add_source_column:
+                    df['_source_file'] = os.path.basename(file)
+                all_dfs.append(df)
+        except Exception as e:
+            print(f"[ERROR] 读取失败 {file}: {e}")
+    
+    if not all_dfs:
+        raise ValueError("没有成功读取到任何数据")
+    
+    print(f"[MERGE] 正在合并 {len(all_dfs)} 个数据源...")
+    merged_df = pd.concat(all_dfs, ignore_index=True)
+    print(f"    合并后总行数: {len(merged_df)}")
+    
+    # 可选：按时间排序
+    if time_column and time_column in merged_df.columns:
+        print(f"[SORT] 正在按 '{time_column}' 排序...")
+        merged_df[time_column] = pd.to_datetime(merged_df[time_column], errors='coerce')
+        merged_df = merged_df.sort_values(by=time_column, na_position='last')
+    elif time_column:
+        print(f"[WARN] 未找到时间列 '{time_column}'，跳过排序")
+    
+    # 保存结果
+    print(f"[SAVE] 正在保存: {output_file}")
+    merged_df.to_csv(output_file, index=False, encoding=default_config.csv_encoding)
+    
+    abs_output = os.path.abspath(output_file)
+    print(f"[OK] 合并完成！")
+    print(f"    输出文件: {abs_output}")
+    print(f"    总行数: {len(merged_df)}")
+    
+    return abs_output
+
+
+def _sort_files(files: List[str]) -> List[str]:
+    """对文件列表进行智能排序"""
+    try:
+        # 尝试按文件名中的数字排序
+        files.sort(key=lambda x: int(os.path.basename(x).split('.')[0]))
+        print("[SORT] 已按文件名数字顺序排序")
+    except ValueError:
+        # 退回到字母排序
+        files.sort()
+        print("[SORT] 已按文件名字母顺序排序")
+    return files
+
+
+def _read_file(file_path: str) -> Optional[pd.DataFrame]:
+    """读取单个文件（支持 CSV 和 Excel）"""
+    ext = os.path.splitext(file_path)[1].lower()
+    
+    print(f"[READ] 读取: {os.path.basename(file_path)}")
+    
+    if ext == '.csv':
+        df = pd.read_csv(file_path, low_memory=False)
+        print(f"    行数: {len(df)}")
+        return df
+    
+    elif ext in ('.xlsx', '.xls'):
+        # 读取 Excel 所有 sheet 并合并
+        xls = pd.ExcelFile(file_path)
+        print(f"    Sheets: {xls.sheet_names}")
+        
+        sheet_dfs = []
+        for sheet_name in xls.sheet_names:
+            df = pd.read_excel(xls, sheet_name=sheet_name)
+            if not df.empty:
+                print(f"    - Sheet '{sheet_name}': {len(df)} 行")
+                sheet_dfs.append(df)
+        
+        if sheet_dfs:
+            return pd.concat(sheet_dfs, ignore_index=True)
+        return None
+    
+    else:
+        print(f"[WARN] 不支持的文件格式: {ext}")
+        return None

data_preprocessing/sort_csv.py

@@ -0,0 +1,45 @@
+
+import pandas as pd
+import os
+
+def sort_csv_by_time(file_path="remotecontrol_merged.csv", time_col="SendTime"):
+    """
+    读取 CSV 文件，按时间列排序，并保存。
+    """
+    if not os.path.exists(file_path):
+        print(f"[ERROR] 文件不存在: {file_path}")
+        return
+
+    print(f"[READ] 正在读取 {file_path} ...")
+    try:
+        # 读取 CSV
+        df = pd.read_csv(file_path, low_memory=False)
+        print(f"   [CHART] 数据行数: {len(df)}")
+        
+        if time_col not in df.columns:
+            print(f"[ERROR] 未找到时间列: {time_col}")
+            print(f"   可用列: {list(df.columns)}")
+            return
+
+        print(f"[LOOP] 正在解析时间列 '{time_col}' ...")
+        # 转换为 datetime 对象，无法解析的设为 NaT
+        df[time_col] = pd.to_datetime(df[time_col], errors='coerce')
+        
+        # 检查无效时间
+        nat_count = df[time_col].isna().sum()
+        if nat_count > 0:
+            print(f"[WARN] 发现 {nat_count} 行无效时间数据，排序时将排在最后")
+
+        print("[LOOP] 正在按时间排序...")
+        df_sorted = df.sort_values(by=time_col)
+        
+        print(f"[CACHE] 正在保存及覆盖文件: {file_path} ...")
+        df_sorted.to_csv(file_path, index=False, encoding="utf-8-sig")
+        
+        print("[OK] 排序并保存完成！")
+        
+    except Exception as e:
+        print(f"[ERROR]处理失败: {e}")
+
+if __name__ == "__main__":
+    sort_csv_by_time()

data_preprocessing/sorter.py

@@ -0,0 +1,82 @@
+# -*- coding: utf-8 -*-
+"""
+数据排序模块
+
+按时间列对 CSV 文件进行排序
+"""
+
+import os
+import pandas as pd
+from typing import Optional
+from .config import default_config
+
+
+def sort_by_time(
+    input_path: str,
+    output_path: Optional[str] = None,
+    time_column: str = None,
+    inplace: bool = False
+) -> str:
+    """
+    按时间列对 CSV 文件排序
+    
+    Args:
+        input_path: 输入 CSV 文件路径
+        output_path: 输出路径。如果为 None 且 inplace=False，则输出到 cleaned_data 目录
+        time_column: 时间列名，默认使用配置中的 default_time_column
+        inplace: 是否原地覆盖输入文件
+        
+    Returns:
+        输出文件的绝对路径
+        
+    Raises:
+        FileNotFoundError: 输入文件不存在
+        KeyError: 时间列不存在
+    """
+    # 参数处理
+    time_column = time_column or default_config.default_time_column
+    
+    if not os.path.exists(input_path):
+        raise FileNotFoundError(f"文件不存在: {input_path}")
+    
+    # 确定输出路径
+    if inplace:
+        output_path = input_path
+    elif output_path is None:
+        default_config.ensure_dirs()
+        basename = os.path.basename(input_path)
+        name, ext = os.path.splitext(basename)
+        output_path = os.path.join(
+            default_config.cleaned_data_dir, 
+            f"{name}_sorted{ext}"
+        )
+    
+    print(f"[READ] 正在读取: {input_path}")
+    df = pd.read_csv(input_path, low_memory=False)
+    print(f"    数据行数: {len(df)}")
+    
+    # 检查时间列是否存在
+    if time_column not in df.columns:
+        available_cols = list(df.columns)
+        raise KeyError(
+            f"未找到时间列 '{time_column}'。可用列: {available_cols}"
+        )
+    
+    print(f"[PARSE] 正在解析时间列 '{time_column}'...")
+    df[time_column] = pd.to_datetime(df[time_column], errors='coerce')
+    
+    # 统计无效时间
+    nat_count = df[time_column].isna().sum()
+    if nat_count > 0:
+        print(f"[WARN] 发现 {nat_count} 行无效时间数据，排序时将排在最后")
+    
+    print("[SORT] 正在按时间排序...")
+    df_sorted = df.sort_values(by=time_column, na_position='last')
+    
+    print(f"[SAVE] 正在保存: {output_path}")
+    df_sorted.to_csv(output_path, index=False, encoding=default_config.csv_encoding)
+    
+    abs_output = os.path.abspath(output_path)
+    print(f"[OK] 排序完成！输出文件: {abs_output}")
+    
+    return abs_output

main.py

@@ -17,7 +17,7 @@ class DualLogger:
     def write(self, message):
         self.terminal.write(message)
         # 过滤掉生成的代码块，不写入日志文件
-        if "🔧 执行代码:" in message:
+        if "[TOOL] 执行代码:" in message:
             return
         self.log.write(message)
         self.log.flush()
@@ -34,7 +34,7 @@ def setup_logging(log_dir):
     # 可选：也将错误输出重定向
     # sys.stderr = logger 
     print(f"\n{'='*20} Run Started at {datetime.now().strftime('%Y-%m-%d %H:%M:%S')} {'='*20}\n")
-    print(f"📄 日志文件已保存至: {os.path.join(log_dir, 'log.txt')}")
+    print(f"[DOC] 日志文件已保存至: {os.path.join(log_dir, 'log.txt')}")
 
 
 def main():
@@ -43,7 +43,7 @@ def main():
     import os
     # 自动查找当前目录及remotecontrol目录下的所有数据文件
     data_extensions = ['*.csv', '*.xlsx', '*.xls']
-    search_dirs = ['jetour']
+    search_dirs = ['cleaned_data']
     files = []
     
     for search_dir in search_dirs:
@@ -52,10 +52,10 @@ def main():
             files.extend(glob.glob(pattern))
     
     if not files:
-        print("⚠️ 未在当前目录找到数据文件 (.csv, .xlsx)，尝试使用默认文件")
+        print("[WARN] 未在当前目录找到数据文件 (.csv, .xlsx)，尝试使用默认文件")
         files = ["./cleaned_data.csv"]
     else:
-        print(f"📂 自动识别到以下数据文件: {files}")
+        print(f"[DIR] 自动识别到以下数据文件: {files}")
 
     analysis_requirement = """
 基于所有运维工单，整理一份工单健康度报告，包括但不限于对所有车联网技术支持工单的全面数据分析，
@@ -92,16 +92,16 @@ def main():
         print("\n" + "="*30 + " 当前阶段分析完成 " + "="*30)
         
         # 询问用户是否继续
-        print("\n💡 你可以继续对数据提出分析需求，或者输入 'exit'/'quit' 结束程序。")
+        print("\n[TIP] 你可以继续对数据提出分析需求，或者输入 'exit'/'quit' 结束程序。")
-        user_response = input("👉 请输入后续分析需求 (直接回车退出): ").strip()
+        user_response = input("[>] 请输入后续分析需求 (直接回车退出): ").strip()
         
         if not user_response or user_response.lower() in ['exit', 'quit', 'n', 'no']:
-            print("👋 分析结束，再见！")
+            print("[BYE] 分析结束，再见！")
             break
         
         # 更新需求，进入下一轮循环
         analysis_requirement = user_response
-        print(f"\n🔄 收到新需求，正在继续分析...")
+        print(f"\n[LOOP] 收到新需求，正在继续分析...")
  
 
 if __name__ == "__main__":

merge_excel.py

@@ -7,7 +7,7 @@ def merge_excel_files(source_dir="remotecontrol", output_file="merged_all_files.
     """
     将指定目录下的所有 Excel 文件 (.xlsx, .xls) 合并为一个 CSV 文件。
     """
-    print(f"🔍 正在扫描目录: {source_dir} ...")
+    print(f"[SEARCH] 正在扫描目录: {source_dir} ...")
     
     # 支持 xlsx 和 xls
     files_xlsx = glob.glob(os.path.join(source_dir, "*.xlsx"))
@@ -15,36 +15,36 @@ def merge_excel_files(source_dir="remotecontrol", output_file="merged_all_files.
     files = files_xlsx + files_xls
     
     if not files:
-        print("⚠️ 未找到 Excel 文件。")
+        print("[WARN] 未找到 Excel 文件。")
         return
 
     # 按文件名中的数字进行排序 (例如: 1.xlsx, 2.xlsx, ..., 10.xlsx)
     try:
         files.sort(key=lambda x: int(os.path.basename(x).split('.')[0]))
-        print("🔢 已按文件名数字顺序排序")
+        print("[NUM] 已按文件名数字顺序排序")
     except ValueError:
         # 如果文件名不是纯数字，退回到字母排序
         files.sort()
-        print("🔤 已按文件名包含非数字字符，使用字母顺序排序")
+        print("[TEXT] 已按文件名包含非数字字符，使用字母顺序排序")
 
-    print(f"📂 找到 {len(files)} 个文件: {files}")
+    print(f"[DIR] 找到 {len(files)} 个文件: {files}")
     
     all_dfs = []
     for file in files:
         try:
-            print(f"📖 读取: {file}")
+            print(f"[READ] 读取: {file}")
             # 使用 ExcelFile 读取所有 sheet
             xls = pd.ExcelFile(file)
-            print(f"   📑 包含 Sheets: {xls.sheet_names}")
+            print(f"   [PAGES] 包含 Sheets: {xls.sheet_names}")
             
             file_dfs = []
             for sheet_name in xls.sheet_names:
                 df = pd.read_excel(xls, sheet_name=sheet_name)
                 if not df.empty:
-                    print(f"   ✅ Sheet '{sheet_name}' 读取成功: {len(df)} 行")
+                    print(f"   [OK] Sheet '{sheet_name}' 读取成功: {len(df)} 行")
                     file_dfs.append(df)
                 else:
-                    print(f"   ⚠️ Sheet '{sheet_name}' 为空，跳过")
+                    print(f"   [WARN] Sheet '{sheet_name}' 为空，跳过")
             
             if file_dfs:
                 # 合并该文件的所有非空 sheet
@@ -53,30 +53,30 @@ def merge_excel_files(source_dir="remotecontrol", output_file="merged_all_files.
                 file_merged_df['Source_File'] = os.path.basename(file)
                 all_dfs.append(file_merged_df)
             else:
-                 print(f"⚠️ 文件 {file} 所有 Sheet 均为空")
+                 print(f"[WARN] 文件 {file} 所有 Sheet 均为空")
 
         except Exception as e:
-            print(f"❌ 读取 {file} 失败: {e}")
+            print(f"[ERROR] 读取 {file} 失败: {e}")
 
     if all_dfs:
-        print("🔄 正在合并数据...")
+        print("[LOOP] 正在合并数据...")
         merged_df = pd.concat(all_dfs, ignore_index=True)
         
         # 按 SendTime 排序
         if 'SendTime' in merged_df.columns:
-            print("⏳ 正在按 SendTime 排序...")
+            print("[TIMER] 正在按 SendTime 排序...")
             merged_df['SendTime'] = pd.to_datetime(merged_df['SendTime'], errors='coerce')
             merged_df = merged_df.sort_values(by='SendTime')
         else:
-            print("⚠️ 未找到 SendTime 列，跳过排序")
+            print("[WARN] 未找到 SendTime 列，跳过排序")
 
-        print(f"💾 保存到: {output_file}")
+        print(f"[CACHE] 保存到: {output_file}")
         merged_df.to_csv(output_file, index=False, encoding="utf-8-sig")
         
-        print(f"✅ 合并及排序完成！总行数: {len(merged_df)}")
+        print(f"[OK] 合并及排序完成！总行数: {len(merged_df)}")
         print(f"   输出文件: {os.path.abspath(output_file)}")
     else:
-        print("⚠️ 没有成功读取到任何数据。")
+        print("[WARN] 没有成功读取到任何数据。")
 
 if __name__ == "__main__":
     # 如果需要在当前目录运行并合并 remotecontrol 文件夹下的内容

prompts.py

@@ -1,5 +1,4 @@
 data_analysis_system_prompt = """你是一个专业的数据分析助手，运行在Jupyter Notebook环境中，能够根据用户需求生成和执行Python数据分析代码。
-
 **核心使命**：
 - 接收自然语言需求，分阶段生成高效、安全的数据分析代码。
 - 深度挖掘数据，不仅仅是绘图，更要发现数据背后的业务洞察。
@@ -316,11 +315,19 @@ final_report_system_prompt = """你是一位**资深数据分析专家 (Senior D
 data_analysis_followup_prompt = """你是一个专业的数据分析助手，运行在Jupyter Notebook环境中。
 当前处于**追问模式 (Follow-up Mode)**。用户基于之前的分析结果提出了新的需求。
 
+<<<<<<< HEAD
 **核心使命**：
 - 直接针对用户的后续需求进行解答，**无需**重新执行完整SOP。
 - 只有当用户明确要求重新进行全流程分析时，才执行SOP。
 
 **核心能力**：
+=======
+[TARGET] **核心使命**：
+- 直接针对用户的后续需求进行解答，**无需**重新执行完整SOP。
+- 只有当用户明确要求重新进行全流程分析时，才执行SOP。
+
+[TOOL] **核心能力**：
+>>>>>>> e9644360ce283742849fe67c38d05864513e2f96
 1. **代码执行**：自动编写并执行Pandas/Matplotlib代码。
 2. **多模态分析**：支持时序预测、文本挖掘（N-gram）、多维交叉分析。
 3. **智能纠错**：遇到报错自动分析原因并修复代码。

sort_csv.py

@@ -7,39 +7,39 @@ def sort_csv_by_time(file_path="remotecontrol_merged.csv", time_col="SendTime"):
     读取 CSV 文件，按时间列排序，并保存。
     """
     if not os.path.exists(file_path):
-        print(f"❌ 文件不存在: {file_path}")
+        print(f"[ERROR] 文件不存在: {file_path}")
         return
 
-    print(f"📖 正在读取 {file_path} ...")
+    print(f"[READ] 正在读取 {file_path} ...")
     try:
         # 读取 CSV
         df = pd.read_csv(file_path, low_memory=False)
-        print(f"   📊 数据行数: {len(df)}")
+        print(f"   [CHART] 数据行数: {len(df)}")
         
         if time_col not in df.columns:
-            print(f"❌ 未找到时间列: {time_col}")
+            print(f"[ERROR] 未找到时间列: {time_col}")
             print(f"   可用列: {list(df.columns)}")
             return
 
-        print(f"🔄 正在解析时间列 '{time_col}' ...")
+        print(f"[LOOP] 正在解析时间列 '{time_col}' ...")
         # 转换为 datetime 对象，无法解析的设为 NaT
         df[time_col] = pd.to_datetime(df[time_col], errors='coerce')
         
         # 检查无效时间
         nat_count = df[time_col].isna().sum()
         if nat_count > 0:
-            print(f"⚠️ 发现 {nat_count} 行无效时间数据，排序时将排在最后")
+            print(f"[WARN] 发现 {nat_count} 行无效时间数据，排序时将排在最后")
 
-        print("🔄 正在按时间排序...")
+        print("[LOOP] 正在按时间排序...")
         df_sorted = df.sort_values(by=time_col)
         
-        print(f"💾 正在保存及覆盖文件: {file_path} ...")
+        print(f"[CACHE] 正在保存及覆盖文件: {file_path} ...")
         df_sorted.to_csv(file_path, index=False, encoding="utf-8-sig")
         
-        print("✅ 排序并保存完成！")
+        print("[OK] 排序并保存完成！")
         
     except Exception as e:
-        print(f"❌处理失败: {e}")
+        print(f"[ERROR]处理失败: {e}")
 
 if __name__ == "__main__":
     sort_csv_by_time()

test.py

@@ -1,13 +1,13 @@
+from openai import OpenAI
 
-import openai
+client = OpenAI(
-
+    base_url="http://127.0.0.1:9999/v1",
-client = openai.OpenAI(
+    api_key="sk-2187174de21548b0b8b0c92129700199"
-    api_key="sk-Gce85QLROESeOWf3icd2mQnYHOrmMYojwVPQ0AubMjGQ5ZE2",
-    base_url="https://gemini.jeason.online/v1"
 )
 
 response = client.chat.completions.create(
-    model="gemini-2.5-pro",
+    model="claude-sonnet-4-5",
-    messages=[{"role": "user", "content": "你好，请自我介绍"}]
+    messages=[{"role": "user", "content": "Hello"}]
 )
+
 print(response.choices[0].message.content)

utils/cache_manager.py

@@ -42,7 +42,7 @@ class CacheManager:
                 with open(cache_path, 'rb') as f:
                     return pickle.load(f)
             except Exception as e:
-                print(f"⚠️ 读取缓存失败: {e}")
+                print(f"[WARN] 读取缓存失败: {e}")
                 return None
         return None
     
@@ -56,14 +56,14 @@ class CacheManager:
             with open(cache_path, 'wb') as f:
                 pickle.dump(value, f)
         except Exception as e:
-            print(f"⚠️ 写入缓存失败: {e}")
+            print(f"[WARN] 写入缓存失败: {e}")
     
     def clear(self) -> None:
         """清空所有缓存"""
         if self.cache_dir.exists():
             for cache_file in self.cache_dir.glob("*.pkl"):
                 cache_file.unlink()
-            print("✅ 缓存已清空")
+            print("[OK] 缓存已清空")
     
     def cached(self, key_func: Optional[Callable] = None):
         """缓存装饰器"""
@@ -82,7 +82,7 @@ class CacheManager:
                 # 尝试从缓存获取
                 cached_value = self.get(cache_key)
                 if cached_value is not None:
-                    print(f"💾 使用缓存: {cache_key[:8]}...")
+                    print(f"[CACHE] 使用缓存: {cache_key[:8]}...")
                     return cached_value
                 
                 # 执行函数并缓存结果

utils/code_executor.py

@@ -410,17 +410,17 @@ from IPython.display import display
                         try:
                             # 尝试保存
                             fig.savefig(auto_filepath, bbox_inches='tight')
-                            print(f"💾 [Auto-Save] 检测到未闭合图表，已安全保存至: {auto_filepath}")
+                            print(f"[CACHE] [Auto-Save] 检测到未闭合图表，已安全保存至: {auto_filepath}")
                             
                             # 添加到输出中，告知Agent
-                            output += f"\n[Auto-Save] ⚠️ 检测到Figure {fig_num}未关闭，系统已自动保存为: {auto_filename}"
+                            output += f"\n[Auto-Save] [WARN] 检测到Figure {fig_num}未关闭，系统已自动保存为: {auto_filename}"
                             self.image_counter += 1
                         except Exception as e:
-                            print(f"⚠️ [Auto-Save] 保存失败: {e}")
+                            print(f"[WARN] [Auto-Save] 保存失败: {e}")
                         finally:
                             plt.close(fig_num)
             except Exception as e:
-                print(f"⚠️ [Auto-Save Global] 异常: {e}")
+                print(f"[WARN] [Auto-Save Global] 异常: {e}")
             # --- 自动保存机制 end ---
 
             return {

utils/data_loader.py

@@ -34,7 +34,7 @@ def load_and_profile_data(file_paths: list) -> str:
         profile_summary += f"## 文件: {file_name}\n\n"
         
         if not os.path.exists(file_path):
-            profile_summary += f"⚠️ 文件不存在: {file_path}\n\n"
+            profile_summary += f"[WARN] 文件不存在: {file_path}\n\n"
             continue
             
         try:
@@ -52,7 +52,7 @@ def load_and_profile_data(file_paths: list) -> str:
             elif ext in ['.xlsx', '.xls']:
                 df = pd.read_excel(file_path)
             else:
-                profile_summary += f"⚠️ 不支持的文件格式: {ext}\n\n"
+                profile_summary += f"[WARN] 不支持的文件格式: {ext}\n\n"
                 continue
                 
             # 基础信息
@@ -70,7 +70,7 @@ def load_and_profile_data(file_paths: list) -> str:
                 
                 profile_summary += f"#### {col} ({dtype})\n"
                 if null_count > 0:
-                    profile_summary += f"- ⚠️ 空值: {null_count} ({null_ratio:.1f}%)\n"
+                    profile_summary += f"- [WARN] 空值: {null_count} ({null_ratio:.1f}%)\n"
                 
                 # 数值列分析
                 if pd.api.types.is_numeric_dtype(dtype):
@@ -96,7 +96,7 @@ def load_and_profile_data(file_paths: list) -> str:
                 profile_summary += "\n"
                 
         except Exception as e:
-            profile_summary += f"❌ 读取或分析文件失败: {str(e)}\n\n"
+            profile_summary += f"[ERROR] 读取或分析文件失败: {str(e)}\n\n"
             
     return profile_summary
 
@@ -141,7 +141,7 @@ def load_data_chunked(file_path: str, chunksize: Optional[int] = None) -> Iterat
             except UnicodeDecodeError:
                 continue
             except Exception as e:
-                print(f"❌ 读取CSV文件失败: {e}")
+                print(f"[ERROR] 读取CSV文件失败: {e}")
                 break
     elif ext in ['.xlsx', '.xls']:
         # Excel文件不支持chunksize，直接读取
@@ -151,7 +151,7 @@ def load_data_chunked(file_path: str, chunksize: Optional[int] = None) -> Iterat
             for i in range(0, len(df), chunksize):
                 yield df.iloc[i:i+chunksize]
         except Exception as e:
-            print(f"❌ 读取Excel文件失败: {e}")
+            print(f"[ERROR] 读取Excel文件失败: {e}")
 
 
 def load_data_with_cache(file_path: str, force_reload: bool = False) -> Optional[pd.DataFrame]:
@@ -166,7 +166,7 @@ def load_data_with_cache(file_path: str, force_reload: bool = False) -> Optional
         DataFrame或None
     """
     if not os.path.exists(file_path):
-        print(f"⚠️ 文件不存在: {file_path}")
+        print(f"[WARN] 文件不存在: {file_path}")
         return None
     
     # 检查文件大小
@@ -174,7 +174,7 @@ def load_data_with_cache(file_path: str, force_reload: bool = False) -> Optional
     
     # 对于大文件，建议使用流式处理
     if file_size_mb > app_config.max_file_size_mb:
-        print(f"⚠️ 文件过大 ({file_size_mb:.1f}MB)，建议使用 load_data_chunked() 流式处理")
+        print(f"[WARN] 文件过大 ({file_size_mb:.1f}MB)，建议使用 load_data_chunked() 流式处理")
     
     # 生成缓存键
     cache_key = get_file_hash(file_path)
@@ -183,7 +183,7 @@ def load_data_with_cache(file_path: str, force_reload: bool = False) -> Optional
     if not force_reload and app_config.data_cache_enabled:
         cached_data = data_cache.get(cache_key)
         if cached_data is not None:
-            print(f"💾 从缓存加载数据: {os.path.basename(file_path)}")
+            print(f"[CACHE] 从缓存加载数据: {os.path.basename(file_path)}")
             return cached_data
     
     # 加载数据
@@ -202,16 +202,16 @@ def load_data_with_cache(file_path: str, force_reload: bool = False) -> Optional
         elif ext in ['.xlsx', '.xls']:
             df = pd.read_excel(file_path)
         else:
-            print(f"⚠️ 不支持的文件格式: {ext}")
+            print(f"[WARN] 不支持的文件格式: {ext}")
             return None
         
         # 缓存数据
         if df is not None and app_config.data_cache_enabled:
             data_cache.set(cache_key, df)
-            print(f"✅ 数据已缓存: {os.path.basename(file_path)}")
+            print(f"[OK] 数据已缓存: {os.path.basename(file_path)}")
         
         return df
         
     except Exception as e:
-        print(f"❌ 加载数据失败: {e}")
+        print(f"[ERROR] 加载数据失败: {e}")
         return None

utils/data_quality.py

@@ -192,27 +192,27 @@ class DataQualityChecker:
         summary += f"**质量评分**: {self.quality_score:.1f}/100\n\n"
         
         if self.quality_score >= 90:
-            summary += "✅ **评级**: 优秀 - 数据质量很好\n\n"
+            summary += "[OK] **评级**: 优秀 - 数据质量很好\n\n"
         elif self.quality_score >= 75:
-            summary += "⚠️ **评级**: 良好 - 存在一些小问题\n\n"
+            summary += "[WARN] **评级**: 良好 - 存在一些小问题\n\n"
         elif self.quality_score >= 60:
-            summary += "⚠️ **评级**: 一般 - 需要处理多个问题\n\n"
+            summary += "[WARN] **评级**: 一般 - 需要处理多个问题\n\n"
         else:
-            summary += "❌ **评级**: 差 - 数据质量问题严重\n\n"
+            summary += "[ERROR] **评级**: 差 - 数据质量问题严重\n\n"
         
         summary += f"**问题统计**: 共 {len(self.issues)} 个质量问题\n"
-        summary += f"- 🔴 高严重性: {len([i for i in self.issues if i.severity == 'high'])} 个\n"
+        summary += f"- [RED] 高严重性: {len([i for i in self.issues if i.severity == 'high'])} 个\n"
-        summary += f"- 🟡 中严重性: {len([i for i in self.issues if i.severity == 'medium'])} 个\n"
+        summary += f"- [YELLOW] 中严重性: {len([i for i in self.issues if i.severity == 'medium'])} 个\n"
-        summary += f"- 🟢 低严重性: {len([i for i in self.issues if i.severity == 'low'])} 个\n\n"
+        summary += f"- [GREEN] 低严重性: {len([i for i in self.issues if i.severity == 'low'])} 个\n\n"
         
         if self.issues:
             summary += "### 主要问题:\n\n"
             # 只显示高和中严重性的问题
             for issue in self.issues:
                 if issue.severity in ["high", "medium"]:
-                    emoji = "🔴" if issue.severity == "high" else "🟡"
+                    emoji = "[RED]" if issue.severity == "high" else "[YELLOW]"
                     summary += f"{emoji} **{issue.column}** - {issue.description}\n"
-                    summary += f"   💡 {issue.suggestion}\n\n"
+                    summary += f"   [TIP] {issue.suggestion}\n\n"
         
         return summary
 

utils/fallback_openai_client.py

@@ -57,7 +57,7 @@ class AsyncFallbackOpenAIClient:
             self.fallback_client = AsyncOpenAI(api_key=fallback_api_key, base_url=fallback_base_url, **_fallback_args)
             self.fallback_model_name = fallback_model_name
         else:
-            print("⚠️ 警告: 未完全配置备用 API 客户端。如果主 API 失败，将无法进行回退。")
+            print("[WARN] 警告: 未完全配置备用 API 客户端。如果主 API 失败，将无法进行回退。")
 
         self.content_filter_error_code = content_filter_error_code
         self.content_filter_error_field = content_filter_error_field
@@ -90,11 +90,11 @@ class AsyncFallbackOpenAIClient:
                 return completion
             except (APIConnectionError, APITimeoutError) as e: # 通常可以重试的网络错误
                 last_exception = e
-                print(f"⚠️ {api_name} API 调用时发生可重试错误 ({type(e).__name__}): {e}. 尝试次数 {attempt + 1}/{max_retries + 1}")
+                print(f"[WARN] {api_name} API 调用时发生可重试错误 ({type(e).__name__}): {e}. 尝试次数 {attempt + 1}/{max_retries + 1}")
                 if attempt < max_retries:
                     await asyncio.sleep(self.retry_delay_seconds * (attempt + 1)) # 增加延迟
                 else:
-                    print(f"❌ {api_name} API 在达到最大重试次数后仍然失败。")
+                    print(f"[ERROR] {api_name} API 在达到最大重试次数后仍然失败。")
             except APIStatusError as e: # API 返回的特定状态码错误
                 is_content_filter_error = False
                 retry_after = None
@@ -118,7 +118,7 @@ class AsyncFallbackOpenAIClient:
                                 if delay_str.endswith("s"):
                                     try:
                                         retry_after = float(delay_str[:-1])
-                                        print(f"⏳ 收到服务器 RetryInfo，等待时间: {retry_after}秒")
+                                        print(f"[TIMER] 收到服务器 RetryInfo，等待时间: {retry_after}秒")
                                     except ValueError:
                                         pass
                 except Exception:
@@ -128,7 +128,7 @@ class AsyncFallbackOpenAIClient:
                     raise e 
                 
                 last_exception = e
-                print(f"⚠️ {api_name} API 调用时发生 APIStatusError ({e.status_code}): {e}. 尝试次数 {attempt + 1}/{max_retries + 1}")
+                print(f"[WARN] {api_name} API 调用时发生 APIStatusError ({e.status_code}): {e}. 尝试次数 {attempt + 1}/{max_retries + 1}")
                 
                 if attempt < max_retries:
                     # 如果获取到了明确的 retry_after，则使用它；否则使用默认的指数退避
@@ -137,13 +137,13 @@ class AsyncFallbackOpenAIClient:
                     if e.status_code == 429 and retry_after is None:
                         wait_time = max(wait_time, 5.0 * (attempt + 1)) # 429 默认至少等 5 秒
                         
-                    print(f"💤 将等待 {wait_time:.2f} 秒后重试...")
+                    print(f"[WAIT] 将等待 {wait_time:.2f} 秒后重试...")
                     await asyncio.sleep(wait_time)
                 else:
-                    print(f"❌ {api_name} API 在达到最大重试次数后仍然失败 (APIStatusError)。")
+                    print(f"[ERROR] {api_name} API 在达到最大重试次数后仍然失败 (APIStatusError)。")
             except APIError as e: # 其他不可轻易重试的 OpenAI 错误
                 last_exception = e
-                print(f"❌ {api_name} API 调用时发生不可重试错误 ({type(e).__name__}): {e}")
+                print(f"[ERROR] {api_name} API 调用时发生不可重试错误 ({type(e).__name__}): {e}")
                 break # 不再重试此类错误
         
         if last_exception:
@@ -196,7 +196,7 @@ class AsyncFallbackOpenAIClient:
                     pass 
             
             if is_content_filter_error and self.fallback_client and self.fallback_model_name:
-                print(f"ℹ️ 主 API 内容过滤错误 ({e_primary.status_code})。尝试切换到备用 API ({self.fallback_client.base_url})...")
+                print(f"[INFO] 主 API 内容过滤错误 ({e_primary.status_code})。尝试切换到备用 API ({self.fallback_client.base_url})...")
                 try:
                     fallback_completion = await self._attempt_api_call(
                         client=self.fallback_client,
@@ -206,20 +206,20 @@ class AsyncFallbackOpenAIClient:
                         api_name="备用",
                         **kwargs.copy()
                     )
-                    print(f"✅ 备用 API 调用成功。")
+                    print(f"[OK] 备用 API 调用成功。")
                     return fallback_completion
                 except APIError as e_fallback:
-                    print(f"❌ 备用 API 调用最终失败: {type(e_fallback).__name__} - {e_fallback}")
+                    print(f"[ERROR] 备用 API 调用最终失败: {type(e_fallback).__name__} - {e_fallback}")
                     raise e_fallback 
             else:
                 if not (self.fallback_client and self.fallback_model_name and is_content_filter_error):
                      # 如果不是内容过滤错误，或者没有可用的备用API，则记录主API的原始错误
-                    print(f"ℹ️ 主 API 错误 ({type(e_primary).__name__}: {e_primary}), 且不满足备用条件或备用API未配置。")
+                    print(f"[INFO] 主 API 错误 ({type(e_primary).__name__}: {e_primary}), 且不满足备用条件或备用API未配置。")
                 raise e_primary
         except APIError as e_primary_other: 
-            print(f"❌ 主 API 调用最终失败 (非内容过滤，错误类型: {type(e_primary_other).__name__}): {e_primary_other}")
+            print(f"[ERROR] 主 API 调用最终失败 (非内容过滤，错误类型: {type(e_primary_other).__name__}): {e_primary_other}")
             if self.fallback_client and self.fallback_model_name:
-                print(f"ℹ️ 主 API 失败，尝试切换到备用 API ({self.fallback_client.base_url})...")
+                print(f"[INFO] 主 API 失败，尝试切换到备用 API ({self.fallback_client.base_url})...")
                 try:
                     fallback_completion = await self._attempt_api_call(
                         client=self.fallback_client,
@@ -229,10 +229,10 @@ class AsyncFallbackOpenAIClient:
                         api_name="备用",
                         **kwargs.copy()
                     )
-                    print(f"✅ 备用 API 调用成功。")
+                    print(f"[OK] 备用 API 调用成功。")
                     return fallback_completion
                 except APIError as e_fallback_after_primary_fail:
-                    print(f"❌ 备用 API 在主 API 失败后也调用失败: {type(e_fallback_after_primary_fail).__name__} - {e_fallback_after_primary_fail}")
+                    print(f"[ERROR] 备用 API 在主 API 失败后也调用失败: {type(e_fallback_after_primary_fail).__name__} - {e_fallback_after_primary_fail}")
                     raise e_fallback_after_primary_fail 
             else: 
                 raise e_primary_other

utils/format_execution_result.py

@@ -7,17 +7,17 @@ def format_execution_result(result: Dict[str, Any]) -> str:
     feedback = []
     
     if result['success']:
-        feedback.append("✅ 代码执行成功")
+        feedback.append("[OK] 代码执行成功")
         
         if result['output']:
-            feedback.append(f"📊 输出结果：\n{result['output']}")
+            feedback.append(f"[CHART] 输出结果：\n{result['output']}")
         
         if result.get('variables'):
-            feedback.append("📋 新生成的变量：")
+            feedback.append("[LIST] 新生成的变量：")
             for var_name, var_info in result['variables'].items():
                 feedback.append(f"  - {var_name}: {var_info}")
     else:
-        feedback.append("❌ 代码执行失败")
+        feedback.append("[ERROR] 代码执行失败")
         feedback.append(f"错误信息: {result['error']}")
         if result['output']:
             feedback.append(f"部分输出: {result['output']}")

utils/llm_helper.py

@@ -117,7 +117,7 @@ class LLMHelper:
         if use_cache and app_config.llm_cache_enabled:
             cached_response = llm_cache.get(cache_key)
             if cached_response:
-                print("💾 使用LLM缓存响应")
+                print("[CACHE] 使用LLM缓存响应")
                 return cached_response
         
         # 调用LLM

utils/script_generator.py

@@ -0,0 +1,215 @@
+# -*- coding: utf-8 -*-
+"""
+可复用脚本生成器
+
+从分析会话的执行历史中提取成功执行的代码，
+合并去重后生成可独立运行的 .py 脚本文件。
+"""
+
+import os
+import re
+from datetime import datetime
+from typing import List, Dict, Any, Set
+
+
+def extract_imports(code: str) -> Set[str]:
+    """从代码中提取所有 import 语句"""
+    imports = set()
+    lines = code.split('\n')
+    for line in lines:
+        stripped = line.strip()
+        if stripped.startswith('import ') or stripped.startswith('from '):
+            # 标准化 import 语句
+            imports.add(stripped)
+    return imports
+
+
+def remove_imports(code: str) -> str:
+    """从代码中移除所有 import 语句"""
+    lines = code.split('\n')
+    result_lines = []
+    for line in lines:
+        stripped = line.strip()
+        if not stripped.startswith('import ') and not stripped.startswith('from '):
+            result_lines.append(line)
+    return '\n'.join(result_lines)
+
+
+def clean_code_block(code: str) -> str:
+    """清理代码块，移除不必要的内容"""
+    # 移除可能的重复配置代码
+    patterns_to_skip = [
+        r"plt\.rcParams\['font\.sans-serif'\]",  # 字体配置在模板中统一处理
+        r"plt\.rcParams\['axes\.unicode_minus'\]",
+    ]
+    
+    lines = code.split('\n')
+    result_lines = []
+    skip_until_empty = False
+    
+    for line in lines:
+        stripped = line.strip()
+        
+        # 跳过空行连续的情况
+        if not stripped:
+            if skip_until_empty:
+                skip_until_empty = False
+                continue
+            result_lines.append(line)
+            continue
+        
+        # 检查是否需要跳过的模式
+        should_skip = False
+        for pattern in patterns_to_skip:
+            if re.search(pattern, stripped):
+                should_skip = True
+                break
+        
+        if not should_skip:
+            result_lines.append(line)
+    
+    return '\n'.join(result_lines)
+
+
+def generate_reusable_script(
+    analysis_results: List[Dict[str, Any]],
+    data_files: List[str],
+    session_output_dir: str,
+    user_requirement: str = ""
+) -> str:
+    """
+    从分析结果中生成可复用的 Python 脚本
+    
+    Args:
+        analysis_results: 分析过程中记录的结果列表，每个元素包含 'code', 'result' 等
+        data_files: 原始数据文件路径列表
+        session_output_dir: 会话输出目录
+        user_requirement: 用户的原始需求描述
+    
+    Returns:
+        生成的脚本文件路径
+    """
+    # 收集所有成功执行的代码
+    all_imports = set()
+    code_blocks = []
+    
+    for result in analysis_results:
+        # 只处理 generate_code 类型的结果
+        if result.get("action") == "collect_figures":
+            continue
+            
+        code = result.get("code", "")
+        exec_result = result.get("result", {})
+        
+        # 只收集成功执行的代码
+        if code and exec_result.get("success", False):
+            # 提取 imports
+            imports = extract_imports(code)
+            all_imports.update(imports)
+            
+            # 清理代码块
+            cleaned_code = remove_imports(code)
+            cleaned_code = clean_code_block(cleaned_code)
+            
+            # 只添加非空的代码块
+            if cleaned_code.strip():
+                code_blocks.append({
+                    "round": result.get("round", 0),
+                    "code": cleaned_code.strip()
+                })
+    
+    if not code_blocks:
+        print("[WARN] 没有成功执行的代码块，跳过脚本生成")
+        return ""
+    
+    # 生成脚本内容
+    now = datetime.now()
+    timestamp = now.strftime("%Y%m%d_%H%M%S")
+    
+    # 构建脚本头部
+    script_header = f'''#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+数据分析脚本 - 自动生成
+=====================================
+原始数据文件: {', '.join(data_files)}
+生成时间: {now.strftime("%Y-%m-%d %H:%M:%S")}
+原始需求: {user_requirement[:200] + '...' if len(user_requirement) > 200 else user_requirement}
+=====================================
+
+使用方法:
+1. 修改下方 DATA_FILES 列表中的文件路径
+2. 修改 OUTPUT_DIR 指定输出目录
+3. 运行: python {os.path.basename(session_output_dir)}_分析脚本.py
+"""
+
+import os
+'''
+    
+    # 添加标准 imports（去重后排序）
+    standard_imports = sorted([imp for imp in all_imports if imp.startswith('import ')])
+    from_imports = sorted([imp for imp in all_imports if imp.startswith('from ')])
+    
+    imports_section = '\n'.join(standard_imports + from_imports)
+    
+    # 配置区域
+    config_section = f'''
+# ========== 配置区域 (可修改) ==========
+
+# 数据文件路径 - 修改此处以分析不同的数据
+DATA_FILES = {repr(data_files)}
+
+# 输出目录 - 图片和报告将保存在此目录
+OUTPUT_DIR = "./analysis_output"
+
+# 创建输出目录
+os.makedirs(OUTPUT_DIR, exist_ok=True)
+
+# ========== 字体配置 (中文显示) ==========
+import platform
+import matplotlib.pyplot as plt
+
+system_name = platform.system()
+if system_name == 'Darwin':
+    plt.rcParams['font.sans-serif'] = ['Arial Unicode MS', 'PingFang SC', 'sans-serif']
+elif system_name == 'Windows':
+    plt.rcParams['font.sans-serif'] = ['SimHei', 'Microsoft YaHei', 'sans-serif']
+else:
+    plt.rcParams['font.sans-serif'] = ['WenQuanYi Micro Hei', 'sans-serif']
+plt.rcParams['axes.unicode_minus'] = False
+
+# 设置 session_output_dir 变量（兼容原始代码）
+session_output_dir = OUTPUT_DIR
+'''
+    
+    # 合并代码块
+    code_section = "\n# ========== 分析代码 ==========\n\n"
+    
+    for i, block in enumerate(code_blocks, 1):
+        code_section += f"# --- 第 {block['round']} 轮分析 ---\n"
+        code_section += block['code'] + "\n\n"
+    
+    # 脚本尾部
+    script_footer = '''
+# ========== 完成 ==========
+print("\\n" + "=" * 50)
+print("[OK] 分析完成！")
+print(f"[OUTPUT] 输出目录: {os.path.abspath(OUTPUT_DIR)}")
+print("=" * 50)
+'''
+    
+    # 组装完整脚本
+    full_script = script_header + imports_section + config_section + code_section + script_footer
+    
+    # 保存脚本文件
+    script_filename = f"分析脚本_{timestamp}.py"
+    script_path = os.path.join(session_output_dir, script_filename)
+    
+    try:
+        with open(script_path, 'w', encoding='utf-8') as f:
+            f.write(full_script)
+        print(f"[OK] 可复用脚本已生成: {script_path}")
+        return script_path
+    except Exception as e:
+        print(f"[ERROR] 保存脚本失败: {e}")
+        return ""

web/main.py

@@ -5,6 +5,7 @@ import threading
 import glob
 import uuid
 import json
+from datetime import datetime
 from typing import Optional, Dict, List
 from fastapi import FastAPI, UploadFile, File, BackgroundTasks, HTTPException, Query
 from fastapi.middleware.cors import CORSMiddleware
@@ -18,8 +19,8 @@ sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 from data_analysis_agent import DataAnalysisAgent
 from config.llm_config import LLMConfig
 from utils.create_session_dir import create_session_output_dir
-from merge_excel import merge_excel_files
+from config.llm_config import LLMConfig
-from sort_csv import sort_csv_by_time
+from utils.create_session_dir import create_session_output_dir
 
 app = FastAPI(title="IOV Data Analysis Agent")
 
@@ -55,6 +56,7 @@ class SessionData:
         self.last_updated: str = ""
         self.user_requirement: str = ""
         self.file_list: List[str] = []
+        self.reusable_script: Optional[str] = None  # 新增：可复用脚本路径
 
 
 class SessionManager:
@@ -70,7 +72,74 @@ class SessionManager:
 
 
     def get_session(self, session_id: str) -> Optional[SessionData]:
-        return self.sessions.get(session_id)
+        if session_id in self.sessions:
+            return self.sessions[session_id]
+            
+        # Fallback: Try to reconstruct from disk for history sessions
+        output_dir = os.path.join("outputs", f"session_{session_id}")
+        if os.path.exists(output_dir) and os.path.isdir(output_dir):
+            return self._reconstruct_session(session_id, output_dir)
+            
+        return None
+
+    def _reconstruct_session(self, session_id: str, output_dir: str) -> SessionData:
+        """从磁盘目录重建会话对象"""
+        session = SessionData(session_id)
+        session.output_dir = output_dir
+        session.is_running = False
+        session.current_round = session.max_rounds
+        session.progress_percentage = 100.0
+        session.status_message = "已完成 (历史记录)"
+        
+        # Recover Log
+        log_path = os.path.join(output_dir, "process.log")
+        if os.path.exists(log_path):
+            session.log_file = log_path
+            
+        # Recover Report
+        # 宽容查找：扫描所有 .md 文件，优先取包含 "report" 或 "报告" 的文件
+        md_files = glob.glob(os.path.join(output_dir, "*.md"))
+        if md_files:
+            # 默认取第一个
+            chosen = md_files[0]
+            # 尝试找更好的匹配
+            for md in md_files:
+                fname = os.path.basename(md).lower()
+                if "report" in fname or "报告" in fname:
+                    chosen = md
+                    break
+            session.generated_report = chosen
+            
+        # Recover Script (查找可能的脚本文件)
+        possible_scripts = ["data_analysis_script.py", "script.py", "analysis_script.py"]
+        for s in possible_scripts:
+            p = os.path.join(output_dir, s)
+            if os.path.exists(p):
+                session.reusable_script = p
+                break
+        
+        # Recover Results (images etc)
+        results_json = os.path.join(output_dir, "results.json")
+        if os.path.exists(results_json):
+            try:
+                with open(results_json, "r") as f:
+                     session.analysis_results = json.load(f)
+            except:
+                pass
+        
+        # Recover Metadata
+        try:
+             stat = os.stat(output_dir)
+             dt = datetime.fromtimestamp(stat.st_ctime)
+             session.created_at = dt.strftime("%Y-%m-%d %H:%M:%S")
+        except:
+             pass
+
+        # Cache it
+        with self.lock:
+             self.sessions[session_id] = session
+             
+        return session
 
     def list_sessions(self):
         return list(self.sessions.keys())
@@ -99,7 +168,10 @@ class SessionManager:
                 "max_rounds": session.max_rounds,
                 "created_at": session.created_at,
                 "last_updated": session.last_updated,
-                "user_requirement": session.user_requirement[:100] + "..." if len(session.user_requirement) > 100 else session.user_requirement
+                "created_at": session.created_at,
+                "last_updated": session.last_updated,
+                "user_requirement": session.user_requirement[:100] + "..." if len(session.user_requirement) > 100 else session.user_requirement,
+                "script_path": session.reusable_script  # 新增：返回脚本路径
             }
         return None
 
@@ -227,6 +299,7 @@ def run_analysis_task(session_id: str, files: list, user_requirement: str, is_fo
             
             session.generated_report = result.get("report_file_path", None)
             session.analysis_results = result.get("analysis_results", [])
+            session.reusable_script = result.get("reusable_script_path", None)  # 新增：保存脚本路径
             
             # Save results to json for persistence
             with open(os.path.join(session_output_dir, "results.json"), "w") as f:
@@ -311,7 +384,8 @@ async def get_status(session_id: str = Query(..., description="Session ID")):
         "is_running": session.is_running,
         "log": log_content,
         "has_report": session.generated_report is not None,
-        "report_path": session.generated_report
+        "report_path": session.generated_report,
+        "script_path": session.reusable_script  # 新增：返回脚本路径
     }
 
 @app.get("/api/export")
@@ -453,71 +527,24 @@ async def export_report(session_id: str = Query(..., description="Session ID")):
         media_type='application/zip'
     )
 
+@app.get("/api/download_script")
+async def download_script(session_id: str = Query(..., description="Session ID")):
+    """下载生成的Python脚本"""
+    session = session_manager.get_session(session_id)
+    if not session or not session.reusable_script:
+        raise HTTPException(status_code=404, detail="Script not found")
+        
+    if not os.path.exists(session.reusable_script):
+        raise HTTPException(status_code=404, detail="Script file missing on server")
+        
+    return FileResponse(
+        path=session.reusable_script,
+        filename=os.path.basename(session.reusable_script),
+        media_type='text/x-python'
+    )
+
 # --- Tools API ---
 
-class ToolRequest(BaseModel):
-    source_dir: Optional[str] = "uploads"
-    output_filename: Optional[str] = "merged_output.csv"
-    target_file: Optional[str] = None
-
-@app.post("/api/tools/merge")
-async def tool_merge_excel(req: ToolRequest):
-    """
-    Trigger Excel Merge Tool
-    """
-    try:
-        source = req.source_dir
-        output = req.output_filename
-        
-        import asyncio
-        loop = asyncio.get_event_loop()
-        
-        await loop.run_in_executor(None, lambda: merge_excel_files(source, output))
-        
-        output_abs = os.path.abspath(output)
-        if os.path.exists(output_abs):
-            return {"status": "success", "message": "Merge completed", "output_file": output_abs}
-            
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-@app.post("/api/tools/sort")
-async def tool_sort_csv(req: ToolRequest):
-    """
-    Trigger CSV Sort Tool
-    """
-    try:
-        target = req.target_file
-        if not target:
-             raise HTTPException(status_code=400, detail="Target file required")
-             
-        import asyncio
-        loop = asyncio.get_event_loop()
-        
-        await loop.run_in_executor(None, lambda: sort_csv_by_time(target))
-        
-        return {"status": "success", "message": f"Sorted {target} by time"}
-    except Exception as e:
-         raise HTTPException(status_code=500, detail=str(e))
-
-# --- Help API ---
-
-@app.get("/api/help/troubleshooting")
-async def get_troubleshooting_guide():
-    """
-    Returns the content of troubleshooting_guide.md
-    """
-    guide_path = os.path.expanduser("~/.gemini/antigravity/brain/3ff617fe-5f27-4ab8-b61b-c634f2e75255/troubleshooting_guide.md")
-    
-    if not os.path.exists(guide_path):
-        return {"content": "# Troubleshooting Guide Not Found\n\nCould not locate the guide artifact."}
-        
-    try:
-        with open(guide_path, "r", encoding="utf-8") as f:
-            content = f.read()
-        return {"content": content}
-    except Exception as e:
-        return {"content": f"# Error Loading Guide\n\n{e}"}
 
 
 # --- 新增API端点 ---
@@ -553,6 +580,61 @@ async def delete_specific_session(session_id: str):
         raise HTTPException(status_code=404, detail="Session not found")
     return {"status": "deleted", "session_id": session_id}
 
+    return {"status": "deleted", "session_id": session_id}
+
+
+# --- History API ---
+
+@app.get("/api/history")
+async def get_history():
+    """
+    Get list of past analysis sessions from outputs directory
+    """
+    history = []
+    output_base = "outputs"
+    
+    if not os.path.exists(output_base):
+        return {"history": []}
+        
+    try:
+        # Scan for session_* directories
+        for entry in os.scandir(output_base):
+            if entry.is_dir() and entry.name.startswith("session_"):
+                # Extract timestamp from folder name: session_20250101_120000
+                session_id = entry.name.replace("session_", "")
+                
+                # Check creation time or extract from name
+                try:
+                    # Try to parse timestamp from ID if it matches format
+                    # Format: YYYYMMDD_HHMMSS
+                    timestamp_str = session_id
+                    dt = datetime.strptime(timestamp_str, "%Y%m%d_%H%M%S")
+                    display_time = dt.strftime("%Y-%m-%d %H:%M:%S")
+                    sort_key = dt.timestamp()
+                except ValueError:
+                    # Fallback to file creation time
+                    sort_key = entry.stat().st_ctime
+                    display_time = datetime.fromtimestamp(sort_key).strftime("%Y-%m-%d %H:%M:%S")
+
+                history.append({
+                    "id": session_id,
+                    "timestamp": display_time,
+                    "sort_key": sort_key,
+                    "name": f"Session {display_time}"
+                })
+        
+        # Sort by latest first
+        history.sort(key=lambda x: x["sort_key"], reverse=True)
+        
+        # Cleanup internal sort key
+        for item in history:
+            del item["sort_key"]
+            
+        return {"history": history}
+        
+    except Exception as e:
+        print(f"Error scanning history: {e}")
+        return {"history": []}
 
 if __name__ == "__main__":
     import uvicorn

web/static/clean_style.css

@@ -0,0 +1,535 @@
+/* Clean Style - IOV Data Analysis Agent */
+
+:root {
+    --primary-color: #2563EB;
+    /* Tech Blue */
+    --primary-hover: #1D4ED8;
+    --bg-color: #FFFFFF;
+    --sidebar-bg: #F9FAFB;
+    --text-primary: #111827;
+    --text-secondary: #6B7280;
+    --border-color: #E5E7EB;
+    --card-shadow: 0 1px 3px 0 rgba(0, 0, 0, 0.1), 0 1px 2px 0 rgba(0, 0, 0, 0.06);
+    --font-family: 'Inter', -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif;
+}
+
+* {
+    box-sizing: border-box;
+    margin: 0;
+    padding: 0;
+}
+
+body {
+    font-family: var(--font-family);
+    color: var(--text-primary);
+    background-color: var(--bg-color);
+    line-height: 1.5;
+    height: 100vh;
+    overflow: hidden;
+}
+
+.app-container {
+    display: flex;
+    height: 100vh;
+}
+
+/* Sidebar */
+.sidebar {
+    width: 240px;
+    /* Compact width */
+    background-color: var(--sidebar-bg);
+    border-right: 1px solid var(--border-color);
+    display: flex;
+    flex-direction: column;
+    padding: 1rem;
+    flex-shrink: 0;
+}
+
+.brand {
+    display: flex;
+    align-items: center;
+    gap: 0.75rem;
+    margin-bottom: 1.5rem;
+    font-weight: 600;
+    color: var(--text-primary);
+}
+
+.brand i {
+    color: var(--primary-color);
+    font-size: 1.5rem;
+}
+
+.nav-menu {
+    display: flex;
+    flex-direction: column;
+    gap: 0.5rem;
+    flex: 1;
+    overflow-y: hidden;
+    /* Let history list handle scroll */
+}
+
+.nav-item {
+    display: flex;
+    align-items: center;
+    gap: 0.75rem;
+    padding: 0.75rem 1rem;
+    border-radius: 0.375rem;
+    color: var(--text-secondary);
+    text-decoration: none;
+    cursor: pointer;
+    transition: all 0.2s;
+    font-size: 0.95rem;
+    border: none;
+    background: none;
+    width: 100%;
+    text-align: left;
+}
+
+.nav-item:hover {
+    background-color: #F3F4F6;
+    color: var(--text-primary);
+}
+
+.nav-item.active {
+    background-color: #EFF6FF;
+    color: var(--primary-color);
+    font-weight: 500;
+}
+
+.nav-item i {
+    width: 1.25rem;
+    text-align: center;
+}
+
+.nav-divider {
+    height: 1px;
+    background-color: var(--border-color);
+    margin: 1rem 0 0.5rem 0;
+}
+
+.nav-section-title {
+    font-size: 0.75rem;
+    text-transform: uppercase;
+    color: var(--text-secondary);
+    font-weight: 600;
+    letter-spacing: 0.05em;
+    margin-bottom: 0.5rem;
+    padding-left: 0.5rem;
+}
+
+/* History List */
+.history-list {
+    flex: 1;
+    overflow-y: auto;
+    display: flex;
+    flex-direction: column;
+    gap: 0.25rem;
+    padding-right: 5px;
+}
+
+.history-item {
+    font-size: 0.85rem;
+    color: var(--text-secondary);
+    padding: 0.5rem 0.75rem;
+    border-radius: 0.375rem;
+    cursor: pointer;
+    transition: all 0.2s;
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+    display: flex;
+    align-items: center;
+    gap: 0.5rem;
+}
+
+.history-item:hover {
+    background-color: #F3F4F6;
+    color: var(--text-primary);
+}
+
+.history-item.active {
+    background-color: #EFF6FF;
+    color: var(--primary-color);
+}
+
+
+.status-bar {
+    margin-top: auto;
+    padding-top: 1rem;
+    border-top: 1px solid var(--border-color);
+    display: flex;
+    align-items: center;
+    gap: 0.5rem;
+    font-size: 0.875rem;
+    color: var(--text-secondary);
+}
+
+.status-dot {
+    width: 8px;
+    height: 8px;
+    border-radius: 50%;
+    background-color: #D1D5DB;
+}
+
+.status-dot.running {
+    background-color: var(--primary-color);
+    box-shadow: 0 0 0 2px rgba(37, 99, 235, 0.2);
+}
+
+/* Main Content */
+.main-content {
+    flex: 1;
+    display: flex;
+    flex-direction: column;
+    height: 100vh;
+    overflow: hidden;
+    background-color: #FFFFFF;
+}
+
+.header {
+    height: 64px;
+    border-bottom: 1px solid var(--border-color);
+    display: flex;
+    align-items: center;
+    padding: 0 2rem;
+    background-color: #FFFFFF;
+}
+
+.header h2 {
+    font-size: 1.25rem;
+    font-weight: 600;
+}
+
+.content-area {
+    flex: 1;
+    overflow-y: auto;
+    padding: 2rem;
+    background-color: #ffffff;
+}
+
+/* Sections & Panel */
+.section {
+    display: none;
+    max-width: 1000px;
+    margin: 0 auto;
+}
+
+.section.active {
+    display: block;
+}
+
+.analysis-grid {
+    display: grid;
+    grid-template-columns: 350px 1fr;
+    gap: 2rem;
+    height: calc(100vh - 64px - 4rem);
+}
+
+.panel {
+    background: #FFFFFF;
+    border: 1px solid var(--border-color);
+    border-radius: 0.5rem;
+    padding: 1.5rem;
+    display: flex;
+    flex-direction: column;
+    gap: 1.5rem;
+}
+
+.panel-title {
+    font-size: 1rem;
+    font-weight: 600;
+    color: var(--text-primary);
+    margin-bottom: 0.5rem;
+    display: flex;
+    align-items: center;
+    justify-content: space-between;
+}
+
+/* Forms */
+.form-group {
+    display: flex;
+    flex-direction: column;
+    gap: 0.5rem;
+}
+
+.form-label {
+    font-size: 0.875rem;
+    font-weight: 500;
+    color: var(--text-secondary);
+}
+
+.form-input,
+.form-textarea {
+    padding: 0.625rem 0.875rem;
+    border: 1px solid var(--border-color);
+    border-radius: 0.375rem;
+    font-family: inherit;
+    font-size: 0.9rem;
+    color: var(--text-primary);
+    outline: none;
+    transition: border-color 0.2s;
+    width: 100%;
+}
+
+.form-input:focus,
+.form-textarea:focus {
+    border-color: var(--primary-color);
+    box-shadow: 0 0 0 2px rgba(37, 99, 235, 0.1);
+}
+
+.form-textarea {
+    resize: vertical;
+    min-height: 100px;
+}
+
+/* Buttons */
+.btn {
+    display: inline-flex;
+    align-items: center;
+    justify-content: center;
+    gap: 0.5rem;
+    padding: 0.625rem 1.25rem;
+    border-radius: 0.375rem;
+    font-weight: 500;
+    font-size: 0.9rem;
+    cursor: pointer;
+    transition: all 0.2s;
+    border: 1px solid transparent;
+}
+
+.btn-primary {
+    background-color: var(--primary-color);
+    color: white;
+}
+
+.btn-primary:hover {
+    background-color: var(--primary-hover);
+}
+
+.btn-secondary {
+    background-color: white;
+    border-color: var(--border-color);
+    color: var(--text-primary);
+}
+
+.btn-secondary:hover {
+    background-color: #F9FAFB;
+    border-color: #D1D5DB;
+}
+
+.btn-sm {
+    padding: 0.375rem 0.75rem;
+    font-size: 0.875rem;
+}
+
+/* Upload Area */
+.upload-area {
+    border: 2px dashed var(--border-color);
+    border-radius: 0.5rem;
+    padding: 2rem;
+    text-align: center;
+    cursor: pointer;
+    transition: all 0.2s;
+    background-color: #F9FAFB;
+}
+
+.upload-area:hover,
+.upload-area.dragover {
+    border-color: var(--primary-color);
+    background-color: #EFF6FF;
+}
+
+.upload-icon {
+    font-size: 1.5rem;
+    color: var(--text-secondary);
+    margin-bottom: 0.75rem;
+}
+
+.file-list {
+    margin-top: 1rem;
+    display: flex;
+    flex-direction: column;
+    gap: 0.5rem;
+}
+
+.file-item {
+    display: flex;
+    align-items: center;
+    gap: 0.5rem;
+    font-size: 0.85rem;
+    color: var(--text-primary);
+    background: #FFFFFF;
+    padding: 0.5rem;
+    border: 1px solid var(--border-color);
+    border-radius: 0.25rem;
+}
+
+/* Tabs */
+.tabs {
+    display: flex;
+    gap: 1rem;
+    margin-left: 1rem;
+}
+
+.tab {
+    padding: 0.25rem 0.5rem;
+    font-size: 0.9rem;
+    color: var(--text-secondary);
+    cursor: pointer;
+    border-bottom: 2px solid transparent;
+    transition: all 0.2s;
+}
+
+.tab:hover {
+    color: var(--text-primary);
+}
+
+.tab.active {
+    color: var(--primary-color);
+    border-bottom-color: var(--primary-color);
+    font-weight: 500;
+}
+
+/* Log & Report Content */
+.output-container {
+    flex: 1;
+    overflow-y: hidden;
+    /* Individual tabs scroll */
+    background: #F9FAFB;
+    border: 1px solid var(--border-color);
+    border-radius: 0.375rem;
+    padding: 1rem;
+    position: relative;
+    display: flex;
+    flex-direction: column;
+}
+
+#logsTab {
+    background-color: #1a1b26;
+    color: #a9b1d6;
+    font-family: 'JetBrains Mono', 'Menlo', 'Monaco', 'Courier New', monospace;
+    padding: 1.5rem;
+}
+
+.log-content {
+    font-family: inherit;
+    font-size: 0.85rem;
+    white-space: pre-wrap;
+    line-height: 1.6;
+    margin: 0;
+}
+
+.report-content {
+    font-size: 0.95rem;
+    line-height: 1.7;
+    color: #1F2937;
+}
+
+.report-content img {
+    max-width: 100%;
+    border-radius: 0.375rem;
+    margin: 1rem 0;
+    box-shadow: var(--card-shadow);
+}
+
+/* Empty State */
+.empty-state {
+    text-align: center;
+    padding: 4rem 2rem;
+    color: var(--text-secondary);
+}
+
+/* Utilities */
+.hidden {
+    display: none !important;
+}
+
+/* Gallery Carousel */
+.carousel-container {
+    position: relative;
+    width: 100%;
+    flex: 1;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    background: #F3F4F6;
+    border-radius: 0.5rem;
+    overflow: hidden;
+    margin-bottom: 1rem;
+}
+
+.carousel-slide {
+    width: 100%;
+    height: 100%;
+    display: flex;
+    flex-direction: column;
+    align-items: center;
+    justify-content: center;
+    padding: 2rem;
+}
+
+.carousel-slide img {
+    max-width: 100%;
+    max-height: 500px;
+    object-fit: contain;
+    border-radius: 0.25rem;
+    box-shadow: 0 10px 15px -3px rgba(0, 0, 0, 0.1);
+    transition: transform 0.2s;
+    background: white;
+}
+
+.carousel-btn {
+    position: absolute;
+    top: 50%;
+    transform: translateY(-50%);
+    background: rgba(255, 255, 255, 0.9);
+    border: 1px solid var(--border-color);
+    border-radius: 50%;
+    width: 44px;
+    height: 44px;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    cursor: pointer;
+    z-index: 10;
+    color: var(--text-primary);
+    box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1);
+    transition: all 0.2s;
+}
+
+.carousel-btn:hover {
+    background: var(--primary-color);
+    color: white;
+    border-color: var(--primary-color);
+    transform: translateY(-50%) scale(1.1);
+}
+
+.carousel-btn.prev {
+    left: 1rem;
+}
+
+.carousel-btn.next {
+    right: 1rem;
+}
+
+.image-info {
+    width: 100%;
+    text-align: center;
+    color: var(--text-primary);
+    background: white;
+    padding: 1rem;
+    border-radius: 0.5rem;
+    border: 1px solid var(--border-color);
+}
+
+.image-title {
+    font-weight: 600;
+    font-size: 1.1rem;
+    margin-bottom: 0.5rem;
+    color: var(--primary-color);
+}
+
+.image-desc {
+    font-size: 0.9rem;
+    color: var(--text-secondary);
+}

web/static/index.html

@@ -5,18 +5,20 @@
     <meta charset="UTF-8">
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
     <title>IOV Data Analysis Agent</title>
-    <link rel="stylesheet" href="/static/style.css?v=2.0">
+    <link rel="stylesheet" href="/static/clean_style.css">
 
-    <!-- Google Fonts -->
+    <!-- Fonts -->
     <link rel="preconnect" href="https://fonts.googleapis.com">
     <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
     <link
-        href="https://fonts.googleapis.com/css2?family=Outfit:wght@300;400;500;600;700&family=Inter:wght@300;400;500;600&display=swap"
+        href="https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600&family=JetBrains+Mono:wght@400;500&display=swap"
         rel="stylesheet">
-    <!-- Markdown Parser -->
+
-    <script src="https://cdn.jsdelivr.net/npm/marked/marked.min.js"></script>
+    <!-- Icons -->
-    <!-- Font Awesome -->
     <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.4.0/css/all.min.css">
+
+    <!-- Markdown -->
+    <script src="https://cdn.jsdelivr.net/npm/marked/marked.min.js"></script>
 </head>
 
 <body>
@@ -24,161 +26,139 @@
         <!-- Sidebar -->
         <aside class="sidebar">
             <div class="brand">
-                <i class="fa-solid fa-robot"></i>
+                <i class="fa-solid fa-cube"></i>
-                <h1>IOV Agent</h1>
+                <span>IOV Agent</span>
             </div>
 
-            <!-- Navigation -->
+            <nav class="nav-menu">
-            <nav class="main-nav">
+                <button class="nav-item active" onclick="switchView('analysis')">
-                <button class="nav-btn active" onclick="switchView('analysis')">
                     <i class="fa-solid fa-chart-line"></i> Analysis
                 </button>
-                <button class="nav-btn" onclick="switchView('tools')">
+
-                    <i class="fa-solid fa-toolbox"></i> Data Tools
+                <div class="nav-divider"></div>
-                </button>
+                <div class="nav-section-title">History</div>
-                <button class="nav-btn" onclick="switchView('gallery')">
+                <div id="historyList" class="history-list">
-                    <i class="fa-solid fa-images"></i> Gallery
+                    <!-- History items loaded via JS -->
-                </button>
+                    <div style="padding:0.5rem; font-size:0.8rem; color:#9CA3AF;">Loading...</div>
-                <button class="nav-btn" onclick="switchView('help')">
+                </div>
-                    <i class="fa-solid fa-circle-question"></i> Help
-                </button>
             </nav>
 
-            <!-- Analysis Controls (Visible only in Analysis View) -->
+            <div class="status-bar">
-            <div id="analysisControls" class="control-group-wrapper">
+                <div id="statusDot" class="status-dot"></div>
-                <div class="control-group">
+                <span id="statusText">Ready</span>
-                    <h3>1. Data Upload</h3>
-                    <div class="upload-zone" id="uploadZone">
-                        <i class="fa-solid fa-cloud-arrow-up"></i>
-                        <p>Drag & Drop CSV/Excel</p>
-                        <input type="file" id="fileInput" accept=".csv,.xlsx,.xls" multiple hidden>
-                        <button class="btn secondary" onclick="document.getElementById('fileInput').click()">Select
-                            Files</button>
-                        <div id="fileList" class="file-list"></div>
-                    </div>
-                </div>
-
-                <div class="control-group">
-                    <h3>2. Analysis Config</h3>
-                    <textarea id="requirementInput"
-                        placeholder="Enter your analysis requirement here...">基于所有运维工单，整理一份工单健康度报告...</textarea>
-                    <button id="startBtn" class="btn primary">
-                        <i class="fa-solid fa-play"></i> Start Analysis
-                    </button>
-                </div>
-            </div>
-
-            <div class="status-indicator">
-                <span id="statusDot" class="dot"></span>
-                <span id="statusText">Idle</span>
             </div>
         </aside>
 
-        <!-- Main Content Area -->
+        <!-- Main Content -->
         <main class="main-content">
+            <header class="header">
+                <h2 id="pageTitle">Analysis Dashboard</h2>
+            </header>
 
+            <div class="content-area">
                 <!-- VIEW: ANALYSIS -->
-            <div id="viewAnalysis" class="view-section active">
+                <div id="viewAnalysis" class="section active">
+                    <div class="analysis-grid">
+
+                        <!-- Configuration Panel -->
+                        <div class="panel">
+                            <div class="panel-title">
+                                <span>Configuration</span>
+                            </div>
+
+                            <div class="form-group">
+                                <label class="form-label">1. Data Upload</label>
+                                <div id="uploadZone" class="upload-area">
+                                    <i class="fa-solid fa-cloud-arrow-up upload-icon"></i>
+                                    <p>Click or Drag CSV/Excel Files</p>
+                                    <div id="fileList" class="file-list"></div>
+                                </div>
+                                <input type="file" id="fileInput" multiple accept=".csv,.xlsx,.xls" hidden>
+                            </div>
+
+                            <div class="form-group">
+                                <label class="form-label">2. Requirement</label>
+                                <textarea id="requirementInput" class="form-textarea"
+                                    placeholder="Describe what you want to analyze..."></textarea>
+                            </div>
+
+                            <button id="startBtn" class="btn btn-primary" style="margin-top: 1rem; width: 100%;">
+                                <i class="fa-solid fa-play"></i> Start Analysis
+                            </button>
+                        </div>
+
+                        <!-- Output Panel -->
+                        <div class="panel" style="overflow:hidden; display:flex; flex-direction:column;">
+                            <div class="panel-title" style="margin-bottom:0.5rem;">
+                                <span>Output</span>
                                 <div class="tabs">
-                    <button class="tab-btn active" onclick="switchTab('logs')">
+                                    <div class="tab active" onclick="switchTab('logs')">Live Log</div>
-                        <i class="fa-solid fa-terminal"></i> Live Logs
+                                    <div class="tab" onclick="switchTab('report')">Report</div>
-                    </button>
+                                    <div class="tab" onclick="switchTab('gallery')">Gallery</div>
-                    <button class="tab-btn" onclick="switchTab('report')">
-                        <i class="fa-solid fa-file-invoice-dollar"></i> Report
-                    </button>
-                    <div style="margin-left: auto; display: flex; align-items: center;">
-                        <button id="exportBtn" class="btn secondary"
-                            style="padding: 0.4rem 1rem; font-size: 0.8rem; width: auto;" onclick="triggerExport()">
-                            <i class="fa-solid fa-download"></i> Export Report (ZIP)
-                        </button>
                                 </div>
+                                <button id="downloadScriptBtn" class="btn btn-sm btn-secondary hidden"
+                                    onclick="downloadScript()" style="margin-left:auto;">
+                                    <i class="fa-solid fa-code"></i> Script
+                                </button>
                             </div>
 
-                <!-- Log View -->
+                            <div class="output-container" id="outputContainer">
-                <div id="logsTab" class="tab-content active">
+                                <!-- Logs Tab -->
-                    <div class="terminal-window">
+                                <div id="logsTab" class="tab-content active" style="height:100%; overflow-y:auto;">
-                        <pre id="logOutput">Waiting to start...</pre>
+                                    <pre id="logOutput" class="log-content">Waiting to start...</pre>
-                    </div>
                                 </div>
 
-                <!-- Report View -->
+                                <!-- Report Tab -->
-                <div id="reportTab" class="tab-content">
+                                <div id="reportTab" class="tab-content hidden" style="height:100%; overflow-y:auto;">
-                    <div id="reportContainer" class="markdown-body">
+                                    <div id="reportContainer" class="report-content markdown-body">
                                         <div class="empty-state">
-                            <i class="fa-solid fa-chart-simple"></i>
+                                            <p>Report will appear here after analysis.</p>
-                            <p>No report generated yet.</p>
+                                        </div>
+                                    </div>
+                                    <div id="followUpSection" class="hidden"
+                                        style="margin-top:2rem; border-top:1px solid var(--border-color); padding-top:1rem;">
+                                        <div class="form-group">
+                                            <label class="form-label">Follow-up Analysis</label>
+                                            <div style="display:flex; gap:0.5rem;">
+                                                <input type="text" id="followUpInput" class="form-input"
+                                                    placeholder="Ask a follow-up question...">
+                                                <button class="btn btn-primary btn-sm"
+                                                    onclick="sendFollowUp()">Send</button>
                                             </div>
                                         </div>
                                     </div>
-            </div>
+                                    <div style="margin-top:1rem; text-align:right">
-
+                                        <button id="exportBtn" class="btn btn-secondary btn-sm"
-            <!-- Follow-up Chat Section -->
+                                            onclick="triggerExport()">
-            <div id="followUpSection" class="chat-input-container" style="display: none;">
+                                            <i class="fa-solid fa-download"></i> Export ZIP
-                <div class="input-wrapper">
-                    <textarea id="followUpInput"
-                        placeholder="Follow-up question... (e.g. 'Analyze the error codes')"></textarea>
-                    <button id="sendFollowUpBtn" class="btn primary" onclick="sendFollowUp()">
-                        <i class="fa-solid fa-paper-plane"></i>
                                         </button>
                                     </div>
                                 </div>
-    </div>
 
-    <!-- VIEW: TOOLS -->
+                                <!-- Gallery Tab -->
-    <div id="viewTools" class="view-section" style="display: none;">
+                                <div id="galleryTab" class="tab-content hidden"
-        <div class="tools-grid">
+                                    style="height:100%; display:flex; flex-direction:column; align-items:center; justify-content:center;">
-            <!-- Tool Card 1: Merge Excel -->
+                                    <div class="carousel-container">
-            <div class="tool-card">
+                                        <button class="carousel-btn prev" onclick="prevImage()"><i
-                <div class="tool-icon"><i class="fa-solid fa-file-csv"></i></div>
+                                                class="fa-solid fa-chevron-left"></i></button>
-                <h3>Excel to CSV Merger</h3>
+                                        <div class="carousel-slide" id="carouselSlide">
-                <p>Merge multiple .xlsx files from the uploads directory into a single CSV for analysis.</p>
+                                            <p class="placeholder-text" style="color:var(--text-secondary);">No images
-                <div class="tool-actions">
+                                                generated.</p>
-                    <input type="text" id="mergeSource" value="uploads" placeholder="Source Directory" class="input-sm">
-                    <button class="btn secondary" onclick="triggerMerge()">
-                        <i class="fa-solid fa-bolt"></i> Merge Now
-                    </button>
                                         </div>
-                <div id="mergeResult" class="tool-result"></div>
+                                        <button class="carousel-btn next" onclick="nextImage()"><i
+                                                class="fa-solid fa-chevron-right"></i></button>
                                     </div>
-
+                                    <div class="image-info" id="imageInfo" style="margin-top:1rem; text-align:center;">
-            <!-- Tool Card 2: Sort CSV -->
+                                        <!-- Title/Desc -->
-            <div class="tool-card">
-                <div class="tool-icon"><i class="fa-solid fa-arrow-down-a-z"></i></div>
-                <h3>Time Sorter</h3>
-                <p>Sort a CSV file by 'SendTime' or time column to fix ordering issues.</p>
-                <div class="tool-actions">
-                    <input type="text" id="sortTarget" value="cleaned_data.csv" placeholder="Target Filename"
-                        class="input-sm">
-                    <button class="btn secondary" onclick="triggerSort()">
-                        <i class="fa-solid fa-sort"></i> Sort Now
-                    </button>
                                     </div>
-                <div id="sortResult" class="tool-result"></div>
                                 </div>
                             </div>
                         </div>
 
-    <!-- VIEW: GALLERY -->
-    <div id="viewGallery" class="view-section" style="display: none;">
-        <div id="galleryContainer" class="gallery-grid">
-            <div class="empty-state">
-                <i class="fa-solid fa-images"></i>
-                <p>No images generated yet.<br>Start an analysis to see results here.</p>
-            </div>
-        </div>
-    </div>
-
-    <!-- VIEW: HELP -->
-    <div id="viewHelp" class="view-section" style="display: none;">
-        <div class="help-header">
-            <h2>Troubleshooting Guide</h2>
-            <button class="btn secondary" onclick="fetchHelp()">Refresh</button>
-        </div>
-        <div id="helpContainer" class="markdown-body help-body">
-            <p>Loading guide...</p>
                     </div>
                 </div>
 
+            </div>
         </main>
     </div>
 

web/static/script.js

@@ -1,4 +1,5 @@
 
+// DOM Elements
 const uploadZone = document.getElementById('uploadZone');
 const fileInput = document.getElementById('fileInput');
 const fileList = document.getElementById('fileList');
@@ -8,7 +9,7 @@ const statusDot = document.getElementById('statusDot');
 const statusText = document.getElementById('statusText');
 const logOutput = document.getElementById('logOutput');
 const reportContainer = document.getElementById('reportContainer');
-const galleryContainer = document.getElementById('galleryContainer');
+const downloadScriptBtn = document.getElementById('downloadScriptBtn');
 
 let isRunning = false;
 let pollingInterval = null;
@@ -26,9 +27,12 @@ if (uploadZone) {
         uploadZone.classList.remove('dragover');
         handleFiles(e.dataTransfer.files);
     });
+    uploadZone.addEventListener('click', () => fileInput.click());
 }
+
 if (fileInput) {
     fileInput.addEventListener('change', (e) => handleFiles(e.target.files));
+    fileInput.addEventListener('click', (e) => e.stopPropagation()); // Prevent bubbling to uploadZone
 }
 
 async function handleFiles(files) {
@@ -40,9 +44,8 @@ async function handleFiles(files) {
     for (const file of files) {
         formData.append('files', file);
         const fileItem = document.createElement('div');
-        fileItem.innerText = `📄 ${file.name}`;
+        fileItem.className = 'file-item';
-        fileItem.style.fontSize = '0.8rem';
+        fileItem.innerHTML = `<i class="fa-regular fa-file-excel"></i> ${file.name}`;
-        fileItem.style.color = '#fff';
         fileList.appendChild(fileItem);
     }
 
@@ -52,8 +55,7 @@ async function handleFiles(files) {
             body: formData
         });
         if (res.ok) {
-            const data = await res.json();
+            console.log('Upload success');
-            console.log('Upload success:', data);
         } else {
             alert('Upload failed');
         }
@@ -63,9 +65,12 @@ async function handleFiles(files) {
     }
 }
 
-// --- Start Analysis ---
+// --- Analysis Logic ---
 if (startBtn) {
-    startBtn.addEventListener('click', async () => {
+    startBtn.addEventListener('click', startAnalysis);
+}
+
+async function startAnalysis() {
     if (isRunning) return;
 
     const requirement = requirementInput.value.trim();
@@ -85,7 +90,7 @@ if (startBtn) {
 
         if (res.ok) {
             const data = await res.json();
-                currentSessionId = data.session_id; // Store Session ID
+            currentSessionId = data.session_id;
             console.log("Started Session:", currentSessionId);
 
             startPolling();
@@ -100,26 +105,35 @@ if (startBtn) {
         alert('Error starting analysis');
         setRunningState(false);
     }
-    });
 }
 
 function setRunningState(running) {
     isRunning = running;
     startBtn.disabled = running;
-    startBtn.innerHTML = running ? '<i class="fa-solid fa-spinner fa-spin"></i> Running...' : '<i class="fa-solid fa-play"></i> Start Analysis';
 
     if (running) {
-        statusDot.className = 'dot running';
+        startBtn.innerHTML = '<i class="fa-solid fa-spinner fa-spin"></i> Analysis in Progress...';
-        statusText.innerText = 'Analysis in Progress';
+        statusDot.className = 'status-dot running';
-        if (document.getElementById('followUpSection')) document.getElementById('followUpSection').style.display = 'none';
+        statusText.innerText = 'Analyzing';
+        statusText.style.color = 'var(--primary-color)';
+
+        // Hide follow-up and download during run
+        const followUpSection = document.getElementById('followUpSection');
+        if (followUpSection) followUpSection.classList.add('hidden');
+        if (downloadScriptBtn) downloadScriptBtn.classList.add('hidden');
     } else {
-        statusDot.className = 'dot done';
+        startBtn.innerHTML = '<i class="fa-solid fa-play"></i> Start Analysis';
+        statusDot.className = 'status-dot';
         statusText.innerText = 'Completed';
-        if (currentSessionId && document.getElementById('followUpSection')) document.getElementById('followUpSection').style.display = 'flex';
+        statusText.style.color = 'var(--text-secondary)';
+
+        const followUpSection = document.getElementById('followUpSection');
+        if (currentSessionId && followUpSection) {
+            followUpSection.classList.remove('hidden');
+        }
     }
 }
 
-// --- Status Polling ---
 function startPolling() {
     if (pollingInterval) clearInterval(pollingInterval);
     if (!currentSessionId) return;
@@ -131,20 +145,31 @@ function startPolling() {
             const data = await res.json();
 
             // Update Logs
-            logOutput.innerText = data.log || "Waiting for logs...";
+            logOutput.innerText = data.log || "Waiting for output...";
-            // Auto scroll to bottom
+
-            const term = document.querySelector('.terminal-window');
+            // Auto scroll
-            if (term) term.scrollTop = term.scrollHeight;
+            const logTab = document.getElementById('logsTab');
+            if (logTab) logTab.scrollTop = logTab.scrollHeight;
 
             if (!data.is_running && isRunning) {
-                // Just finished
+                // Finished
                 setRunningState(false);
                 clearInterval(pollingInterval);
 
                 if (data.has_report) {
-                    loadReport();
+                    await loadReport();
-                    loadGallery(); // Load images when done
+
+                    // 强制跳转到 Report Tab
                     switchTab('report');
+                    console.log("Analysis done, switched to report tab");
+                }
+
+                // Check for script
+                if (data.script_path) {
+                    if (downloadScriptBtn) {
+                        downloadScriptBtn.classList.remove('hidden');
+                        downloadScriptBtn.style.display = 'inline-flex';
+                    }
                 }
             }
         } catch (e) {
@@ -153,129 +178,122 @@ function startPolling() {
     }, 2000);
 }
 
+// --- Report Logic ---
 async function loadReport() {
     if (!currentSessionId) return;
     try {
         const res = await fetch(`/api/report?session_id=${currentSessionId}`);
         const data = await res.json();
 
-        // Render Markdown
+        if (!data.content || data.content === "Report not ready.") {
+            reportContainer.innerHTML = '<div class="empty-state"><p>Analysis in progress or no report generated yet.</p></div>';
+        } else {
             reportContainer.innerHTML = marked.parse(data.content);
-
-        // Fix images relative path for display if needed
-        // The backend should return a base_path or we handle it here
-        if (data.base_path) {
-            // Backend already handled replacement? 
-            // The backend returns content with updated paths.
         }
-
     } catch (e) {
         reportContainer.innerHTML = '<p class="error">Failed to load report.</p>';
-        console.error(e);
     }
 }
 
+// --- Gallery Logic ---
+let galleryImages = [];
+let currentImageIndex = 0;
+
 async function loadGallery() {
     if (!currentSessionId) return;
-
-    // Switch to gallery view logic if we were already there
-    // But this is just data loading
     try {
         const res = await fetch(`/api/figures?session_id=${currentSessionId}`);
         const data = await res.json();
 
-        const galleryGrid = document.getElementById('galleryContainer');
+        galleryImages = data.figures || [];
-        if (!data.figures || data.figures.length === 0) {
+        currentImageIndex = 0;
-            galleryGrid.innerHTML = `
+        renderGalleryImage();
-                <div class="empty-state">
-                    <i class="fa-solid fa-images"></i>
-                    <p>No images generated in this session.</p>
-                </div>
-            `;
-            return;
-        }
-
-        let html = '';
-        data.figures.forEach(fig => {
-            html += `
-                <div class="gallery-card">
-                    <div class="img-wrapper">
-                        <img src="${fig.web_url}" alt="${fig.filename}" onclick="window.open('${fig.web_url}', '_blank')">
-                    </div>
-                    <div class="card-content">
-                        <h4>${fig.filename}</h4>
-                        <p class="desc">${fig.description || 'No description'}</p>
-                        ${fig.analysis ? `<div class="analysis-box"><i class="fa-solid fa-magnifying-glass"></i> ${fig.analysis}</div>` : ''}
-                    </div>
-                </div>
-            `;
-        });
-        galleryGrid.innerHTML = html;
 
     } catch (e) {
         console.error("Gallery load failed", e);
+        document.getElementById('carouselSlide').innerHTML = '<p class="error">Failed to load images.</p>';
     }
 }
 
-// --- Export Report ---
+function renderGalleryImage() {
+    const slide = document.getElementById('carouselSlide');
+    const info = document.getElementById('imageInfo');
+
+    if (galleryImages.length === 0) {
+        slide.innerHTML = '<p class="placeholder-text" style="color:var(--text-secondary);">No images generated in this session.</p>';
+        info.innerHTML = '';
+        return;
+    }
+
+    const img = galleryImages[currentImageIndex];
+
+    // Image
+    slide.innerHTML = `<img src="${img.web_url}" alt="${img.filename}" onclick="window.open('${img.web_url}', '_blank')">`;
+
+    // Info
+    info.innerHTML = `
+        <div class="image-title">${img.filename} (${currentImageIndex + 1}/${galleryImages.length})</div>
+        <div class="image-desc">${img.description || 'No description available.'}</div>
+        ${img.analysis ? `<div style="font-size:0.8rem; margin-top:0.5rem; color:#4B5563; background:#F3F4F6; padding:0.5rem; border-radius:4px;">${img.analysis}</div>` : ''}
+    `;
+}
+
+window.prevImage = function () {
+    if (galleryImages.length === 0) return;
+    currentImageIndex = (currentImageIndex - 1 + galleryImages.length) % galleryImages.length;
+    renderGalleryImage();
+}
+
+window.nextImage = function () {
+    if (galleryImages.length === 0) return;
+    currentImageIndex = (currentImageIndex + 1) % galleryImages.length;
+    renderGalleryImage();
+}
+
+// --- Download Script ---
+window.downloadScript = async function () {
+    if (!currentSessionId) return;
+    const link = document.createElement('a');
+    link.href = `/api/download_script?session_id=${currentSessionId}`;
+    link.download = '';
+    document.body.appendChild(link);
+    link.click();
+    document.body.removeChild(link);
+}
+
 // --- Export Report ---
 window.triggerExport = async function () {
     if (!currentSessionId) {
         alert("No active session to export.");
         return;
     }
-
     const btn = document.getElementById('exportBtn');
-    const originalText = btn.innerHTML;
+    const originalContent = btn.innerHTML;
     btn.innerHTML = '<i class="fa-solid fa-spinner fa-spin"></i> Zipping...';
     btn.disabled = true;
 
     try {
         const url = `/api/export?session_id=${currentSessionId}`;
-        const res = await fetch(url); // Default GET
+        window.open(url, '_blank');
 
-        if (res.ok) {
-            const blob = await res.blob();
-            const downloadUrl = window.URL.createObjectURL(blob);
-            const a = document.createElement('a');
-            a.href = downloadUrl;
-            a.download = `analysis_export_${currentSessionId}.zip`;
-            document.body.appendChild(a);
-            a.click();
-            a.remove();
-            window.URL.revokeObjectURL(downloadUrl);
-        } else {
-            // Try to parse error
-            let errMsg = "Unknown error";
-            try {
-                const err = await res.json();
-                errMsg = err.detail || errMsg;
-            } catch (jsonErr) {
-                errMsg = res.statusText;
-            }
-            alert("Export failed: " + errMsg);
-        }
     } catch (e) {
         alert("Export failed: " + e.message);
     } finally {
-        btn.innerHTML = originalText;
+        setTimeout(() => {
+            btn.innerHTML = originalContent;
             btn.disabled = false;
+        }, 2000);
     }
 }
 
 // --- Follow-up Chat ---
 window.sendFollowUp = async function () {
     if (!currentSessionId || isRunning) return;
-
     const input = document.getElementById('followUpInput');
     const message = input.value.trim();
     if (!message) return;
 
-    // UI Loading state
-    const btn = document.getElementById('sendFollowUpBtn');
-    btn.disabled = true;
     input.disabled = true;
-
     try {
         const res = await fetch('/api/chat', {
             method: 'POST',
@@ -289,128 +307,128 @@ window.sendFollowUp = async function () {
             startPolling();
             switchTab('logs');
         } else {
-            const err = await res.json();
+            alert('Failed to send request');
-            alert('Error: ' + err.detail);
         }
     } catch (e) {
         console.error(e);
-        alert('Failed to send request');
     } finally {
-        btn.disabled = false;
         input.disabled = false;
     }
 }
 
+// --- History Logic ---
+async function loadHistory() {
+    const list = document.getElementById('historyList');
+    if (!list) return;
 
+    try {
+        const res = await fetch('/api/history');
+        const data = await res.json();
 
-// --- Tabs (Inner) ---
+        if (data.history.length === 0) {
-window.switchTab = function (tabName) {
+            list.innerHTML = '<div style="padding:0.5rem; font-size:0.8rem; color:#9CA3AF;">No history yet</div>';
-    document.querySelectorAll('.tab-btn').forEach(b => b.classList.remove('active'));
+            return;
-    document.querySelectorAll('.tab-content').forEach(c => c.classList.remove('active'));
+        }
 
-    const btn = document.querySelector(`button[onclick="switchTab('${tabName}')"]`);
+        let html = '';
-    if (btn) btn.classList.add('active');
+        data.history.forEach(item => {
+            // item: {id, timestamp, name}
+            const timeStr = item.timestamp.split(' ')[0]; // Just date for compactness
+            html += `
+                <div class="history-item" onclick="loadSession('${item.id}')" id="hist-${item.id}">
+                    <i class="fa-regular fa-clock"></i>
+                    <span>${item.id}</span>
+                </div>
+            `;
+        });
+        list.innerHTML = html;
 
-    const tab = document.getElementById(`${tabName}Tab`);
+    } catch (e) {
-    if (tab) tab.classList.add('active');
+        console.error("Failed to load history", e);
+    }
 }
 
-// --- View Navigation (Outer Sidebar) ---
+window.loadSession = async function (sessionId) {
+    if (isRunning) {
+        alert("Analysis in progress, please wait.");
+        return;
+    }
+
+    currentSessionId = sessionId;
+
+    // Update active class
+    document.querySelectorAll('.history-item').forEach(el => el.classList.remove('active'));
+    const activeItem = document.getElementById(`hist-${sessionId}`);
+    if (activeItem) activeItem.classList.add('active');
+
+    // Reset UI
+    logOutput.innerText = "Loading session data...";
+    reportContainer.innerHTML = "";
+    if (downloadScriptBtn) downloadScriptBtn.classList.add('hidden');
+
+    // Fetch Status to get logs and check report
+    try {
+        const res = await fetch(`/api/status?session_id=${sessionId}`);
+        if (res.ok) {
+            const data = await res.json();
+            logOutput.innerText = data.log || "No logs available.";
+
+            // Auto scroll log
+            const logTab = document.getElementById('logsTab');
+            if (logTab) logTab.scrollTop = logTab.scrollHeight;
+
+            if (data.has_report) {
+                await loadReport();
+                // Check if script exists
+                if (data.script_path && downloadScriptBtn) {
+                    downloadScriptBtn.classList.remove('hidden');
+                    downloadScriptBtn.style.display = 'inline-flex';
+                }
+                switchTab('report');
+            } else {
+                switchTab('logs');
+            }
+        }
+    } catch (e) {
+        logOutput.innerText = "Error loading session.";
+    }
+}
+
+// Initialize
+document.addEventListener('DOMContentLoaded', () => {
+    loadHistory();
+});
+
+// --- Navigation ---
+// No-op for switchView as sidebar is simplified
 window.switchView = function (viewName) {
-    // 1. Update Sidebar Buttons
+    console.log("View switch requested:", viewName);
-    document.querySelectorAll('.nav-btn').forEach(b => b.classList.remove('active'));
+}
-    const navBtn = document.querySelector(`button[onclick="switchView('${viewName}')"]`);
-    if (navBtn) navBtn.classList.add('active');
 
-    // 2. Switch Main Content Sections
+window.switchTab = function (tabName) {
-    const viewId = 'view' + viewName.charAt(0).toUpperCase() + viewName.slice(1);
+    // Buttons
+    document.querySelectorAll('.tab').forEach(t => t.classList.remove('active'));
+    // Content
+    ['logs', 'report', 'gallery'].forEach(name => {
+        const content = document.getElementById(`${name}Tab`);
+        if (content) content.classList.add('hidden');
 
-    document.querySelectorAll('.view-section').forEach(v => {
+        // 找到对应的 Tab 按钮并激活
-        // Hide all
+        // 这里假设 Tab 按钮的 onclick 包含 tabName
-        v.style.display = 'none';
+        document.querySelectorAll('.tab').forEach(btn => {
-        v.classList.remove('active');
+            if (btn.getAttribute('onclick') && btn.getAttribute('onclick').includes(`'${tabName}'`)) {
+                btn.classList.add('active');
+            }
+        });
     });
 
-    const activeView = document.getElementById(viewId);
+    // Valid tabs logic
-    if (activeView) {
+    if (tabName === 'logs') {
-        // Analysis view uses flex for layout (logs scrolling), others use block
+        document.getElementById('logsTab').classList.remove('hidden');
-        if (viewName === 'analysis') {
+    } else if (tabName === 'report') {
-            activeView.style.display = 'flex';
+        document.getElementById('reportTab').classList.remove('hidden');
-            activeView.style.flexDirection = 'column';
+    } else if (tabName === 'gallery') {
-        } else {
+        document.getElementById('galleryTab').classList.remove('hidden');
-            activeView.style.display = 'block';
+        if (currentSessionId) loadGallery();
-            // If switching to gallery, reload it if session exists
-            if (viewName === 'gallery' && currentSessionId) {
-                loadGallery();
-            }
-        }
-        activeView.classList.add('active');
-    }
-
-    // 3. Toggle Sidebar Controls (only show Analysis Controls in analysis view)
-    const analysisControls = document.getElementById('analysisControls');
-    if (analysisControls) {
-        analysisControls.style.display = (viewName === 'analysis') ? 'block' : 'none';
-    }
-}
-
-// --- Tool Functions ---
-window.triggerMerge = async function () {
-    const sourceDir = document.getElementById('mergeSource').value;
-    const resultDiv = document.getElementById('mergeResult');
-
-    resultDiv.innerHTML = '<i class="fa-solid fa-spinner fa-spin"></i> Merging...';
-
-    try {
-        const res = await fetch('/api/tools/merge', {
-            method: 'POST',
-            headers: { 'Content-Type': 'application/json' },
-            body: JSON.stringify({ source_dir: sourceDir, output_filename: 'merged_output.csv' })
-        });
-        const data = await res.json();
-        if (data.status === 'success') {
-            resultDiv.innerHTML = `<span style="color:var(--success)"><i class="fa-solid fa-check"></i> ${data.message}</span>`;
-        } else {
-            resultDiv.innerHTML = `<span style="color:var(--warning)">${data.message}</span>`;
-        }
-    } catch (e) {
-        resultDiv.innerHTML = `<span style="color:red">Error: ${e.message}</span>`;
-    }
-}
-
-window.triggerSort = async function () {
-    const targetFile = document.getElementById('sortTarget').value;
-    const resultDiv = document.getElementById('sortResult');
-
-    resultDiv.innerHTML = '<i class="fa-solid fa-spinner fa-spin"></i> Sorting...';
-
-    try {
-        const res = await fetch('/api/tools/sort', {
-            method: 'POST',
-            headers: { 'Content-Type': 'application/json' },
-            body: JSON.stringify({ target_file: targetFile })
-        });
-        const data = await res.json();
-        if (data.status === 'success') {
-            resultDiv.innerHTML = `<span style="color:var(--success)"><i class="fa-solid fa-check"></i> ${data.message}</span>`;
-        } else {
-            resultDiv.innerHTML = `<span style="color:var(--warning)">${data.message}</span>`;
-        }
-    } catch (e) {
-        resultDiv.innerHTML = `<span style="color:red">Error: ${e.message}</span>`;
-    }
-}
-
-// --- Help Functions ---
-window.fetchHelp = async function () {
-    const container = document.getElementById('helpContainer');
-    container.innerHTML = 'Loading...';
-
-    try {
-        const res = await fetch('/api/help/troubleshooting');
-        const data = await res.json();
-        container.innerHTML = marked.parse(data.content);
-    } catch (e) {
-        container.innerHTML = 'Failed to load guide.';
     }
 }

web/static/style.css

@@ -1,501 +0,0 @@
-@import url('https://fonts.googleapis.com/css2?family=Outfit:wght@300;400;500;600;700&family=Inter:wght@300;400;500;600&family=JetBrains+Mono:wght@400;500&display=swap');
-
-:root {
-    /* Nebula Theme Palette */
-    --bg-deep: #020617;
-    --bg-secondary: #0f172a;
-
-    --sidebar-bg: rgba(15, 23, 42, 0.6);
-    --card-bg: rgba(30, 41, 59, 0.3);
-    --glass-border: 1px solid rgba(148, 163, 184, 0.08);
-
-    --primary-color: #6366f1;
-    --primary-glow: #6366f1aa;
-    --accent-color: #0ea5e9;
-
-    --text-main: #f8fafc;
-    --text-muted: #94a3b8;
-
-    --success: #10b981;
-    --warning: #f59e0b;
-    --danger: #ef4444;
-
-    --radius-lg: 1rem;
-    --radius-md: 0.75rem;
-    --radius-sm: 0.5rem;
-}
-
-* {
-    box-sizing: border-box;
-    margin: 0;
-    padding: 0;
-}
-
-body {
-    font-family: 'Inter', sans-serif;
-    background-color: var(--bg-deep);
-    background-image:
-        radial-gradient(circle at 15% 50%, rgba(99, 102, 241, 0.08) 0%, transparent 50%),
-        radial-gradient(circle at 85% 30%, rgba(14, 165, 233, 0.08) 0%, transparent 50%);
-    color: var(--text-main);
-    height: 100vh;
-    overflow: hidden;
-    display: flex;
-    justify-content: center;
-    align-items: center;
-}
-
-.app-container {
-    display: flex;
-    height: 96vh;
-    width: 98vw;
-    gap: 1rem;
-    border-radius: var(--radius-lg);
-    overflow: hidden;
-}
-
-/* --- Floating Sidebar --- */
-.sidebar {
-    width: 280px;
-    background: var(--sidebar-bg);
-    backdrop-filter: blur(20px);
-    -webkit-backdrop-filter: blur(20px);
-    border: var(--glass-border);
-    border-radius: var(--radius-lg);
-    padding: 1.5rem;
-    display: flex;
-    flex-direction: column;
-    gap: 2rem;
-    transition: all 0.3s ease;
-    box-shadow: 0 8px 32px rgba(0, 0, 0, 0.2);
-}
-
-.brand {
-    display: flex;
-    align-items: center;
-    gap: 0.75rem;
-    padding: 0.5rem 0.5rem 1rem 0.5rem;
-    border-bottom: var(--glass-border);
-}
-
-.brand i {
-    font-size: 1.75rem;
-    background: linear-gradient(135deg, var(--primary-color), var(--accent-color));
-    -webkit-background-clip: text;
-    background-clip: text;
-    -webkit-text-fill-color: transparent;
-    filter: drop-shadow(0 0 10px rgba(99, 102, 241, 0.5));
-}
-
-.brand h1 {
-    font-family: 'Outfit', sans-serif;
-    font-size: 1.5rem;
-    font-weight: 700;
-    letter-spacing: -0.02em;
-    background: linear-gradient(to right, #fff, #94a3b8);
-    -webkit-background-clip: text;
-    background-clip: text;
-    -webkit-text-fill-color: transparent;
-}
-
-/* Nav Buttons */
-.nav-btn {
-    width: 100%;
-    padding: 0.875rem 1rem;
-    border: none;
-    background: transparent;
-    color: var(--text-muted);
-    font-family: 'Outfit', sans-serif;
-    font-weight: 500;
-    text-align: left;
-    cursor: pointer;
-    border-radius: var(--radius-md);
-    transition: all 0.2s cubic-bezier(0.4, 0, 0.2, 1);
-    display: flex;
-    align-items: center;
-    gap: 0.75rem;
-    font-size: 0.95rem;
-}
-
-.nav-btn i {
-    font-size: 1.1rem;
-    transition: transform 0.2s;
-}
-
-.nav-btn:hover {
-    background: rgba(255, 255, 255, 0.03);
-    color: var(--text-main);
-    transform: translateX(4px);
-}
-
-.nav-btn.active {
-    background: linear-gradient(90deg, rgba(99, 102, 241, 0.1), transparent);
-    color: var(--primary-color);
-    border-left: 3px solid var(--primary-color);
-    border-radius: 4px var(--radius-md) var(--radius-md) 4px;
-}
-
-.nav-btn.active i {
-    color: var(--primary-color);
-    transform: scale(1.1);
-}
-
-/* --- Main Content --- */
-.main-content {
-    flex: 1;
-    background: rgba(15, 23, 42, 0.4);
-    backdrop-filter: blur(12px);
-    border: var(--glass-border);
-    border-radius: var(--radius-lg);
-    padding: 2rem;
-    display: flex;
-    flex-direction: column;
-    overflow: hidden;
-    position: relative;
-    box-shadow: 0 8px 32px rgba(0, 0, 0, 0.2);
-}
-
-/* Controls */
-.control-group-wrapper {
-    display: flex;
-    flex-direction: column;
-    gap: 1.5rem;
-}
-
-.control-group h3 {
-    font-family: 'Outfit', sans-serif;
-    font-size: 0.75rem;
-    color: #475569;
-    text-transform: uppercase;
-    letter-spacing: 0.1em;
-    font-weight: 700;
-    margin-bottom: 0.75rem;
-}
-
-/* Upload Zone */
-.upload-zone {
-    border: 1px dashed rgba(255, 255, 255, 0.1);
-    border-radius: 1rem;
-    padding: 1.5rem;
-    text-align: center;
-    transition: all 0.3s ease;
-    background: rgba(2, 6, 23, 0.3);
-    position: relative;
-    overflow: hidden;
-}
-
-.upload-zone::before {
-    content: '';
-    position: absolute;
-    inset: 0;
-    background: radial-gradient(circle at center, rgba(99, 102, 241, 0.1), transparent 70%);
-    opacity: 0;
-    transition: opacity 0.3s;
-}
-
-.upload-zone:hover::before {
-    opacity: 1;
-}
-
-.upload-zone.dragover {
-    border-color: var(--primary-color);
-    box-shadow: 0 0 20px rgba(99, 102, 241, 0.2);
-}
-
-.upload-zone i {
-    font-size: 2rem;
-    background: linear-gradient(to bottom, #94a3b8, #475569);
-    -webkit-background-clip: text;
-    background-clip: text;
-    -webkit-text-fill-color: transparent;
-    margin-bottom: 0.5rem;
-}
-
-.file-list {
-    margin-top: 0.5rem;
-    display: flex;
-    flex-direction: column;
-    gap: 0.25rem;
-}
-
-/* Buttons */
-.btn {
-    width: 100%;
-    padding: 0.875rem;
-    border-radius: var(--radius-md);
-    border: none;
-    cursor: pointer;
-    font-family: 'Outfit', sans-serif;
-    font-weight: 600;
-    font-size: 0.9rem;
-    display: flex;
-    align-items: center;
-    justify-content: center;
-    gap: 0.5rem;
-    transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1);
-    position: relative;
-    overflow: hidden;
-}
-
-.btn.primary {
-    background: linear-gradient(135deg, var(--primary-color), var(--primary-hover, #4f46e5));
-    color: white;
-    box-shadow: 0 4px 12px rgba(99, 102, 241, 0.3);
-}
-
-.btn.primary:hover {
-    box-shadow: 0 6px 20px rgba(99, 102, 241, 0.4);
-    transform: translateY(-1px);
-}
-
-.btn.primary::after {
-    content: '';
-    position: absolute;
-    top: 0;
-    left: -100%;
-    width: 100%;
-    height: 100%;
-    background: linear-gradient(90deg, transparent, rgba(255, 255, 255, 0.2), transparent);
-    transition: 0.5s;
-}
-
-.btn.primary:hover::after {
-    left: 100%;
-}
-
-.btn.secondary {
-    background: rgba(255, 255, 255, 0.05);
-    color: var(--text-main);
-    border: 1px solid rgba(255, 255, 255, 0.05);
-}
-
-.btn.secondary:hover {
-    background: rgba(255, 255, 255, 0.1);
-    border-color: rgba(255, 255, 255, 0.2);
-}
-
-/* Inputs */
-textarea,
-input[type="text"] {
-    width: 100%;
-    background: rgba(2, 6, 23, 0.3);
-    border: 1px solid rgba(255, 255, 255, 0.05);
-    border-radius: var(--radius-md);
-    padding: 1rem;
-    color: var(--text-main);
-    font-family: 'Inter', sans-serif;
-    font-size: 0.9rem;
-    transition: all 0.2s;
-}
-
-textarea:focus,
-input[type="text"]:focus {
-    outline: none;
-    border-color: var(--primary-color);
-    box-shadow: 0 0 0 2px rgba(99, 102, 241, 0.1);
-}
-
-/* Tabs */
-.tabs {
-    display: flex;
-    gap: 0.5rem;
-    margin-bottom: 1.5rem;
-    background: rgba(2, 6, 23, 0.2);
-    padding: 0.3rem;
-    border-radius: var(--radius-lg);
-    width: fit-content;
-}
-
-.tab-btn {
-    padding: 0.6rem 1.25rem;
-    border: none;
-    background: transparent;
-    color: var(--text-muted);
-    font-family: 'Outfit', sans-serif;
-    font-weight: 500;
-    font-size: 0.85rem;
-    border-radius: var(--radius-md);
-    cursor: pointer;
-    transition: all 0.2s;
-    display: flex;
-    align-items: center;
-    gap: 0.5rem;
-}
-
-.tab-btn:hover {
-    color: var(--text-main);
-}
-
-.tab-btn.active {
-    background: rgba(255, 255, 255, 0.08);
-    color: white;
-    box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
-}
-
-/* Terminal / Log Window */
-.terminal-window {
-    background: #09090b;
-    border-radius: var(--radius-lg);
-    padding: 1.5rem;
-    flex: 1;
-    overflow-y: auto;
-    border: 1px solid rgba(255, 255, 255, 0.05);
-    font-family: 'JetBrains Mono', monospace;
-    font-size: 0.85rem;
-    color: #22c55e;
-    box-shadow: inset 0 0 20px rgba(0, 0, 0, 0.5);
-    min-height: 0;
-}
-
-.terminal-window::-webkit-scrollbar {
-    width: 8px;
-}
-
-.terminal-window::-webkit-scrollbar-thumb {
-    background: rgba(255, 255, 255, 0.1);
-    border-radius: 4px;
-}
-
-/* Report Container */
-#reportContainer {
-    background: rgba(255, 255, 255, 0.95);
-    color: #1e293b;
-    border-radius: var(--radius-lg);
-    padding: 2.5rem;
-    flex: 1;
-    overflow-y: auto;
-    box-shadow: 0 10px 30px rgba(0, 0, 0, 0.2);
-}
-
-.empty-state {
-    display: flex;
-    flex-direction: column;
-    align-items: center;
-    justify-content: center;
-    height: 100%;
-    color: rgba(255, 255, 255, 0.2);
-    gap: 1rem;
-}
-
-.empty-state i {
-    font-size: 4rem;
-}
-
-/* Follow-up Chat */
-.chat-input-container {
-    margin-top: 1rem;
-    background: rgba(2, 6, 23, 0.4);
-    border: var(--glass-border);
-    border-radius: var(--radius-lg);
-    padding: 0.5rem;
-}
-
-.input-wrapper {
-    display: flex;
-    gap: 0.5rem;
-    align-items: flex-end;
-}
-
-#followUpInput {
-    background: transparent;
-    border: none;
-    height: 50px;
-    padding: 0.8rem;
-    resize: none;
-    box-shadow: none;
-}
-
-#sendFollowUpBtn {
-    width: 50px;
-    height: 50px;
-    border-radius: var(--radius-md);
-    padding: 0;
-    flex-shrink: 0;
-}
-
-/* Gallery Grid */
-.gallery-grid {
-    display: grid;
-    grid-template-columns: repeat(auto-fill, minmax(280px, 1fr));
-    gap: 1.5rem;
-    padding-bottom: 2rem;
-    overflow-y: auto;
-}
-
-.gallery-card {
-    background: rgba(255, 255, 255, 0.03);
-    border: var(--glass-border);
-    border-radius: var(--radius-lg);
-    overflow: hidden;
-    transition: all 0.3s;
-}
-
-.gallery-card:hover {
-    transform: translateY(-4px);
-    border-color: var(--primary-color);
-    box-shadow: 0 10px 30px rgba(0, 0, 0, 0.2);
-}
-
-.img-wrapper {
-    height: 180px;
-    overflow: hidden;
-    background: rgba(0, 0, 0, 0.2);
-    cursor: pointer;
-}
-
-.img-wrapper img {
-    width: 100%;
-    height: 100%;
-    object-fit: cover;
-    transition: transform 0.5s;
-}
-
-.img-wrapper:hover img {
-    transform: scale(1.05);
-}
-
-.card-content {
-    padding: 1rem;
-}
-
-.card-content h4 {
-    font-family: 'Outfit', sans-serif;
-    margin-bottom: 0.5rem;
-    font-size: 1rem;
-}
-
-.card-content .desc {
-    color: var(--text-muted);
-    font-size: 0.85rem;
-}
-
-/* Status Dot */
-.status-indicator {
-    margin-top: auto;
-    padding-top: 1.5rem;
-    border-top: 1px solid rgba(255, 255, 255, 0.05);
-    display: flex;
-    align-items: center;
-    gap: 0.75rem;
-    color: var(--text-muted);
-    font-size: 0.85rem;
-}
-
-/* Animations */
-@keyframes fadeIn {
-    from {
-        opacity: 0;
-        transform: translateY(10px);
-    }
-
-    to {
-        opacity: 1;
-        transform: translateY(0);
-    }
-}
-
-.view-section {
-    animation: fadeIn 0.4s ease-out;
-    width: 100%;
-    height: 100%;
-}