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.gitignore
vendored
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.gitignore
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__pycache__
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workspace
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RUN_STREAMLIT.md
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RUN_STREAMLIT.md
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# Streamlit 运行说明
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## 📂 生成的代码在哪里？
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当您运行 `streamlit run frontend/streamlit_app_v3.py` 并启动 SDLC 工作流后，所有生成的文件都保存在：
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```
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c:\Workspace\AI_AutoGen\workspace\
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```
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## 📁 目录结构
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```
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c:\Workspace\AI_AutoGen/
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├── workspace/ ← 生成的代码在这里！
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│ ├── SRS.md # 软件需求规格说明书
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│ ├── test_battery_health.py # 测试用例
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│ ├── src_battery_health.py # 源代码
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│ ├── bdd_scenarios.md # BDD 测试场景
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│ ├── coverage_report.md # 测试覆盖率报告
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│ └── FINAL_REPORT.md # 最终项目报告
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├── logs/ ← 对话日志
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│ └── session_*.jsonl # 会话日志
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└── frontend/
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└── streamlit_app_v3.py
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```
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## 🔍 如何查看生成的文件
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### 方法 1: 在 Streamlit 界面查看（推荐）
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运行 Streamlit 后，在界面右侧边栏会显示：
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- **"生成的文件"** 区域
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- 点击文件名可以预览内容
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- 支持查看 `.md`, `.py`, `.txt` 等格式
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### 方法 2: 直接在文件管理器查看
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**Windows:**
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```powershell
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# 打开 workspace 目录
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explorer c:\Workspace\AI_AutoGen\workspace
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```
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**命令行查看:**
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```bash
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# 查看所有生成的文件
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dir c:\Workspace\AI_AutoGen\workspace
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# 查看 SRS 文档
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type c:\Workspace\AI_AutoGen\workspace\SRS.md
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# 查看源代码
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type c:\Workspace\AI_AutoGen\workspace\src_battery_health.py
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```
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### 方法 3: 使用 Python 脚本查看
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创建一个快速查看脚本：
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```python
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# view_generated_files.py
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from pathlib import Path
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workspace = Path("workspace")
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if workspace.exists():
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print("生成的文件列表:")
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for file in workspace.glob("*"):
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if file.is_file():
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print(f" 📄 {file.name} ({file.stat().st_size:,} bytes)")
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else:
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print("workspace 目录不存在，请先运行 SDLC 工作流")
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```
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## 🎯 典型生成的文件
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运行一次完整的 SDLC 工作流后，通常会生成以下文件：
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| 文件名 | 类型 | 说明 | 生成 Agent |
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|--------|------|------|-----------|
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| `SRS.md` | Markdown | 软件需求规格说明书 | PM Agent |
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| `test_*.py` | Python | 测试用例脚本 | QA Agent |
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| `src_*.py` | Python | 源代码实现 | Dev Agent |
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| `bdd_scenarios.md` | Markdown | BDD 测试场景 | QA Agent |
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| `coverage_report.md` | Markdown | 测试覆盖率报告 | QA Agent |
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| `FINAL_REPORT.md` | Markdown | 最终项目总结 | Orchestrator |
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## 💡 示例：查看生成的代码
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假设您运行了"电池健康预测 API"的示例，生成的代码会在：
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**源代码位置:**
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```
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c:\Workspace\AI_AutoGen\workspace\src_battery_health.py
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```
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**测试代码位置:**
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```
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c:\Workspace\AI_AutoGen\workspace\test_battery_health.py
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```
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**需求文档位置:**
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```
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c:\Workspace\AI_AutoGen\workspace\SRS.md
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```
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## 🔧 在 Streamlit 中添加文件查看器
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如果想要在 Streamlit 界面中直接查看生成的文件，可以在 `streamlit_app_v3.py` 中添加以下代码：
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```python
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# 在 sidebar 中添加
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st.sidebar.subheader("📁 生成的文件")
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workspace_dir = Path("workspace")
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if workspace_dir.exists():
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files = list(workspace_dir.glob("*"))
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for file in files:
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if file.is_file():
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with st.sidebar.expander(f"📄 {file.name}"):
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try:
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content = file.read_text(encoding='utf-8')
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st.code(content[:1000] + ("..." if len(content) > 1000 else ""))
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# 下载按钮
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st.download_button(
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label="⬇️ 下载",
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data=content,
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file_name=file.name,
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mime="text/plain"
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)
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except Exception as e:
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st.error(f"读取失败：{e}")
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else:
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st.sidebar.info("工作目录为空，请先运行工作流")
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```
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## ⚠️ 注意事项
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1. **首次运行会创建目录** - workspace 目录会在第一次运行时自动创建
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2. **文件会覆盖** - 每次运行新的需求会覆盖之前的文件
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3. **及时备份** - 重要的生成物请及时复制到其他目录
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4. **日志目录** - 对话历史保存在 `logs/` 目录，格式为 JSONL
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## 📊 查看对话日志
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对话日志保存在 `logs/` 目录：
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```bash
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# 查看最新的会话日志
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dir c:\Workspace\AI_AutoGen\logs\session_*.jsonl
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# 使用 Python 查看
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python -c "import json; [print(json.loads(line)) for line in open('logs/session_*.jsonl')]"
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```
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---
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**🎉 现在您知道生成的代码在哪里了！**
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运行 `streamlit run frontend/streamlit_app_v3.py` 后，所有生成的文件都会出现在 `workspace/` 目录中。
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@@ -411,6 +411,74 @@ def display_chat_flow():
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""", unsafe_allow_html=True)
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def save_generated_files():
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"""从对话中提取并保存生成的文件到 workspace 目录"""
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workspace_dir = Path("workspace")
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workspace_dir.mkdir(parents=True, exist_ok=True)
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files_saved = []
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# 遍历所有消息，提取文件内容
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for msg in st.session_state.messages:
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content = msg.get("content", "")
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agent_key = msg.get("agent_key", "")
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# PM Agent 生成 SRS.md
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if agent_key == "PM_Agent" and ("SRS" in content or "软件需求规格" in content):
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srs_file = workspace_dir / "SRS.md"
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# 提取 SRS 内容（查找包含 FR- 或 NFR- 的段落）
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srs_content = content
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if "功能性需求" in content:
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srs_content = content[content.find("功能性需求"):]
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with open(srs_file, 'w', encoding='utf-8') as f:
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f.write(f"# 软件需求规格说明书 (SRS)\n\n")
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f.write(f"**生成时间**: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n")
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f.write(srs_content)
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files_saved.append(str(srs_file))
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# QA Agent 生成测试文件
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if agent_key == "QA_Agent" and ("test_" in content or "def test_" in content):
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test_file = workspace_dir / "test_battery_health.py"
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# 提取 Python 代码
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if "```python" in content:
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code = content.split("```python")[1].split("```")[0]
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else:
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code = content
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with open(test_file, 'w', encoding='utf-8') as f:
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f.write(f'"""\n电池健康状态测试用例\n生成时间：{datetime.now().strftime("%Y-%m-%d %H:%M:%S")}\n"""\n\n')
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f.write(code)
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files_saved.append(str(test_file))
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# Dev Agent 生成源代码
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if agent_key == "Dev_Agent" and ("def " in content or "class " in content):
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src_file = workspace_dir / "src_battery_health.py"
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# 提取 Python 代码
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if "```python" in content:
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code = content.split("```python")[1].split("```")[0]
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else:
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code = content
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with open(src_file, 'w', encoding='utf-8') as f:
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f.write(f'"""\n电池健康状态计算模块\n生成时间：{datetime.now().strftime("%Y-%m-%d %H:%M:%S")}\n"""\n\n')
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f.write(code)
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files_saved.append(str(src_file))
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# Orchestrator 生成最终报告
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if agent_key == "Orchestrator" and ("完成" in content and "SDLC" in content):
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report_file = workspace_dir / "FINAL_REPORT.md"
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with open(report_file, 'w', encoding='utf-8') as f:
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f.write(f"# SDLC 项目最终报告\n\n")
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f.write(f"**生成时间**: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n")
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f.write("## 项目概述\n\n")
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f.write("基于 AutoGen 多智能体系统完成的软件交付项目。\n\n")
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f.write("## 生成文件列表\n\n")
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for i, saved_file in enumerate(files_saved, 1):
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f.write(f"{i}. {saved_file}\n")
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f.write(f"\n## 项目总结\n\n{content}\n")
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files_saved.append(str(report_file))
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return files_saved
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def create_agents(api_key: str, base_url: str, model: str):
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"""创建所有 Agent"""
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llm_config = get_llm_config(model=model, api_key=api_key, base_url=base_url)
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@@ -526,6 +594,34 @@ def main():
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mime="application/json"
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)
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st.divider()
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# 显示生成的文件
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st.subheader("📁 生成的文件")
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workspace_dir = Path("workspace")
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if workspace_dir.exists():
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files = list(workspace_dir.glob("*"))
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if files:
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for file in files:
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if file.is_file():
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with st.expander(f"📄 {file.name}"):
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try:
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content = file.read_text(encoding='utf-8')
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st.code(content[:500] + ("..." if len(content) > 500 else ""))
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st.download_button(
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label="⬇️ 下载",
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data=content,
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file_name=file.name,
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mime="text/plain",
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key=f"download_{file.name}"
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)
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except Exception as e:
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st.error(f"读取失败：{e}")
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else:
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st.info("工作目录为空，请先运行工作流")
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else:
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st.info("工作目录不存在")
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# 主界面
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display_agent_status_row()
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st.divider()
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# 完成
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add_message("Orchestrator", "✅ SDLC 流程完成！所有任务已完成。", "总结完成")
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progress_placeholder.success("✅ SDLC 工作流完成！查看上方的对话流了解详情。")
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# 保存生成的文件
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progress_placeholder.info("💾 正在保存生成的文件...")
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saved_files = save_generated_files()
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if saved_files:
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progress_placeholder.success(f"✅ SDLC 工作流完成！已保存 {len(saved_files)} 个文件到 workspace/ 目录")
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else:
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progress_placeholder.success("✅ SDLC 工作流完成！查看上方的对话流了解详情。")
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st.session_state.is_running = False
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st.rerun()
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Reference in New Issue
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