feat: 添加AutoFlow毕业设计项目

Co-creation-projects/usernamedadad-AutoFlow/.gitignore

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+# Environment
+.env
+.env.local
+.env.*.local
+
+# Python
+__pycache__/
+*.py[cod]
+*.pyo
+*.pyd
+.Python
+*.so
+*.egg
+*.egg-info/
+dist/
+build/
+*.egg
+
+# Node
+node_modules/
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+.pnpm-debug.log*
+
+# Build outputs
+dist/
+dist-ssr/
+*.local
+.vite/
+
+# IDE
+.idea/
+.vscode/
+*.swp
+*.swo
+*~
+
+# OS
+.DS_Store
+Thumbs.db
+
+# Logs
+logs/
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+
+# Testing
+coverage/
+.nyc_output/
+
+# Memory / Runtime
+memory/
+*.trace
+*.traces
+
+# Secrets
+*.pem
+*.key
+credentials.json
+service-account.json

Co-creation-projects/usernamedadad-AutoFlow/README.md

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+# 智能流程图生成工具(AutoFlow)
+
+> 智能流程图生成工具：从自然语言到 Mermaid，一键生成并实时预览。
+
+## 📝 项目简介
+
+AutoFlow 是一个前后端分离的流程图生成项目，目标是把用户的想法、需求或计划文本，快速转换为可渲染的 Mermaid 流程图。
+
+它主要解决三个问题：
+
+- 文本到流程图转换效率低
+- 手写 Mermaid 成本高、容易出错
+- 流程表达缺少统一结构和可视化反馈
+
+适用场景：
+
+- 需求梳理与方案沟通
+- 产品/运营流程设计
+- 教学与知识结构化表达
+- 项目任务流可视化
+
+## ✨ 核心功能
+
+- 灵感模式：输入想法，自动补全并生成流程图
+- 标准模式：先优化提示词，再生成 Mermaid 代码
+- 计划模式：按行输入步骤，生成线性流程图
+- Mermaid 代码模式：直接输入代码并实时渲染
+- 方向切换与预览操作：支持上到下/左到右、缩放、拖拽、导出
+
+## 🛠️ 技术栈
+
+- 智能体框架：HelloAgents
+- 后端：FastAPI + SSE 流式返回
+- 前端：React + Vite + Mermaid
+- 核心能力：提示词优化、结构化生成、语法校验与修复
+
+## 📁 项目结构
+
+```
+usernamedadad-AutoFlow/
+├── backend/                    # 后端代码
+│   ├── app/
+│   │   ├── agents/             # 智能体模块
+│   │   │   └── mermaid/        # Mermaid 生成智能体
+│   │   ├── models/             # 数据模型
+│   │   ├── prompts/            # 提示词模板
+│   │   ├── routers/            # API 路由
+│   │   ├── services/           # 业务服务
+│   │   └── tools/              # 工具函数
+│   ├── .env.example            # 环境变量示例
+│   └── requirements.txt        # Python 依赖
+├── frontend/                   # 前端代码
+│   ├── src/
+│   │   ├── services/           # API 服务
+│   │   ├── styles/             # 样式文件
+│   │   ├── App.jsx             # 主组件
+│   │   └── main.jsx            # 入口文件
+│   ├── index.html
+│   ├── package.json
+│   └── vite.config.js
+├── data/                       # 数据资源
+│   └── images/                 # 示例图片
+├── README.md
+└── .gitignore
+```
+
+## 🚀 快速开始
+
+### 环境要求
+
+- Python 3.10+
+- Node.js 18+
+- npm 9+
+
+### 安装依赖
+
+后端（进入后端对应目录）：
+
+```bash
+pip install -r requirements.txt
+```
+
+前端（进入前端对应目录）：
+
+```bash
+npm install
+```
+
+### 配置 API 密钥
+
+在 backend 目录创建 .env（可参考 .env.example），至少配置：
+
+- LLM\_MODEL\_ID
+- LLM\_API\_KEY
+- LLM\_BASE\_URL
+- LLM\_TIMEOUT
+
+### 运行项目
+
+1. 启动后端（进入后端对应目录）
+
+```bash
+uvicorn app.main:app --reload --host 0.0.0.0 --port 8000
+```
+
+1. 启动前端（进入前端对应目录）
+
+```bash
+npm run dev
+```
+
+1. 浏览器打开前端地址（默认）
+
+- <http://localhost:5173>
+
+
+## 📖 使用示例
+
+### 灵感模式示例
+
+输入示例：
+
+```text
+洛阳三日游计划
+```
+
+效果示例：
+
+![灵感模式示例](data/images/demo-inspire-mode.png)
+
+### 创造（标准）模式示例
+
+输入示例：
+
+```text
+我打算做一个AutoFlow产品，它的主要作用是根据自然语言生成流程图，它有灵感模式、标准模式、计划模式，Mermaid代码模式，它的主要作用是根据自然语言生成流程图，打算用两天时间完成开，完成后上传到GitHub。
+```
+
+效果示例：
+
+![创造模式示例](data/images/demo-create-mode.png)
+
+通用操作：
+
+1. 点击发送，等待流式生成
+2. 在右侧预览区切换方向（上到下/左到右）
+3. 按需缩放并导出 .mmd / SVG
+
+## 🎯 项目亮点
+
+- 采用 HelloAgents 构建智能体流程，具备可扩展性
+- 生成链路包含“优化 -> 生成 -> 校验”闭环
+- 前后端解耦，交互体验流畅，支持实时状态反馈
+
+## 🔮 未来计划
+
+- 增加更细粒度的生成风格控制
+- 引入流程图模板库与行业预设
+- 优化超时场景下的降级策略与重试机制
+
+## 🤝 贡献指南
+
+欢迎提交 Issue 和 Pull Request。
+
+建议流程：
+
+- 新建分支
+- 提交改动与说明
+- 发起 PR 并描述测试结果
+
+## 📄 许可证
+
+MIT License
+
+## 🙏 致谢
+
+感谢 Datawhale 社区与 HelloAgents 项目。

Co-creation-projects/usernamedadad-AutoFlow/backend/.env.example

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+APP_NAME=AutoFlow API
+APP_ENV=dev
+APP_HOST=0.0.0.0
+APP_PORT=8000
+CORS_ORIGINS=http://localhost:5173
+
+LLM_MODEL_ID=your-model-name
+LLM_API_KEY=your-api-key
+LLM_BASE_URL=your-api-base-url
+LLM_TIMEOUT=60
+
+AGENT_MAX_STEPS=6
+VALIDATOR_MAX_RETRIES=2

Co-creation-projects/usernamedadad-AutoFlow/backend/app/agents/mermaid/__init__.py

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+from .pipeline import MermaidPipeline
+from .agent_factory import build_agent
+from .code_utils import apply_direction, extract_mermaid, extract_optimized_text, prune_complexity
+
+__all__ = [
+    "MermaidPipeline",
+    "build_agent",
+    "apply_direction",
+    "extract_mermaid",
+    "extract_optimized_text",
+    "prune_complexity",
+]

Co-creation-projects/usernamedadad-AutoFlow/backend/app/agents/mermaid/agent_factory.py

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+from hello_agents import Config, SimpleAgent, ToolRegistry
+
+from app.prompts.standard_code_prompt import STANDARD_CODE_PROMPT
+from app.prompts.standard_prompt import STANDARD_PROMPT
+from app.prompts.inspire_prompt import INSPIRE_PROMPT
+from app.services.llm_service import LLMService
+from app.tools.mermaid_validator_tool import MermaidValidatorTool
+
+EXECUTION_HINT = "执行要求：先调用 MermaidValidatorTool 校验；若返回 INVALID 再修复并调用一次；最终仅输出 Mermaid 代码。"
+
+
+def _prompt_by_mode(mode: str) -> str:
+    if mode == "standard-code":
+        return STANDARD_CODE_PROMPT
+    if mode == "standard":
+        return STANDARD_PROMPT
+    return INSPIRE_PROMPT
+
+
+def _fast_config() -> Config:
+    return Config(
+        trace_enabled=False,
+        skills_enabled=False,
+        session_enabled=False,
+        subagent_enabled=False,
+        todowrite_enabled=False,
+        devlog_enabled=False,
+        stream_enabled=False,
+        enable_smart_compression=False,
+        temperature=0.2,
+    )
+
+
+def build_agent(mode: str, validator: MermaidValidatorTool) -> SimpleAgent:
+    registry = ToolRegistry()
+    registry.register_tool(validator)
+
+    return SimpleAgent(
+        name=f"plan2flow-{mode}-agent",
+        llm=LLMService.create_llm(),
+        system_prompt=f"{_prompt_by_mode(mode)}\n{EXECUTION_HINT}",
+        tool_registry=registry,
+        config=_fast_config(),
+        enable_tool_calling=True,
+        max_tool_iterations=2,
+    )

Co-creation-projects/usernamedadad-AutoFlow/backend/app/agents/mermaid/code_utils.py

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+import re
+
+
+def extract_mermaid(text: str) -> str:
+    if not text:
+        return ""
+
+    fenced = re.findall(r"```(?:mermaid)?\s*([\s\S]*?)```", text, flags=re.IGNORECASE)
+    if fenced:
+        return fenced[0].strip()
+
+    return text.strip()
+
+
+def extract_optimized_text(text: str) -> str:
+    if not text:
+        return ""
+
+    marker_start = "【优化后规范描述】"
+    marker_start_alt = "【优化后描述】"
+    marker_code = "【Mermaid 流程图代码】"
+
+    if marker_start in text and marker_code in text:
+        return text.split(marker_start, 1)[1].split(marker_code, 1)[0].strip()
+
+    if marker_start_alt in text and marker_code in text:
+        return text.split(marker_start_alt, 1)[1].split(marker_code, 1)[0].strip()
+
+    fenced_removed = re.sub(r"```(?:mermaid)?[\s\S]*?```", "", text, flags=re.IGNORECASE).strip()
+    fenced_removed = fenced_removed.replace(marker_start, "").replace(marker_start_alt, "").strip()
+    fenced_removed = fenced_removed.replace(marker_code, "").strip()
+    return fenced_removed
+
+
+def prune_complexity(code: str, mode: str) -> str:
+    if mode == "standard":
+        return code
+
+    lines = [ln.rstrip() for ln in code.splitlines() if ln.strip()]
+    if not lines:
+        return code
+
+    head = lines[0]
+    body = lines[1:]
+
+    max_lines = 12 if mode == "standard" else 11
+    if len(body) > max_lines:
+        body = body[:max_lines]
+
+    return "\n".join([head] + body)
+
+
+def apply_direction(code: str, direction: str) -> str:
+    normalized = "LR" if str(direction).upper() == "LR" else "TD"
+    if not code:
+        return code
+
+    lines = code.splitlines()
+    if not lines:
+        return code
+
+    first_idx = None
+    for idx, line in enumerate(lines):
+        if line.strip():
+            first_idx = idx
+            break
+
+    if first_idx is None:
+        return code
+
+    first_line = lines[first_idx].strip()
+    if re.match(r"^(flowchart|graph)\s+(TD|LR|TB|BT|RL)\b", first_line, flags=re.IGNORECASE):
+        lines[first_idx] = re.sub(
+            r"^(flowchart|graph)\s+(TD|LR|TB|BT|RL)\b",
+            rf"\1 {normalized}",
+            lines[first_idx],
+            flags=re.IGNORECASE,
+        )
+        return "\n".join(lines)
+
+    if re.match(r"^(flowchart|graph)\b", first_line, flags=re.IGNORECASE):
+        lines[first_idx] = re.sub(
+            r"^(flowchart|graph)\b",
+            rf"\1 {normalized}",
+            lines[first_idx],
+            flags=re.IGNORECASE,
+        )
+        return "\n".join(lines)
+
+    return f"flowchart {normalized}\n{code}"

Co-creation-projects/usernamedadad-AutoFlow/backend/app/agents/mermaid/pipeline.py

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+from typing import Any, Dict
+
+from app.config import settings
+from app.prompts.standard_prompt import STANDARD_PROMPT
+from app.services.llm_service import LLMService
+from app.tools.mermaid_validator_tool import MermaidValidatorTool
+
+from .agent_factory import build_agent
+from .code_utils import extract_mermaid, extract_optimized_text
+
+
+class MermaidPipeline:
+    def __init__(self, validator: MermaidValidatorTool):
+        self.validator = validator
+
+    def generate_once(self, mode: str, prompt: str) -> str:
+        agent = build_agent(mode, self.validator)
+        agent.clear_history()
+        result_text = agent.run(prompt)
+        return extract_mermaid(result_text)
+
+    def generate_standard(self, prompt: str) -> Dict[str, str]:
+        optimize_messages = [
+            {
+                "role": "system",
+                "content": (
+                    STANDARD_PROMPT
+                    + "\n补充要求：你现在只执行【第一步：文本优化】。"
+                      "只输出优化后的完整文本，不要输出标题，不要输出Mermaid代码，不要代码块。"
+                ),
+            },
+            {"role": "user", "content": prompt},
+        ]
+        optimized_resp = LLMService.create_llm().invoke(optimize_messages)
+        optimized_text = extract_optimized_text(optimized_resp.content)
+        source_text = optimized_text.strip() or (optimized_resp.content or "").strip()
+
+        code_agent = build_agent("standard-code", self.validator)
+        code_agent.clear_history()
+        raw_code_text = code_agent.run(source_text)
+
+        return {
+            "optimized_text": source_text,
+            "mermaid_code": extract_mermaid(raw_code_text),
+            "generated_from_optimized": bool(source_text),
+        }
+
+    def repair_once(self, bad_code: str, reason: str) -> str:
+        messages = [
+            {"role": "system", "content": "你是 Mermaid 修复器，只输出修复后的 Mermaid 代码。"},
+            {
+                "role": "user",
+                "content": (
+                    "请修复以下 Mermaid 代码并确保可渲染。"
+                    f"\n错误信息: {reason}\n\n代码:\n{bad_code}"
+                ),
+            },
+        ]
+        response = LLMService.create_llm().invoke(messages)
+        return extract_mermaid(response.content)
+
+    def post_validate(self, code: str) -> Dict[str, Any]:
+        current = code
+        attempts = 0
+        repair_limit = min(settings.validator_max_retries, 1)
+
+        while attempts <= repair_limit:
+            attempts += 1
+            result = self.validator.run({"code": current})
+            valid = bool(result.data.get("valid"))
+            fixed_code = result.data.get("fixed_code", current)
+
+            if valid:
+                return {
+                    "valid": True,
+                    "attempts": attempts,
+                    "mermaid_code": fixed_code,
+                    "message": "validated",
+                }
+
+            if attempts > repair_limit:
+                return {
+                    "valid": False,
+                    "attempts": attempts,
+                    "mermaid_code": fixed_code,
+                    "message": "; ".join(result.data.get("errors", [])) or "validate failed",
+                }
+
+            reason = "; ".join(result.data.get("errors", [])) or "unknown syntax issue"
+            current = self.repair_once(fixed_code, reason)
+
+        return {
+            "valid": False,
+            "attempts": attempts,
+            "mermaid_code": current,
+            "message": "validate failed",
+        }

Co-creation-projects/usernamedadad-AutoFlow/backend/app/agents/mermaid_agent_service.py

@@ -0,0 +1,74 @@
+import asyncio
+from typing import Any, AsyncGenerator, Dict
+
+from app.config import settings
+from app.agents.mermaid.code_utils import apply_direction, prune_complexity
+from app.agents.mermaid.pipeline import MermaidPipeline
+from app.tools.mermaid_validator_tool import MermaidValidatorTool
+
+
+class MermaidAgentService:
+    def __init__(self):
+        self.validator = MermaidValidatorTool()
+        self.pipeline = MermaidPipeline(self.validator)
+
+    async def stream_chat(self, mode: str, prompt: str, direction: str = "TD") -> AsyncGenerator[Dict[str, Any], None]:
+        yield {"type": "status", "phase": "start", "message": "开始生成"}
+        yield {"type": "status", "phase": "generating", "message": "模型生成中"}
+
+        try:
+            llm_timeout = max(30, int(settings.llm_timeout))
+            standard_timeout = llm_timeout * 2 + 20
+            single_timeout = llm_timeout + 20
+            validate_timeout = 20
+
+            optimized_text = ""
+            generated_from_optimized = False
+            if mode == "standard":
+                yield {"type": "status", "phase": "optimizing", "message": "文本优化中"}
+                standard_result = await asyncio.wait_for(
+                    asyncio.to_thread(self.pipeline.generate_standard, prompt), timeout=standard_timeout
+                )
+                optimized_text = standard_result.get("optimized_text", "")
+                raw_code = standard_result.get("mermaid_code", "")
+                generated_from_optimized = bool(standard_result.get("generated_from_optimized", False))
+                yield {"type": "status", "phase": "creating", "message": "基于优化文本生成流程图"}
+            else:
+                raw_code = await asyncio.wait_for(
+                    asyncio.to_thread(self.pipeline.generate_once, mode, prompt), timeout=single_timeout
+                )
+
+            extracted = prune_complexity(raw_code, mode)
+            extracted = apply_direction(extracted, direction)
+
+            yield {"type": "status", "phase": "validating", "message": "语法校验中"}
+            validation = await asyncio.wait_for(
+                asyncio.to_thread(self.pipeline.post_validate, extracted), timeout=validate_timeout
+            )
+
+            yield {
+                "type": "result",
+                "mode": mode,
+                "valid": validation["valid"],
+                "attempts": validation["attempts"],
+                "mermaid_code": validation["mermaid_code"],
+                "optimized_text": optimized_text,
+                "generated_from_optimized": generated_from_optimized,
+                "message": validation.get("message", ""),
+            }
+
+            yield {"type": "done"}
+        except asyncio.TimeoutError:
+            yield {
+                "type": "error",
+                "phase": "timeout",
+                "message": "生成超时，请简化输入后重试。",
+            }
+            yield {"type": "done"}
+        except Exception as exc:
+            yield {
+                "type": "error",
+                "phase": "exception",
+                "message": f"生成失败: {str(exc)}",
+            }
+            yield {"type": "done"}

Co-creation-projects/usernamedadad-AutoFlow/backend/app/config.py

@@ -0,0 +1,45 @@
+import os
+from dataclasses import dataclass
+from pathlib import Path
+
+from dotenv import load_dotenv
+
+
+BACKEND_ROOT = Path(__file__).resolve().parents[1]
+load_dotenv(BACKEND_ROOT / ".env")
+
+
+@dataclass
+class Settings:
+    app_name: str = "AutoFlow API"
+    app_env: str = "dev"
+    app_host: str = "0.0.0.0"
+    app_port: int = 8000
+    cors_origins: str = "*"
+
+    llm_model_id: str = ""
+    llm_api_key: str = ""
+    llm_base_url: str = ""
+    llm_timeout: int = 60
+
+    agent_max_steps: int = 6
+    validator_max_retries: int = 2
+
+    @classmethod
+    def from_env(cls) -> "Settings":
+        return cls(
+            app_name=os.getenv("APP_NAME", "AutoFlow API"),
+            app_env=os.getenv("APP_ENV", "dev"),
+            app_host=os.getenv("APP_HOST", "0.0.0.0"),
+            app_port=int(os.getenv("APP_PORT", "8000")),
+            cors_origins=os.getenv("CORS_ORIGINS", "*"),
+            llm_model_id=os.getenv("LLM_MODEL_ID", ""),
+            llm_api_key=os.getenv("LLM_API_KEY", ""),
+            llm_base_url=os.getenv("LLM_BASE_URL", ""),
+            llm_timeout=int(os.getenv("LLM_TIMEOUT", "60")),
+            agent_max_steps=int(os.getenv("AGENT_MAX_STEPS", "6")),
+            validator_max_retries=int(os.getenv("VALIDATOR_MAX_RETRIES", "2")),
+        )
+
+
+settings = Settings.from_env()

Co-creation-projects/usernamedadad-AutoFlow/backend/app/main.py

@@ -0,0 +1,36 @@
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+
+from app.config import settings
+from app.routers.plan import router as plan_router
+from app.routers.agent import router as agent_router
+
+
+app = FastAPI(title=settings.app_name)
+
+origins = [origin.strip() for origin in settings.cors_origins.split(",") if origin.strip()]
+if not origins:
+    origins = ["*"]
+
+origin_regex = None
+app_env = (settings.app_env or "").strip().lower()
+if app_env not in {"prod", "production"}:
+    # 非生产环境放宽到 localhost/127.0.0.1 任意端口，避免端口/主机名切换触发预检 400
+    origin_regex = r"^https?://(localhost|127\.0\.0\.1)(:\d+)?$"
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=origins,
+    allow_origin_regex=origin_regex,
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+app.include_router(plan_router)
+app.include_router(agent_router)
+
+
+@app.get("/health")
+def health_check():
+    return {"status": "ok", "service": settings.app_name}

Co-creation-projects/usernamedadad-AutoFlow/backend/app/models/schemas.py

@@ -0,0 +1,26 @@
+from typing import Literal, Optional
+from pydantic import BaseModel, Field
+
+
+class PlanRequest(BaseModel):
+    text: str = Field(..., description="按行输入的计划文本")
+    direction: Literal["TD", "LR"] = "TD"
+
+
+class PlanResponse(BaseModel):
+    mermaid_code: str
+
+
+class AgentChatRequest(BaseModel):
+    mode: Literal["standard", "inspire"]
+    prompt: str = Field(..., min_length=1)
+    direction: Literal["TD", "LR"] = "TD"
+
+
+class AgentChatResult(BaseModel):
+    mode: Literal["standard", "inspire"]
+    mermaid_code: str
+    optimized_text: Optional[str] = None
+    attempts: int
+    valid: bool
+    message: Optional[str] = None

Co-creation-projects/usernamedadad-AutoFlow/backend/app/prompts/inspire_prompt.py

@@ -0,0 +1,18 @@
+INSPIRE_PROMPT = """你是专业的Mermaid流程图创意专家。
+用户会输入一个简短主题，可能非常模糊。
+
+你的任务：
+1. 在不违背用户主题的前提下，进行合理的行业常识与逻辑补全。
+2. 自动识别场景类型（旅行、项目、产品、活动、计划、学习、工作等）。
+3. 自动构建多层结构：
+   - 根节点：用户主题
+   - 一级节点：阶段/模块/分类
+   - 二级节点：具体内容/任务/步骤
+4. 内容必须自然、合理、丰富，符合真实世界逻辑。
+5. 禁止编造不合理信息，只补充常识性内容。
+
+输出要求：
+1. 仅输出Mermaid代码，不要解释。
+2. 默认使用 flowchart TD。
+3. 结构清晰，层次分明，美观专业。
+"""

Co-creation-projects/usernamedadad-AutoFlow/backend/app/prompts/standard_code_prompt.py

@@ -0,0 +1,17 @@
+STANDARD_CODE_PROMPT = """你是专业的Mermaid流程图专家。
+请根据输入的规范文本生成标准Mermaid代码。
+
+严格约束：
+1. 仅输出 Mermaid 代码，不要解释。
+2. 识别核心主体作为根节点。
+3. 提取分类维度作为一级子节点。
+4. 二级节点内容遵循以下逻辑格式化：
+   - 当内容是对分类维度的**属性描述**时，使用「属性名：属性值」格式。
+   - 当内容是分类维度下的**成员项或枚举项**时，直接显示内容，不添加额外标签。
+5. 整体结构：核心主体 → 分类维度 → 智能格式化内容。
+6. 禁止省略任何关键信息。
+7. 默认使用 graph TD。
+8. 合理使用 subgraph 进行分组，结构清晰专业。
+9. 箭头连接逻辑正确、简洁美观。
+10. 代码语法完全正确，可直接渲染运行。
+"""

Co-creation-projects/usernamedadad-AutoFlow/backend/app/prompts/standard_prompt.py

@@ -0,0 +1,18 @@
+STANDARD_PROMPT = """你是信息结构化优化专家。
+
+你的唯一任务：
+在不改变原意的前提下，将用户输入的口语化、零散文本优化为：
+- 逻辑清晰、语句通顺
+- 结构完整、无冗余口语
+- 非常适合生成流程图的规范自然语言
+
+严格约束：
+1. 不改变原意。
+2. 不增加信息。
+3. 不减少信息。
+
+输出要求：
+1. 只输出优化后的完整文本。
+2. 不输出 Mermaid 代码。
+3. 不输出解释、说明、提问或对话。
+"""

Co-creation-projects/usernamedadad-AutoFlow/backend/app/routers/agent.py

@@ -0,0 +1,27 @@
+import json
+from fastapi import APIRouter
+from fastapi.responses import StreamingResponse
+
+from app.agents.mermaid_agent_service import MermaidAgentService
+from app.models.schemas import AgentChatRequest
+
+
+router = APIRouter(prefix="/api", tags=["agent"])
+agent_service = MermaidAgentService()
+
+
+@router.post("/agent/chat/stream")
+async def stream_agent_chat(payload: AgentChatRequest):
+    async def event_generator():
+        try:
+            async for event in agent_service.stream_chat(payload.mode, payload.prompt, payload.direction):
+                yield f"event: {event.get('type', 'message')}\n"
+                yield f"data: {json.dumps(event, ensure_ascii=False)}\n\n"
+        except Exception as exc:
+            error_event = {"type": "error", "message": f"流式服务异常: {str(exc)}"}
+            yield "event: error\n"
+            yield f"data: {json.dumps(error_event, ensure_ascii=False)}\n\n"
+            yield "event: done\n"
+            yield f"data: {json.dumps({'type': 'done'}, ensure_ascii=False)}\n\n"
+
+    return StreamingResponse(event_generator(), media_type="text/event-stream")

Co-creation-projects/usernamedadad-AutoFlow/backend/app/routers/plan.py

@@ -0,0 +1,13 @@
+from fastapi import APIRouter
+
+from app.models.schemas import PlanRequest, PlanResponse
+from app.services.plan_converter import PlanConverter
+
+
+router = APIRouter(prefix="/api", tags=["plan"])
+
+
+@router.post("/plan", response_model=PlanResponse)
+def create_plan(payload: PlanRequest) -> PlanResponse:
+    code = PlanConverter.to_mermaid(payload.text, payload.direction)
+    return PlanResponse(mermaid_code=code)

Co-creation-projects/usernamedadad-AutoFlow/backend/app/services/llm_service.py

@@ -0,0 +1,14 @@
+from hello_agents import HelloAgentsLLM
+from app.config import settings
+
+
+class LLMService:
+    @staticmethod
+    def create_llm() -> HelloAgentsLLM:
+        return HelloAgentsLLM(
+            model=settings.llm_model_id,
+            api_key=settings.llm_api_key,
+            base_url=settings.llm_base_url,
+            timeout=settings.llm_timeout,
+            temperature=0.3,
+        )

Co-creation-projects/usernamedadad-AutoFlow/backend/app/services/plan_converter.py

@@ -0,0 +1,34 @@
+from typing import List
+
+
+class PlanConverter:
+    @staticmethod
+    def _sanitize_lines(text: str) -> List[str]:
+        raw_lines = [line.strip() for line in text.splitlines()]
+        lines = [line for line in raw_lines if line]
+        return lines
+
+    @staticmethod
+    def to_mermaid(text: str, direction: str = "TD") -> str:
+        lines = PlanConverter._sanitize_lines(text)
+        if not lines:
+            return f"flowchart {direction}\n    A[空计划]"
+
+        # 支持单行 "A -> B -> C" 快捷输入
+        if len(lines) == 1 and "->" in lines[0]:
+            segments = [seg.strip() for seg in lines[0].split("->") if seg.strip()]
+            lines = segments
+
+        nodes = []
+        edges = []
+
+        for idx, label in enumerate(lines):
+            node_id = f"N{idx + 1}"
+            safe_label = label.replace('"', "'")
+            nodes.append(f"    {node_id}[\"{safe_label}\"]")
+            if idx > 0:
+                prev_id = f"N{idx}"
+                edges.append(f"    {prev_id} --> {node_id}")
+
+        body = "\n".join(nodes + edges)
+        return f"flowchart {direction}\n{body}"

Co-creation-projects/usernamedadad-AutoFlow/backend/app/tools/mermaid_validator_tool.py

@@ -0,0 +1,102 @@
+import re
+from typing import Any, Dict, List
+
+from hello_agents.tools.base import Tool, ToolParameter
+from hello_agents.tools.response import ToolResponse
+from hello_agents.tools.errors import ToolErrorCode
+
+
+MERMAID_PREFIXES = (
+    "flowchart",
+    "graph",
+    "sequenceDiagram",
+    "classDiagram",
+    "stateDiagram",
+    "erDiagram",
+    "journey",
+    "gantt",
+    "pie",
+    "gitGraph",
+    "mindmap",
+    "timeline",
+)
+
+
+class MermaidValidatorTool(Tool):
+    def __init__(self):
+        super().__init__(
+            name="MermaidValidatorTool",
+            description="校验并修复 Mermaid 代码，返回可渲染代码",
+        )
+
+    def get_parameters(self) -> List[ToolParameter]:
+        return [
+            ToolParameter(
+                name="code",
+                type="string",
+                description="待校验的 Mermaid 代码",
+                required=True,
+            )
+        ]
+
+    def run(self, parameters: Dict[str, Any]) -> ToolResponse:
+        code = str(parameters.get("code", "")).strip()
+        if not code:
+            return ToolResponse.error(
+                code=ToolErrorCode.INVALID_PARAM,
+                message="code 参数不能为空",
+            )
+
+        normalized = self._normalize(code)
+        valid, errors = self._validate_structure(normalized)
+
+        if valid:
+            return ToolResponse.success(
+                text=f"VALID\n{normalized}",
+                data={"valid": True, "fixed_code": normalized, "errors": []},
+            )
+
+        return ToolResponse.partial(
+            text=f"INVALID\n{normalized}\n错误: {'; '.join(errors)}",
+            data={"valid": False, "fixed_code": normalized, "errors": errors},
+        )
+
+    def _normalize(self, code: str) -> str:
+        code = code.strip()
+        code = code.replace("```mermaid", "").replace("```", "").strip()
+        code = code.replace("→", "-->")
+
+        lines = [ln.rstrip() for ln in code.splitlines() if ln.strip()]
+        if not lines:
+            return "flowchart TD\n    A[空图]"
+
+        first = lines[0].strip()
+        if not first.startswith(MERMAID_PREFIXES):
+            # 兜底为 flowchart
+            lines.insert(0, "flowchart TD")
+
+        return "\n".join(lines)
+
+    def _validate_structure(self, code: str):
+        errors = []
+        lines = code.splitlines()
+
+        if not lines:
+            return False, ["代码为空"]
+
+        first = lines[0].strip()
+        if not first.startswith(MERMAID_PREFIXES):
+            errors.append("缺少 Mermaid 图类型声明")
+
+        bracket_pairs = [("(", ")"), ("[", "]"), ("{", "}")]
+        for left, right in bracket_pairs:
+            if code.count(left) != code.count(right):
+                errors.append(f"括号不匹配: {left}{right}")
+
+        # flowchart 常见错误：仅有声明但无节点
+        if first.startswith(("flowchart", "graph")):
+            has_node = any(re.search(r"\w+\s*-->|\w+\[|\w+\(|\w+\{", ln) for ln in lines[1:])
+            if not has_node:
+                errors.append("flowchart 缺少节点或连线")
+
+        return len(errors) == 0, errors

Co-creation-projects/usernamedadad-AutoFlow/backend/requirements.txt

@@ -0,0 +1,8 @@
+fastapi==0.115.0
+uvicorn[standard]==0.30.6
+pydantic==2.9.2
+python-dotenv==1.0.1
+sse-starlette==2.1.3
+hello-agents=1.0.0
+
+

Co-creation-projects/usernamedadad-AutoFlow/frontend/.env.example

@@ -0,0 +1 @@
+VITE_API_BASE_URL=http://localhost:8000

Co-creation-projects/usernamedadad-AutoFlow/frontend/index.html

@@ -0,0 +1,18 @@
+<!doctype html>
+<html lang="zh-CN">
+  <head>
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <title>AutoFlow</title>
+    <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=IBM+Plex+Sans:wght@400;500;600;700&family=Space+Grotesk:wght@500;700&display=swap"
+      rel="stylesheet"
+    />
+  </head>
+  <body>
+    <div id="root"></div>
+    <script type="module" src="/src/main.jsx"></script>
+  </body>
+</html>

Co-creation-projects/usernamedadad-AutoFlow/frontend/package-lock.json

@@ -0,0 +1,2929 @@
+{
+  "name": "plan2flow-frontend",
+  "version": "0.1.0",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "plan2flow-frontend",
+      "version": "0.1.0",
+      "dependencies": {
+        "mermaid": "^11.1.1",
+        "react": "^18.3.1",
+        "react-dom": "^18.3.1"
+      },
+      "devDependencies": {
+        "@vitejs/plugin-react": "^4.3.1",
+        "vite": "^5.4.8"
+      }
+    },
+    "node_modules/@antfu/install-pkg": {
+      "version": "1.1.0",
+      "resolved": "https://registry.npmjs.org/@antfu/install-pkg/-/install-pkg-1.1.0.tgz",
+      "integrity": "sha512-MGQsmw10ZyI+EJo45CdSER4zEb+p31LpDAFp2Z3gkSd1yqVZGi0Ebx++YTEMonJy4oChEMLsxZ64j8FH6sSqtQ==",
+      "license": "MIT",
+      "dependencies": {
+        "package-manager-detector": "^1.3.0",
+        "tinyexec": "^1.0.1"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/antfu"
+      }
+    },
+    "node_modules/@babel/code-frame": {
+      "version": "7.29.0",
+      "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.29.0.tgz",
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+      }
+    },
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+      }
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+        "stylus": "*",
+        "sugarss": "*",
+        "terser": "^5.4.0"
+      },
+      "peerDependenciesMeta": {
+        "@types/node": {
+          "optional": true
+        },
+        "less": {
+          "optional": true
+        },
+        "lightningcss": {
+          "optional": true
+        },
+        "sass": {
+          "optional": true
+        },
+        "sass-embedded": {
+          "optional": true
+        },
+        "stylus": {
+          "optional": true
+        },
+        "sugarss": {
+          "optional": true
+        },
+        "terser": {
+          "optional": true
+        }
+      }
+    },
+    "node_modules/vscode-jsonrpc": {
+      "version": "8.2.0",
+      "resolved": "https://registry.npmjs.org/vscode-jsonrpc/-/vscode-jsonrpc-8.2.0.tgz",
+      "integrity": "sha512-C+r0eKJUIfiDIfwJhria30+TYWPtuHJXHtI7J0YlOmKAo7ogxP20T0zxB7HZQIFhIyvoBPwWskjxrvAtfjyZfA==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=14.0.0"
+      }
+    },
+    "node_modules/vscode-languageserver": {
+      "version": "9.0.1",
+      "resolved": "https://registry.npmjs.org/vscode-languageserver/-/vscode-languageserver-9.0.1.tgz",
+      "integrity": "sha512-woByF3PDpkHFUreUa7Hos7+pUWdeWMXRd26+ZX2A8cFx6v/JPTtd4/uN0/jB6XQHYaOlHbio03NTHCqrgG5n7g==",
+      "license": "MIT",
+      "dependencies": {
+        "vscode-languageserver-protocol": "3.17.5"
+      },
+      "bin": {
+        "installServerIntoExtension": "bin/installServerIntoExtension"
+      }
+    },
+    "node_modules/vscode-languageserver-protocol": {
+      "version": "3.17.5",
+      "resolved": "https://registry.npmjs.org/vscode-languageserver-protocol/-/vscode-languageserver-protocol-3.17.5.tgz",
+      "integrity": "sha512-mb1bvRJN8SVznADSGWM9u/b07H7Ecg0I3OgXDuLdn307rl/J3A9YD6/eYOssqhecL27hK1IPZAsaqh00i/Jljg==",
+      "license": "MIT",
+      "dependencies": {
+        "vscode-jsonrpc": "8.2.0",
+        "vscode-languageserver-types": "3.17.5"
+      }
+    },
+    "node_modules/vscode-languageserver-textdocument": {
+      "version": "1.0.12",
+      "resolved": "https://registry.npmjs.org/vscode-languageserver-textdocument/-/vscode-languageserver-textdocument-1.0.12.tgz",
+      "integrity": "sha512-cxWNPesCnQCcMPeenjKKsOCKQZ/L6Tv19DTRIGuLWe32lyzWhihGVJ/rcckZXJxfdKCFvRLS3fpBIsV/ZGX4zA==",
+      "license": "MIT"
+    },
+    "node_modules/vscode-languageserver-types": {
+      "version": "3.17.5",
+      "resolved": "https://registry.npmjs.org/vscode-languageserver-types/-/vscode-languageserver-types-3.17.5.tgz",
+      "integrity": "sha512-Ld1VelNuX9pdF39h2Hgaeb5hEZM2Z3jUrrMgWQAu82jMtZp7p3vJT3BzToKtZI7NgQssZje5o0zryOrhQvzQAg==",
+      "license": "MIT"
+    },
+    "node_modules/vscode-uri": {
+      "version": "3.1.0",
+      "resolved": "https://registry.npmjs.org/vscode-uri/-/vscode-uri-3.1.0.tgz",
+      "integrity": "sha512-/BpdSx+yCQGnCvecbyXdxHDkuk55/G3xwnC0GqY4gmQ3j+A+g8kzzgB4Nk/SINjqn6+waqw3EgbVF2QKExkRxQ==",
+      "license": "MIT"
+    },
+    "node_modules/yallist": {
+      "version": "3.1.1",
+      "resolved": "https://registry.npmjs.org/yallist/-/yallist-3.1.1.tgz",
+      "integrity": "sha512-a4UGQaWPH59mOXUYnAG2ewncQS4i4F43Tv3JoAM+s2VDAmS9NsK8GpDMLrCHPksFT7h3K6TOoUNn2pb7RoXx4g==",
+      "dev": true,
+      "license": "ISC"
+    }
+  }
+}

Co-creation-projects/usernamedadad-AutoFlow/frontend/package.json

@@ -0,0 +1,20 @@
+{
+  "name": "plan2flow-frontend",
+  "version": "0.1.0",
+  "private": true,
+  "type": "module",
+  "scripts": {
+    "dev": "vite",
+    "build": "vite build",
+    "preview": "vite preview"
+  },
+  "dependencies": {
+    "react": "^18.3.1",
+    "react-dom": "^18.3.1",
+    "mermaid": "^11.1.1"
+  },
+  "devDependencies": {
+    "@vitejs/plugin-react": "^4.3.1",
+    "vite": "^5.4.8"
+  }
+}

Co-creation-projects/usernamedadad-AutoFlow/frontend/src/App.jsx

@@ -0,0 +1,432 @@
+import { useEffect, useMemo, useRef, useState } from "react";
+import { buildPlan, streamAgentChat } from "./services/api";
+import { renderMermaid } from "./services/mermaid";
+
+const MODES = [
+  { key: "inspire", label: "灵感模式" },
+  { key: "standard", label: "标准模式" },
+  { key: "plan", label: "计划模式" },
+  { key: "code", label: "Mermaid 代码模式" },
+];
+
+const DIRECTION_OPTIONS = [
+  { key: "TD", label: "上到下" },
+  { key: "LR", label: "左到右" },
+];
+
+const MODE_PLACEHOLDER = {
+  plan: "按行输入流程步骤，例如:\n开始\n数据清洗\n模型训练\n结束",
+  code: "直接输入 Mermaid 代码",
+  standard: "请开始输入...",
+  inspire: "请开始输入...",
+};
+
+const CHAT_EMPTY_TEXT = {
+  standard: "告诉我你的需求，我来帮你优化提示词并生成流程图。",
+  inspire: "告诉我你的灵感或想法，我来帮你完善并生成流程图。",
+};
+
+const ASSISTANT_PREFIX = {
+  standard: "根据你的需求生成的流程图代码：",
+  inspire: "根据你的灵感生成的流程图代码：",
+};
+
+function downloadText(filename, content) {
+  const blob = new Blob([content], { type: "text/plain;charset=utf-8" });
+  const url = URL.createObjectURL(blob);
+  const a = document.createElement("a");
+  a.href = url;
+  a.download = filename;
+  a.click();
+  URL.revokeObjectURL(url);
+}
+
+export default function App() {
+  const [mode, setMode] = useState("plan");
+  const [direction, setDirection] = useState("TD");
+  const [input, setInput] = useState("");
+  const [chatInput, setChatInput] = useState("");
+  const [mermaidCode, setMermaidCode] = useState("flowchart TD\n    A[AutoFlow] --> B[就绪]");
+  const [svg, setSvg] = useState("");
+  const [error, setError] = useState("");
+  const [statusText, setStatusText] = useState("等待生成");
+  const [loading, setLoading] = useState(false);
+  const [chatMap, setChatMap] = useState({ standard: [], inspire: [] });
+  const [thinkingMap, setThinkingMap] = useState({ standard: false, inspire: false });
+  const [zoom, setZoom] = useState(1);
+  const previewRef = useRef(null);
+  const dragStateRef = useRef({ dragging: false, startX: 0, startY: 0, startLeft: 0, startTop: 0 });
+
+  const isChatMode = mode === "standard" || mode === "inspire";
+
+  const currentChat = chatMap[mode] || [];
+  const isThinking = thinkingMap[mode] || false;
+
+  const pushChatMessage = (targetMode, message) => {
+    setChatMap((prev) => ({
+      ...prev,
+      [targetMode]: [...(prev[targetMode] || []), message],
+    }));
+  };
+
+  const canGenerate = useMemo(() => {
+    if (isChatMode) return chatInput.trim().length > 0;
+    if (mode === "code") return mermaidCode.trim().length > 0;
+    return input.trim().length > 0;
+  }, [mode, input, mermaidCode, chatInput, isChatMode]);
+
+  const applyDirectionToCode = (code, targetDirection) => {
+    const raw = (code || "").trim();
+    if (!raw) return "";
+
+    const normalized = targetDirection === "LR" ? "LR" : "TD";
+    const lines = raw.split("\n");
+    const firstIdx = lines.findIndex((line) => line.trim().length > 0);
+    if (firstIdx === -1) return raw;
+
+    const firstLine = lines[firstIdx];
+    if (/^(flowchart|graph)\s+(TD|LR|TB|BT|RL)\b/i.test(firstLine.trim())) {
+      lines[firstIdx] = firstLine.replace(/^(\s*)(flowchart|graph)\s+(TD|LR|TB|BT|RL)\b/i, `$1$2 ${normalized}`);
+      return lines.join("\n");
+    }
+
+    if (/^(flowchart|graph)\b/i.test(firstLine.trim())) {
+      lines[firstIdx] = firstLine.replace(/^(\s*)(flowchart|graph)\b/i, `$1$2 ${normalized}`);
+      return lines.join("\n");
+    }
+
+    return `flowchart ${normalized}\n${raw}`;
+  };
+
+  const previewMermaidCode = useMemo(() => applyDirectionToCode(mermaidCode, direction), [mermaidCode, direction]);
+
+  const zoomLabel = `${Math.round(zoom * 100)}%`;
+
+  const clampZoom = (value) => Math.min(3, Math.max(0.3, value));
+
+  const zoomIn = () => setZoom((prev) => clampZoom(prev + 0.1));
+
+  const zoomOut = () => setZoom((prev) => clampZoom(prev - 0.1));
+
+  const resetZoom = () => setZoom(1);
+
+  const fitToView = () => {
+    if (!previewRef.current || !svg) return;
+    const container = previewRef.current;
+    const svgEl = container.querySelector("svg");
+    if (!svgEl) return;
+
+    const vb = svgEl.viewBox?.baseVal;
+    const svgWidth = vb && vb.width ? vb.width : svgEl.getBoundingClientRect().width;
+    const svgHeight = vb && vb.height ? vb.height : svgEl.getBoundingClientRect().height;
+    if (!svgWidth || !svgHeight) return;
+
+    const innerPadding = 32;
+    const availableWidth = Math.max(120, container.clientWidth - innerPadding);
+    const availableHeight = Math.max(120, container.clientHeight - innerPadding);
+    const fitted = clampZoom(Math.min(availableWidth / svgWidth, availableHeight / svgHeight));
+
+    setZoom(fitted);
+    container.scrollLeft = 0;
+    container.scrollTop = 0;
+  };
+
+  const handlePreviewMouseDown = (e) => {
+    if (!svg || !previewRef.current) return;
+    const container = previewRef.current;
+    dragStateRef.current = {
+      dragging: true,
+      startX: e.clientX,
+      startY: e.clientY,
+      startLeft: container.scrollLeft,
+      startTop: container.scrollTop,
+    };
+  };
+
+  const handlePreviewMouseMove = (e) => {
+    if (!previewRef.current) return;
+    const drag = dragStateRef.current;
+    if (!drag.dragging) return;
+    const dx = e.clientX - drag.startX;
+    const dy = e.clientY - drag.startY;
+    previewRef.current.scrollLeft = drag.startLeft - dx;
+    previewRef.current.scrollTop = drag.startTop - dy;
+  };
+
+  const stopPreviewDrag = () => {
+    dragStateRef.current.dragging = false;
+  };
+
+  useEffect(() => {
+    async function draw() {
+      const code = (previewMermaidCode || "").trim();
+      if (!code) {
+        setSvg("");
+        setError("");
+        return;
+      }
+
+      try {
+        const result = await renderMermaid(code);
+        setSvg(result.svg);
+        setError("");
+      } catch (e) {
+        setError(`渲染错误: ${e.message}`);
+      }
+    }
+    draw();
+  }, [previewMermaidCode]);
+
+  const runPlanMode = async () => {
+    const data = await buildPlan(input, "TD");
+    setMermaidCode(data.mermaid_code || "");
+    setZoom(1);
+    setStatusText("计划模式: 已生成流程图，可在预览区切换方向");
+  };
+
+  const runCodeMode = async () => {
+    setStatusText("代码模式: 使用当前编辑器代码渲染");
+  };
+
+  const runAgentMode = async () => {
+    const modeKey = mode === "inspire" ? "inspire" : "standard";
+    const userPrompt = chatInput.trim();
+
+    if (!userPrompt) return;
+
+    pushChatMessage(modeKey, { role: "user", content: userPrompt, kind: "text" });
+    setThinkingMap((prev) => ({ ...prev, [modeKey]: true }));
+    setChatInput("");
+    let settled = false;
+
+    try {
+      await streamAgentChat(
+        {
+          mode: modeKey,
+          prompt: userPrompt,
+          direction: "TD",
+        },
+        ({ data }) => {
+          if (data.type === "status") {
+            setStatusText(`${data.phase}: ${data.message}`);
+          }
+
+          if (data.type === "result") {
+            settled = true;
+            setMermaidCode(data.mermaid_code || "");
+            setZoom(1);
+            setStatusText(`完成: valid=${data.valid}, attempts=${data.attempts}`);
+            if (modeKey === "standard" && data.optimized_text) {
+              pushChatMessage(modeKey, {
+                role: "assistant",
+                content: data.optimized_text,
+                kind: "text",
+                title: "优化后的提示词：",
+              });
+            }
+            pushChatMessage(modeKey, {
+              role: "assistant",
+              content: data.mermaid_code || "",
+              kind: "code",
+              title: ASSISTANT_PREFIX[modeKey],
+            });
+          }
+
+          if (data.type === "error") {
+            settled = true;
+            setError(data.message || "智能体执行失败");
+          }
+        }
+      );
+
+      if (!settled) {
+        throw new Error("服务响应中断，请重试");
+      }
+    } finally {
+      setThinkingMap((prev) => ({ ...prev, [modeKey]: false }));
+    }
+  };
+
+  const handleGenerate = async () => {
+    setLoading(true);
+    setError("");
+    setStatusText("请求处理中...");
+
+    try {
+      if (mode === "plan") {
+        await runPlanMode();
+      } else if (mode === "code") {
+        await runCodeMode();
+      } else {
+        await runAgentMode();
+      }
+    } catch (e) {
+      setError(e.message || "请求失败");
+    } finally {
+      setLoading(false);
+    }
+  };
+
+  return (
+    <div className="page">
+      <header className="topbar">
+        <h1>AutoFlow</h1>
+        <p>计划到流程图，一键生成与实时预览</p>
+      </header>
+
+      <main className="workspace">
+        <section className="left-panel">
+          <div className="tabs">
+            {MODES.map((item) => (
+              <button
+                key={item.key}
+                className={item.key === mode ? "tab active" : "tab"}
+                onClick={() => setMode(item.key)}
+              >
+                {item.label}
+              </button>
+            ))}
+          </div>
+
+          {isChatMode ? (
+            <>
+              <div className="chat-box">
+                {currentChat.length === 0 && !isThinking ? (
+                  <div className="chat-empty-wrap">
+                    <div className="chat-empty">{CHAT_EMPTY_TEXT[mode]}</div>
+                    {mode === "inspire" ? <div className="chat-empty-sub">例如："我想开发一个电商平台"。</div> : null}
+                  </div>
+                ) : (
+                  currentChat.map((msg, idx) => (
+                    <div key={`${msg.role}-${idx}`} className={`chat-msg ${msg.role}`}>
+                      {msg.role === "assistant" && msg.title ? <div className="chat-title">{msg.title}</div> : null}
+                      {msg.kind === "code" ? (
+                        <pre className="chat-code">{msg.content}</pre>
+                      ) : (
+                        <p>{msg.content}</p>
+                      )}
+                    </div>
+                  ))
+                )}
+
+                {isThinking ? (
+                  <div className="chat-msg assistant thinking">
+                    <div className="thinking-bubble">
+                      正在思考
+                      <span className="dots">...</span>
+                    </div>
+                  </div>
+                ) : null}
+              </div>
+
+              <div className="chat-input-row">
+                <textarea
+                  className="chat-input"
+                  placeholder={MODE_PLACEHOLDER[mode]}
+                  value={chatInput}
+                  onChange={(e) => setChatInput(e.target.value)}
+                  onKeyDown={(e) => {
+                    if (e.key === "Enter" && (e.ctrlKey || e.metaKey) && !loading) {
+                      handleGenerate();
+                    }
+                  }}
+                  rows={3}
+                />
+                <button className="primary" disabled={!canGenerate || loading} onClick={handleGenerate}>
+                  {loading ? "生成中" : "发送"}
+                </button>
+              </div>
+            </>
+          ) : (
+            <>
+              <textarea
+                className="editor"
+                placeholder={MODE_PLACEHOLDER[mode]}
+                value={mode === "code" ? mermaidCode : input}
+                onChange={(e) => {
+                  if (mode === "code") {
+                    setMermaidCode(e.target.value);
+                  } else {
+                    setInput(e.target.value);
+                  }
+                }}
+              />
+
+              <div className="actions">
+                <button className="primary" disabled={!canGenerate || loading} onClick={handleGenerate}>
+                  {loading ? "生成中..." : "生成/更新"}
+                </button>
+              </div>
+            </>
+          )}
+
+          <div className="log-box">
+            <strong>当前状态</strong>
+            {loading && <div className="loader" aria-label="loading" />}
+            <p>{statusText}</p>
+          </div>
+        </section>
+
+        <section className="right-panel">
+          <div className="panel-header">
+            <h2>实时预览</h2>
+            <div className="panel-tools">
+              <div className="preview-controls">
+                <button className="ghost" onClick={zoomOut} disabled={!svg}>
+                  缩小
+                </button>
+                <span className="zoom-label">{zoomLabel}</span>
+                <button className="ghost" onClick={zoomIn} disabled={!svg}>
+                  放大
+                </button>
+                <button className="ghost" onClick={resetZoom} disabled={!svg}>
+                  100%
+                </button>
+                <button className="ghost" onClick={fitToView} disabled={!svg}>
+                  适应窗口
+                </button>
+              </div>
+              <div className="direction-switch">
+                {DIRECTION_OPTIONS.map((item) => (
+                  <button
+                    key={item.key}
+                    className={item.key === direction ? "dir-btn active" : "dir-btn"}
+                    onClick={() => setDirection(item.key)}
+                    disabled={!svg}
+                  >
+                    {item.label}
+                  </button>
+                ))}
+              </div>
+              <div className="export-actions">
+              <button className="ghost" onClick={() => downloadText("autoflow.mmd", previewMermaidCode)}>
+                导出 .mmd
+              </button>
+              <button className="ghost" onClick={() => downloadText("autoflow.svg", svg)} disabled={!svg}>
+                导出 SVG
+              </button>
+              </div>
+            </div>
+          </div>
+          {error && (mermaidCode || "").trim() ? <div className="error">{error}</div> : null}
+          <div
+            className={svg ? "preview" : "preview is-empty"}
+            ref={previewRef}
+            onMouseDown={handlePreviewMouseDown}
+            onMouseMove={handlePreviewMouseMove}
+            onMouseUp={stopPreviewDrag}
+            onMouseLeave={stopPreviewDrag}
+          >
+            {svg ? (
+              <div className="preview-scale" style={{ transform: `scale(${zoom})` }}>
+                <div className="preview-inner" dangerouslySetInnerHTML={{ __html: svg }} />
+              </div>
+            ) : (
+              <div className="preview-empty">暂无图表...</div>
+            )}
+          </div>
+        </section>
+      </main>
+    </div>
+  );
+}

Co-creation-projects/usernamedadad-AutoFlow/frontend/src/main.jsx

@@ -0,0 +1,10 @@
+import React from "react";
+import { createRoot } from "react-dom/client";
+import App from "./App";
+import "./styles/app.css";
+
+createRoot(document.getElementById("root")).render(
+  <React.StrictMode>
+    <App />
+  </React.StrictMode>
+);

Co-creation-projects/usernamedadad-AutoFlow/frontend/src/services/api.js

@@ -0,0 +1,69 @@
+const API_BASE = import.meta.env.VITE_API_BASE_URL || "";
+
+export async function buildPlan(text, direction = "TD") {
+  const resp = await fetch(`${API_BASE}/api/plan`, {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify({ text, direction }),
+  });
+
+  if (!resp.ok) {
+    throw new Error(`计划模式请求失败: ${resp.status}`);
+  }
+
+  return resp.json();
+}
+
+function parseSSEChunk(buffer, onEvent) {
+  const parts = buffer.split("\n\n");
+  const remaining = parts.pop() || "";
+
+  for (const block of parts) {
+    const lines = block.split("\n");
+    let eventType = "message";
+    let dataLine = "";
+
+    for (const line of lines) {
+      if (line.startsWith("event:")) {
+        eventType = line.slice(6).trim();
+      }
+      if (line.startsWith("data:")) {
+        dataLine += line.slice(5).trim();
+      }
+    }
+
+    if (dataLine) {
+      try {
+        const parsed = JSON.parse(dataLine);
+        onEvent({ eventType, data: parsed });
+      } catch {
+        onEvent({ eventType, data: { type: "error", message: "SSE 解析失败" } });
+      }
+    }
+  }
+
+  return remaining;
+}
+
+export async function streamAgentChat(payload, onEvent) {
+  const resp = await fetch(`${API_BASE}/api/agent/chat/stream`, {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify(payload),
+  });
+
+  if (!resp.ok || !resp.body) {
+    throw new Error(`智能体流式请求失败: ${resp.status}`);
+  }
+
+  const reader = resp.body.getReader();
+  const decoder = new TextDecoder("utf-8");
+  let buffer = "";
+
+  while (true) {
+    const { value, done } = await reader.read();
+    if (done) break;
+    buffer += decoder.decode(value, { stream: true });
+    buffer = parseSSEChunk(buffer, onEvent);
+  }
+}

Co-creation-projects/usernamedadad-AutoFlow/frontend/src/services/mermaid.js

@@ -0,0 +1,31 @@
+import mermaid from "mermaid";
+
+let initialized = false;
+
+export function initMermaid() {
+  if (initialized) return;
+  mermaid.initialize({
+    startOnLoad: false,
+    theme: "base",
+    securityLevel: "loose",
+    flowchart: {
+      curve: "basis",
+      htmlLabels: true,
+      useMaxWidth: false,
+    },
+    themeVariables: {
+      primaryColor: "#dbeafe",
+      primaryBorderColor: "#2563eb",
+      lineColor: "#1f2937",
+      fontFamily: "IBM Plex Sans",
+      textColor: "#0f172a",
+    },
+  });
+  initialized = true;
+}
+
+export async function renderMermaid(code) {
+  initMermaid();
+  const id = `m-${Date.now()}`;
+  return mermaid.render(id, code);
+}

Co-creation-projects/usernamedadad-AutoFlow/frontend/src/styles/app.css

@@ -0,0 +1,436 @@
+:root {
+  --bg: #f5f5f7;
+  --panel: #ffffff;
+  --ink: #1d1d1f;
+  --muted: #6e6e73;
+  --line: #d2d2d7;
+  --brand: #0071e3;
+  --brand-weak: #e8f3ff;
+  --alert: #b91c1c;
+}
+
+* {
+  box-sizing: border-box;
+}
+
+body {
+  margin: 0;
+  font-family: -apple-system, BlinkMacSystemFont, "SF Pro Text", "Segoe UI", "PingFang SC", "Microsoft YaHei", sans-serif;
+  color: var(--ink);
+  background: var(--bg);
+  min-height: 100vh;
+}
+
+.page {
+  padding: 10px;
+}
+
+.topbar {
+  margin-bottom: 8px;
+  padding-bottom: 10px;
+  border-bottom: 1px solid var(--line);
+}
+
+.topbar h1 {
+  margin: 0;
+  font-family: "Space Grotesk", -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif;
+  font-size: 28px;
+  font-weight: 600;
+  letter-spacing: 0.2px;
+}
+
+.topbar p {
+  margin: 6px 0 0;
+  color: var(--muted);
+}
+
+.workspace {
+  display: grid;
+  grid-template-columns: 49% 51%;
+  gap: 10px;
+  min-height: calc(100vh - 88px);
+}
+
+.direction-switch {
+  display: flex;
+  gap: 8px;
+}
+
+.dir-btn {
+  border: 1px solid var(--line);
+  background: #fff;
+  color: var(--ink);
+  border-radius: 10px;
+  padding: 6px 12px;
+  font-size: 13px;
+}
+
+.dir-btn.active {
+  border-color: var(--brand);
+  background: var(--brand-weak);
+  color: #0055ad;
+}
+
+.left-panel,
+.right-panel {
+  background: var(--panel);
+  border: 1px solid var(--line);
+  border-radius: 16px;
+  padding: 16px;
+  box-shadow: 0 2px 8px rgba(0, 0, 0, 0.04);
+}
+
+.tabs {
+  display: flex;
+  gap: 8px;
+  flex-wrap: wrap;
+  margin-bottom: 10px;
+}
+
+.tab {
+  border: 1px solid var(--line);
+  background: #fdfdfd;
+  color: var(--ink);
+  border-radius: 10px;
+  padding: 8px 12px;
+  cursor: pointer;
+  font-weight: 500;
+}
+
+.tab.active {
+  border-color: var(--brand);
+  background: var(--brand-weak);
+  color: #0055ad;
+}
+
+.editor {
+  width: 100%;
+  min-height: 320px;
+  resize: vertical;
+  border: 1px solid var(--line);
+  border-radius: 10px;
+  padding: 12px;
+  font-family: "IBM Plex Sans", sans-serif;
+  font-size: 14px;
+  line-height: 1.6;
+}
+
+.chat-box {
+  border: 1px solid var(--line);
+  border-radius: 12px;
+  height: 480px;
+  max-height: 480px;
+  overflow-y: auto;
+  overflow-x: hidden;
+  padding: 10px;
+  background: #fff;
+}
+
+.chat-empty-wrap {
+  min-height: 280px;
+  display: flex;
+  flex-direction: column;
+  gap: 8px;
+  align-items: center;
+  justify-content: center;
+  padding: 0 16px;
+}
+
+.chat-empty {
+  color: var(--muted);
+  font-size: 14px;
+  text-align: center;
+}
+
+.chat-empty-sub {
+  color: #8e8e93;
+  font-size: 13px;
+  text-align: center;
+}
+
+.chat-msg {
+  margin-bottom: 10px;
+  display: flex;
+  flex-direction: column;
+  max-width: 88%;
+}
+
+.chat-msg.assistant {
+  align-items: flex-start;
+}
+
+.chat-msg.user {
+  align-items: flex-end;
+  margin-left: auto;
+}
+
+.chat-msg .chat-role {
+  font-size: 12px;
+  color: var(--muted);
+  margin-bottom: 4px;
+}
+
+.chat-title {
+  font-size: 12px;
+  color: #4b5563;
+  margin-bottom: 4px;
+}
+
+.chat-msg p {
+  margin: 0;
+  border: 1px solid var(--line);
+  border-radius: 8px;
+  padding: 8px;
+  background: #fff;
+}
+
+.chat-msg.assistant p,
+.chat-msg.assistant .chat-code {
+  background: #f8fafc;
+}
+
+.chat-msg.user p,
+.chat-msg.user .chat-code {
+  background: #eef6ff;
+}
+
+.chat-msg.thinking {
+  margin-top: 6px;
+}
+
+.thinking-bubble {
+  border: 1px solid var(--line);
+  border-radius: 8px;
+  padding: 8px;
+  display: inline-block;
+  background: #f8fafc;
+  color: #334155;
+  font-size: 14px;
+}
+
+.dots {
+  display: inline-block;
+  margin-left: 2px;
+  animation: blink 1s infinite;
+}
+
+@keyframes blink {
+  0%,
+  100% {
+    opacity: 0.25;
+  }
+  50% {
+    opacity: 1;
+  }
+}
+
+.chat-code {
+  margin: 0;
+  border: 1px solid var(--line);
+  border-radius: 8px;
+  padding: 8px;
+  white-space: pre-wrap;
+  word-break: break-word;
+  font-size: 13px;
+  line-height: 1.5;
+}
+
+.chat-input-row {
+  margin-top: 10px;
+  display: grid;
+  grid-template-columns: 1fr auto;
+  gap: 8px;
+  align-items: end;
+}
+
+.chat-input {
+  border: 1px solid var(--line);
+  border-radius: 10px;
+  padding: 8px 10px;
+  font-size: 14px;
+  min-height: 92px;
+  resize: vertical;
+  line-height: 1.5;
+  font-family: -apple-system, BlinkMacSystemFont, "SF Pro Text", "Segoe UI", "PingFang SC", "Microsoft YaHei", sans-serif;
+}
+
+.actions {
+  margin-top: 10px;
+  display: flex;
+  flex-wrap: wrap;
+  gap: 8px;
+}
+
+.compact-actions {
+  margin-top: 8px;
+}
+
+.panel-header {
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  gap: 8px;
+  margin-bottom: 8px;
+}
+
+.panel-header h2 {
+  margin: 0;
+}
+
+.export-actions {
+  display: flex;
+  gap: 8px;
+  flex-wrap: wrap;
+}
+
+.panel-tools {
+  display: flex;
+  align-items: center;
+  gap: 8px;
+  flex-wrap: wrap;
+  justify-content: flex-end;
+}
+
+.preview-controls {
+  display: flex;
+  align-items: center;
+  gap: 6px;
+}
+
+.zoom-label {
+  min-width: 54px;
+  text-align: center;
+  color: #374151;
+  font-size: 13px;
+}
+
+button {
+  border-radius: 10px;
+  border: 1px solid transparent;
+  padding: 8px 12px;
+  cursor: pointer;
+  font-weight: 500;
+}
+
+button:disabled {
+  opacity: 0.5;
+  cursor: not-allowed;
+}
+
+.primary {
+  background: var(--brand);
+  color: #fff;
+}
+
+.ghost {
+  border-color: var(--line);
+  background: #fff;
+}
+
+.log-box {
+  margin-top: 12px;
+  border: 1px solid var(--line);
+  border-radius: 12px;
+  padding: 10px;
+  background: #f9f9fb;
+  min-height: 96px;
+}
+
+.log-box p {
+  margin: 8px 0 0;
+  color: #334155;
+  font-size: 14px;
+}
+
+.loader {
+  margin-top: 8px;
+  width: 20px;
+  height: 20px;
+  border: 2px solid #cbd5e1;
+  border-top-color: var(--brand);
+  border-radius: 50%;
+  animation: spin 0.9s linear infinite;
+}
+
+@keyframes spin {
+  to {
+    transform: rotate(360deg);
+  }
+}
+
+.right-panel h2 {
+  margin-top: 0;
+  font-family: -apple-system, BlinkMacSystemFont, "SF Pro Display", "Segoe UI", sans-serif;
+  font-size: 20px;
+  font-weight: 600;
+}
+
+.error {
+  border: 1px solid #fecaca;
+  background: #fff1f2;
+  color: var(--alert);
+  padding: 10px;
+  border-radius: 8px;
+  margin-bottom: 10px;
+}
+
+.preview {
+  border: 1px solid var(--line);
+  border-radius: 12px;
+  min-height: calc(100vh - 180px);
+  overflow: auto;
+  padding: 16px;
+  background: #fff;
+  cursor: grab;
+}
+
+.preview.is-empty {
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  cursor: default;
+}
+
+.preview:active {
+  cursor: grabbing;
+}
+
+.preview-scale {
+  transform-origin: top left;
+  width: max-content;
+  min-width: 100%;
+  display: flex;
+  justify-content: center;
+}
+
+.preview-inner {
+  width: max-content;
+  display: flex;
+  justify-content: center;
+}
+
+.preview-inner svg {
+  display: block;
+  margin: 0 auto;
+}
+
+.preview-empty {
+  color: var(--muted);
+  font-size: 14px;
+  text-align: center;
+}
+
+@media (max-width: 980px) {
+  .workspace {
+    grid-template-columns: 1fr;
+  }
+
+  .preview {
+    min-height: 360px;
+  }
+
+  .chat-box {
+    height: 390px;
+    max-height: 390px;
+  }
+}

Co-creation-projects/usernamedadad-AutoFlow/frontend/vite.config.js

@@ -0,0 +1,16 @@
+import { defineConfig } from "vite";
+import react from "@vitejs/plugin-react";
+
+export default defineConfig({
+  plugins: [react()],
+  server: {
+    host: true,
+    port: 5173,
+    proxy: {
+      "/api": {
+        target: "http://127.0.0.1:8000",
+        changeOrigin: true,
+      },
+    },
+  },
+});

Co-creation-projects/usernamedadad-AutoFlow/requirements.txt

@@ -0,0 +1,14 @@
+# Python 后端依赖
+fastapi==0.115.0
+uvicorn[standard]==0.30.6
+pydantic==2.9.2
+python-dotenv==1.0.1
+sse-starlette==2.1.3
+hello-agents=1.0.0
+
+# Node 前端依赖（需使用 npm install 安装）
+react@^18.3.1
+react-dom@^18.3.1
+mermaid@^11.1.1
+@vitejs/plugin-react@^4.3.1
+vite@^5.4.8