#!/usr/bin/env python3 """ 为模板市场添加假数据 """ import sys import os sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) from app.core.database import SessionLocal, engine from app.models.workflow_template import WorkflowTemplate, TemplateRating, TemplateFavorite from app.models.user import User from sqlalchemy import text import uuid from datetime import datetime, timedelta import random # 模板数据 TEMPLATE_DATA = [ { "name": "智能客服工作流", "description": "一个完整的智能客服工作流，支持自动回复、问题分类和转人工功能。", "category": "llm", "tags": ["客服", "AI", "自动化"], "nodes": [ {"id": "start", "type": "start", "position": {"x": 100, "y": 100}, "data": {"label": "开始"}}, {"id": "input", "type": "input", "position": {"x": 300, "y": 100}, "data": {"label": "接收用户消息"}}, {"id": "llm", "type": "llm", "position": {"x": 500, "y": 100}, "data": {"label": "AI回复", "model": "gpt-3.5-turbo", "prompt": "你是一个专业的客服助手"}}, {"id": "condition", "type": "condition", "position": {"x": 700, "y": 100}, "data": {"label": "是否需要转人工", "expression": "sentiment_score < 0.3"}}, {"id": "output1", "type": "output", "position": {"x": 900, "y": 50}, "data": {"label": "AI回复"}}, {"id": "output2", "type": "output", "position": {"x": 900, "y": 150}, "data": {"label": "转人工"}}, {"id": "end", "type": "end", "position": {"x": 1100, "y": 100}, "data": {"label": "结束"}} ], "edges": [ {"id": "e1", "source": "start", "target": "input"}, {"id": "e2", "source": "input", "target": "llm"}, {"id": "e3", "source": "llm", "target": "condition"}, {"id": "e4", "source": "condition", "target": "output1", "sourceHandle": "true"}, {"id": "e5", "source": "condition", "target": "output2", "sourceHandle": "false"}, {"id": "e6", "source": "output1", "target": "end"}, {"id": "e7", "source": "output2", "target": "end"} ] }, { "name": "数据清洗工作流", "description": "自动清洗和转换数据，支持多种数据源格式。", "category": "data_processing", "tags": ["数据处理", "ETL", "数据清洗"], "nodes": [ {"id": "start", "type": "start", "position": {"x": 100, "y": 100}, "data": {"label": "开始"}}, {"id": "input", "type": "input", "position": {"x": 300, "y": 100}, "data": {"label": "读取数据"}}, {"id": "transform1", "type": "transform", "position": {"x": 500, "y": 100}, "data": {"label": "数据清洗", "mappings": [{"from": "name", "to": "姓名"}]}}, {"id": "transform2", "type": "transform", "position": {"x": 700, "y": 100}, "data": {"label": "数据验证"}}, {"id": "output", "type": "output", "position": {"x": 900, "y": 100}, "data": {"label": "输出结果"}}, {"id": "end", "type": "end", "position": {"x": 1100, "y": 100}, "data": {"label": "结束"}} ], "edges": [ {"id": "e1", "source": "start", "target": "input"}, {"id": "e2", "source": "input", "target": "transform1"}, {"id": "e3", "source": "transform1", "target": "transform2"}, {"id": "e4", "source": "transform2", "target": "output"}, {"id": "e5", "source": "output", "target": "end"} ] }, { "name": "定时数据同步", "description": "定时从数据库同步数据到另一个系统，支持增量同步。", "category": "automation", "tags": ["定时任务", "数据同步", "自动化"], "nodes": [ {"id": "start", "type": "start", "position": {"x": 100, "y": 100}, "data": {"label": "开始"}}, {"id": "schedule", "type": "schedule", "position": {"x": 300, "y": 100}, "data": {"label": "定时触发", "delay_type": "fixed", "delay_value": 3600, "delay_unit": "seconds"}}, {"id": "db1", "type": "database", "position": {"x": 500, "y": 100}, "data": {"label": "读取源数据", "query": "SELECT * FROM source_table"}}, {"id": "transform", "type": "transform", "position": {"x": 700, "y": 100}, "data": {"label": "数据转换"}}, {"id": "db2", "type": "database", "position": {"x": 900, "y": 100}, "data": {"label": "写入目标", "query": "INSERT INTO target_table"}}, {"id": "end", "type": "end", "position": {"x": 1100, "y": 100}, "data": {"label": "结束"}} ], "edges": [ {"id": "e1", "source": "start", "target": "schedule"}, {"id": "e2", "source": "schedule", "target": "db1"}, {"id": "e3", "source": "db1", "target": "transform"}, {"id": "e4", "source": "transform", "target": "db2"}, {"id": "e5", "source": "db2", "target": "end"} ] }, { "name": "API数据聚合", "description": "从多个API获取数据并聚合处理，支持错误重试。", "category": "integration", "tags": ["API", "数据聚合", "集成"], "nodes": [ {"id": "start", "type": "start", "position": {"x": 100, "y": 100}, "data": {"label": "开始"}}, {"id": "http1", "type": "http", "position": {"x": 300, "y": 50}, "data": {"label": "API 1", "url": "https://api1.example.com/data", "method": "GET"}}, {"id": "http2", "type": "http", "position": {"x": 300, "y": 150}, "data": {"label": "API 2", "url": "https://api2.example.com/data", "method": "GET"}}, {"id": "transform", "type": "transform", "position": {"x": 500, "y": 100}, "data": {"label": "数据聚合"}}, {"id": "output", "type": "output", "position": {"x": 700, "y": 100}, "data": {"label": "输出结果"}}, {"id": "end", "type": "end", "position": {"x": 900, "y": 100}, "data": {"label": "结束"}} ], "edges": [ {"id": "e1", "source": "start", "target": "http1"}, {"id": "e2", "source": "start", "target": "http2"}, {"id": "e3", "source": "http1", "target": "transform"}, {"id": "e4", "source": "http2", "target": "transform"}, {"id": "e5", "source": "transform", "target": "output"}, {"id": "e6", "source": "output", "target": "end"} ] }, { "name": "邮件通知工作流", "description": "根据条件发送邮件通知，支持HTML格式和附件。", "category": "automation", "tags": ["邮件", "通知", "自动化"], "nodes": [ {"id": "start", "type": "start", "position": {"x": 100, "y": 100}, "data": {"label": "开始"}}, {"id": "input", "type": "input", "position": {"x": 300, "y": 100}, "data": {"label": "接收事件"}}, {"id": "condition", "type": "condition", "position": {"x": 500, "y": 100}, "data": {"label": "判断是否需要通知", "expression": "event_type == 'alert'"}}, {"id": "email", "type": "email", "position": {"x": 700, "y": 100}, "data": {"label": "发送邮件", "to_email": "admin@example.com", "subject": "系统通知"}}, {"id": "end", "type": "end", "position": {"x": 900, "y": 100}, "data": {"label": "结束"}} ], "edges": [ {"id": "e1", "source": "start", "target": "input"}, {"id": "e2", "source": "input", "target": "condition"}, {"id": "e3", "source": "condition", "target": "email", "sourceHandle": "true"}, {"id": "e4", "source": "condition", "target": "end", "sourceHandle": "false"}, {"id": "e5", "source": "email", "target": "end"} ] }, { "name": "内容生成工作流", "description": "使用AI生成文章、摘要等内容，支持多种格式输出。", "category": "llm", "tags": ["AI", "内容生成", "LLM"], "nodes": [ {"id": "start", "type": "start", "position": {"x": 100, "y": 100}, "data": {"label": "开始"}}, {"id": "input", "type": "input", "position": {"x": 300, "y": 100}, "data": {"label": "输入主题"}}, {"id": "llm1", "type": "llm", "position": {"x": 500, "y": 100}, "data": {"label": "生成大纲", "model": "gpt-4", "prompt": "根据主题生成文章大纲"}}, {"id": "llm2", "type": "llm", "position": {"x": 700, "y": 100}, "data": {"label": "生成内容", "model": "gpt-4", "prompt": "根据大纲生成完整文章"}}, {"id": "transform", "type": "transform", "position": {"x": 900, "y": 100}, "data": {"label": "格式化输出"}}, {"id": "output", "type": "output", "position": {"x": 1100, "y": 100}, "data": {"label": "输出文章"}}, {"id": "end", "type": "end", "position": {"x": 1300, "y": 100}, "data": {"label": "结束"}} ], "edges": [ {"id": "e1", "source": "start", "target": "input"}, {"id": "e2", "source": "input", "target": "llm1"}, {"id": "e3", "source": "llm1", "target": "llm2"}, {"id": "e4", "source": "llm2", "target": "transform"}, {"id": "e5", "source": "transform", "target": "output"}, {"id": "e6", "source": "output", "target": "end"} ] }, { "name": "文件处理工作流", "description": "批量处理文件，支持上传、下载、格式转换等功能。", "category": "data_processing", "tags": ["文件处理", "批量操作"], "nodes": [ {"id": "start", "type": "start", "position": {"x": 100, "y": 100}, "data": {"label": "开始"}}, {"id": "loop", "type": "loop", "position": {"x": 300, "y": 100}, "data": {"label": "遍历文件列表"}}, {"id": "file_read", "type": "file_operation", "position": {"x": 500, "y": 100}, "data": {"label": "读取文件", "operation": "read"}}, {"id": "transform", "type": "transform", "position": {"x": 700, "y": 100}, "data": {"label": "处理文件"}}, {"id": "file_write", "type": "file_operation", "position": {"x": 900, "y": 100}, "data": {"label": "保存文件", "operation": "write"}}, {"id": "loop_end", "type": "loop_end", "position": {"x": 1100, "y": 100}, "data": {"label": "循环结束"}}, {"id": "end", "type": "end", "position": {"x": 1300, "y": 100}, "data": {"label": "结束"}} ], "edges": [ {"id": "e1", "source": "start", "target": "loop"}, {"id": "e2", "source": "loop", "target": "file_read"}, {"id": "e3", "source": "file_read", "target": "transform"}, {"id": "e4", "source": "transform", "target": "file_write"}, {"id": "e5", "source": "file_write", "target": "loop_end"}, {"id": "e6", "source": "loop_end", "target": "loop"}, {"id": "e7", "source": "loop_end", "target": "end"} ] }, { "name": "Webhook触发器", "description": "接收外部Webhook请求并触发工作流，支持多种认证方式。", "category": "integration", "tags": ["Webhook", "触发器", "集成"], "nodes": [ {"id": "start", "type": "start", "position": {"x": 100, "y": 100}, "data": {"label": "开始"}}, {"id": "webhook", "type": "webhook", "position": {"x": 300, "y": 100}, "data": {"label": "接收Webhook", "url": "/api/v1/webhooks/trigger"}}, {"id": "transform", "type": "transform", "position": {"x": 500, "y": 100}, "data": {"label": "处理数据"}}, {"id": "http", "type": "http", "position": {"x": 700, "y": 100}, "data": {"label": "调用外部API", "url": "https://api.example.com/process", "method": "POST"}}, {"id": "output", "type": "output", "position": {"x": 900, "y": 100}, "data": {"label": "返回结果"}}, {"id": "end", "type": "end", "position": {"x": 1100, "y": 100}, "data": {"label": "结束"}} ], "edges": [ {"id": "e1", "source": "start", "target": "webhook"}, {"id": "e2", "source": "webhook", "target": "transform"}, {"id": "e3", "source": "transform", "target": "http"}, {"id": "e4", "source": "http", "target": "output"}, {"id": "e5", "source": "output", "target": "end"} ] } ] def get_random_user(db): """获取一个随机用户""" users = db.query(User).all() if users: return random.choice(users) return None def add_template_data(): """添加模板数据""" db = SessionLocal() try: # 获取用户 user = get_random_user(db) if not user: print("❌ 没有找到用户，请先创建用户") return print(f"✅ 使用用户: {user.username}") print(f"📝 开始添加模板数据...\n") added_count = 0 skipped_count = 0 for template_info in TEMPLATE_DATA: # 检查模板是否已存在 existing = db.query(WorkflowTemplate).filter( WorkflowTemplate.name == template_info["name"], WorkflowTemplate.user_id == user.id ).first() if existing: print(f"ℹ️ 模板已存在: {template_info['name']}") skipped_count += 1 continue # 创建模板 template = WorkflowTemplate( id=str(uuid.uuid4()), name=template_info["name"], description=template_info["description"], category=template_info["category"], tags=template_info["tags"], nodes=template_info["nodes"], edges=template_info["edges"], is_public=True, is_featured=random.choice([True, False]), # 随机设置为精选 view_count=random.randint(0, 1000), use_count=random.randint(0, 100), rating_count=random.randint(0, 50), rating_avg=round(random.uniform(3.5, 5.0), 1), user_id=user.id, created_at=datetime.now() - timedelta(days=random.randint(0, 30)), updated_at=datetime.now() - timedelta(days=random.randint(0, 7)) ) db.add(template) added_count += 1 print(f"✅ 添加模板: {template_info['name']}") db.commit() print(f"\n{'='*60}") print(f"✅ 数据添加完成！") print(f" 新增: {added_count} 个模板") print(f" 跳过: {skipped_count} 个模板（已存在）") print(f"{'='*60}") # 添加一些评分和收藏数据 print(f"\n📝 添加评分和收藏数据...") templates = db.query(WorkflowTemplate).filter( WorkflowTemplate.is_public == True ).all() if templates and user: # 为部分模板添加评分 for template in random.sample(templates, min(5, len(templates))): existing_rating = db.query(TemplateRating).filter( TemplateRating.template_id == template.id, TemplateRating.user_id == user.id ).first() if not existing_rating: rating = TemplateRating( id=str(uuid.uuid4()), template_id=template.id, user_id=user.id, rating=random.randint(4, 5), comment=random.choice([ "非常好用的模板！", "简单易用，推荐！", "功能完整，值得收藏。", "帮我节省了很多时间。", "模板设计得很专业。" ]) ) db.add(rating) # 为部分模板添加收藏 for template in random.sample(templates, min(3, len(templates))): existing_favorite = db.query(TemplateFavorite).filter( TemplateFavorite.template_id == template.id, TemplateFavorite.user_id == user.id ).first() if not existing_favorite: favorite = TemplateFavorite( id=str(uuid.uuid4()), template_id=template.id, user_id=user.id ) db.add(favorite) db.commit() print(f"✅ 已添加评分和收藏数据") except Exception as e: db.rollback() print(f"❌ 添加数据失败: {e}") import traceback traceback.print_exc() finally: db.close() if __name__ == "__main__": print("="*60) print("模板市场假数据生成工具") print("="*60) print() add_template_data()