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