360 lines
13 KiB
Python
360 lines
13 KiB
Python
"""
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生成测试工作流 - 包含多个节点的完整工作流
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用于验证工作流功能
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"""
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import sys
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import os
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from pathlib import Path
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import json
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from datetime import datetime
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# 添加项目根目录到路径
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from sqlalchemy import create_engine
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from sqlalchemy.orm import sessionmaker
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from app.core.config import settings
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from app.models.workflow import Workflow
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from app.models.user import User
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def generate_test_workflow():
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"""生成测试工作流"""
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# 创建数据库连接
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engine = create_engine(settings.DATABASE_URL)
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Session = sessionmaker(bind=engine)
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session = Session()
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try:
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# 获取第一个用户
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user = session.query(User).first()
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if not user:
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print("❌ 错误：数据库中没有用户，请先创建用户")
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return
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print(f"✅ 使用用户: {user.username} (ID: {user.id})")
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# 定义测试工作流的节点
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nodes = [
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{
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"id": "start-1",
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"type": "start",
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"position": {"x": 100, "y": 100},
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"data": {
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"label": "开始",
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"description": "工作流开始节点"
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}
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},
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{
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"id": "llm-1",
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"type": "llm",
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"position": {"x": 300, "y": 100},
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"data": {
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"label": "LLM处理",
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"provider": "deepseek",
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"model": "deepseek-chat",
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"prompt": "请分析用户输入的内容：{input}\n\n要求：\n1. 提取关键信息\n2. 判断内容类型\n3. 返回JSON格式：{\"type\": \"类型\", \"keywords\": [\"关键词1\", \"关键词2\"], \"sentiment\": \"情感\"}",
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"temperature": 0.7,
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"max_tokens": 1500
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}
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},
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{
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"id": "condition-1",
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"type": "condition",
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"position": {"x": 500, "y": 100},
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"data": {
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"label": "判断类型",
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"condition": "JSON.parse(input).type === 'question'"
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}
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},
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{
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"id": "llm-2",
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"type": "llm",
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"position": {"x": 700, "y": 50},
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"data": {
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"label": "回答问题",
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"provider": "deepseek",
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"model": "deepseek-chat",
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"prompt": "用户提出了一个问题，请提供详细、准确的回答。\n\n问题：{input}\n\n要求：\n1. 回答要准确、专业\n2. 如果涉及技术问题，提供代码示例\n3. 回答要友好、易懂",
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"temperature": 0.7,
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"max_tokens": 2000
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}
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},
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{
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"id": "llm-3",
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"type": "llm",
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"position": {"x": 700, "y": 150},
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"data": {
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"label": "处理其他",
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"provider": "deepseek",
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"model": "deepseek-chat",
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"prompt": "用户输入了其他类型的内容，请进行适当的处理。\n\n内容：{input}\n\n要求：\n1. 理解用户意图\n2. 提供合适的响应\n3. 保持友好和专业",
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"temperature": 0.7,
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"max_tokens": 1500
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}
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},
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{
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"id": "transform-1",
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"type": "transform",
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"position": {"x": 900, "y": 100},
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"data": {
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"label": "格式化输出",
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"transform": "const data = typeof input === 'string' ? JSON.parse(input) : input;\nreturn JSON.stringify({\n success: true,\n result: data,\n timestamp: new Date().toISOString()\n}, null, 2);"
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}
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},
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{
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"id": "end-1",
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"type": "end",
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"position": {"x": 1100, "y": 100},
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"data": {
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"label": "结束",
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"description": "工作流结束节点"
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}
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}
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]
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# 定义边（连接）
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edges = [
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{
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"id": "edge-start-llm1",
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"source": "start-1",
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"target": "llm-1",
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"sourceHandle": "bottom",
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"targetHandle": "top",
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"type": "smoothstep"
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},
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{
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"id": "edge-llm1-condition",
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"source": "llm-1",
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"target": "condition-1",
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"sourceHandle": "bottom",
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"targetHandle": "top",
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"type": "smoothstep"
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},
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{
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"id": "edge-condition-llm2",
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"source": "condition-1",
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"target": "llm-2",
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"sourceHandle": "top",
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"targetHandle": "left",
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"type": "smoothstep",
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"label": "是问题"
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},
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{
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"id": "edge-condition-llm3",
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"source": "condition-1",
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"target": "llm-3",
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"sourceHandle": "bottom",
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"targetHandle": "left",
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"type": "smoothstep",
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"label": "其他"
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},
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{
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"id": "edge-llm2-transform",
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"source": "llm-2",
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"target": "transform-1",
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"sourceHandle": "right",
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"targetHandle": "left",
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"type": "smoothstep"
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},
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{
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"id": "edge-llm3-transform",
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"source": "llm-3",
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"target": "transform-1",
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"sourceHandle": "right",
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"targetHandle": "left",
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"type": "smoothstep"
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},
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{
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"id": "edge-transform-end",
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"source": "transform-1",
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"target": "end-1",
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"sourceHandle": "right",
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"targetHandle": "left",
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"type": "smoothstep"
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}
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]
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# 检查是否已存在同名工作流
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existing = session.query(Workflow).filter(
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Workflow.name == "智能问答工作流（测试）",
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Workflow.user_id == user.id
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).first()
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if existing:
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print(f"⏭️ 工作流已存在，更新现有工作流...")
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existing.nodes = nodes
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existing.edges = edges
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existing.description = "一个包含多个节点的测试工作流，用于验证工作流功能。包含：开始节点、LLM节点、条件判断、数据转换、结束节点"
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existing.status = "draft"
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existing.updated_at = datetime.now()
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workflow = existing
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else:
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# 创建新工作流
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workflow = Workflow(
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name="智能问答工作流（测试）",
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description="一个包含多个节点的测试工作流，用于验证工作流功能。包含：开始节点、LLM节点、条件判断、数据转换、结束节点",
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nodes=nodes,
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edges=edges,
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status="draft",
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user_id=user.id
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)
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session.add(workflow)
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session.commit()
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session.refresh(workflow)
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print(f"\n✅ 测试工作流创建成功！")
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print(f" - 工作流ID: {workflow.id}")
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print(f" - 工作流名称: {workflow.name}")
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print(f" - 节点数量: {len(nodes)} 个")
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print(f" - 连接数量: {len(edges)} 个")
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print(f"\n📋 节点列表:")
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for i, node in enumerate(nodes, 1):
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print(f" {i}. {node['data']['label']} ({node['type']})")
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print(f"\n🔗 连接关系:")
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for i, edge in enumerate(edges, 1):
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source_node = next(n for n in nodes if n['id'] == edge['source'])
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target_node = next(n for n in nodes if n['id'] == edge['target'])
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label = edge.get('label', '')
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print(f" {i}. {source_node['data']['label']} → {target_node['data']['label']} {label}")
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print(f"\n💡 使用说明:")
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print(f" 1. 在工作流列表中点击'编辑'按钮")
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print(f" 2. 可以查看和修改工作流配置")
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print(f" 3. 点击'运行'按钮测试工作流")
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print(f" 4. 输入测试数据，例如：'什么是Python？'")
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except Exception as e:
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session.rollback()
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print(f"❌ 创建失败: {e}")
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import traceback
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traceback.print_exc()
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finally:
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session.close()
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def generate_simple_test_workflow():
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"""生成简单的测试工作流（仅包含基本节点）"""
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# 创建数据库连接
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engine = create_engine(settings.DATABASE_URL)
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Session = sessionmaker(bind=engine)
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session = Session()
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try:
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# 获取第一个用户
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user = session.query(User).first()
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if not user:
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print("❌ 错误：数据库中没有用户，请先创建用户")
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return
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print(f"✅ 使用用户: {user.username} (ID: {user.id})")
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# 定义简单工作流的节点
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nodes = [
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{
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"id": "start-1",
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"type": "start",
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"position": {"x": 100, "y": 100},
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"data": {
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"label": "开始",
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"description": "工作流开始"
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}
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},
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{
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"id": "llm-1",
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"type": "llm",
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"position": {"x": 300, "y": 100},
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"data": {
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"label": "LLM处理",
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"provider": "deepseek",
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"model": "deepseek-chat",
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"prompt": "请回答用户的问题：{input}\n\n要求：\n1. 回答要准确、专业\n2. 语言要友好、易懂\n3. 如果问题不清楚，可以询问更多信息",
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"temperature": 0.7,
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"max_tokens": 1500
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}
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},
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{
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"id": "end-1",
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"type": "end",
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"position": {"x": 500, "y": 100},
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"data": {
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"label": "结束",
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"description": "工作流结束"
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}
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}
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]
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# 定义边（连接）
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edges = [
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{
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"id": "edge-start-llm",
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"source": "start-1",
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"target": "llm-1",
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"sourceHandle": "bottom",
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"targetHandle": "top",
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"type": "smoothstep"
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},
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{
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"id": "edge-llm-end",
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"source": "llm-1",
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"target": "end-1",
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"sourceHandle": "right",
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"targetHandle": "left",
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"type": "smoothstep"
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}
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]
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# 检查是否已存在同名工作流
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existing = session.query(Workflow).filter(
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Workflow.name == "简单问答工作流（测试）",
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Workflow.user_id == user.id
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).first()
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if existing:
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print(f"⏭️ 工作流已存在，更新现有工作流...")
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existing.nodes = nodes
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existing.edges = edges
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existing.description = "一个简单的测试工作流，包含开始、LLM处理、结束三个节点"
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existing.status = "draft"
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existing.updated_at = datetime.now()
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workflow = existing
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else:
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# 创建新工作流
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workflow = Workflow(
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name="简单问答工作流（测试）",
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description="一个简单的测试工作流，包含开始、LLM处理、结束三个节点",
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nodes=nodes,
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edges=edges,
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status="draft",
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user_id=user.id
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)
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session.add(workflow)
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session.commit()
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session.refresh(workflow)
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print(f"\n✅ 简单测试工作流创建成功！")
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print(f" - 工作流ID: {workflow.id}")
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print(f" - 工作流名称: {workflow.name}")
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print(f" - 节点数量: {len(nodes)} 个")
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print(f" - 连接数量: {len(edges)} 个")
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except Exception as e:
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session.rollback()
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print(f"❌ 创建失败: {e}")
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import traceback
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traceback.print_exc()
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finally:
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session.close()
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if __name__ == '__main__':
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print("=" * 60)
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print("生成复杂测试工作流（包含条件判断）")
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print("=" * 60)
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generate_test_workflow()
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print("\n" + "=" * 60)
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print("生成简单测试工作流（仅基本节点）")
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print("=" * 60)
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generate_simple_test_workflow()
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