369 lines
12 KiB
Python
Executable File
369 lines
12 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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测试工具调用可视化功能
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创建一个简单的Agent，使用工具调用，然后查看执行详情
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"""
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import requests
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import json
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import time
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import sys
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BASE_URL = "http://localhost:8037"
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def print_section(title):
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print("\n" + "=" * 80)
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print(f" {title}")
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print("=" * 80)
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def print_info(message):
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print(f"ℹ️ {message}")
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def print_success(message):
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print(f"✅ {message}")
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def print_error(message):
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print(f"❌ {message}")
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def login():
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"""用户登录"""
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print_section("1. 用户登录")
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login_data = {"username": "admin", "password": "123456"}
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try:
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response = requests.post(f"{BASE_URL}/api/v1/auth/login", data=login_data)
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if response.status_code != 200:
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print_error(f"登录失败: {response.status_code}")
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return None
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token = response.json().get("access_token")
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if not token:
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print_error("登录失败: 未获取到token")
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return None
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print_success(f"登录成功")
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return {"Authorization": f"Bearer {token}"}
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except Exception as e:
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print_error(f"登录异常: {str(e)}")
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return None
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def create_test_workflow(headers):
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"""创建测试工作流（使用工具调用）"""
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print_section("2. 创建测试工作流")
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workflow_data = {
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"name": "工具调用可视化测试工作流",
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"description": "用于测试工具调用可视化功能",
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"nodes": [
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{
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"id": "start",
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"type": "start",
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"position": {"x": 100, "y": 200},
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"data": {"label": "开始"}
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},
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{
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"id": "llm-with-tools",
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"type": "llm",
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"position": {"x": 400, "y": 200},
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"data": {
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"label": "工具调用测试",
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"provider": "deepseek",
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"model": "deepseek-chat",
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"temperature": 0.7,
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"max_tokens": 1000,
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"enable_tools": True,
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"selected_tools": ["http_request", "datetime", "math_calculate"],
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"prompt": """用户请求：{{input.query}}
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请根据用户需求，选择合适的工具执行任务。可以使用以下工具：
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- http_request: 发送HTTP请求
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- datetime: 获取当前时间
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- math_calculate: 执行数学计算
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请分析用户需求，调用合适的工具，然后基于工具返回的结果生成回复。"""
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}
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},
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{
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"id": "end",
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"type": "end",
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"position": {"x": 700, "y": 200},
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"data": {"label": "结束"}
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}
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],
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"edges": [
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{
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"id": "e1",
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"source": "start",
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"target": "llm-with-tools",
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"sourceHandle": "right",
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"targetHandle": "left"
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},
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{
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"id": "e2",
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"source": "llm-with-tools",
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"target": "end",
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"sourceHandle": "right",
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"targetHandle": "left"
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}
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]
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}
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try:
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response = requests.post(
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f"{BASE_URL}/api/v1/workflows",
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headers=headers,
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json=workflow_data
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)
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if response.status_code not in [200, 201]:
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print_error(f"创建工作流失败: {response.status_code}")
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print(f"响应: {response.text}")
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return None
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workflow = response.json()
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print_success(f"工作流创建成功: {workflow.get('id')}")
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return workflow
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except Exception as e:
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print_error(f"创建工作流异常: {str(e)}")
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return None
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def execute_workflow(headers, workflow_id, input_data):
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"""执行工作流"""
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print_section("3. 执行工作流")
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execution_data = {
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"workflow_id": workflow_id,
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"input_data": input_data
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}
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try:
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response = requests.post(
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f"{BASE_URL}/api/v1/executions",
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headers=headers,
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json=execution_data
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)
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if response.status_code not in [200, 201]:
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print_error(f"执行工作流失败: {response.status_code}")
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print(f"响应: {response.text}")
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return None
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execution = response.json()
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execution_id = execution.get("id")
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print_success(f"执行已创建: {execution_id}")
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return execution_id
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except Exception as e:
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print_error(f"执行工作流异常: {str(e)}")
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return None
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def wait_for_completion(headers, execution_id, timeout=60):
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"""等待执行完成"""
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print_section("4. 等待执行完成")
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start_time = time.time()
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while time.time() - start_time < timeout:
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try:
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response = requests.get(
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f"{BASE_URL}/api/v1/executions/{execution_id}",
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headers=headers
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)
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if response.status_code != 200:
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print_error(f"获取执行状态失败: {response.status_code}")
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return None
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execution = response.json()
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status = execution.get("status")
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print_info(f"执行状态: {status}")
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if status in ["completed", "failed"]:
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print_success(f"执行完成，状态: {status}")
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return execution
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time.sleep(2)
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except Exception as e:
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print_error(f"获取执行状态异常: {str(e)}")
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return None
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print_error("执行超时")
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return None
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def get_execution_logs(headers, execution_id):
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"""获取执行日志"""
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print_section("5. 获取执行日志（包含工具调用信息）")
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try:
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response = requests.get(
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f"{BASE_URL}/api/v1/execution-logs/executions/{execution_id}",
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headers=headers,
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params={"limit": 100}
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)
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if response.status_code != 200:
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print_error(f"获取执行日志失败: {response.status_code}")
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print(f"响应: {response.text}")
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return None
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logs = response.json()
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print_success(f"获取到 {len(logs)} 条日志")
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# 查找工具调用相关的日志
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tool_call_logs = []
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for log in logs:
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if not log:
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continue
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data = log.get("data") or {}
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if isinstance(data, str):
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try:
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data = json.loads(data)
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except:
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data = {}
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if data.get("tool_name") or "工具" in log.get("message", ""):
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tool_call_logs.append(log)
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if tool_call_logs:
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print_success(f"找到 {len(tool_call_logs)} 条工具调用日志")
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print("\n工具调用日志详情:")
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for i, log in enumerate(tool_call_logs, 1):
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print(f"\n{i}. {log.get('message')}")
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print(f" 时间: {log.get('timestamp')}")
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print(f" 节点: {log.get('node_id')}")
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data = log.get("data", {})
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if data.get("tool_name"):
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print(f" 工具名称: {data.get('tool_name')}")
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print(f" 状态: {data.get('status')}")
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if data.get("tool_args"):
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print(f" 参数: {json.dumps(data.get('tool_args'), ensure_ascii=False, indent=2)}")
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if data.get("duration"):
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print(f" 耗时: {data.get('duration')}ms")
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else:
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print_info("未找到工具调用日志")
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return logs
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except Exception as e:
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print_error(f"获取执行日志异常: {str(e)}")
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return None
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def get_node_execution_data(headers, execution_id, node_id):
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"""获取节点执行数据"""
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print_section(f"6. 获取节点执行数据 (节点: {node_id})")
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try:
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response = requests.get(
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f"{BASE_URL}/api/v1/execution-logs/executions/{execution_id}",
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headers=headers,
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params={"node_id": node_id, "limit": 100}
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)
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if response.status_code != 200:
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print_error(f"获取节点执行数据失败: {response.status_code}")
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return None
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logs = response.json()
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print_success(f"获取到 {len(logs)} 条节点日志")
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# 显示工具调用信息
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tool_calls = []
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for log in logs:
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if not log:
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continue
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data = log.get("data") or {}
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if isinstance(data, str):
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try:
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data = json.loads(data)
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except:
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data = {}
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if data.get("tool_name"):
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tool_calls.append({
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"tool_name": data.get("tool_name"),
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"status": data.get("status"),
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"args": data.get("tool_args"),
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"result": data.get("tool_result"),
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"duration": data.get("duration"),
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"timestamp": log.get("timestamp")
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})
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if tool_calls:
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print_success(f"找到 {len(tool_calls)} 个工具调用")
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for i, call in enumerate(tool_calls, 1):
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print(f"\n工具调用 {i}:")
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print(f" 工具: {call['tool_name']}")
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print(f" 状态: {call['status']}")
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print(f" 参数: {json.dumps(call['args'], ensure_ascii=False, indent=2) if call['args'] else '无'}")
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if call.get('result'):
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result_preview = call['result'][:200] if len(call['result']) > 200 else call['result']
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print(f" 结果预览: {result_preview}...")
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print(f" 耗时: {call.get('duration', 'N/A')}ms")
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print(f" 时间: {call['timestamp']}")
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else:
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print_info("该节点没有工具调用")
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return logs
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except Exception as e:
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print_error(f"获取节点执行数据异常: {str(e)}")
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return None
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def main():
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"""主函数"""
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print_section("工具调用可视化功能测试")
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# 1. 登录
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headers = login()
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if not headers:
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return
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# 2. 创建测试工作流
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workflow = create_test_workflow(headers)
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if not workflow:
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return
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workflow_id = workflow.get("id")
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# 3. 执行工作流（使用不同的测试用例）
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test_cases = [
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{
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"name": "测试HTTP请求工具",
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"input": {"query": "请查询 https://api.github.com/users/octocat 的信息"}
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},
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{
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"name": "测试时间工具",
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"input": {"query": "现在是什么时间？"}
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},
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{
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"name": "测试数学计算工具",
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"input": {"query": "计算 123 * 456 的结果"}
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}
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]
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for i, test_case in enumerate(test_cases, 1):
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print_section(f"测试用例 {i}: {test_case['name']}")
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# 执行工作流
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execution_id = execute_workflow(headers, workflow_id, test_case["input"])
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if not execution_id:
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continue
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# 等待完成
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execution = wait_for_completion(headers, execution_id)
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if not execution:
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continue
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# 获取执行日志
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logs = get_execution_logs(headers, execution_id)
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# 获取节点执行数据
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node_logs = get_node_execution_data(headers, execution_id, "llm-with-tools")
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print_success(f"测试用例 {i} 完成")
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print("\n" + "-" * 80)
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print_section("测试完成")
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print_success("所有测试用例执行完成！")
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print_info("请在前端查看执行详情，验证工具调用可视化功能：")
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print_info(f"1. 打开执行详情页面: http://localhost:8038/executions/{execution_id}")
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print_info("2. 点击节点查看节点执行详情")
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print_info("3. 检查工具调用可视化是否正确显示")
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if __name__ == "__main__":
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main()
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