new version

agent_templates/tests/test_search_agent.sh

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+#!/bin/bash
+
+# Search Agent 测试脚本
+# 测试通过 agent-manager 创建和使用 search agent
+
+set -e
+
+AGENT_MANAGER_URL="${AGENT_MANAGER_URL:-http://localhost:8000}"
+AGENT_NAME="test-search-agent-$(date +%s)"
+IMAGE="agnettaiji.azurecr.io/ai-agents/search-agent:v1.0"
+
+echo "=========================================="
+echo "Search Agent 集成测试"
+echo "=========================================="
+echo "Agent Manager: ${AGENT_MANAGER_URL}"
+echo "Agent Name: ${AGENT_NAME}"
+echo "Image: ${IMAGE}"
+echo ""
+
+# 1. 创建 Agent
+echo "📝 步骤 1: 创建 Search Agent..."
+CREATE_RESPONSE=$(curl -s -X POST "${AGENT_MANAGER_URL}/agents" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "name": "'"${AGENT_NAME}"'",
+    "template": "search_agent",
+    "config": {
+      "cpu_request": "500m",
+      "memory_request": "512Mi",
+      "cpu_limit": "1000m",
+      "memory_limit": "1Gi"
+    },
+    "env": {
+      "LLM_BASE_URL": "https://apis.openroutex.com/openai/deployments/xchat52",
+      "LLM_API_KEY": "your-llm-key",
+      "LLM_MODEL": "xchat52",
+      "SERPER_API_KEY": "your-serper-key",
+      "JINA_API_KEY": "your-jina-key",
+      "MAX_ITERATIONS": "3",
+      "LOG_LEVEL": "INFO"
+    }
+  }')
+
+echo "响应: ${CREATE_RESPONSE}"
+echo ""
+
+# 检查创建是否成功
+if echo "${CREATE_RESPONSE}" | grep -q "error"; then
+    echo "❌ 创建失败"
+    exit 1
+fi
+
+echo "✅ Agent 创建成功"
+echo ""
+
+# 2. 等待 Agent 启动
+echo "⏳ 步骤 2: 等待 Agent 启动..."
+sleep 10
+
+# 3. 获取 Agent 状态
+echo "📊 步骤 3: 获取 Agent 状态..."
+STATUS_RESPONSE=$(curl -s "${AGENT_MANAGER_URL}/agents/${AGENT_NAME}/status")
+echo "状态: ${STATUS_RESPONSE}"
+echo ""
+
+# 4. 获取 Agent 服务 URL
+SERVICE_URL=$(echo "${STATUS_RESPONSE}" | python3 -c "import sys, json; data=json.load(sys.stdin); print(data.get('service_url', ''))" 2>/dev/null || echo "")
+echo "Service URL: ${SERVICE_URL}"
+echo ""
+
+if [ -z "${SERVICE_URL}" ]; then
+    echo "❌ 无法获取 Service URL"
+    exit 1
+fi
+
+# 5. 测试健康检查
+echo "🏥 步骤 4: 测试健康检查..."
+HEALTH_RESPONSE=$(curl -s "${SERVICE_URL}/health")
+echo "健康检查响应: ${HEALTH_RESPONSE}"
+echo ""
+
+# 6. 测试搜索功能（如果有配置的 API keys）
+echo "🔍 步骤 5: 测试搜索功能..."
+SEARCH_RESPONSE=$(curl -s -X POST "${SERVICE_URL}/search" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "query": "什么是Kubernetes?",
+    "auto_configure": true
+  }')
+echo "搜索响应: ${SEARCH_RESPONSE}"
+echo ""
+
+# 7. 列出所有 Agents
+echo "📋 步骤 6: 列出所有 Agents..."
+LIST_RESPONSE=$(curl -s "${AGENT_MANAGER_URL}/agents")
+echo "Agent 列表: ${LIST_RESPONSE}"
+echo ""
+
+# 8. 清理（可选）
+read -p "是否删除测试 Agent? (y/N): " -n 1 -r
+echo
+if [[ $REPLY =~ ^[Yy]$ ]]; then
+    echo "🗑️  删除 Agent..."
+    DELETE_RESPONSE=$(curl -s -X DELETE "${AGENT_MANAGER_URL}/agents/${AGENT_NAME}")
+    echo "删除响应: ${DELETE_RESPONSE}"
+    echo ""
+    echo "✅ Agent 已删除"
+else
+    echo "⏭️  保留 Agent: ${AGENT_NAME}"
+    echo ""
+    echo "手动删除命令:"
+    echo "  curl -X DELETE ${AGENT_MANAGER_URL}/agents/${AGENT_NAME}"
+fi
+
+echo ""
+echo "=========================================="
+echo "测试完成！"
+echo "=========================================="

agent_templates/tests/test_search_import.py

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+#!/usr/bin/env python3
+"""测试 search_agent.py 的导入"""
+import sys
+import os
+
+# 模拟 Docker 容器中的路径结构
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'search_agent'))
+
+print("当前工作目录:", os.getcwd())
+print("Python 路径:", sys.path[:3])
+print("")
+
+try:
+    print("测试导入 config...")
+    from config import Config
+    print("✅ config.Config 导入成功")
+    
+    print("\n测试导入 agent.search_agent...")
+    from agent.search_agent import SearchAgent
+    print("✅ agent.search_agent.SearchAgent 导入成功")
+    
+    print("\n测试导入 agent_callback_utils...")
+    from agent_callback_utils import AgentCallbackHandler, CallbackContextManager
+    print("✅ agent_callback_utils 导入成功")
+    
+    print("\n" + "="*50)
+    print("✅ 所有导入测试通过！")
+    print("="*50)
+    
+except Exception as e:
+    print(f"\n❌ 导入失败: {e}")
+    import traceback
+    traceback.print_exc()
+    sys.exit(1)