test_api_simple.py

#!/usr/bin/env python3
"""
Simple test script for the API (no Docker needed).
Run this after starting the API server.
"""

import requests
import json
import time

def test_api():
    """Test the API endpoints."""
    base_url = "http://localhost:8000"
    headers = {
        "Authorization": "Bearer demo-key-12345",
        "Content-Type": "application/json"
    }
    
    print("🧪 Testing Agentic AI API")
    print("=" * 40)
    
    try:
        # 1. Health check
        print("\\n1. Health Check...")
        response = requests.get(f"{base_url}/health")
        if response.status_code == 200:
            health = response.json()
            print(f"   ✅ Status: {health['status']}")
            print(f"   ⏱️  Uptime: {health['uptime']:.1f}s")
        else:
            print(f"   ❌ Health check failed: {response.status_code}")
            return
        
        # 2. Process a query
        print("\\n2. Processing Query...")
        query_data = {
            "query": "Find machine learning datasets for image classification",
            "include_debug": True,
            "max_api_calls": 3
        }
        
        response = requests.post(
            f"{base_url}/query",
            headers=headers,
            json=query_data
        )
        
        if response.status_code == 200:
            result = response.json()
            print(f"   ✅ Success in {result['processing_time']:.3f}s")
            print(f"   🔍 Request ID: {result['request_id']}")
            
            # Show results
            results = result['results']
            query_info = results.get('query', {})
            api_matches = results.get('api_matches', {})
            
            print(f"   📝 Keywords: {query_info.get('keywords', [])[:3]}")
            print(f"   🎯 Intent: {query_info.get('intent')}")
            print(f"   🔗 API Matches: {api_matches.get('count', 0)}")
            print(f"   📊 Summary: {results.get('summary', 'N/A')[:60]}...")
        else:
            print(f"   ❌ Query failed: {response.status_code}")
            print(f"   Error: {response.text}")
        
        # 3. List APIs
        print("\\n3. Available APIs...")
        response = requests.get(f"{base_url}/apis", headers=headers)
        if response.status_code == 200:
            apis = response.json()
            print(f"   ✅ Found {len(apis)} APIs:")
            for api in apis[:3]:
                print(f"      • {api['name']} ({api['method']} {api['endpoint']})")
        
        # 4. Extract keywords
        print("\\n4. Keyword Extraction...")
        test_query = "Create a new neural network for classification"
        response = requests.get(
            f"{base_url}/keywords/{test_query}",
            headers=headers
        )
        if response.status_code == 200:
            keywords = response.json()
            print(f"   ✅ Extracted {keywords['count']} keywords:")
            print(f"      {keywords['keywords'][:5]}")
        
        print("\\n" + "=" * 40)
        print("🎉 All tests passed!")
        print("\\n💡 Try these URLs in your browser:")
        print(f"   📚 API Docs: {base_url}/docs")
        print(f"   🔍 Health: {base_url}/health")
        
    except requests.exceptions.ConnectionError:
        print("\\n❌ Cannot connect to API server!")
        print("💡 Start the server first:")
        print("   python run_api.py")
    except Exception as e:
        print(f"\\n❌ Test failed: {e}")

if __name__ == "__main__":
    test_api()