example_usage.py

#!/usr/bin/env python3
"""
Example usage of the Vector Knowledge Base API

This script demonstrates how to:
1. Upload a PDF document
2. Query the knowledge base
3. Process the results

Before running: Set VKB_API_KEY environment variable
Usage: python example_usage.py
"""

import os
import requests
import json

# Configuration
API_BASE_URL = "http://localhost:8080/api"  # Change to your deployed URL
API_KEY = os.environ.get("VKB_API_KEY")

if not API_KEY:
    print("Please set VKB_API_KEY environment variable")
    exit(1)

def upload_document(file_path):
    """Upload a PDF document to the knowledge base"""
    headers = {"X-API-KEY": API_KEY}
    
    with open(file_path, 'rb') as f:
        files = {'file': (os.path.basename(file_path), f, 'application/pdf')}
        response = requests.post(f"{API_BASE_URL}/upload", files=files, headers=headers)
    
    if response.status_code == 200:
        result = response.json()
        print(f"✅ Upload successful! Document ID: {result['document_id']}")
        return result['document_id']
    else:
        print(f"❌ Upload failed: {response.text}")
        return None

def query_documents(query):
    """Query the knowledge base"""
    headers = {"X-API-KEY": API_KEY, "Content-Type": "application/json"}
    data = {"query": query}
    
    response = requests.post(f"{API_BASE_URL}/query", json=data, headers=headers)
    
    if response.status_code == 200:
        results = response.json()
        print(f"✅ Found {len(results['results'])} results for: '{query}'")
        
        for i, result in enumerate(results['results'], 1):
            print(f"\n--- Result {i} ---")
            print(f"Source: {result['title']}")
            print(f"Score: {result['score']:.3f}")
            print(f"Content: {result['content'][:200]}...")
        
        return results
    else:
        print(f"❌ Query failed: {response.text}")
        return None

if __name__ == "__main__":
    print("Vector Knowledge Base API Example")
    print("=" * 40)
    
    # Example 1: Upload a document (if you have a PDF file)
    # doc_id = upload_document("your_document.pdf")
    
    # Example 2: Query the knowledge base
    query_examples = [
        "What is machine learning?",
        "Tell me about artificial intelligence",
        "How does neural network work?"
    ]
    
    for query in query_examples:
        print(f"\n🔍 Searching: {query}")
        results = query_documents(query)
        if results and results['results']:
            print("✅ Search completed successfully")
        else:
            print("ℹ️ No results found - try uploading some documents first")
        print("-" * 50)