#!/usr/bin/env python3
"""
Debug the documents endpoint response format
"""

import requests
import json

# Configuration
BASE_URL = "http://localhost:3015"
API_KEY = "jleu1212"
HEADERS = {"X-API-Key": API_KEY}

def debug_documents():
    """Debug the documents endpoint response"""
    print("=== DEBUGGING DOCUMENTS ENDPOINT ===")
    
    try:
        docs_url = f"{BASE_URL}/documents"
        response = requests.get(docs_url, headers=HEADERS)
        
        print(f"Response status: {response.status_code}")
        print(f"Response headers: {response.headers}")
        print(f"Response content type: {response.headers.get('content-type', 'Unknown')}")
        
        # Try to parse as JSON
        try:
            data = response.json()
            print(f"JSON response type: {type(data)}")
            print(f"JSON response: {json.dumps(data, indent=2)}")
            
            # Check if it's a list or dict
            if isinstance(data, list):
                print(f"Found {len(data)} documents in list")
                for i, doc in enumerate(data):
                    print(f"Document {i}: {doc}")
            elif isinstance(data, dict):
                print(f"Found dictionary response with keys: {list(data.keys())}")
            else:
                print(f"Unexpected response type: {type(data)}")
                
        except json.JSONDecodeError as e:
            print(f"JSON decode error: {e}")
            print(f"Raw response text: {response.text[:500]}...")
            
    except Exception as e:
        print(f"Exception: {e}")

def perform_search_directly():
    """Perform search directly without checking documents first"""
    print("\n=== PERFORMING SEARCH DIRECTLY ===")
    
    search_queries = [
        "artificial intelligence",
        "machine learning",
        "neural networks",
        "computer vision"
    ]
    
    search_url = f"{BASE_URL}/api/search"
    
    for query in search_queries:
        print(f"\n--- Searching: '{query}' ---")
        
        search_data = {
            "query": query,
            "top_k": 5,
            "mode": "hybrid"
        }
        
        try:
            response = requests.post(search_url, json=search_data, headers=HEADERS)
            
            if response.status_code == 200:
                results = response.json()
                
                if "results" in results and results["results"]:
                    print(f"✅ Found {len(results['results'])} results:")
                    
                    for i, result in enumerate(results["results"], 1):
                        score = result.get('score', 0)
                        text = result.get('text', '')[:200]
                        source = result.get('metadata', {}).get('source', 'Unknown')
                        
                        print(f"  {i}. Score: {score:.4f}")
                        print(f"     Text: {text}...")
                        print(f"     Source: {source}")
                else:
                    print("  No results found")
            else:
                print(f"  Search failed: {response.status_code} - {response.text}")
                
        except Exception as e:
            print(f"  Search error: {e}")

def main():
    print("Debugging LightRAG Documents and Search")
    print("=" * 50)
    
    # Debug documents endpoint
    debug_documents()
    
    # Try search directly
    perform_search_directly()

if __name__ == "__main__":
    main()