| |
| """ |
| Test script: Demonstrates usage of aquery_data FastAPI endpoint |
| Query content: Who is the author of LightRAG |
| """ |
|
|
| import requests |
| import time |
| from typing import Dict, Any |
|
|
| |
| API_KEY = "your-secure-api-key-here-123" |
| BASE_URL = "http://localhost:9621" |
|
|
| |
| AUTH_HEADERS = {"Content-Type": "application/json", "X-API-Key": API_KEY} |
|
|
|
|
| def test_aquery_data_endpoint(): |
| """Test the /query/data endpoint""" |
|
|
| |
| endpoint = f"{BASE_URL}/query/data" |
|
|
| |
| query_request = { |
| "query": "who authored LighRAG", |
| "mode": "mix", |
| "top_k": 20, |
| "chunk_top_k": 15, |
| "max_entity_tokens": 4000, |
| "max_relation_tokens": 4000, |
| "max_total_tokens": 16000, |
| "enable_rerank": True, |
| } |
|
|
| print("=" * 60) |
| print("LightRAG aquery_data endpoint test") |
| print( |
| " Returns structured data including entities, relationships and text chunks" |
| ) |
| print(" Can be used for custom processing and analysis") |
| print("=" * 60) |
| print(f"Query content: {query_request['query']}") |
| print(f"Query mode: {query_request['mode']}") |
| print(f"API endpoint: {endpoint}") |
| print("-" * 60) |
|
|
| try: |
| |
| print("Sending request...") |
| start_time = time.time() |
|
|
| response = requests.post( |
| endpoint, json=query_request, headers=AUTH_HEADERS, timeout=30 |
| ) |
|
|
| end_time = time.time() |
| response_time = end_time - start_time |
|
|
| print(f"Response time: {response_time:.2f} seconds") |
| print(f"HTTP status code: {response.status_code}") |
|
|
| if response.status_code == 200: |
| data = response.json() |
| print_query_results(data) |
| else: |
| print(f"Request failed: {response.status_code}") |
| print(f"Error message: {response.text}") |
|
|
| except requests.exceptions.ConnectionError: |
| print("❌ Connection failed: Please ensure LightRAG API service is running") |
| print(" Start command: python -m lightrag.api.lightrag_server") |
| except requests.exceptions.Timeout: |
| print("❌ Request timeout: Query processing took too long") |
| except Exception as e: |
| print(f"❌ Error occurred: {str(e)}") |
|
|
|
|
| def print_query_results(data: Dict[str, Any]): |
| """Format and print query results""" |
|
|
| entities = data.get("entities", []) |
| relationships = data.get("relationships", []) |
| chunks = data.get("chunks", []) |
| metadata = data.get("metadata", {}) |
|
|
| print("\n📊 Query result statistics:") |
| print(f" Entity count: {len(entities)}") |
| print(f" Relationship count: {len(relationships)}") |
| print(f" Text chunk count: {len(chunks)}") |
|
|
| |
| if metadata: |
| print("\n🔍 Query metadata:") |
| print(f" Query mode: {metadata.get('query_mode', 'unknown')}") |
|
|
| keywords = metadata.get("keywords", {}) |
| if keywords: |
| high_level = keywords.get("high_level", []) |
| low_level = keywords.get("low_level", []) |
| if high_level: |
| print(f" High-level keywords: {', '.join(high_level)}") |
| if low_level: |
| print(f" Low-level keywords: {', '.join(low_level)}") |
|
|
| processing_info = metadata.get("processing_info", {}) |
| if processing_info: |
| print(" Processing info:") |
| for key, value in processing_info.items(): |
| print(f" {key}: {value}") |
|
|
| |
| if entities: |
| print("\n👥 Retrieved entities (first 5):") |
| for i, entity in enumerate(entities[:5]): |
| entity_name = entity.get("entity_name", "Unknown") |
| entity_type = entity.get("entity_type", "Unknown") |
| description = entity.get("description", "No description") |
| file_path = entity.get("file_path", "Unknown source") |
|
|
| print(f" {i+1}. {entity_name} ({entity_type})") |
| print( |
| f" Description: {description[:100]}{'...' if len(description) > 100 else ''}" |
| ) |
| print(f" Source: {file_path}") |
| print() |
|
|
| |
| if relationships: |
| print("🔗 Retrieved relationships (first 5):") |
| for i, rel in enumerate(relationships[:5]): |
| src = rel.get("src_id", "Unknown") |
| tgt = rel.get("tgt_id", "Unknown") |
| description = rel.get("description", "No description") |
| keywords = rel.get("keywords", "No keywords") |
| file_path = rel.get("file_path", "Unknown source") |
|
|
| print(f" {i+1}. {src} → {tgt}") |
| print(f" Keywords: {keywords}") |
| print( |
| f" Description: {description[:100]}{'...' if len(description) > 100 else ''}" |
| ) |
| print(f" Source: {file_path}") |
| print() |
|
|
| |
| if chunks: |
| print("📄 Retrieved text chunks (first 3):") |
| for i, chunk in enumerate(chunks[:3]): |
| content = chunk.get("content", "No content") |
| file_path = chunk.get("file_path", "Unknown source") |
| chunk_id = chunk.get("chunk_id", "Unknown ID") |
|
|
| print(f" {i+1}. Text chunk ID: {chunk_id}") |
| print(f" Source: {file_path}") |
| print( |
| f" Content: {content[:200]}{'...' if len(content) > 200 else ''}" |
| ) |
| print() |
|
|
| print("=" * 60) |
|
|
|
|
| def compare_with_regular_query(): |
| """Compare results between regular query and data query""" |
|
|
| query_text = "LightRAG的作者是谁" |
|
|
| print("\n🔄 Comparison test: Regular query vs Data query") |
| print("-" * 60) |
|
|
| |
| try: |
| print("1. Regular query (/query):") |
| regular_response = requests.post( |
| f"{BASE_URL}/query", |
| json={"query": query_text, "mode": "mix"}, |
| headers=AUTH_HEADERS, |
| timeout=30, |
| ) |
|
|
| if regular_response.status_code == 200: |
| regular_data = regular_response.json() |
| response_text = regular_data.get("response", "No response") |
| print( |
| f" Generated answer: {response_text[:300]}{'...' if len(response_text) > 300 else ''}" |
| ) |
| else: |
| print(f" Regular query failed: {regular_response.status_code}") |
| if regular_response.status_code == 403: |
| print(" Authentication failed - Please check API Key configuration") |
| elif regular_response.status_code == 401: |
| print(" Unauthorized - Please check authentication information") |
| print(f" Error details: {regular_response.text}") |
|
|
| except Exception as e: |
| print(f" Regular query error: {str(e)}") |
|
|
|
|
| if __name__ == "__main__": |
| |
| test_aquery_data_endpoint() |
|
|
| |
| compare_with_regular_query() |
|
|
| print("\n💡 Usage tips:") |
| print("1. Ensure LightRAG API service is running") |
| print("2. Adjust base_url and authentication information as needed") |
| print("3. Modify query parameters to test different retrieval strategies") |
| print("4. Data query results can be used for further analysis and processing") |
|
|