diff --git a/lightrag/tools/check_initialization.py b/lightrag/tools/check_initialization.py new file mode 100644 index 00000000..6bcb17e3 --- /dev/null +++ b/lightrag/tools/check_initialization.py @@ -0,0 +1,180 @@ +#!/usr/bin/env python3 +""" +Diagnostic tool to check LightRAG initialization status. + +This tool helps developers verify that their LightRAG instance is properly +initialized before use, preventing common initialization errors. + +Usage: + python -m lightrag.tools.check_initialization +""" + +import asyncio +import sys +from pathlib import Path + +# Add parent directory to path for imports +sys.path.insert(0, str(Path(__file__).parent.parent.parent)) + +from lightrag import LightRAG +from lightrag.base import StoragesStatus + + +async def check_lightrag_setup(rag_instance: LightRAG, verbose: bool = False) -> bool: + """ + Check if a LightRAG instance is properly initialized. + + Args: + rag_instance: The LightRAG instance to check + verbose: If True, print detailed diagnostic information + + Returns: + True if properly initialized, False otherwise + """ + issues = [] + warnings = [] + + print("šŸ” Checking LightRAG initialization status...\n") + + # Check storage initialization status + if not hasattr(rag_instance, "_storages_status"): + issues.append("LightRAG instance missing _storages_status attribute") + elif rag_instance._storages_status != StoragesStatus.INITIALIZED: + issues.append( + f"Storages not initialized (status: {rag_instance._storages_status.name})" + ) + else: + print("āœ… Storage status: INITIALIZED") + + # Check individual storage components + storage_components = [ + ("full_docs", "Document storage"), + ("text_chunks", "Text chunks storage"), + ("entities_vdb", "Entity vector database"), + ("relationships_vdb", "Relationship vector database"), + ("chunks_vdb", "Chunks vector database"), + ("doc_status", "Document status tracker"), + ("llm_response_cache", "LLM response cache"), + ("full_entities", "Entity storage"), + ("full_relations", "Relation storage"), + ("chunk_entity_relation_graph", "Graph storage"), + ] + + if verbose: + print("\nšŸ“¦ Storage Components:") + + for component, description in storage_components: + if not hasattr(rag_instance, component): + issues.append(f"Missing storage component: {component} ({description})") + else: + storage = getattr(rag_instance, component) + if storage is None: + warnings.append(f"Storage {component} is None (might be optional)") + elif hasattr(storage, "_storage_lock"): + if storage._storage_lock is None: + issues.append(f"Storage {component} not initialized (lock is None)") + elif verbose: + print(f" āœ… {description}: Ready") + elif verbose: + print(f" āœ… {description}: Ready") + + # Check pipeline status + try: + from lightrag.kg.shared_storage import get_namespace_data + + get_namespace_data("pipeline_status") + print("āœ… Pipeline status: INITIALIZED") + except KeyError: + issues.append( + "Pipeline status not initialized - call initialize_pipeline_status()" + ) + except Exception as e: + issues.append(f"Error checking pipeline status: {str(e)}") + + # Print results + print("\n" + "=" * 50) + + if issues: + print("āŒ Issues found:\n") + for issue in issues: + print(f" • {issue}") + + print("\nšŸ“ To fix, run this initialization sequence:\n") + print(" await rag.initialize_storages()") + print(" from lightrag.kg.shared_storage import initialize_pipeline_status") + print(" await initialize_pipeline_status()") + print( + "\nšŸ“š Documentation: https://github.com/HKUDS/LightRAG#important-initialization-requirements" + ) + + if warnings and verbose: + print("\nāš ļø Warnings (might be normal):") + for warning in warnings: + print(f" • {warning}") + + return False + else: + print("āœ… LightRAG is properly initialized and ready to use!") + + if warnings and verbose: + print("\nāš ļø Warnings (might be normal):") + for warning in warnings: + print(f" • {warning}") + + return True + + +async def demo(): + """Demonstrate the diagnostic tool with a test instance.""" + from lightrag.llm.openai import openai_embed, gpt_4o_mini_complete + from lightrag.kg.shared_storage import initialize_pipeline_status + + print("=" * 50) + print("LightRAG Initialization Diagnostic Tool") + print("=" * 50) + + # Create test instance + rag = LightRAG( + working_dir="./test_diagnostic", + embedding_func=openai_embed, + llm_model_func=gpt_4o_mini_complete, + ) + + print("\nšŸ”“ BEFORE initialization:\n") + await check_lightrag_setup(rag, verbose=True) + + print("\n" + "=" * 50) + print("\nšŸ”„ Initializing...\n") + await rag.initialize_storages() + await initialize_pipeline_status() + + print("\n🟢 AFTER initialization:\n") + await check_lightrag_setup(rag, verbose=True) + + # Cleanup + import shutil + + shutil.rmtree("./test_diagnostic", ignore_errors=True) + + +if __name__ == "__main__": + import argparse + + parser = argparse.ArgumentParser(description="Check LightRAG initialization status") + parser.add_argument( + "--demo", action="store_true", help="Run a demonstration with a test instance" + ) + parser.add_argument( + "--verbose", + "-v", + action="store_true", + help="Show detailed diagnostic information", + ) + + args = parser.parse_args() + + if args.demo: + asyncio.run(demo()) + else: + print("Run with --demo to see the diagnostic tool in action") + print("Or import this module and use check_lightrag_setup() with your instance")