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Improve LightRAG initialization checker tool with better usage docs

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• Add workspace param to get_namespace_data
• Update docstring with proper usage example
• Simplify demo to show correct workflow
• Remove confusing before/after comparison
• Clarify tool should run after init

(cherry picked from commit 393f880311)
This commit is contained in:
yangdx 2025-11-17 15:42:54 +08:00 • committed by Raphaël MANSUY
parent dcf88a8273
commit 67007ed9a6
1 changed files with 14 additions and 15 deletions
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29
lightrag/tools/check_initialization.py
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@ -3,10 +3,17 @@
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.
initialized and ready to use. It should be called AFTER initialize_storages()
to validate that all components are correctly set up.
Usage:
python -m lightrag.tools.check_initialization
# Basic usage in your code:
rag = LightRAG(...)
await rag.initialize_storages()
await check_lightrag_setup(rag, verbose=True)
# Run demo from command line:
python -m lightrag.tools.check_initialization --demo
"""
import asyncio
@ -82,11 +89,11 @@ async def check_lightrag_setup(rag_instance: LightRAG, verbose: bool = False) ->
try:
from lightrag.kg.shared_storage import get_namespace_data
get_namespace_data("pipeline_status")
get_namespace_data("pipeline_status", workspace=rag_instance.workspace)
print("✅ Pipeline status: INITIALIZED")
except KeyError:
issues.append(
"Pipeline status not initialized - call initialize_pipeline_status()"
"Pipeline status not initialized - call rag.initialize_storages() first"
)
except Exception as e:
issues.append(f"Error checking pipeline status: {str(e)}")
@ -101,8 +108,6 @@ async def check_lightrag_setup(rag_instance: LightRAG, verbose: bool = False) ->
print("\n📝 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(
"\n📚 Documentation: https://github.com/HKUDS/LightRAG#important-initialization-requirements"
)
@ -127,7 +132,6 @@ async def check_lightrag_setup(rag_instance: LightRAG, verbose: bool = False) ->
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")
@ -140,15 +144,10 @@ async def demo():
llm_model_func=gpt_4o_mini_complete,
)
print("\n🔴 BEFORE initialization:\n")
await check_lightrag_setup(rag, verbose=True)
print("\n🔄 Initializing storages...\n")
await rag.initialize_storages() # Auto-initializes pipeline_status
print("\n" + "=" * 50)
print("\n🔄 Initializing...\n")
await rag.initialize_storages()
await initialize_pipeline_status()
print("\n🟢 AFTER initialization:\n")
print("\n🔍 Checking initialization status:\n")
await check_lightrag_setup(rag, verbose=True)
# Cleanup