From 67007ed9a6acb351679da9c913e2a37673e114c9 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 17 Nov 2025 15:42:54 +0800
Subject: [PATCH] Improve LightRAG initialization checker tool with better
 usage docs
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• 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 393f8803116cb3a7d2647c7b6f58ef33524f2689)
---
 lightrag/tools/check_initialization.py | 29 +++++++++++++-------------
 1 file changed, 14 insertions(+), 15 deletions(-)

diff --git a/lightrag/tools/check_initialization.py b/lightrag/tools/check_initialization.py
index 6bcb17e3..ee650824 100644
--- a/lightrag/tools/check_initialization.py
+++ b/lightrag/tools/check_initialization.py
@@ -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