fix demo

examples/lightrag_api_openai_compatible_demo.py

@@ -1,4 +1,5 @@
 from fastapi import FastAPI, HTTPException, File, UploadFile
+from contextlib import asynccontextmanager
 from pydantic import BaseModel
 import os
 from lightrag import LightRAG, QueryParam
@@ -8,6 +9,7 @@ import numpy as np
 from typing import Optional
 import asyncio
 import nest_asyncio
+from lightrag.kg.shared_storage import initialize_pipeline_status
 
 # Apply nest_asyncio to solve event loop issues
 nest_asyncio.apply()
@@ -71,16 +73,35 @@ async def get_embedding_dim():
 
 
 # Initialize RAG instance
-rag = LightRAG(
-    working_dir=WORKING_DIR,
-    llm_model_func=llm_model_func,
-    embedding_func=EmbeddingFunc(
-        embedding_dim=asyncio.run(get_embedding_dim()),
-        max_token_size=EMBEDDING_MAX_TOKEN_SIZE,
-        func=embedding_func,
-    ),
-)
+async def init():
+    embedding_dimension = await get_embedding_dim()
+    
+    rag = LightRAG(
+        working_dir=WORKING_DIR,
+        llm_model_func=llm_model_func,
+        embedding_func=EmbeddingFunc(
+            embedding_dim=embedding_dimension,
+            max_token_size=EMBEDDING_MAX_TOKEN_SIZE,
+            func=embedding_func,
+        ),
+    )
 
+    await rag.initialize_storages()
+    await initialize_pipeline_status()
+    
+    return rag
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    global rag
+    rag = await init()
+    print("done!")
+    yield
+
+
+app = FastAPI(
+    title="LightRAG API", description="API for RAG operations", lifespan=lifespan
+)
 
 # Data models