edge degree next almost done

testkg.py

@@ -0,0 +1,36 @@
+import os
+from lightrag import LightRAG, QueryParam
+from lightrag.llm import gpt_4o_mini_complete, gpt_4o_complete
+
+#########
+# Uncomment the below two lines if running in a jupyter notebook to handle the async nature of rag.insert()
+# import nest_asyncio 
+# nest_asyncio.apply() 
+#########
+
+WORKING_DIR = "./neo4jWorkDir"
+
+
+if not os.path.exists(WORKING_DIR):
+    os.mkdir(WORKING_DIR)
+
+rag = LightRAG(
+    working_dir=WORKING_DIR,
+    llm_model_func=gpt_4o_mini_complete  # Use gpt_4o_mini_complete LLM model
+    # llm_model_func=gpt_4o_complete  # Optionally, use a stronger model
+)
+
+with open("./book.txt") as f:
+    rag.insert(f.read())
+
+# Perform naive search
+print(rag.query("What are the top themes in this story?", param=QueryParam(mode="naive")))
+
+# Perform local search
+print(rag.query("What are the top themes in this story?", param=QueryParam(mode="local")))
+
+# Perform global search
+print(rag.query("What are the top themes in this story?", param=QueryParam(mode="global")))
+
+# Perform hybrid search
+print(rag.query("What are the top themes in this story?", param=QueryParam(mode="hybrid")))