Remove deprected demo code

examples/lightrag_multi_model_all_modes_demo.py

@@ -1,88 +0,0 @@
-import os
-import asyncio
-from lightrag import LightRAG, QueryParam
-from lightrag.llm.openai import gpt_4o_mini_complete, gpt_4o_complete, openai_embed
-from lightrag.kg.shared_storage import initialize_pipeline_status
-
-WORKING_DIR = "./lightrag_demo"
-
-if not os.path.exists(WORKING_DIR):
-    os.mkdir(WORKING_DIR)
-
-
-async def initialize_rag():
-    rag = LightRAG(
-        working_dir=WORKING_DIR,
-        embedding_func=openai_embed,
-        llm_model_func=gpt_4o_mini_complete,  # Default model for queries
-    )
-
-    await rag.initialize_storages()
-    await initialize_pipeline_status()
-
-    return rag
-
-
-def main():
-    # Initialize RAG instance
-    rag = asyncio.run(initialize_rag())
-
-    # Load the data
-    with open("./book.txt", "r", encoding="utf-8") as f:
-        rag.insert(f.read())
-
-    # Query with naive mode (default model)
-    print("--- NAIVE mode ---")
-    print(
-        rag.query(
-            "What are the main themes in this story?", param=QueryParam(mode="naive")
-        )
-    )
-
-    # Query with local mode (default model)
-    print("\n--- LOCAL mode ---")
-    print(
-        rag.query(
-            "What are the main themes in this story?", param=QueryParam(mode="local")
-        )
-    )
-
-    # Query with global mode (default model)
-    print("\n--- GLOBAL mode ---")
-    print(
-        rag.query(
-            "What are the main themes in this story?", param=QueryParam(mode="global")
-        )
-    )
-
-    # Query with hybrid mode (default model)
-    print("\n--- HYBRID mode ---")
-    print(
-        rag.query(
-            "What are the main themes in this story?", param=QueryParam(mode="hybrid")
-        )
-    )
-
-    # Query with mix mode (default model)
-    print("\n--- MIX mode ---")
-    print(
-        rag.query(
-            "What are the main themes in this story?", param=QueryParam(mode="mix")
-        )
-    )
-
-    # Query with a custom model (gpt-4o) for a more complex question
-    print("\n--- Using custom model for complex analysis ---")
-    print(
-        rag.query(
-            "How does the character development reflect Victorian-era attitudes?",
-            param=QueryParam(
-                mode="global",
-                model_func=gpt_4o_complete,  # Override default model with more capable one
-            ),
-        )
-    )
-
-
-if __name__ == "__main__":
-    main()