import asyncio import logging import os import time from lightrag import LightRAG, QueryParam from lightrag.utils import EmbeddingFunc from lightrag.kg.shared_storage import initialize_pipeline_status from Config.Config import EMBED_DIM, EMBED_MAX_TOKEN_SIZE, LLM_MODEL_NAME from Util.LightRagUtil import embedding_func, llm_model_func # 在程序开始时添加以下配置 logging.basicConfig( level=logging.INFO, # 设置日志级别为INFO format='%(asctime)s - %(name)s - %(levelname)s - %(message)s' ) # 或者如果你想更详细地控制日志输出 logger = logging.getLogger('lightrag') logger.setLevel(logging.INFO) handler = logging.StreamHandler() handler.setFormatter(logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')) logger.addHandler(handler) ROOT_DIR = '.' WORKING_DIR = f"{ROOT_DIR}/dickens-pg" logging.basicConfig(format="%(levelname)s:%(message)s", level=logging.INFO) if not os.path.exists(WORKING_DIR): os.mkdir(WORKING_DIR) # AGE os.environ["AGE_GRAPH_NAME"] = "dickens" os.environ["POSTGRES_HOST"] = "10.10.14.208" os.environ["POSTGRES_PORT"] = "5432" os.environ["POSTGRES_USER"] = "postgres" os.environ["POSTGRES_PASSWORD"] = "postgres" os.environ["POSTGRES_DATABASE"] = "rag" async def initialize_rag(): rag = LightRAG( working_dir=WORKING_DIR, llm_model_func=llm_model_func, llm_model_name=LLM_MODEL_NAME, llm_model_max_async=4, llm_model_max_token_size=32768, enable_llm_cache_for_entity_extract=True, embedding_func=EmbeddingFunc( embedding_dim=EMBED_DIM, max_token_size=EMBED_MAX_TOKEN_SIZE, func=embedding_func ), kv_storage="PGKVStorage", doc_status_storage="PGDocStatusStorage", graph_storage="PGGraphStorage", vector_storage="PGVectorStorage", auto_manage_storages_states=False, ) await rag.initialize_storages() await initialize_pipeline_status() return rag async def main(): try: rag = await initialize_rag() #with open(f"{ROOT_DIR}/book.txt", "r", encoding="utf-8") as f: # await rag.ainsert(f.read()) print("==== Trying to test the rag queries ====") print("**** Start Naive Query ****") start_time = time.time() # Perform naive search await rag.aquery( "What are the top themes in this story?", param=QueryParam(mode="naive") ) print(f"Naive Query Time: {time.time() - start_time} seconds") except Exception as e: #logger.error(f"Main execution error: {e}") pass finally: # 确保所有资源正确释放 await asyncio.sleep(0.1) # 给pending任务完成的时间 if __name__ == "__main__": asyncio.run(main())