| import os | |
| from lightrag import LightRAG, QueryParam | |
| from lightrag.llm.openai import gpt_4o_mini_complete | |
| WORKING_DIR = "./dickens" | |
| if not os.path.exists(WORKING_DIR): | |
| os.mkdir(WORKING_DIR) | |
| rag = LightRAG( | |
| working_dir=WORKING_DIR, | |
| llm_model_func=gpt_4o_mini_complete, | |
| # llm_model_func=gpt_4o_complete | |
| ) | |
| with open("./book.txt", "r", encoding="utf-8") 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")) | |
| ) | |