| """ | |
| LightRAG meets Amazon Bedrock ⛰️ | |
| """ | |
| import os | |
| import logging | |
| from lightrag import LightRAG, QueryParam | |
| from lightrag.llm.bedrock import bedrock_complete, bedrock_embed | |
| from lightrag.utils import EmbeddingFunc | |
| logging.getLogger("aiobotocore").setLevel(logging.WARNING) | |
| WORKING_DIR = "./dickens" | |
| if not os.path.exists(WORKING_DIR): | |
| os.mkdir(WORKING_DIR) | |
| rag = LightRAG( | |
| working_dir=WORKING_DIR, | |
| llm_model_func=bedrock_complete, | |
| llm_model_name="Anthropic Claude 3 Haiku // Amazon Bedrock", | |
| embedding_func=EmbeddingFunc( | |
| embedding_dim=1024, max_token_size=8192, func=bedrock_embed | |
| ), | |
| ) | |
| with open("./book.txt", "r", encoding="utf-8") as f: | |
| rag.insert(f.read()) | |
| for mode in ["naive", "local", "global", "hybrid"]: | |
| print("\n+-" + "-" * len(mode) + "-+") | |
| print(f"| {mode.capitalize()} |") | |
| print("+-" + "-" * len(mode) + "-+\n") | |
| print( | |
| rag.query("What are the top themes in this story?", param=QueryParam(mode=mode)) | |
| ) | |