LightRAG/examples/lightrag_bedrock_demo.py

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"""
LightRAG meets Amazon Bedrock
"""
import os
import logging
from lightrag import LightRAG, QueryParam
from lightrag.llm import bedrock_complete, bedrock_embedding
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_embedding
)
)
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)
)
)