chore: Update device for HuggingFaceBgeEmbeddings to dynamic device selection

app.py

@@ -1,10 +1,11 @@
 import os
+import torch
 
 import gradio as gr
 from dotenv import load_dotenv
 from langchain.callbacks.base import BaseCallbackHandler
 from langchain.embeddings import CacheBackedEmbeddings
-from langchain.retrievers import BM25Retriever, EnsembleRetriever
+from langchain_community.retrievers import BM25Retriever, EnsembleRetriever
 from langchain.storage import LocalFileStore
 from langchain_anthropic import ChatAnthropic
 from langchain_community.chat_models import ChatOllama
@@ -100,11 +101,25 @@ print(f"분할된 .ipynb 파일의 개수: {len(ipynb_docs)}")
 combined_documents = py_docs + mdx_docs + ipynb_docs
 print(f"총 도큐먼트 개수: {len(combined_documents)}")
 
+
+# Define the device setting function
+def get_device():
+    if torch.cuda.is_available():
+        return "cuda:0"
+    elif torch.backends.mps.is_available():
+        return "mps"
+    else:
+        return "cpu"
+
+
+# Use the function to set the device in model_kwargs
+device = get_device()
+
 # Initialize embeddings and cache
 store = LocalFileStore("~/.cache/embedding")
 embeddings = HuggingFaceBgeEmbeddings(
     model_name="BAAI/bge-m3",
-    model_kwargs={"device": "cuda:0"},
+    model_kwargs={"device": device},
     encode_kwargs={"normalize_embeddings": True},
 )
 cached_embeddings = CacheBackedEmbeddings.from_bytes_store(