Fix

app.py

@@ -11,10 +11,11 @@ os.environ["PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION"] = "python"
 hf_token = os.getenv("HUGGINGFACE_INFERENCE_TOKEN")
 serper_api_key = os.getenv("SERPER_API_KEY")
 
-# ---- Imports ----
+# ---- Updated Imports ----
 from langgraph.graph import START, StateGraph, MessagesState
 from langgraph.prebuilt import tools_condition, ToolNode
 from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint
+from langchain_community.embeddings import HuggingFaceEmbeddings  # Updated import
 from langchain_community.tools.tavily_search import TavilySearchResults
 from langchain_community.document_loaders import WikipediaLoader, ArxivLoader
 from langchain_community.vectorstores import Chroma
@@ -22,7 +23,6 @@ from langchain_core.documents import Document
 from langchain_core.messages import SystemMessage, HumanMessage
 from langchain_core.tools import tool
 from langchain.tools.retriever import create_retriever_tool
-from langchain.embeddings import HuggingFaceEmbeddings
 import json
 
 # ---- Tools ----
@@ -100,9 +100,12 @@ def arxiv_search(query: str) -> str:
     except Exception as e:
         return f"ArXiv search failed: {str(e)}"
 
-# ---- Embedding & Vector Store Setup ----
-
-embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2")
+# ---- Updated Embedding & Vector Store Setup ----
+try:
+    embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2")
+except Exception as e:
+    print(f"Error loading embeddings: {e}")
+    raise
 
 # Load QA pairs
 json_QA = []